describe the stages in economic problem solving process

How to master the seven-step problem-solving process

In this episode of the McKinsey Podcast , Simon London speaks with Charles Conn, CEO of venture-capital firm Oxford Sciences Innovation, and McKinsey senior partner Hugo Sarrazin about the complexities of different problem-solving strategies.

Podcast transcript

Simon London: Hello, and welcome to this episode of the McKinsey Podcast , with me, Simon London. What’s the number-one skill you need to succeed professionally? Salesmanship, perhaps? Or a facility with statistics? Or maybe the ability to communicate crisply and clearly? Many would argue that at the very top of the list comes problem solving: that is, the ability to think through and come up with an optimal course of action to address any complex challenge—in business, in public policy, or indeed in life.

Looked at this way, it’s no surprise that McKinsey takes problem solving very seriously, testing for it during the recruiting process and then honing it, in McKinsey consultants, through immersion in a structured seven-step method. To discuss the art of problem solving, I sat down in California with McKinsey senior partner Hugo Sarrazin and also with Charles Conn. Charles is a former McKinsey partner, entrepreneur, executive, and coauthor of the book Bulletproof Problem Solving: The One Skill That Changes Everything [John Wiley & Sons, 2018].

Charles and Hugo, welcome to the podcast. Thank you for being here.

Hugo Sarrazin: Our pleasure.

Charles Conn: It’s terrific to be here.

Simon London: Problem solving is a really interesting piece of terminology. It could mean so many different things. I have a son who’s a teenage climber. They talk about solving problems. Climbing is problem solving. Charles, when you talk about problem solving, what are you talking about?

Charles Conn: For me, problem solving is the answer to the question “What should I do?” It’s interesting when there’s uncertainty and complexity, and when it’s meaningful because there are consequences. Your son’s climbing is a perfect example. There are consequences, and it’s complicated, and there’s uncertainty—can he make that grab? I think we can apply that same frame almost at any level. You can think about questions like “What town would I like to live in?” or “Should I put solar panels on my roof?”

You might think that’s a funny thing to apply problem solving to, but in my mind it’s not fundamentally different from business problem solving, which answers the question “What should my strategy be?” Or problem solving at the policy level: “How do we combat climate change?” “Should I support the local school bond?” I think these are all part and parcel of the same type of question, “What should I do?”

I’m a big fan of structured problem solving. By following steps, we can more clearly understand what problem it is we’re solving, what are the components of the problem that we’re solving, which components are the most important ones for us to pay attention to, which analytic techniques we should apply to those, and how we can synthesize what we’ve learned back into a compelling story. That’s all it is, at its heart.

I think sometimes when people think about seven steps, they assume that there’s a rigidity to this. That’s not it at all. It’s actually to give you the scope for creativity, which often doesn’t exist when your problem solving is muddled.

Simon London: You were just talking about the seven-step process. That’s what’s written down in the book, but it’s a very McKinsey process as well. Without getting too deep into the weeds, let’s go through the steps, one by one. You were just talking about problem definition as being a particularly important thing to get right first. That’s the first step. Hugo, tell us about that.

Hugo Sarrazin: It is surprising how often people jump past this step and make a bunch of assumptions. The most powerful thing is to step back and ask the basic questions—“What are we trying to solve? What are the constraints that exist? What are the dependencies?” Let’s make those explicit and really push the thinking and defining. At McKinsey, we spend an enormous amount of time in writing that little statement, and the statement, if you’re a logic purist, is great. You debate. “Is it an ‘or’? Is it an ‘and’? What’s the action verb?” Because all these specific words help you get to the heart of what matters.

Want to subscribe to The McKinsey Podcast ?

Simon London: So this is a concise problem statement.

Hugo Sarrazin: Yeah. It’s not like “Can we grow in Japan?” That’s interesting, but it is “What, specifically, are we trying to uncover in the growth of a product in Japan? Or a segment in Japan? Or a channel in Japan?” When you spend an enormous amount of time, in the first meeting of the different stakeholders, debating this and having different people put forward what they think the problem definition is, you realize that people have completely different views of why they’re here. That, to me, is the most important step.

Charles Conn: I would agree with that. For me, the problem context is critical. When we understand “What are the forces acting upon your decision maker? How quickly is the answer needed? With what precision is the answer needed? Are there areas that are off limits or areas where we would particularly like to find our solution? Is the decision maker open to exploring other areas?” then you not only become more efficient, and move toward what we call the critical path in problem solving, but you also make it so much more likely that you’re not going to waste your time or your decision maker’s time.

How often do especially bright young people run off with half of the idea about what the problem is and start collecting data and start building models—only to discover that they’ve really gone off half-cocked.

Hugo Sarrazin: Yeah.

Charles Conn: And in the wrong direction.

Simon London: OK. So step one—and there is a real art and a structure to it—is define the problem. Step two, Charles?

Charles Conn: My favorite step is step two, which is to use logic trees to disaggregate the problem. Every problem we’re solving has some complexity and some uncertainty in it. The only way that we can really get our team working on the problem is to take the problem apart into logical pieces.

What we find, of course, is that the way to disaggregate the problem often gives you an insight into the answer to the problem quite quickly. I love to do two or three different cuts at it, each one giving a bit of a different insight into what might be going wrong. By doing sensible disaggregations, using logic trees, we can figure out which parts of the problem we should be looking at, and we can assign those different parts to team members.

Simon London: What’s a good example of a logic tree on a sort of ratable problem?

Charles Conn: Maybe the easiest one is the classic profit tree. Almost in every business that I would take a look at, I would start with a profit or return-on-assets tree. In its simplest form, you have the components of revenue, which are price and quantity, and the components of cost, which are cost and quantity. Each of those can be broken out. Cost can be broken into variable cost and fixed cost. The components of price can be broken into what your pricing scheme is. That simple tree often provides insight into what’s going on in a business or what the difference is between that business and the competitors.

If we add the leg, which is “What’s the asset base or investment element?”—so profit divided by assets—then we can ask the question “Is the business using its investments sensibly?” whether that’s in stores or in manufacturing or in transportation assets. I hope we can see just how simple this is, even though we’re describing it in words.

When I went to work with Gordon Moore at the Moore Foundation, the problem that he asked us to look at was “How can we save Pacific salmon?” Now, that sounds like an impossible question, but it was amenable to precisely the same type of disaggregation and allowed us to organize what became a 15-year effort to improve the likelihood of good outcomes for Pacific salmon.

Simon London: Now, is there a danger that your logic tree can be impossibly large? This, I think, brings us onto the third step in the process, which is that you have to prioritize.

Charles Conn: Absolutely. The third step, which we also emphasize, along with good problem definition, is rigorous prioritization—we ask the questions “How important is this lever or this branch of the tree in the overall outcome that we seek to achieve? How much can I move that lever?” Obviously, we try and focus our efforts on ones that have a big impact on the problem and the ones that we have the ability to change. With salmon, ocean conditions turned out to be a big lever, but not one that we could adjust. We focused our attention on fish habitats and fish-harvesting practices, which were big levers that we could affect.

People spend a lot of time arguing about branches that are either not important or that none of us can change. We see it in the public square. When we deal with questions at the policy level—“Should you support the death penalty?” “How do we affect climate change?” “How can we uncover the causes and address homelessness?”—it’s even more important that we’re focusing on levers that are big and movable.

Would you like to learn more about our Strategy & Corporate Finance Practice ?

Simon London: Let’s move swiftly on to step four. You’ve defined your problem, you disaggregate it, you prioritize where you want to analyze—what you want to really look at hard. Then you got to the work plan. Now, what does that mean in practice?

Hugo Sarrazin: Depending on what you’ve prioritized, there are many things you could do. It could be breaking the work among the team members so that people have a clear piece of the work to do. It could be defining the specific analyses that need to get done and executed, and being clear on time lines. There’s always a level-one answer, there’s a level-two answer, there’s a level-three answer. Without being too flippant, I can solve any problem during a good dinner with wine. It won’t have a whole lot of backing.

Simon London: Not going to have a lot of depth to it.

Hugo Sarrazin: No, but it may be useful as a starting point. If the stakes are not that high, that could be OK. If it’s really high stakes, you may need level three and have the whole model validated in three different ways. You need to find a work plan that reflects the level of precision, the time frame you have, and the stakeholders you need to bring along in the exercise.

Charles Conn: I love the way you’ve described that, because, again, some people think of problem solving as a linear thing, but of course what’s critical is that it’s iterative. As you say, you can solve the problem in one day or even one hour.

Charles Conn: We encourage our teams everywhere to do that. We call it the one-day answer or the one-hour answer. In work planning, we’re always iterating. Every time you see a 50-page work plan that stretches out to three months, you know it’s wrong. It will be outmoded very quickly by that learning process that you described. Iterative problem solving is a critical part of this. Sometimes, people think work planning sounds dull, but it isn’t. It’s how we know what’s expected of us and when we need to deliver it and how we’re progressing toward the answer. It’s also the place where we can deal with biases. Bias is a feature of every human decision-making process. If we design our team interactions intelligently, we can avoid the worst sort of biases.

Simon London: Here we’re talking about cognitive biases primarily, right? It’s not that I’m biased against you because of your accent or something. These are the cognitive biases that behavioral sciences have shown we all carry around, things like anchoring, overoptimism—these kinds of things.

Both: Yeah.

Charles Conn: Availability bias is the one that I’m always alert to. You think you’ve seen the problem before, and therefore what’s available is your previous conception of it—and we have to be most careful about that. In any human setting, we also have to be careful about biases that are based on hierarchies, sometimes called sunflower bias. I’m sure, Hugo, with your teams, you make sure that the youngest team members speak first. Not the oldest team members, because it’s easy for people to look at who’s senior and alter their own creative approaches.

Hugo Sarrazin: It’s helpful, at that moment—if someone is asserting a point of view—to ask the question “This was true in what context?” You’re trying to apply something that worked in one context to a different one. That can be deadly if the context has changed, and that’s why organizations struggle to change. You promote all these people because they did something that worked well in the past, and then there’s a disruption in the industry, and they keep doing what got them promoted even though the context has changed.

Simon London: Right. Right.

Hugo Sarrazin: So it’s the same thing in problem solving.

Charles Conn: And it’s why diversity in our teams is so important. It’s one of the best things about the world that we’re in now. We’re likely to have people from different socioeconomic, ethnic, and national backgrounds, each of whom sees problems from a slightly different perspective. It is therefore much more likely that the team will uncover a truly creative and clever approach to problem solving.

Simon London: Let’s move on to step five. You’ve done your work plan. Now you’ve actually got to do the analysis. The thing that strikes me here is that the range of tools that we have at our disposal now, of course, is just huge, particularly with advances in computation, advanced analytics. There’s so many things that you can apply here. Just talk about the analysis stage. How do you pick the right tools?

Charles Conn: For me, the most important thing is that we start with simple heuristics and explanatory statistics before we go off and use the big-gun tools. We need to understand the shape and scope of our problem before we start applying these massive and complex analytical approaches.

Simon London: Would you agree with that?

Hugo Sarrazin: I agree. I think there are so many wonderful heuristics. You need to start there before you go deep into the modeling exercise. There’s an interesting dynamic that’s happening, though. In some cases, for some types of problems, it is even better to set yourself up to maximize your learning. Your problem-solving methodology is test and learn, test and learn, test and learn, and iterate. That is a heuristic in itself, the A/B testing that is used in many parts of the world. So that’s a problem-solving methodology. It’s nothing different. It just uses technology and feedback loops in a fast way. The other one is exploratory data analysis. When you’re dealing with a large-scale problem, and there’s so much data, I can get to the heuristics that Charles was talking about through very clever visualization of data.

You test with your data. You need to set up an environment to do so, but don’t get caught up in neural-network modeling immediately. You’re testing, you’re checking—“Is the data right? Is it sound? Does it make sense?”—before you launch too far.

Simon London: You do hear these ideas—that if you have a big enough data set and enough algorithms, they’re going to find things that you just wouldn’t have spotted, find solutions that maybe you wouldn’t have thought of. Does machine learning sort of revolutionize the problem-solving process? Or are these actually just other tools in the toolbox for structured problem solving?

Charles Conn: It can be revolutionary. There are some areas in which the pattern recognition of large data sets and good algorithms can help us see things that we otherwise couldn’t see. But I do think it’s terribly important we don’t think that this particular technique is a substitute for superb problem solving, starting with good problem definition. Many people use machine learning without understanding algorithms that themselves can have biases built into them. Just as 20 years ago, when we were doing statistical analysis, we knew that we needed good model definition, we still need a good understanding of our algorithms and really good problem definition before we launch off into big data sets and unknown algorithms.

Simon London: Step six. You’ve done your analysis.

Charles Conn: I take six and seven together, and this is the place where young problem solvers often make a mistake. They’ve got their analysis, and they assume that’s the answer, and of course it isn’t the answer. The ability to synthesize the pieces that came out of the analysis and begin to weave those into a story that helps people answer the question “What should I do?” This is back to where we started. If we can’t synthesize, and we can’t tell a story, then our decision maker can’t find the answer to “What should I do?”

Simon London: But, again, these final steps are about motivating people to action, right?

Charles Conn: Yeah.

Simon London: I am slightly torn about the nomenclature of problem solving because it’s on paper, right? Until you motivate people to action, you actually haven’t solved anything.

Charles Conn: I love this question because I think decision-making theory, without a bias to action, is a waste of time. Everything in how I approach this is to help people take action that makes the world better.

Simon London: Hence, these are absolutely critical steps. If you don’t do this well, you’ve just got a bunch of analysis.

Charles Conn: We end up in exactly the same place where we started, which is people speaking across each other, past each other in the public square, rather than actually working together, shoulder to shoulder, to crack these important problems.

Simon London: In the real world, we have a lot of uncertainty—arguably, increasing uncertainty. How do good problem solvers deal with that?

Hugo Sarrazin: At every step of the process. In the problem definition, when you’re defining the context, you need to understand those sources of uncertainty and whether they’re important or not important. It becomes important in the definition of the tree.

You need to think carefully about the branches of the tree that are more certain and less certain as you define them. They don’t have equal weight just because they’ve got equal space on the page. Then, when you’re prioritizing, your prioritization approach may put more emphasis on things that have low probability but huge impact—or, vice versa, may put a lot of priority on things that are very likely and, hopefully, have a reasonable impact. You can introduce that along the way. When you come back to the synthesis, you just need to be nuanced about what you’re understanding, the likelihood.

Often, people lack humility in the way they make their recommendations: “This is the answer.” They’re very precise, and I think we would all be well-served to say, “This is a likely answer under the following sets of conditions” and then make the level of uncertainty clearer, if that is appropriate. It doesn’t mean you’re always in the gray zone; it doesn’t mean you don’t have a point of view. It just means that you can be explicit about the certainty of your answer when you make that recommendation.

Simon London: So it sounds like there is an underlying principle: “Acknowledge and embrace the uncertainty. Don’t pretend that it isn’t there. Be very clear about what the uncertainties are up front, and then build that into every step of the process.”

Hugo Sarrazin: Every step of the process.

Simon London: Yeah. We have just walked through a particular structured methodology for problem solving. But, of course, this is not the only structured methodology for problem solving. One that is also very well-known is design thinking, which comes at things very differently. So, Hugo, I know you have worked with a lot of designers. Just give us a very quick summary. Design thinking—what is it, and how does it relate?

Hugo Sarrazin: It starts with an incredible amount of empathy for the user and uses that to define the problem. It does pause and go out in the wild and spend an enormous amount of time seeing how people interact with objects, seeing the experience they’re getting, seeing the pain points or joy—and uses that to infer and define the problem.

Simon London: Problem definition, but out in the world.

Hugo Sarrazin: With an enormous amount of empathy. There’s a huge emphasis on empathy. Traditional, more classic problem solving is you define the problem based on an understanding of the situation. This one almost presupposes that we don’t know the problem until we go see it. The second thing is you need to come up with multiple scenarios or answers or ideas or concepts, and there’s a lot of divergent thinking initially. That’s slightly different, versus the prioritization, but not for long. Eventually, you need to kind of say, “OK, I’m going to converge again.” Then you go and you bring things back to the customer and get feedback and iterate. Then you rinse and repeat, rinse and repeat. There’s a lot of tactile building, along the way, of prototypes and things like that. It’s very iterative.

Simon London: So, Charles, are these complements or are these alternatives?

Charles Conn: I think they’re entirely complementary, and I think Hugo’s description is perfect. When we do problem definition well in classic problem solving, we are demonstrating the kind of empathy, at the very beginning of our problem, that design thinking asks us to approach. When we ideate—and that’s very similar to the disaggregation, prioritization, and work-planning steps—we do precisely the same thing, and often we use contrasting teams, so that we do have divergent thinking. The best teams allow divergent thinking to bump them off whatever their initial biases in problem solving are. For me, design thinking gives us a constant reminder of creativity, empathy, and the tactile nature of problem solving, but it’s absolutely complementary, not alternative.

Simon London: I think, in a world of cross-functional teams, an interesting question is do people with design-thinking backgrounds really work well together with classical problem solvers? How do you make that chemistry happen?

Hugo Sarrazin: Yeah, it is not easy when people have spent an enormous amount of time seeped in design thinking or user-centric design, whichever word you want to use. If the person who’s applying classic problem-solving methodology is very rigid and mechanical in the way they’re doing it, there could be an enormous amount of tension. If there’s not clarity in the role and not clarity in the process, I think having the two together can be, sometimes, problematic.

The second thing that happens often is that the artifacts the two methodologies try to gravitate toward can be different. Classic problem solving often gravitates toward a model; design thinking migrates toward a prototype. Rather than writing a big deck with all my supporting evidence, they’ll bring an example, a thing, and that feels different. Then you spend your time differently to achieve those two end products, so that’s another source of friction.

Now, I still think it can be an incredibly powerful thing to have the two—if there are the right people with the right mind-set, if there is a team that is explicit about the roles, if we’re clear about the kind of outcomes we are attempting to bring forward. There’s an enormous amount of collaborativeness and respect.

Simon London: But they have to respect each other’s methodology and be prepared to flex, maybe, a little bit, in how this process is going to work.

Hugo Sarrazin: Absolutely.

Simon London: The other area where, it strikes me, there could be a little bit of a different sort of friction is this whole concept of the day-one answer, which is what we were just talking about in classical problem solving. Now, you know that this is probably not going to be your final answer, but that’s how you begin to structure the problem. Whereas I would imagine your design thinkers—no, they’re going off to do their ethnographic research and get out into the field, potentially for a long time, before they come back with at least an initial hypothesis.

Want better strategies? Become a bulletproof problem solver

Hugo Sarrazin: That is a great callout, and that’s another difference. Designers typically will like to soak into the situation and avoid converging too quickly. There’s optionality and exploring different options. There’s a strong belief that keeps the solution space wide enough that you can come up with more radical ideas. If there’s a large design team or many designers on the team, and you come on Friday and say, “What’s our week-one answer?” they’re going to struggle. They’re not going to be comfortable, naturally, to give that answer. It doesn’t mean they don’t have an answer; it’s just not where they are in their thinking process.

Simon London: I think we are, sadly, out of time for today. But Charles and Hugo, thank you so much.

Charles Conn: It was a pleasure to be here, Simon.

Hugo Sarrazin: It was a pleasure. Thank you.

Simon London: And thanks, as always, to you, our listeners, for tuning into this episode of the McKinsey Podcast . If you want to learn more about problem solving, you can find the book, Bulletproof Problem Solving: The One Skill That Changes Everything , online or order it through your local bookstore. To learn more about McKinsey, you can of course find us at McKinsey.com.

Charles Conn is CEO of Oxford Sciences Innovation and an alumnus of McKinsey’s Sydney office. Hugo Sarrazin is a senior partner in the Silicon Valley office, where Simon London, a member of McKinsey Publishing, is also based.

Explore a career with us

Related articles.

Strategy to beat the odds

Five routes to more innovative problem solving

6.1 Problem Solving to Find Entrepreneurial Solutions

Portions of the material in this section are based on original work by Geoffrey Graybeal and produced with support from the Rebus Community. The original is freely available under the terms of the CC BY 4.0 license at https://press.rebus.community/media-innovation-and-entrepreneurship/.

Learning Objectives

By the end of this section, you will be able to:

• Define problem solving in the context of entrepreneurship
• Describe and compare the adaptive model and the innovative model of problem solving
• Identify the skills entrepreneurs need for effective problem solving
• Identify types of problem solvers

As you’ve learned, entrepreneurs often visualize an opportunity gap, a gap between what exists and what could exist, as Hirabayashi and Lidey did with Shine. Entrepreneurial problem solving is the process of using innovation and creative solutions to close that gap by resolving societal, business, or technological problems. Sometimes, personal problems can lead to entrepreneurial opportunities if validated in the market. The entrepreneur visualizes the prospect of filling the gap with an innovative solution that might entail the revision of a product or the creation of an entirely new product. In any case, the entrepreneur approaches the problem-solving process in various ways. This chapter is more about problem solving as it pertains to the entrepreneur’s thought process and approach rather than on problem solving in the sense of opportunity recognition and filling those gaps with new products.

For example, as we read in Identifying Entrepreneurial Opportunity , Sara Blakely (as shown in Figure 6.2 ) saw a need for body contouring and smoothing undergarments one day in the late 1990s when she was getting dressed for a party and couldn’t find what she needed to give her a silhouette she’d be pleased with in a pair of slacks. She saw a problem: a market need. But her problem-solving efforts are what drove her to turn her solution (Spanx undergarments) into a viable product. Those efforts came from her self-admitted can-do attitude: “It’s really important to be resourceful and scrappy—a glass half-full mindset.” 1 Her efforts at creating a new undergarment met resistance with hosiery executives, most of whom were male and out of touch with their female consumers. The hosiery owner who decided to help Blakely initially passed on the idea until running it by his daughters and realizing she was on to something. That something became Spanx , and today, Blakely is a successful entrepreneur. 2

Before getting into the heart of this chapter, we need to make a distinction: Decision making is different from problem solving . A decision is needed to continue or smooth a process affecting the operation of a firm. It can be intuitive or might require research and a long period of consideration. Problem solving , however, is more direct. It entails the solution of some problem where a gap exists between a current state and a desired state. Entrepreneurs are problem solvers who offer solutions using creativity or innovative ventures that exploit opportunities. This chapter focuses on different approaches to problem solving and need recognition that help potential entrepreneurs come up with ideas and refine those ideas.

Two Problem Solving Models: Adaptive and Innovative

There are two prominent established problem-solving models: adaptive and innovative . A renowned British psychologist, Michael Kirton , developed the Kirton Adaption-Innovation (KAI) Inventory to measure an individual’s style of problem solving. 3 Problem-solving preferences are dependent on the personality characteristics of originality, conformity, and efficiency, according to Kirton. The KAI inventory identifies an individual’s problem-solving approach by measuring agreement with statements that align with characteristics, such as the ability to produce many novel ideas, to follow rules and get along in groups, and to systematically orient daily behavior. The results categorize an individual as an innovator or an adaptor. Innovators are highly original, do not like to conform, and value efficiency less than adaptors.

The first and more conservative approach an entrepreneur may use to solve problems is the adaptive model. The adaptive model seeks solutions for problems in ways that are tested and known to be effective. An adaptive model accepts the problem definition and is concerned with resolving problems rather than finding them. This approach seeks greater efficiency while aiming at continuity and stability. The second and more creative approach is the innovative model of entrepreneurial problem solving, which uses techniques that are unknown to the market and that bring advantage to an organization. An innovative problem-solving style challenges the problem definition, discovers problems and avenues for their solutions, and questions existing assumptions—in a nutshell, it does things differently. It uses outside-the-box thinking and searches for novel solutions. Novelty is a shared trait of creative entrepreneurship, and it’s why entrepreneurs gravitate toward this method of problem solving. According to Dr. Shaun M. Powell , a senior lecturer at the University of Wollongong, Australia: “Creative entrepreneurs are notable for a distinctive management style that is based on intuition, informality and rapid decision making, whereas the more conventional thinking styles are not in accord with the unique attributes of creative entrepreneurs.” 4 This way of problem solving doesn’t alter an existing product. It is the creation of something entirely new.

For example, healthcare facilities have long been known as a source of methicillin-resistant Staphylococcus aureus (MRSA), a deadly infection that can have long-term effects on patients. Vital Vio , led by Colleen Costello , has developed white light technology that effectively disinfects healthcare facilities by targeting a molecule specific to bacteria. The light, safe to humans, can burn constantly to kill regenerative bacteria. An adaptive problem-solving model would seek to minimize harm of MRSA within a hospital—to respond to it—whereas the Vital Vio is an entirely new technique that seeks to eliminate it. Adaptive solutions to MRSA include established processes and protocols for prevention, such as having doctors, nurses, and other healthcare providers clean their hands with soap and water, or an alcohol-based hand rub before and after patient care, testing patients to see if they have MRSA on their skin, cleaning hospital rooms and medical equipment, and washing and drying clothes and bed linens in the warmest recommended temperatures. 5

Link to Learning

Visit Inc. Magazine for support and advice for up-and-coming startups to learn more. Examples of how “Dorm Room” entrepreneurs spot and pursue opportunities are shared along with tips and advice for making your startup a success.

Problem-Solving Skills

While identifying problems is a necessary part of the origin of the entrepreneurial process, managing problems is an entirely different aspect once a venture is off the ground and running. An entrepreneur does not have the luxury of avoiding problems and is often responsible for all problem solving in a startup or other form of business. There are certain skills that entrepreneurs possess that make them particularly good problem solvers. Let’s examine each skill (shown in Figure 6.3 ) .

Critical Thinking

Critical thinking is the complex analysis of a problem or issue with the goal of solving the problem or making a decision. The entrepreneur analyzes and peels away the layers of a problem to find the core of an issue facing a business. The entrepreneur focuses on the heart of the problem and responds reasonably and openly to suggestions for solving it. Critical thinking is not only important for developing entrepreneurial ideas: it is a sought-after asset in education and employment. Entrepreneur Rebecca Kantar dropped out of Harvard in 2015 to found the tech startup Imbellus , which aims to replace standardized college admissions tests like the SAT with interactive scenarios that test critical-thinking skills. Many standardized tests may include multiple choice questions asking for the answer to a straightforward knowledge question or math problem. Kantar seeks to create tests that are more concerned with the analytic ability and reasoning that goes into the process of solving the problem. Imbellus says it aims to test “how people think,” not just what they know. The platform, which has not yet launched, will use simulations for its user assessments. 6

Read more about problem solving and EnterpriseWorks/Vita’s story at Harvard Business Review .

Communication

Communication skills , the ability to communicate messages effectively to an intended recipient, are the skills entrepreneurs use to pool resources for the purposes of investigating solutions leading to innovative problem solving and competitive advantage. Good communication allows for the free association of ideas between entrepreneurs and businesses. It can illustrate a problem area or a shared vision, and seeks stakeholder buy-in from various constituencies. Networking and communication within an industry allow the entrepreneur to recognize the position of an enterprise in the market and work toward verbalizing solutions that move an organization beyond its current state. By “verbalizing,” we mean communication from and with the company/entity. Internal communications include company emails, newsletters, presentations, and reports that can set strategic goals and objectives, and report on what has been accomplished and what goals and objectives remain, so that employees within an organization are knowledgeable and can work on solving problems that remain within the organization. External communications could include press releases, blogs and websites, social media, public speeches, and presentations that explain the company’s solutions to problems. They could also be investor pitches complete with business plans and financial projections.

Ideation exercises, such as brainstorming sessions (discussed in Creativity, Innovation, and Invention , are good communication tools that entrepreneurs can use to generate solutions to problems. Another such tool is a hackathon —an event, usually hosted by a tech company or organization, which brings together programmers and workers with other degrees of specialization within the company, community, or organization to collaborate on a project over a short period of time. These can last from twenty-four hours to a few days over a weekend. A hackathon can be an internal company-wide initiative or an external event that brings community participants together. A business model canvas , which is covered in Business Model and Plan and other activities outlined in other chapters can be used internally or externally to identify problems and work toward creating a viable solution.

Networking is an important manifestation of useful communication. What better method is there of presenting one’s concept, gaining funding and buy-in, and marketing for the startup than through building a network of individuals willing to support your venture? A network may consist of potential employees, customers, board members, outside advisors, investors, or champions (people who just love your product) with no direct vested interest. Social networks consist of weak ties and strong ties. Sociologist Mark Granovetter studied such networks back in the 1970s, and his findings still apply today, even if we include social media networks in the definition too. Weak ties facilitate flow of information and community organization, he said, whereas strong ties represent strong connections among close friends, family members, and supportive coworkers. 7 Strong ties require more work to maintain than weak ties (as illustrated by the strong lines and weak dotted lines in Figure 6.4 ) and in a business context, they don’t lead to many new opportunities. Weak ties, in contrast, do open doors in that they act as bridges to other weak ties within functional areas or departments that you might not have had access to directly or through strong ties. 8

In fact, many young entrepreneurs, including tech entrepreneur Oliver Isaacs , realize college is a great place to begin building teams. Isaacs is the founder of viral opinion network Amirite.com , which is widely credited as the place where Internet memes started and online slang got a foothold. 9 Amirite.com consists of a large network of pages and partnerships on Facebook and Instagram that reach 15 million users each month. Isaacs recommends using your alumni network to build a team and customer base for your own venture because you never know if you’re talking to a future employee or partner.

Sharing of ideas and resources is highly valued in the entrepreneurial process. Communication is a vital skill in problem solving because the ability to identify and articulate the problem (define the problem space) is necessary to adequately address a problem. A problem can be too vague or broad or narrow. Thus, communicating the problem is important, as is conveying the solution.

Decisiveness

Decisiveness is as it sounds: the ability to make a quick, effective decision, not letting too much time go by in the process. Entrepreneurs must be productive, even in the face of risk. They often rely on intuition as well as on hard facts in making a choice. They ask what problem needs to be solved, think about solutions, and then consider the means necessary to implement an idea. And the decisions must be informed with research.

For example, as explained in Adam Grant’s book The Originals , the co-founders of Warby Parker, a venture-backed startup focused on the eyewear industry, started their company while they were graduate students. At the time they knew little about the industry, but after conducting some detailed research, they learned that the industry was dominated by one major player—Luxottica. They used this information and other data to refine their strategy and business model (focusing mainly on value, quality, and convenience via an online channel). By the time they decided to launch the business, they had thought through the key details, and they attained rapid early success. Today Warby Parker has over 100 retail stores in the US, is profitable, and is valued at almost $2 billion.

Decisiveness is the catapult to progress. Amazon founder Jeff Bezos preaches the importance of decisiveness throughout his organization. Bezos believes that decisiveness can even lead to innovation. Bezos advocates for making decisions after obtaining 70 percent of the information you need to do so: “Being wrong may be less costly than you think, whereas being slow is going to be expensive for sure,” Bezos wrote in a 2017 annual letter to stockholders. 10

Read this LinkedIn blog post on decisiveness to learn more.

Ability to Analyze Data

Data analysis is the process of analyzing data and modeling it into a structure that leads to innovative conclusions. Identifying Entrepreneurial Opportunity covered much of the sources of data that entrepreneurs might seek. But it is one thing to amass information and statistics. It is another to make sense of that data, to use it to fill a market need or forecast a trend to come. Successful founders know how to pose questions about and make meaning out of information. And if they can’t do that themselves, they know how to bring in experts who can.

In addition to public sources of broad data, a business can collect data on customers when they interact with the company on social media or when they visit the company website, especially if they complete a credit card transaction. They can collect their own specific data on their own customers, including location, name, activity, and how they got to the website. Analyzing these data will give the entrepreneur a better idea about the interested audience’s demographic.

In entrepreneurship, analyzing data can help with opportunity recognition, creation, and assessment by analyzing data in a variety of ways. Entrepreneurs can explore and leverage different data sources to identify and compare “attractive” opportunities, since such analyses can describe what has happened, why it happened, and how likely it is to happen again in the future. In business in general, analytics is used to help managers/entrepreneurs gain improved insight about their business operations/emerging ventures and make better, fact-based decisions.

Analytics can be descriptive, predictive, or prescriptive. Descriptive analytics involves understanding what has happened and what is happening; predictive analytics uses data from past performance to estimate future performance; and prescriptive analytics uses the results of descriptive and predictive analytics to make decisions. Data analysis can be applied to manage customer relations, inform financial and marketing activities, make pricing decisions, manage the supply chain, and plan for human resource needs, among other functions of a venture. In addition to statistical analysis, quantitative methods, and computer models to aid decision-making, companies are also increasingly using artificial intelligence algorithms to analyze data and make quick decisions.

Understanding of Business and Industry

Entrepreneurs need sound understanding of markets and industries. Often times, they are already working in a large organization when they see growth opportunities or inefficiencies in a market. The employee gains a deep understanding of the industry at hand. If the employee considers a possible solution for a problem, this solution might become the basis for a new business.

For example, consider a marketing agency that used traditional marketing for thirty years. This agency had an established clientele. An executive in the organization began studying social media analytics and social media. The executive approached the owner of the business to change processes and begin serving clients through social media, but the owner refused. Clients within the agency began to clamor for exposure on social media. The marketing executive investigated the possibility of building an agency in her locale servicing clients who wish to utilize social media. The marketing executive left the organization and started her own agency (providing, of course, that this is in compliance with any noncompete clauses in her contract). Her competitive advantage was familiarity with both traditional and social media venues. Later, the original agency started floundering because it did not offer social media advertising. Our intrepid executive purchased the agency to gain the clientele and serve those wishing to move away from traditional marketing.

A similar experience occurred for entrepreneur Katie Witkin . After working in traditional marketing roles, the University of Wisconsin-Madison graduate, pictured in Figure 6.5 , left agency life behind four years out of college to cofound her own company, AGW Group . In 2009, Witkin had been interning at a music marketing agency that didn’t have a social media department. She knew, both from her time at college and from observing industry trends, that social media was changing the way companies connected with customers. For her own venture, she expanded the focus to all supporting brands to manage all things digital. Today, the cultural and marketing communications agency has fifteen employees and big-name clients ranging from HBO to Red Bull. 11

Resourcefulness

Resourcefulness is the ability to discover clever solutions to obstacles. Sherrie Campbell , a psychologist, author, and frequent contributor to Entrepreneur magazine on business topics, put it this way:

“There is not a more useful or important trait to possess than resourcefulness in the pursuit of success. Resourcefulness is a mindset, and is especially relevant when the goals you have set are difficult to achieve or you cannot envision a clear path to get to where you desire to go. With a resourcefulness mindset you are driven to find a way. An attitude of resourcefulness inspires out-of-the-box thinking, the generation of new ideas, and the ability to visualize all the possible ways to achieve what you desire. Resourcefulness turns you into a scrappy, inventive and enterprising entrepreneur. It places you a cut above the rest.” 12

Entrepreneurs start thinking about a business venture or startup by talking to people and procuring experts to help create, fund, and begin a business. Entrepreneurs are risk takers, passionate about new endeavors. If they don’t have a college degree or a great deal of business experience, they understand there are many resources available to support them in the endeavor, such as the Service Corps of Retired Executives (SCORE) and the Small Business Administration (SBA) . There are many sources available to fund the business with little or no debt and options, as you will see in the chapter on Entrepreneurial Finance and Accounting . The entrepreneur follows a vision and researches opportunities to move toward a dream.

For example, in the late 1990s, Bill McBean and his business partner Billy Sterett had an opportunity to buy an underperforming auto dealership that would make their company the dominant one in the market. Neither wanting to take cash from other ventures nor wanting to borrow more money and tie themselves to more debt, the entrepreneurs were resourceful by finding another path forward to obtaining the money necessary for the acquisition they both coveted. They changed banks and renegotiated their banking payback requirements, lowering their interest payments, reducing fees, and lowering their monthly payments, ultimately freeing up a significant amount of cash that allowed them to buy the new company. 13

Types of Problem Solvers

Entrepreneurs have an insatiable appetite for problem solving. This drive motivates them to find a resolution when a gap in a product or service occurs. They recognize opportunities and take advantage of them. There are several types of entrepreneurial problem solvers, including self-regulators, theorists, and petitioners.

Self-Regulating Problem Solvers

Self-regulating problem solvers are autonomous and work on their own without external influence. They have the ability to see a problem, visualize a possible solution to the problem, and seek to devise a solution, as Figure 6.6 illustrates. The solution may be a risk, but a self-regulating problem solver will recognize, evaluate, and mitigate the risk. For example, an entrepreneur has programmed a computerized process for a client, but in testing it, finds the program continually falls into a loop, meaning it gets stuck in a cycle and doesn’t progress. Rather than wait for the client to find the problem, the entrepreneur searches the code for the error causing the loop, immediately edits it, and delivers the corrected program to the customer. There is immediate analysis, immediate correction, and immediate implementation. The self-regulating problem solvers’ biggest competitive advantage is the speed with which they recognize and provide solutions to problems.

Theorist Problem Solvers

Theorist problem solvers see a problem and begin to consider a path toward solving the problem using a theory. Theorist problem solvers are process oriented and systematic. While managers may start with a problem and focus on an outcome with little consideration of a means to an end, entrepreneurs may see a problem and begin to build a path with what is known, a theory, toward an outcome. That is, the entrepreneur proceeds through the steps to solve the problem and then builds on the successes, rejects the failures, and works toward the outcome by experimenting and building on known results. At this point, the problem solver may not know the outcome, but a solution will arise as experiments toward a solution occur. Figure 6.7 shows this process.

For example, if we consider Marie Curie as an entrepreneur, Curie worked toward the isolation of an element. As different approaches to isolating the element failed, Curie recorded the failures and attempted other possible solutions. Curie’s failed theories eventually revealed the outcome for the isolation of radium. Like Curie, theorists use considered analysis, considered corrective action, and a considered implementation process. When time is of the essence, entrepreneurs should understand continual experimentation slows the problem-solving process.

Petitioner Problem Solvers

Petitioner problem solvers ( Figure 6.8 ) see a problem and ask others for solution ideas. This entrepreneur likes to consult a person who has “been there and done that.” The petitioner might also prefer to solve the problem in a team environment. Petitioning the entrepreneurial team for input ensures that the entrepreneur is on a consensus-driven path. This type of problem solving takes the longest to complete because the entrepreneur must engage in a democratic process that allows all members on the team to have input. The process involves exploration of alternatives for the ultimate solution. In organizational decision-making, for example, comprehensiveness is a measure of the extent a firm attempts to be inclusive or exhaustive in its decision-making. Comprehensiveness can be gauged by the number of scheduled meetings, the process by which information is sought, the process by which input is obtained from external sources, the number of employees involved, the use of specialized consultants and the functional expertise of the people involved, the years of historical data review, and the assignment of primary responsibility, among other factors. Comprehensive decision-making would be an example of a petitioner problem-solving style, as it seeks input from a vast number of team members.

A charette —a meeting to resolve conflicts and identify solutions—is another example that employs a petitioner problem-solving approach. Often times, a developer of a new project might hold a community charette to aid in the design of a project, hoping to gain approval from elected officials. In the building example, this could consist of the developer and his team of architects, project designers, and people with expertise in the project working alongside community members, business executives, elected officials, or representatives like staff members or citizen-appointed boards like a planning board. Such an activity is representative of a petitioner problem-solving approach, as opposed to a developer representative designing the project with no input from anyone else.

In summary, there is no right or wrong style of problem solving; each problem solver must rely on the instincts that best drive innovation. Further, they must remember that not all problem-solving methods work in every situation. They must be willing to adapt their own preference to the situation to maximize efficiency and ensure they find an effective solution. Attempting to force a problem-solving style may prevent an organization from finding the best solution. While general entrepreneurial problem-solving skills such as critical thinking, decisiveness, communication, and the ability to analyze data will likely be used on a regular basis in your life and entrepreneurial journey, other problem-solving skills and the approach you take will depend on the problem as it arises.

There are a number of resources online that can help analyze your problem-solving abilities. Mindtools.com is one such resource. These are useful to learn your general problem-solving tendencies before being called upon to apply them in a real-world setting. One of the problem-solving techniques available from mindtools.com offers that problems can be addressed from six different perspectives. Called CATWOE , the approach is an acronym for Customers, Actors (people within the organization), Transformative, Worldwide, Owner, and Environment (organizational).

Learn more about the CATWOE technique for problem solving.

• 1 Helen Lock. “‘I Put My Butt on the Line’: How Spanx Took Over the World.” The Guardian. July 11, 2016. https://www.theguardian.com/small-business-network/2016/jul/11/put-butt-on-the-line-how-spanx-world
• 2 Gary Keller. “Business Success Series, Part 1: Sara Blakely-Spanx.” The One Thing. n.d. https://www.the1thing.com/blog/the-one-thing/business-success-series-part-1-sara-blakely-spanx/
• 3 “Characteristics of Adaptors and Innovators.” Kirton KAI Inventory Tool . n.d. http://pubs.acs.org/subscribe/archive/ci/31/i11/html/11hipple_box3.ci.html
• 4 Shaun Powell. “The Management and Consumption of Organisational Creativity.” Journal of Consumer Marketing 25, no. 3 (2008): 158–166.
• 5 N.C Healthcare-Associated Infections Prevention Program. Healthcare-Associated Infections in North Carolina: 2014 Annual Report, Healthcare Consumer Version. April 2015. https://epi.dph.ncdhhs.gov/cd/hai/figures/hai_apr2015_consumers_annual.pdf
• 6 Romesh Ratnesar. “What If Instead of Taking the SAT You Got to Play a Video Game?” Bloomberg BusinessWeek. March 19, 2019. https://www.bloomberg.com/news/features/2019-03-19/a-harvard-dropout-s-plan-to-fix-college-admissions-with-video-games
• 7 Mark Granovetter. “The Strength of Weak Ties.” American Journal of Sociology 5 (1973): 1360–1380.
• 8 Jacob Morgan. “Why Every Employee Should Be Building Weak Ties at Work.” Forbes. March 11, 2014. https://www.forbes.com/sites/jacobmorgan/2014/03/11/every-employee-weak-ties-work/#277851063168
• 9 John White. “Top UK Influencer Oliver Isaacs Reveals What It Takes to Go Viral.” Inc . August 6, 2017. https://www.inc.com/john-white/top-uk-influencer-oliver-isaacs-reveals-what-it-ta.html
• 10 Erik Larson. “How Jeff Bezos Uses Faster Better Decisions to Keep Amazon Innovating.” Forbes . September 24, 2018. https://www.forbes.com/sites/eriklarson/2018/09/24/how-jeff-bezos-uses-faster-better-decisions-to-keep-amazon-innovating/#492c351b7a65
• 11 Stephanie Schomer. “How Getting Laid Off Empowered This Entrepreneur to Start Her Own Award-Winning Marketing Agency.” Entrepreneur. January 15, 2019. https://www.entrepreneur.com/article/326212
• 12 Sherrie Campbell. “6 Characteristics of Resourceful People That Bring Them Success.” Entrepreneur. March 10, 2016. https://www.entrepreneur.com/article/272171
• 13 “Resourcefulness Is More Important Than Resources.” The Ecommerce Mindset: How Successful Store Owners Think. n.d. https://www.oberlo.com/ebooks/mindset/resourceful-entrepreneur

As an Amazon Associate we earn from qualifying purchases.

This book may not be used in the training of large language models or otherwise be ingested into large language models or generative AI offerings without OpenStax's permission.

Want to cite, share, or modify this book? This book uses the Creative Commons Attribution License and you must attribute OpenStax.

Access for free at https://openstax.org/books/entrepreneurship/pages/1-introduction

• Authors: Michael Laverty, Chris Littel
• Publisher/website: OpenStax
• Book title: Entrepreneurship
• Publication date: Jan 16, 2020
• Location: Houston, Texas
• Book URL: https://openstax.org/books/entrepreneurship/pages/1-introduction
• Section URL: https://openstax.org/books/entrepreneurship/pages/6-1-problem-solving-to-find-entrepreneurial-solutions

© Jan 4, 2024 OpenStax. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution License . The OpenStax name, OpenStax logo, OpenStax book covers, OpenStax CNX name, and OpenStax CNX logo are not subject to the Creative Commons license and may not be reproduced without the prior and express written consent of Rice University.

• SUGGESTED TOPICS
• The Magazine
• Newsletters
• Managing Yourself
• Managing Teams
• Work-life Balance
• The Big Idea
• Data & Visuals
• Reading Lists
• Case Selections
• HBR Learning
• Topic Feeds
• Account Settings
• Email Preferences

Share Podcast

The Right Way to Solve Complex Business Problems

Corey Phelps, a strategy professor at McGill University, says great problem solvers are hard to find. Even seasoned professionals at the highest levels of organizations regularly...

• Apple Podcasts
• Google Podcasts

Corey Phelps, a strategy professor at McGill University, says great problem solvers are hard to find. Even seasoned professionals at the highest levels of organizations regularly fail to identify the real problem and instead jump to exploring solutions. Phelps identifies the common traps and outlines a research-proven method to solve problems effectively. He’s the coauthor of the book, Cracked it! How to solve big problems and sell solutions like top strategy consultants.

Download this podcast

Welcome to the IdeaCast from Harvard Business Review. I’m Curt Nickisch.

Problem-solving is in demand. It’s considered the top skill for success at management consulting firms. And it’s increasingly desired for everyone, not just new MBA’s.

A report from the World Economic Forum predicts that more than one-third of all jobs across all industries will require complex problem-solving as one of their core skills by 2020.

The problem is, we’re often really bad at problem-solving. Our guest today says even the most educated and experienced of senior leaders go about it the wrong way.

COREY PHELPS: I think this is one of the misnomers about problem-solving. There’s this belief that because we do it so frequently – and especially for senior leaders, they have a lot of experience, they solve problems for a living – and as such we would expect them to be quite good at it. And I think what we find is that they’re not. They don’t solve problems well because they fall prey to basically the foibles of being a human being – they fall prey to the cognitive biases and the pitfalls of problem-solving.

CURT NICKISCH: That’s Corey Phelps. He says fixing these foibles is possible and almost straightforward. You can improve your problem-solving skills by following a disciplined method.

Corey Phelps is a strategy professor at McGill University. He’s also the co-author of the book “Cracked It: How to Solve Big Problems and Sell Solutions like Top Strategy C onsultants.” Corey thanks for coming on the show.

COREY PHELPS: Thank you for the opportunity to talk.

CURT NICKISCH: Another probably many, many biases that prevent people from solving big problems well.

COREY PHELPS: Absolutely.

CURT NICKISCH: What are some of the most common, or your favorite stumbling blocks?

COREY PHELPS: Well, one of my favorites is essentially the problem of jumping to solutions or the challenge of jumping to solutions.

CURT NICKISCH: Oh, come on Corey. That’s so much fun.

COREY PHELPS: It is, and it’s very much a result of how our brains have evolved to process information, but it’s my favorite because we all do it. And especially I would say it happens in organizations because in organizations when you layer on these time pressures and you layer on these concerns about efficiency and productivity, it creates enormous, I would say incentive to say “I don’t have time to carefully define and analyze the problem. I got to get a solution. I got to implement it as quick as possible.” And the fundamental bias I think is, is illustrated beautifully by Danny Kahneman in his book “Thinking, Fast and Slow,” is that our minds are essentially hardwired to think fast.

We are able to pay attention to a tiny little bit of information. We can then weave a very coherent story that makes sense to us. And then we can use that story to jump very quickly to a solution that we just know will work. And if we just were able to move from that approach of what Kahneman and cognitive psychologists called “System 1 thinking” to “System 2 thinking” – that is to slow down, be more deliberative, be more structured – we would be able to better understand the problem that we’re trying to solve and be more effective and exhaustive with the tools that we want to use to understand the problem before we actually go into solution-generation mode.

CURT NICKISCH: Complex problems demand different areas of expertise and often as individuals we’re coming to those problems with one of them. And I wonder if that’s often the problem of problem-solving, which is that a manager is approaching it from their own expertise and because of that, they see the problem through a certain way. Is that one of the cognitive biases that stop people from being effective problem solvers?

COREY PHELPS: Yeah. That’s often referred to as the expertise trap. It basically colors and influences what we pay attention to with respect to a particular problem. And it limits us with respect to the tools that we can bring to bear to solve that problem. In the world of psychology, there’s famous psychologist, Abraham Maslow, who is famous for the hierarchy of needs. He’s also famous for something that was a also known as MaSlow’s axiom, Maslow’s law. It’s also called the law of the instrument, and to paraphrase Maslow, he basically said, “Look, I suppose if the only tool that you have in your toolkit is a hammer, everything looks like a nail.”

His point is that if you’re, for example, a finance expert and your toolkit is the toolkit of let’s say, discounted cash flow analysis for valuation, then you’re going to see problems through that very narrow lens. Now, one of the ways out of this, I think to your point is collaboration becomes fundamentally important. And collaboration starts with the recognition that I don’t have all of the tools, all of the knowledge in me to effectively solve this. So I need to recruit people that can actually help me.

CURT NICKISCH: That’s really interesting. I wonder how much the fact that you have solved a problem before it makes you have a bias for that same solution for future problems?

COREY PHELPS: Yeah, that’s a great question. What you’re alluding to is analogical reasoning, and we know that human beings, one of the things that allows us to operate in novel settings is that we can draw on our past experience. And we do so when it comes to problem solving, often times without being conscious or mentally aware of it. We reach into our memory and we ask ourselves a very simple question: “Have I seen a problem like this before?”

And if it looks familiar to me, the tendency then is to say, “Okay, well what worked in solving that problem that I faced before?” And then to say, “Well, if it worked in that setting, then it should work in this setting.” So that’s reasoning by analogy.

Reasoning by analogy has a great upside. It allows human beings to not become overwhelmed by the tremendous novelty that they face in their daily lives. The downside is that if we don’t truly understand it at sort of a deep level, whether or not the two problems are similar or different, then we can make what cognitive psychologists called surface-level analogies.

And we can then say, “Oh, this looks a lot like the problem I faced before, that solution that worked there is going to easily work here.” And we try that solution and it fails and it fails largely because if we dug a little bit deeper, the two problems actually aren’t much alike at all in terms of their underlying causes.

CURT NICKISCH: The starkest example of this, I think, in your book is Ron Johnson who left Apple to become CEO of JC Penney. Can you talk about that a little bit and what that episode for the company says about this?

COREY PHELPS: So yes, its – Ron Johnson had been hired away from Target in the United States to, by Steve Jobs to help create Apple stores. Apple stores are as many people know the most successful physical retailer on the planet measured by, for example, sales per square foot or per square meter. He’s got the golden touch. He’s created this tremendously successful retail format for Apple.

So the day that it was announced that Ron Johnson was going to step into the CEO role at JC Penney, the stock price of JC Penney went up by almost 18 percent. So clearly he was viewed as the savior. Johnson moves very, very quickly. Within a few months, he announces that he has a strategic plan and it basically comes in three parts.

Part number one is he’s going to eliminate discount pricing. JC Penney had been a very aggressive sales promoter. The second piece of it is he’s going to completely change how they organize merchandise. It’s no longer going to be organized by function – so menswear, housewares, those sorts of things. It’s going to be organized by boutique, so there’s going to be a Levi’s boutique, a Martha Stewart Boutique, a Joe Fresh Boutique and so on.

And it would drop the JC P enney name, they would call it JCP. And he rolls this out over the course of about 12 months across the entire chain of over 1100 stores. What this tells us, he’s so confident in his solution, his strategic transformation, that he doesn’t think it’s worth it to test this out on one or two pilot stores.

CURT NICKISCH: Yeah, he was quoted as saying: “At Apple, we didn’t test anything.”

COREY PHELPS: We didn’t test. Yes. What worked at Apple, he assumed would work at JC Penney. And the critical thing that I think he missed is that JC Penney customers are very different from Apple store customers. In fact, JC Penney customers love the discount. They love the thrill of hunting for a deal.

CURT NICKISCH: Which seems so fundamental to business, right? Understanding your customer. It’s just kind of shocking, I guess, to hear the story.

COREY PHELPS: It is shocking and especially when you consider that Ron Johnson had spent his entire career in retail, so this is someone that had faced, had seen, problems in retailers for decades – for over three decades by the time that he got to JC Penney. So you would expect someone with that degree of experience in that industry wouldn’t make that leap of, well, what worked at Apple stores is going to work at JC Penney stores, but in fact that’s exactly what happened.

CURT NICKISCH: In your book, you essentially suggest four steps that you recommend people use. Tell us about the four steps then.

COREY PHELPS: So in the book we describe what we call the “Four S method,” so four stages, each of which starts with the letter “s”. So the first stage is “state the problem.” Stating the problem is fundamentally about defining what the problem is that you are attempting to solve.

CURT NICKISCH: And you probably would say don’t hurry over that first step or the other three are going to be kind of pointless.

COREY PHELPS: Yeah, that’s exactly the point of of laying out the four s’s. There’s a tremendous amount of desire even amongst senior executives to want to get in and fix the problem. In other words, what’s the trouble? What are the symptoms? What would define success? What are the constraints that we would be operating under? Who owns the problem? And then who are the key stakeholders?

Oftentimes that step is skipped over and we go right into, “I’ve got a hypothesis about what I think the solution is and I’m so obsessed with getting this thing fixed quickly, I’m not going to bother to analyze it particularly well or test the validity of my assumptions. I’m going to go right into implementation mode.”

The second step, what we call “structure the problem” is once you have defined the problem, you need to then start to identify what are the potential causes of that problem. So there are different tools that we talked about in the book that you can structure a problem for analysis. Once you’ve structured the problem for analysis and you’ve conducted the analysis that helps you identify what are the underlying causes that are contributing to it, which will then inform the third stage which is generating solutions for the problem and then testing and evaluating those solutions.

CURT NICKISCH: Is the danger that that third step – generating solutions – is the step that people spend the most time on or have the most fun with?

COREY PHELPS: Yeah. The danger is, is that what that’s naturally what people gravitate towards. So we want to skip over the first two, state and structure.

CURT NICKISCH: As soon as you said it, I was like, “let’s talk about that more.”

COREY PHELPS: Yeah. And we want to jump right into solutioning because people love to talk about their ideas that are going to fix the problem. And that’s actually a useful way to frame a discussion about solutions – we could, or we might do this – because it opens up possibilities for experimentation.

And the problem is that when we often talk about what we could do, we have very little understanding of what the problem is that we’re trying to solve and what are the underlying causes of that problem. Because as you said, solution generation is fun. Look, the classic example is brainstorming. Let’s get a bunch of people in a room and let’s talk about the ideas on how to fix this thing. And again, be deliberate, be disciplined. Do those first stages, the first two stages – state and structure – before you get into the solution generation phase.

CURT NICKISCH: Yeah. The other thing that often happens there is just the lack of awareness of just the cost of the different solutions – how much time, or what they would actually take to do.

COREY PHELPS: Yeah, and again, I’ll go back to that example I used of brainstorming where it’s fun to get a group of people together and talk about our ideas and how to fix the problem. There’s a couple challenges of that. One is what often happens when we do that is we tend to censor the solutions that we come up with. In other words, we ask ourselves, “if I say this idea, people are gonna, think I’m crazy, or people going to say: that’s stupid, that’ll never work, we can’t do that in our organization. It’s going to be too expensive, it’s going to take too much time. We don’t have the resources to do it.”

So brainstorming downside is we we self-sensor, so that’s where you need to have deep insight into your organization in terms of A. what’s going to be feasible, B. what’s going to be desirable on the part of the people that actually have the problem, who you’re trying to solve the problem for and C. from a business standpoint, is it going to be financially attractive for us?

So applying again a set of disciplined criteria that help you choose amongst those ideas for potential solutions. Then the last stage of the process which is selling – because it’s rare in any organization that someone or the group of people that come up with the solution actually have the power and the resources to implement it, so that means they’re going to have to persuade other people to buy into it and want to help.

CURT NICKISCH: Design thinking is another really different method essentially for solving problems or coming up with solutions that just aren’t arrived at through usual problem-solving or usual decision-making processes. I’m just wondering how design thinking comes to play when you’re also outlining these, you know, disciplined methods for stating and solving problems.

COREY PHELPS: For us it’s about choosing the right approach. You know what the potential causes of a problem are. You just don’t know which ones are operating in the particular problem you’re trying to solve. And what that means is that you’ve got a theory – and this is largely the world of strategy consultants – strategy consultants have theories. They have, if you hear them speak, deep understanding of different types of organizational problems, and what they bring is an analytic tool kit that says, “first we’re going to identify all the possible problems, all the possible causes I should say, of this problem. We’re going to figure out which ones are operating and we’re going to use that to come up with a solution.” Then you’ve got problems that you have no idea what the causes are. You’re in a world of unknown unknowns or unk-unks as the operations management people call them.

CURT NICKISCH: That’s terrible.

COREY PHELPS: In other words, you don’t have a theory. So the question is, how do you begin? Well, this is where design thinking can be quite valuable. Design thinking says: first off, let’s find out who are the human beings, the people that are actually experiencing this problem, and let’s go out and let’s talk to them. Let’s observe them. Let’s immerse ourselves in their experience and let’s start to develop an understanding of the causes of the problem from their perspective.

So rather than go into it and say, “I have a theory,” let’s go the design thinking route and let’s actually based upon interactions with users or customers, let’s actually develop a theory. And then we’ll use our new understanding or new insight into the causes of the problem to move into the solution generation phase.

CURT NICKISCH: Problem-solving – we know that that’s something that employers look for when they’re recruiting people. It is one of those phrases that, you know, I’m sure somebody out there has, has the title at a company Chief Problem Solver instead of CEO, right? So, it’s almost one of those phrases that so over used it can lose its meaning.

And if you are being hired or you’re trying to make a case for being on a team that’s tackling a problem, how do you make a compelling case that you are a good problem solver? How can you actually show it?

COREY PHELPS: It’s a great question and then I have two answers to this question. So one is, look at the end of the day, the proof is in the pudding. In other words, can you point to successful solutions that you’ve come up with – solutions that have actually been effective in solving a problem? So that’s one.

The second thing is can you actually articulate how you approach problem-solving? In other words, do you follow a method or are you reinventing the wheel every time you solve a problem? Is it an ad hoc approach? And I think this issue really comes to a head when it comes to the world of strategy consulting firms when they recruit. For example, Mckinsey, you’ve got the Mckinsey problem-solving test, which is again, a test that’s actually trying to elicit the extent to which people are good applicants are good at solving problems

And then you’ve got the case interview. And in the case interview, what they’re looking at is do you have a mastery over certain tools. But what they’re really looking at is, are you actually following a logical process to solve this problem? Because again, what they’re interested in is finding- to your point – people that are going to be good at solving complex organizational problems. So they’re trying to get some evidence that they can demonstrate that they’re good at it and some evidence that they follow a deliberate process.

CURT NICKISCH: So even if you’re not interviewing at a consulting firm, that’s a good approach, to show your thinking, show your process, show the questions you ask?

COREY PHELPS: Yeah, and to your point earlier, at least if we look at what recruiters of MBA students are saying these days, they’re saying, for example, according to the FT’s recent survey, they’re saying that we want people with really good problem solving skills, and by the same token, we find that that’s a skill that’s difficult for us to recruit for. And that reinforces our interest in this area because the fundamental idea for the book is to give people a method. We’re trying to equip not just MBA students but everybody that’s going to face complex problems with a toolkit to solve them better.

CURT NICKISCH: Corey, this has been really great. Thank you.

COREY PHELPS: Thanks for the opportunity. I appreciate it.

CURT NICKISCH: That’s Corey Phelps. He teaches strategy at McGill University, and he co-wrote the book “Cracked It: How to Solve Big Problems and Sell Solutions Like Top Strategy Consultants.”

This episode was produced by Mary Dooe. We got technical help from Rob Eckhardt. Adam Buchholz is our audio product manager.

Thanks for listening to the HBR IdeaCast. I’m Curt Nickisch.

• Subscribe On:

Latest in this series

This article is about decision making and problem solving, partner center.

• The Art of Effective Problem Solving: A Step-by-Step Guide
• Learn Lean Sigma
• Problem Solving

Whether we realise it or not, problem solving skills are an important part of our daily lives. From resolving a minor annoyance at home to tackling complex business challenges at work, our ability to solve problems has a significant impact on our success and happiness. However, not everyone is naturally gifted at problem-solving, and even those who are can always improve their skills. In this blog post, we will go over the art of effective problem-solving step by step.

You will learn how to define a problem, gather information, assess alternatives, and implement a solution, all while honing your critical thinking and creative problem-solving skills. Whether you’re a seasoned problem solver or just getting started, this guide will arm you with the knowledge and tools you need to face any challenge with confidence. So let’s get started!

Table of Contents

Problem solving methodologies.

Individuals and organisations can use a variety of problem-solving methodologies to address complex challenges. 8D and A3 problem solving techniques are two popular methodologies in the Lean Six Sigma framework.

Methodology of 8D (Eight Discipline) Problem Solving:

The 8D problem solving methodology is a systematic, team-based approach to problem solving. It is a method that guides a team through eight distinct steps to solve a problem in a systematic and comprehensive manner.

The 8D process consists of the following steps:

• Form a team: Assemble a group of people who have the necessary expertise to work on the problem.
• Define the issue: Clearly identify and define the problem, including the root cause and the customer impact.
• Create a temporary containment plan: Put in place a plan to lessen the impact of the problem until a permanent solution can be found.
• Identify the root cause: To identify the underlying causes of the problem, use root cause analysis techniques such as Fishbone diagrams and Pareto charts.
• Create and test long-term corrective actions: Create and test a long-term solution to eliminate the root cause of the problem.
• Implement and validate the permanent solution: Implement and validate the permanent solution’s effectiveness.
• Prevent recurrence: Put in place measures to keep the problem from recurring.
• Recognize and reward the team: Recognize and reward the team for its efforts.

Download the 8D Problem Solving Template

A3 Problem Solving Method:

The A3 problem solving technique is a visual, team-based problem-solving approach that is frequently used in Lean Six Sigma projects. The A3 report is a one-page document that clearly and concisely outlines the problem, root cause analysis, and proposed solution.

The A3 problem-solving procedure consists of the following steps:

• Determine the issue: Define the issue clearly, including its impact on the customer.
• Perform root cause analysis: Identify the underlying causes of the problem using root cause analysis techniques.
• Create and implement a solution: Create and implement a solution that addresses the problem’s root cause.
• Monitor and improve the solution: Keep an eye on the solution’s effectiveness and make any necessary changes.

Subsequently, in the Lean Six Sigma framework, the 8D and A3 problem solving methodologies are two popular approaches to problem solving. Both methodologies provide a structured, team-based problem-solving approach that guides individuals through a comprehensive and systematic process of identifying, analysing, and resolving problems in an effective and efficient manner.

Step 1 – Define the Problem

The definition of the problem is the first step in effective problem solving. This may appear to be a simple task, but it is actually quite difficult. This is because problems are frequently complex and multi-layered, making it easy to confuse symptoms with the underlying cause. To avoid this pitfall, it is critical to thoroughly understand the problem.

To begin, ask yourself some clarifying questions:

• What exactly is the issue?
• What are the problem’s symptoms or consequences?
• Who or what is impacted by the issue?
• When and where does the issue arise?

Answering these questions will assist you in determining the scope of the problem. However, simply describing the problem is not always sufficient; you must also identify the root cause. The root cause is the underlying cause of the problem and is usually the key to resolving it permanently.

Try asking “why” questions to find the root cause:

• What causes the problem?
• Why does it continue?
• Why does it have the effects that it does?

By repeatedly asking “ why ,” you’ll eventually get to the bottom of the problem. This is an important step in the problem-solving process because it ensures that you’re dealing with the root cause rather than just the symptoms.

Once you have a firm grasp on the issue, it is time to divide it into smaller, more manageable chunks. This makes tackling the problem easier and reduces the risk of becoming overwhelmed. For example, if you’re attempting to solve a complex business problem, you might divide it into smaller components like market research, product development, and sales strategies.

To summarise step 1, defining the problem is an important first step in effective problem-solving. You will be able to identify the root cause and break it down into manageable parts if you take the time to thoroughly understand the problem. This will prepare you for the next step in the problem-solving process, which is gathering information and brainstorming ideas.

Step 2 – Gather Information and Brainstorm Ideas

Gathering information and brainstorming ideas is the next step in effective problem solving. This entails researching the problem and relevant information, collaborating with others, and coming up with a variety of potential solutions. This increases your chances of finding the best solution to the problem.

Begin by researching the problem and relevant information. This could include reading articles, conducting surveys, or consulting with experts. The goal is to collect as much information as possible in order to better understand the problem and possible solutions.

Next, work with others to gather a variety of perspectives. Brainstorming with others can be an excellent way to come up with new and creative ideas. Encourage everyone to share their thoughts and ideas when working in a group, and make an effort to actively listen to what others have to say. Be open to new and unconventional ideas and resist the urge to dismiss them too quickly.

Finally, use brainstorming to generate a wide range of potential solutions. This is the place where you can let your imagination run wild. At this stage, don’t worry about the feasibility or practicality of the solutions; instead, focus on generating as many ideas as possible. Write down everything that comes to mind, no matter how ridiculous or unusual it may appear. This can be done individually or in groups.

Once you’ve compiled a list of potential solutions, it’s time to assess them and select the best one. This is the next step in the problem-solving process, which we’ll go over in greater detail in the following section.

Step 3 – Evaluate Options and Choose the Best Solution

Once you’ve compiled a list of potential solutions, it’s time to assess them and select the best one. This is the third step in effective problem solving, and it entails weighing the advantages and disadvantages of each solution, considering their feasibility and practicability, and selecting the solution that is most likely to solve the problem effectively.

To begin, weigh the advantages and disadvantages of each solution. This will assist you in determining the potential outcomes of each solution and deciding which is the best option. For example, a quick and easy solution may not be the most effective in the long run, whereas a more complex and time-consuming solution may be more effective in solving the problem in the long run.

Consider each solution’s feasibility and practicability. Consider the following:

• Can the solution be implemented within the available resources, time, and budget?
• What are the possible barriers to implementing the solution?
• Is the solution feasible in today’s political, economic, and social environment?

You’ll be able to tell which solutions are likely to succeed and which aren’t by assessing their feasibility and practicability.

Finally, choose the solution that is most likely to effectively solve the problem. This solution should be based on the criteria you’ve established, such as the advantages and disadvantages of each solution, their feasibility and practicability, and your overall goals.

It is critical to remember that there is no one-size-fits-all solution to problems. What is effective for one person or situation may not be effective for another. This is why it is critical to consider a wide range of solutions and evaluate each one based on its ability to effectively solve the problem.

Step 4 – Implement and Monitor the Solution

When you’ve decided on the best solution, it’s time to put it into action. The fourth and final step in effective problem solving is to put the solution into action, monitor its progress, and make any necessary adjustments.

To begin, implement the solution. This may entail delegating tasks, developing a strategy, and allocating resources. Ascertain that everyone involved understands their role and responsibilities in the solution’s implementation.

Next, keep an eye on the solution’s progress. This may entail scheduling regular check-ins, tracking metrics, and soliciting feedback from others. You will be able to identify any potential roadblocks and make any necessary adjustments in a timely manner if you monitor the progress of the solution.

Finally, make any necessary modifications to the solution. This could entail changing the solution, altering the plan of action, or delegating different tasks. Be willing to make changes if they will improve the solution or help it solve the problem more effectively.

It’s important to remember that problem solving is an iterative process, and there may be times when you need to start from scratch. This is especially true if the initial solution does not effectively solve the problem. In these situations, it’s critical to be adaptable and flexible and to keep trying new solutions until you find the one that works best.

To summarise, effective problem solving is a critical skill that can assist individuals and organisations in overcoming challenges and achieving their objectives. Effective problem solving consists of four key steps: defining the problem, generating potential solutions, evaluating alternatives and selecting the best solution, and implementing the solution.

You can increase your chances of success in problem solving by following these steps and considering factors such as the pros and cons of each solution, their feasibility and practicability, and making any necessary adjustments. Furthermore, keep in mind that problem solving is an iterative process, and there may be times when you need to go back to the beginning and restart. Maintain your adaptability and try new solutions until you find the one that works best for you.

• Novick, L.R. and Bassok, M., 2005.  Problem Solving . Cambridge University Press.

Daniel Croft

Daniel Croft is a seasoned continuous improvement manager with a Black Belt in Lean Six Sigma. With over 10 years of real-world application experience across diverse sectors, Daniel has a passion for optimizing processes and fostering a culture of efficiency. He's not just a practitioner but also an avid learner, constantly seeking to expand his knowledge. Outside of his professional life, Daniel has a keen Investing, statistics and knowledge-sharing, which led him to create the website learnleansigma.com, a platform dedicated to Lean Six Sigma and process improvement insights.

Free Lean Six Sigma Templates

Improve your Lean Six Sigma projects with our free templates. They're designed to make implementation and management easier, helping you achieve better results.

5S Floor Marking Best Practices

In lean manufacturing, the 5S System is a foundational tool, involving the steps: Sort, Set…

How to Measure the ROI of Continuous Improvement Initiatives

When it comes to business, knowing the value you’re getting for your money is crucial,…

8D Problem-Solving: Common Mistakes to Avoid

In today’s competitive business landscape, effective problem-solving is the cornerstone of organizational success. The 8D…

The Evolution of 8D Problem-Solving: From Basics to Excellence

In a world where efficiency and effectiveness are more than just buzzwords, the need for…

8D: Tools and Techniques

Are you grappling with recurring problems in your organization and searching for a structured way…

How to Select the Right Lean Six Sigma Projects: A Comprehensive Guide

Going on a Lean Six Sigma journey is an invigorating experience filled with opportunities for…

Six Steps to Develop an Effective Problem-Solving Process

by Rawzaba Alhalabi Published on November 1, 2017

Problem-solving involves thought and understanding. Although it may appear simple, identifying a problem may be a challenging process.

“Problems are only opportunities in work clothes”, says American industrialist Henry Kaiser. According to Concise Oxford Dictionary (1995), a problem is “ doubtful or difficult matter requiring a solution” and “something hard to understand or accomplish or deal with.” Such situations are at the center of what many people do at work every day.

Whether to help a client solve a problem, support a problem-solver, or to discover new problems, problem-solving is a crucial element to the workplace ingredients. Everyone can benefit from effective problem-solving skills that would make people happier. Everyone wins. Hence, this approach is a critical element but how can you do it effectively? You need to find a solution, but not right away. People tend to put the solution at the beginning of the process but they actually needed it at the end of the process.

Here are six steps to an effective problem-solving process:

Identify the issues, understand everyone’s interests, list the possible solutions, make a decision, implement the solution.

By following the whole process, you will be able to enhance your problem-solving skills and increase your patience. Keep in mind that effective problem solving does take some time and attention. You have to always be ready to hit the brakes and slow down. A problem is like a bump road. Take it right and you’ll find yourself in good shape for the straightaway that follows. Take it too fast and you may not be in as good shape.

Case study 1:

According to Real Time Economics, there are industries that have genuinely evolved, with more roles for people with analytical and problem-solving skills. In healthcare, for example, a regulatory change requiring the digitization of health records has led to greater demand for medical records technicians. Technological change in the manufacturing industry has reduced routine factory jobs while demanding more skilled workers who can operate complex machinery.

Case study 2:

Yolanda was having a hard time dealing with difficult clients and dealing with her team at the office, so she decided to take a problem-solving course. “I was very pleased with the 2-day Problem Solving program at RSM.  It is an excellent investment for anyone involved in the strategic decision-making process—be it in their own company or as a consultant charged with supporting organizations facing strategic challenges.“

Yolanda Barreros Gutiérrez, B&C Consulting

As a response to the COVID-19 outbreak, Potential.com is offering individuals free access to our future skills library (20+ Courses) to support you during the COVID outbreak. It’s your chance to learn essential skills to help you prepare for future jobs. Register now for free using your details and coupon code: potentialreader .

Click here to register (coupon embedded) .

Having read this I believed it was extremely enlightening. I appreciate you taking the time and energy to put tis informative article together. I onc again findd myself spending a significant amount of time both reading and leavfing comments. But so what, it was still worth it!

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Save my name, email, and website in this browser for the next time I comment.

Subscribe to our newsletter

• Bipolar Disorder
• Therapy Center
• When To See a Therapist
• Types of Therapy
• Best Online Therapy
• Best Couples Therapy
• Best Family Therapy
• Managing Stress
• Sleep and Dreaming
• Understanding Emotions
• Self-Improvement
• Healthy Relationships
• Student Resources
• Personality Types
• Guided Meditations
• Verywell Mind Insights
• 2023 Verywell Mind 25
• Mental Health in the Classroom
• Editorial Process
• Meet Our Review Board
• Crisis Support

Overview of the Problem-Solving Mental Process

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Rachel Goldman, PhD FTOS, is a licensed psychologist, clinical assistant professor, speaker, wellness expert specializing in eating behaviors, stress management, and health behavior change.

• Identify the Problem
• Define the Problem
• Form a Strategy
• Organize Information
• Allocate Resources
• Monitor Progress
• Evaluate the Results

Frequently Asked Questions

Problem-solving is a mental process that involves discovering, analyzing, and solving problems. The ultimate goal of problem-solving is to overcome obstacles and find a solution that best resolves the issue.

The best strategy for solving a problem depends largely on the unique situation. In some cases, people are better off learning everything they can about the issue and then using factual knowledge to come up with a solution. In other instances, creativity and insight are the best options.

It is not necessary to follow problem-solving steps sequentially, It is common to skip steps or even go back through steps multiple times until the desired solution is reached.

In order to correctly solve a problem, it is often important to follow a series of steps. Researchers sometimes refer to this as the problem-solving cycle. While this cycle is portrayed sequentially, people rarely follow a rigid series of steps to find a solution.

The following steps include developing strategies and organizing knowledge.

1. Identifying the Problem

While it may seem like an obvious step, identifying the problem is not always as simple as it sounds. In some cases, people might mistakenly identify the wrong source of a problem, which will make attempts to solve it inefficient or even useless.

Some strategies that you might use to figure out the source of a problem include :

• Asking questions about the problem
• Breaking the problem down into smaller pieces
• Looking at the problem from different perspectives
• Conducting research to figure out what relationships exist between different variables

2. Defining the Problem

After the problem has been identified, it is important to fully define the problem so that it can be solved. You can define a problem by operationally defining each aspect of the problem and setting goals for what aspects of the problem you will address

At this point, you should focus on figuring out which aspects of the problems are facts and which are opinions. State the problem clearly and identify the scope of the solution.

3. Forming a Strategy

After the problem has been identified, it is time to start brainstorming potential solutions. This step usually involves generating as many ideas as possible without judging their quality. Once several possibilities have been generated, they can be evaluated and narrowed down.

The next step is to develop a strategy to solve the problem. The approach used will vary depending upon the situation and the individual's unique preferences. Common problem-solving strategies include heuristics and algorithms.

• Heuristics are mental shortcuts that are often based on solutions that have worked in the past. They can work well if the problem is similar to something you have encountered before and are often the best choice if you need a fast solution.
• Algorithms are step-by-step strategies that are guaranteed to produce a correct result. While this approach is great for accuracy, it can also consume time and resources.

Heuristics are often best used when time is of the essence, while algorithms are a better choice when a decision needs to be as accurate as possible.

4. Organizing Information

Before coming up with a solution, you need to first organize the available information. What do you know about the problem? What do you not know? The more information that is available the better prepared you will be to come up with an accurate solution.

When approaching a problem, it is important to make sure that you have all the data you need. Making a decision without adequate information can lead to biased or inaccurate results.

5. Allocating Resources

Of course, we don't always have unlimited money, time, and other resources to solve a problem. Before you begin to solve a problem, you need to determine how high priority it is.

If it is an important problem, it is probably worth allocating more resources to solving it. If, however, it is a fairly unimportant problem, then you do not want to spend too much of your available resources on coming up with a solution.

At this stage, it is important to consider all of the factors that might affect the problem at hand. This includes looking at the available resources, deadlines that need to be met, and any possible risks involved in each solution. After careful evaluation, a decision can be made about which solution to pursue.

6. Monitoring Progress

After selecting a problem-solving strategy, it is time to put the plan into action and see if it works. This step might involve trying out different solutions to see which one is the most effective.

It is also important to monitor the situation after implementing a solution to ensure that the problem has been solved and that no new problems have arisen as a result of the proposed solution.

Effective problem-solvers tend to monitor their progress as they work towards a solution. If they are not making good progress toward reaching their goal, they will reevaluate their approach or look for new strategies .

7. Evaluating the Results

After a solution has been reached, it is important to evaluate the results to determine if it is the best possible solution to the problem. This evaluation might be immediate, such as checking the results of a math problem to ensure the answer is correct, or it can be delayed, such as evaluating the success of a therapy program after several months of treatment.

Once a problem has been solved, it is important to take some time to reflect on the process that was used and evaluate the results. This will help you to improve your problem-solving skills and become more efficient at solving future problems.

A Word From Verywell​

It is important to remember that there are many different problem-solving processes with different steps, and this is just one example. Problem-solving in real-world situations requires a great deal of resourcefulness, flexibility, resilience, and continuous interaction with the environment.

Get Advice From The Verywell Mind Podcast

Hosted by therapist Amy Morin, LCSW, this episode of The Verywell Mind Podcast shares how you can stop dwelling in a negative mindset.

Follow Now : Apple Podcasts / Spotify / Google Podcasts

You can become a better problem solving by:

• Practicing brainstorming and coming up with multiple potential solutions to problems
• Being open-minded and considering all possible options before making a decision
• Breaking down problems into smaller, more manageable pieces
• Asking for help when needed
• Researching different problem-solving techniques and trying out new ones
• Learning from mistakes and using them as opportunities to grow

It's important to communicate openly and honestly with your partner about what's going on. Try to see things from their perspective as well as your own. Work together to find a resolution that works for both of you. Be willing to compromise and accept that there may not be a perfect solution.

Take breaks if things are getting too heated, and come back to the problem when you feel calm and collected. Don't try to fix every problem on your own—consider asking a therapist or counselor for help and insight.

If you've tried everything and there doesn't seem to be a way to fix the problem, you may have to learn to accept it. This can be difficult, but try to focus on the positive aspects of your life and remember that every situation is temporary. Don't dwell on what's going wrong—instead, think about what's going right. Find support by talking to friends or family. Seek professional help if you're having trouble coping.

Davidson JE, Sternberg RJ, editors.  The Psychology of Problem Solving .  Cambridge University Press; 2003. doi:10.1017/CBO9780511615771

Sarathy V. Real world problem-solving .  Front Hum Neurosci . 2018;12:261. Published 2018 Jun 26. doi:10.3389/fnhum.2018.00261

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

What is Problem Solving? (Steps, Techniques, Examples)

By Status.net Editorial Team on May 7, 2023 — 5 minutes to read

What Is Problem Solving?

Definition and importance.

Problem solving is the process of finding solutions to obstacles or challenges you encounter in your life or work. It is a crucial skill that allows you to tackle complex situations, adapt to changes, and overcome difficulties with ease. Mastering this ability will contribute to both your personal and professional growth, leading to more successful outcomes and better decision-making.

Problem-Solving Steps

The problem-solving process typically includes the following steps:

• Identify the issue : Recognize the problem that needs to be solved.
• Analyze the situation : Examine the issue in depth, gather all relevant information, and consider any limitations or constraints that may be present.
• Generate potential solutions : Brainstorm a list of possible solutions to the issue, without immediately judging or evaluating them.
• Evaluate options : Weigh the pros and cons of each potential solution, considering factors such as feasibility, effectiveness, and potential risks.
• Select the best solution : Choose the option that best addresses the problem and aligns with your objectives.
• Implement the solution : Put the selected solution into action and monitor the results to ensure it resolves the issue.
• Review and learn : Reflect on the problem-solving process, identify any improvements or adjustments that can be made, and apply these learnings to future situations.

Defining the Problem

To start tackling a problem, first, identify and understand it. Analyzing the issue thoroughly helps to clarify its scope and nature. Ask questions to gather information and consider the problem from various angles. Some strategies to define the problem include:

• Brainstorming with others
• Asking the 5 Ws and 1 H (Who, What, When, Where, Why, and How)
• Analyzing cause and effect
• Creating a problem statement

Generating Solutions

Once the problem is clearly understood, brainstorm possible solutions. Think creatively and keep an open mind, as well as considering lessons from past experiences. Consider:

• Creating a list of potential ideas to solve the problem
• Grouping and categorizing similar solutions
• Prioritizing potential solutions based on feasibility, cost, and resources required
• Involving others to share diverse opinions and inputs

Evaluating and Selecting Solutions

Evaluate each potential solution, weighing its pros and cons. To facilitate decision-making, use techniques such as:

• SWOT analysis (Strengths, Weaknesses, Opportunities, Threats)
• Decision-making matrices
• Pros and cons lists
• Risk assessments

After evaluating, choose the most suitable solution based on effectiveness, cost, and time constraints.

Implementing and Monitoring the Solution

Implement the chosen solution and monitor its progress. Key actions include:

• Communicating the solution to relevant parties
• Setting timelines and milestones
• Assigning tasks and responsibilities
• Monitoring the solution and making adjustments as necessary
• Evaluating the effectiveness of the solution after implementation

Utilize feedback from stakeholders and consider potential improvements. Remember that problem-solving is an ongoing process that can always be refined and enhanced.

Problem-Solving Techniques

During each step, you may find it helpful to utilize various problem-solving techniques, such as:

• Brainstorming : A free-flowing, open-minded session where ideas are generated and listed without judgment, to encourage creativity and innovative thinking.
• Root cause analysis : A method that explores the underlying causes of a problem to find the most effective solution rather than addressing superficial symptoms.
• SWOT analysis : A tool used to evaluate the strengths, weaknesses, opportunities, and threats related to a problem or decision, providing a comprehensive view of the situation.
• Mind mapping : A visual technique that uses diagrams to organize and connect ideas, helping to identify patterns, relationships, and possible solutions.

Brainstorming

When facing a problem, start by conducting a brainstorming session. Gather your team and encourage an open discussion where everyone contributes ideas, no matter how outlandish they may seem. This helps you:

• Generate a diverse range of solutions
• Encourage all team members to participate
• Foster creative thinking

When brainstorming, remember to:

• Reserve judgment until the session is over
• Encourage wild ideas
• Combine and improve upon ideas

Root Cause Analysis

For effective problem-solving, identifying the root cause of the issue at hand is crucial. Try these methods:

• 5 Whys : Ask “why” five times to get to the underlying cause.
• Fishbone Diagram : Create a diagram representing the problem and break it down into categories of potential causes.
• Pareto Analysis : Determine the few most significant causes underlying the majority of problems.

SWOT Analysis

SWOT analysis helps you examine the Strengths, Weaknesses, Opportunities, and Threats related to your problem. To perform a SWOT analysis:

• List your problem’s strengths, such as relevant resources or strong partnerships.
• Identify its weaknesses, such as knowledge gaps or limited resources.
• Explore opportunities, like trends or new technologies, that could help solve the problem.
• Recognize potential threats, like competition or regulatory barriers.

SWOT analysis aids in understanding the internal and external factors affecting the problem, which can help guide your solution.

Mind Mapping

A mind map is a visual representation of your problem and potential solutions. It enables you to organize information in a structured and intuitive manner. To create a mind map:

• Write the problem in the center of a blank page.
• Draw branches from the central problem to related sub-problems or contributing factors.
• Add more branches to represent potential solutions or further ideas.

Mind mapping allows you to visually see connections between ideas and promotes creativity in problem-solving.

Examples of Problem Solving in Various Contexts

In the business world, you might encounter problems related to finances, operations, or communication. Applying problem-solving skills in these situations could look like:

• Identifying areas of improvement in your company’s financial performance and implementing cost-saving measures
• Resolving internal conflicts among team members by listening and understanding different perspectives, then proposing and negotiating solutions
• Streamlining a process for better productivity by removing redundancies, automating tasks, or re-allocating resources

In educational contexts, problem-solving can be seen in various aspects, such as:

• Addressing a gap in students’ understanding by employing diverse teaching methods to cater to different learning styles
• Developing a strategy for successful time management to balance academic responsibilities and extracurricular activities
• Seeking resources and support to provide equal opportunities for learners with special needs or disabilities

Everyday life is full of challenges that require problem-solving skills. Some examples include:

• Overcoming a personal obstacle, such as improving your fitness level, by establishing achievable goals, measuring progress, and adjusting your approach accordingly
• Navigating a new environment or city by researching your surroundings, asking for directions, or using technology like GPS to guide you
• Dealing with a sudden change, like a change in your work schedule, by assessing the situation, identifying potential impacts, and adapting your plans to accommodate the change.
• How to Resolve Employee Conflict at Work [Steps, Tips, Examples]
• How to Write Inspiring Core Values? 5 Steps with Examples
• 30 Employee Feedback Examples (Positive & Negative)

• Skip to main content
• Skip to primary sidebar
• Skip to footer

Additional menu

The 5 steps of the solving problem process

August 17, 2023 by MindManager Blog

Whether you run a business, manage a team, or work in an industry where change is the norm, it may feel like something is always going wrong. Thankfully, becoming proficient in the problem solving process can alleviate a great deal of the stress that business issues can create.

Understanding the right way to solve problems not only takes the guesswork out of how to deal with difficult, unexpected, or complex situations, it can lead to more effective long-term solutions.

In this article, we’ll walk you through the 5 steps of problem solving, and help you explore a few examples of problem solving scenarios where you can see the problem solving process in action before putting it to work.

Understanding the problem solving process

When something isn’t working, it’s important to understand what’s at the root of the problem so you can fix it and prevent it from happening again. That’s why resolving difficult or complex issues works best when you apply proven business problem solving tools and techniques – from soft skills, to software.

The problem solving process typically includes:

• Pinpointing what’s broken by gathering data and consulting with team members.
• Figuring out why it’s not working by mapping out and troubleshooting the problem.
• Deciding on the most effective way to fix it by brainstorming and then implementing a solution.

While skills like active listening, collaboration, and leadership play an important role in problem solving, tools like visual mapping software make it easier to define and share problem solving objectives, play out various solutions, and even put the best fit to work.

Before you can take your first step toward solving a problem, you need to have a clear idea of what the issue is and the outcome you want to achieve by resolving it.

For example, if your company currently manufactures 50 widgets a day, but you’ve started processing orders for 75 widgets a day, you could simply say you have a production deficit.

However, the problem solving process will prove far more valuable if you define the start and end point by clarifying that production is running short by 25 widgets a day, and you need to increase daily production by 50%.

Once you know where you’re at and where you need to end up, these five steps will take you from Point A to Point B:

• Figure out what’s causing the problem . You may need to gather knowledge and evaluate input from different documents, departments, and personnel to isolate the factors that are contributing to your problem. Knowledge visualization software like MindManager can help.
• Come up with a few viable solutions . Since hitting on exactly the right solution – right away – can be tough, brainstorming with your team and mapping out various scenarios is the best way to move forward. If your first strategy doesn’t pan out, you’ll have others on tap you can turn to.
• Choose the best option . Decision-making skills, and software that lets you lay out process relationships, priorities, and criteria, are invaluable for selecting the most promising solution. Whether it’s you or someone higher up making that choice, it should include weighing costs, time commitments, and any implementation hurdles.
• Put your chosen solution to work . Before implementing your fix of choice, you should make key personnel aware of changes that might affect their daily workflow, and set up benchmarks that will make it easy to see if your solution is working.
• Evaluate your outcome . Now comes the moment of truth: did the solution you implemented solve your problem? Do your benchmarks show you achieved the outcome you wanted? If so, congratulations! If not, you’ll need to tweak your solution to meet your problem solving goal.

In practice, you might not hit a home-run with every solution you execute. But the beauty of a repeatable process like problem solving is that you can carry out steps 4 and 5 again by drawing from the brainstorm options you documented during step 2.

Examples of problem solving scenarios

The best way to get a sense of how the problem solving process works before you try it for yourself is to work through some simple scenarios.

Here are three examples of how you can apply business problem solving techniques to common workplace challenges.

Scenario #1: Manufacturing

Building on our original manufacturing example, you determine that your company is consistently short producing 25 widgets a day and needs to increase daily production by 50%.

Since you’d like to gather data and input from both your manufacturing and sales order departments, you schedule a brainstorming session to discover the root cause of the shortage.

After examining four key production areas – machines, materials, methods, and management – you determine the cause of the problem: the material used to manufacture your widgets can only be fed into your equipment once the machinery warms up to a specific temperature for the day.

Your team comes up with three possible solutions.

• Leave your machinery running 24 hours so it’s always at temperature.
• Invest in equipment that heats up faster.
• Find an alternate material for your widgets.

After weighing the expense of the first two solutions, and conducting some online research, you decide that switching to a comparable but less expensive material that can be worked at a lower temperature is your best option.

You implement your plan, monitor your widget quality and output over the following week, and declare your solution a success when daily production increases by 100%.

Scenario #2: Service Delivery

Business training is booming and you’ve had to onboard new staff over the past month. Now you learn that several clients have expressed concern about the quality of your recent training sessions.

After speaking with both clients and staff, you discover there are actually two distinct factors contributing to your quality problem:

• The additional conference room you’ve leased to accommodate your expanding training sessions has terrible acoustics
• The AV equipment you’ve purchased to accommodate your expanding workforce is on back-order – and your new hires have been making do without

You could look for a new conference room or re-schedule upcoming training sessions until after your new equipment arrives. But your team collaboratively determines that the best way to mitigate both issues at once is by temporarily renting the high-quality sound and visual system they need.

Using benchmarks that include several weeks of feedback from session attendees, and random session spot-checks you conduct personally, you conclude the solution has worked.

Scenario #3: Marketing

You’ve invested heavily in product marketing, but still can’t meet your sales goals. Specifically, you missed your revenue target by 30% last year and would like to meet that same target this year.

After collecting and examining reams of information from your sales and accounting departments, you sit down with your marketing team to figure out what’s hindering your success in the marketplace.

Determining that your product isn’t competitively priced, you map out two viable solutions.

• Hire a third-party specialist to conduct a detailed market analysis.
• Drop the price of your product to undercut competitors.

Since you’re in a hurry for results, you decide to immediately reduce the price of your product and market it accordingly.

When revenue figures for the following quarter show sales have declined even further – and marketing surveys show potential customers are doubting the quality of your product – you revert back to your original pricing, revisit your problem solving process, and implement the market analysis solution instead.

With the valuable information you gain, you finally arrive at just the right product price for your target market and sales begin to pick up. Although you miss your revenue target again this year, you meet it by the second quarter of the following year.

Kickstart your collaborative brainstorming sessions and  try MindManager for free today !

Ready to take the next step?

MindManager helps boost collaboration and productivity among remote and hybrid teams to achieve better results, faster.

Why choose MindManager?

MindManager® helps individuals, teams, and enterprises bring greater clarity and structure to plans, projects, and processes. It provides visual productivity tools and mind mapping software to help take you and your organization to where you want to be.

Explore MindManager

7 Steps to an Effective Problem-Solving Process

September 1, 2016 | Leadership Articles

An effective problem-solving process is one of the key attributes that separate great leaders from average ones.

Being a successful leader doesn’t mean that you don’t have any problems. Rather, it means that you know how to solve problems effectively as they arise. If you never had to deal with any problems, chances are pretty high that your company doesn’t really need you. They could hire an entry-level person to do your job!

Unfortunately, there are many examples of leaders out there who have been promoted to management or leadership positions because they are competent and excel in the technical skills needed to do the work. These people find themselves suddenly needing to “think on their feet” and solve problems that are far more high-level and complicated than they’ve ever really had to deal with before. Are there tools available to these people to help them solve the problem correctly and effectively? Absolutely!

Today, I am going to introduce you to the Seven Steps of Effective Problem Solving that Bullet Proof® Managers are learning about, developing, and implementing in their teams.

Step 1: Identify the Problem

What are things like when they are the way we want them to be?

This question helps you find the standard against which we’re going to measure where we are now. If things were going the way we want them to go, what does that look like? If this person were doing the job we want him or her to do, what would they be doing?

And then ask this important question: How much variation from the norm is tolerable?

Therein lies the problem. From an engineering perspective, you might have very little tolerance. From a behavioral perspective, you might have more tolerance. You might say it’s okay with me when this person doesn’t do it exactly as I say because I’m okay with them taking some liberty with this. Some other issue you may need 100% compliance.

Step 2: Analyze the Problem

At what stage is this problem? This helps you identify the urgency of the problem, and there are generally three stages.

The emergent stage is where the problem is just beginning to happen. It does not cause an immediate threat to the way business operates every day. It is just beginning to happen and you have time on your side to be able to correct it without it causing much damage to the processes it is affecting. The mature stage is where this problem is causing more than just minor damage. Some amount of damage has been done, and you need to jump on it immediately to fix it before it becomes a problem where the consequences may be greater, deeper, and more expensive if we don’t solve this problem fast.

The third stage is the crisis stage, when the problem is so serious it must be corrected immediately. At this stage, real damage has been done to company processes, reputation, finances, etc. that will have potentially long-term effects on your ability to do business.

Step 3: Describe the Problem

You should be able to describe a problem by writing it in the form of a statement and you should do it in 12 words or less, assuming it’s not a complicated, scientific problem. This way, you have clarity exactly what the issue is. Then, perhaps try distributing it to your team to ensure they agree that this is the root of the problem, that it makes sense, and everyone that is working toward a solution is working toward the same goal.

The most important question of all, when describing your problem: Is your premise correct?

Let me give you an example of what I mean. We’ve all heard – or read – the story of the engineer’s take on the old “half empty, half full” question. A speaker holds up the glass of water and asks if the glass is half empty or half full, a discussion within the group ensues, and you generally expect some sort of lesson in optimism, etc. from it. In this version, an engineer is in the room and answers, “I see this glass of water as being twice the size it needs to be.”

You see, sometimes when you are the one in charge of the problem, you tend to set the premise of the problem from your own perspective. But, that premise may not be accurate, or it may just need an alternate perspective from which to see it. If your premise is not correct, or at least incomplete, you are not fully understanding the problem and considering all the best options for a solution.

Step 4: Look for Root Causes

This step involves asking and answering a lot of questions. Ask questions like: What caused this problem? Who is responsible for this problem? When did this problem first emerge? Why did this happen? How did this variance from the standard come to be? Where does it hurt us the most? How do we go about resolving this problem?

Also, ask the most important question: Can we solve this problem for good so it will never occur again? Because an important aspect to leadership is coming up with solutions that people can use for a long-term benefit, rather than having to deal with the same problems over and over and over.

Step 5: Develop Alternate Solutions

Just about any problem you have to deal with has more solutions to it than the one that you think of first. So, it is best to develop a list of alternate solutions that you and your team can assess and decide which one will be the best for the particular problem. I often use the ⅓ + 1 Rule to create consensus around one – or the top two or three solutions – that will be best for everyone involved.

Then rank those solutions based on efficiency, cost, long-term value, what resources you have and that you can commit to the solution of the problem. Then, look at every one of those solutions carefully and decide what you believe to be the best solution to this problem at this time.

Step 6: Implement the Solution

Implementing the solution you decide on can include creating an implementation plan. It could also include planning on what happens next if something goes wrong with the solution if it doesn’t work out the way you thought it would. Implementation means that everyone on your team knows and understands their part in making the solution work, that there are timelines for execution, and also that you have a system in place to track whether or not the solution has corrected the problem.

Step 7: Measure the Results

From your implementation plan in step 6, make sure you track and measure the results so you can answer questions such as: Did it work? Was this a good solution? Did we learn something here in the implementation that we could apply to other potential problems?

These seven simple steps will help you become a more effective, efficient problem solver in your organization. As you practice this process and develop the skills, these steps will become more natural to you until the point that you are using them without noticing!

About Crestcom International, LLC.

Crestcom International, LLC is an international leadership development organization, training more than one million leaders for 25,000 businesses in over 60 countries across the globe. Crestcom achieves this through a blend of live-facilitated multimedia video, interactive exercises, and shared learning experiences. Crestcom implements action plans and coaching accountability sessions to ensure measured development in key leadership competency areas. For more information, please contact your local Crestcom representative found here .

Interested in a free Leadership Skills Workshop with your team?

• Address instantly fixable issues that impact customer perceptions and employee morale.
• Learn and practice a habit that will raise employee performance.
• Set actions with specific and measurable steps that they'll gladly be accountable to achieve.
• Case Studies
• Leadership Articles
• Multi-Generational Leadership
• Owning a franchise
• Press Releases

Latest Posts

Stay Updated

Browse by topic.

[st-tag-cloud]

Privacy Overview

Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.

14.3 Problem Solving and Decision Making in Groups

Learning objectives.

• Discuss the common components and characteristics of problems.
• Explain the five steps of the group problem-solving process.
• Describe the brainstorming and discussion that should take place before the group makes a decision.
• Compare and contrast the different decision-making techniques.
• Discuss the various influences on decision making.

Although the steps of problem solving and decision making that we will discuss next may seem obvious, we often don’t think to or choose not to use them. Instead, we start working on a problem and later realize we are lost and have to backtrack. I’m sure we’ve all reached a point in a project or task and had the “OK, now what?” moment. I’ve recently taken up some carpentry projects as a functional hobby, and I have developed a great respect for the importance of advanced planning. It’s frustrating to get to a crucial point in building or fixing something only to realize that you have to unscrew a support board that you already screwed in, have to drive back to the hardware store to get something that you didn’t think to get earlier, or have to completely start over. In this section, we will discuss the group problem-solving process, methods of decision making, and influences on these processes.

Group Problem Solving

The problem-solving process involves thoughts, discussions, actions, and decisions that occur from the first consideration of a problematic situation to the goal. The problems that groups face are varied, but some common problems include budgeting funds, raising funds, planning events, addressing customer or citizen complaints, creating or adapting products or services to fit needs, supporting members, and raising awareness about issues or causes.

Problems of all sorts have three common components (Adams & Galanes, 2009):

• An undesirable situation. When conditions are desirable, there isn’t a problem.
• A desired situation. Even though it may only be a vague idea, there is a drive to better the undesirable situation. The vague idea may develop into a more precise goal that can be achieved, although solutions are not yet generated.
• Obstacles between undesirable and desirable situation. These are things that stand in the way between the current situation and the group’s goal of addressing it. This component of a problem requires the most work, and it is the part where decision making occurs. Some examples of obstacles include limited funding, resources, personnel, time, or information. Obstacles can also take the form of people who are working against the group, including people resistant to change or people who disagree.

Discussion of these three elements of a problem helps the group tailor its problem-solving process, as each problem will vary. While these three general elements are present in each problem, the group should also address specific characteristics of the problem. Five common and important characteristics to consider are task difficulty, number of possible solutions, group member interest in problem, group member familiarity with problem, and the need for solution acceptance (Adams & Galanes, 2009).

• Task difficulty. Difficult tasks are also typically more complex. Groups should be prepared to spend time researching and discussing a difficult and complex task in order to develop a shared foundational knowledge. This typically requires individual work outside of the group and frequent group meetings to share information.
• Number of possible solutions. There are usually multiple ways to solve a problem or complete a task, but some problems have more potential solutions than others. Figuring out how to prepare a beach house for an approaching hurricane is fairly complex and difficult, but there are still a limited number of things to do—for example, taping and boarding up windows; turning off water, electricity, and gas; trimming trees; and securing loose outside objects. Other problems may be more creatively based. For example, designing a new restaurant may entail using some standard solutions but could also entail many different types of innovation with layout and design.
• Group member interest in problem. When group members are interested in the problem, they will be more engaged with the problem-solving process and invested in finding a quality solution. Groups with high interest in and knowledge about the problem may want more freedom to develop and implement solutions, while groups with low interest may prefer a leader who provides structure and direction.
• Group familiarity with problem. Some groups encounter a problem regularly, while other problems are more unique or unexpected. A family who has lived in hurricane alley for decades probably has a better idea of how to prepare its house for a hurricane than does a family that just recently moved from the Midwest. Many groups that rely on funding have to revisit a budget every year, and in recent years, groups have had to get more creative with budgets as funding has been cut in nearly every sector. When group members aren’t familiar with a problem, they will need to do background research on what similar groups have done and may also need to bring in outside experts.
• Need for solution acceptance. In this step, groups must consider how many people the decision will affect and how much “buy-in” from others the group needs in order for their solution to be successfully implemented. Some small groups have many stakeholders on whom the success of a solution depends. Other groups are answerable only to themselves. When a small group is planning on building a new park in a crowded neighborhood or implementing a new policy in a large business, it can be very difficult to develop solutions that will be accepted by all. In such cases, groups will want to poll those who will be affected by the solution and may want to do a pilot implementation to see how people react. Imposing an excellent solution that doesn’t have buy-in from stakeholders can still lead to failure.

Group problem solving can be a confusing puzzle unless it is approached systematically.

Muness Castle – Problem Solving – CC BY-SA 2.0.

Group Problem-Solving Process

There are several variations of similar problem-solving models based on US American scholar John Dewey’s reflective thinking process (Bormann & Bormann, 1988). As you read through the steps in the process, think about how you can apply what we learned regarding the general and specific elements of problems. Some of the following steps are straightforward, and they are things we would logically do when faced with a problem. However, taking a deliberate and systematic approach to problem solving has been shown to benefit group functioning and performance. A deliberate approach is especially beneficial for groups that do not have an established history of working together and will only be able to meet occasionally. Although a group should attend to each step of the process, group leaders or other group members who facilitate problem solving should be cautious not to dogmatically follow each element of the process or force a group along. Such a lack of flexibility could limit group member input and negatively affect the group’s cohesion and climate.

Step 1: Define the Problem

Define the problem by considering the three elements shared by every problem: the current undesirable situation, the goal or more desirable situation, and obstacles in the way (Adams & Galanes, 2009). At this stage, group members share what they know about the current situation, without proposing solutions or evaluating the information. Here are some good questions to ask during this stage: What is the current difficulty? How did we come to know that the difficulty exists? Who/what is involved? Why is it meaningful/urgent/important? What have the effects been so far? What, if any, elements of the difficulty require clarification? At the end of this stage, the group should be able to compose a single sentence that summarizes the problem called a problem statement . Avoid wording in the problem statement or question that hints at potential solutions. A small group formed to investigate ethical violations of city officials could use the following problem statement: “Our state does not currently have a mechanism for citizens to report suspected ethical violations by city officials.”

Step 2: Analyze the Problem

During this step a group should analyze the problem and the group’s relationship to the problem. Whereas the first step involved exploring the “what” related to the problem, this step focuses on the “why.” At this stage, group members can discuss the potential causes of the difficulty. Group members may also want to begin setting out an agenda or timeline for the group’s problem-solving process, looking forward to the other steps. To fully analyze the problem, the group can discuss the five common problem variables discussed before. Here are two examples of questions that the group formed to address ethics violations might ask: Why doesn’t our city have an ethics reporting mechanism? Do cities of similar size have such a mechanism? Once the problem has been analyzed, the group can pose a problem question that will guide the group as it generates possible solutions. “How can citizens report suspected ethical violations of city officials and how will such reports be processed and addressed?” As you can see, the problem question is more complex than the problem statement, since the group has moved on to more in-depth discussion of the problem during step 2.

Step 3: Generate Possible Solutions

During this step, group members generate possible solutions to the problem. Again, solutions should not be evaluated at this point, only proposed and clarified. The question should be what could we do to address this problem, not what should we do to address it. It is perfectly OK for a group member to question another person’s idea by asking something like “What do you mean?” or “Could you explain your reasoning more?” Discussions at this stage may reveal a need to return to previous steps to better define or more fully analyze a problem. Since many problems are multifaceted, it is necessary for group members to generate solutions for each part of the problem separately, making sure to have multiple solutions for each part. Stopping the solution-generating process prematurely can lead to groupthink. For the problem question previously posed, the group would need to generate solutions for all three parts of the problem included in the question. Possible solutions for the first part of the problem (How can citizens report ethical violations?) may include “online reporting system, e-mail, in-person, anonymously, on-the-record,” and so on. Possible solutions for the second part of the problem (How will reports be processed?) may include “daily by a newly appointed ethics officer, weekly by a nonpartisan nongovernment employee,” and so on. Possible solutions for the third part of the problem (How will reports be addressed?) may include “by a newly appointed ethics commission, by the accused’s supervisor, by the city manager,” and so on.

Step 4: Evaluate Solutions

During this step, solutions can be critically evaluated based on their credibility, completeness, and worth. Once the potential solutions have been narrowed based on more obvious differences in relevance and/or merit, the group should analyze each solution based on its potential effects—especially negative effects. Groups that are required to report the rationale for their decision or whose decisions may be subject to public scrutiny would be wise to make a set list of criteria for evaluating each solution. Additionally, solutions can be evaluated based on how well they fit with the group’s charge and the abilities of the group. To do this, group members may ask, “Does this solution live up to the original purpose or mission of the group?” and “Can the solution actually be implemented with our current resources and connections?” and “How will this solution be supported, funded, enforced, and assessed?” Secondary tensions and substantive conflict, two concepts discussed earlier, emerge during this step of problem solving, and group members will need to employ effective critical thinking and listening skills.

Decision making is part of the larger process of problem solving and it plays a prominent role in this step. While there are several fairly similar models for problem solving, there are many varied decision-making techniques that groups can use. For example, to narrow the list of proposed solutions, group members may decide by majority vote, by weighing the pros and cons, or by discussing them until a consensus is reached. There are also more complex decision-making models like the “six hats method,” which we will discuss later. Once the final decision is reached, the group leader or facilitator should confirm that the group is in agreement. It may be beneficial to let the group break for a while or even to delay the final decision until a later meeting to allow people time to evaluate it outside of the group context.

Step 5: Implement and Assess the Solution

Implementing the solution requires some advanced planning, and it should not be rushed unless the group is operating under strict time restraints or delay may lead to some kind of harm. Although some solutions can be implemented immediately, others may take days, months, or years. As was noted earlier, it may be beneficial for groups to poll those who will be affected by the solution as to their opinion of it or even to do a pilot test to observe the effectiveness of the solution and how people react to it. Before implementation, groups should also determine how and when they would assess the effectiveness of the solution by asking, “How will we know if the solution is working or not?” Since solution assessment will vary based on whether or not the group is disbanded, groups should also consider the following questions: If the group disbands after implementation, who will be responsible for assessing the solution? If the solution fails, will the same group reconvene or will a new group be formed?

Once a solution has been reached and the group has the “green light” to implement it, it should proceed deliberately and cautiously, making sure to consider possible consequences and address them as needed.

Jocko Benoit – Prodigal Light – CC BY-NC-ND 2.0.

Certain elements of the solution may need to be delegated out to various people inside and outside the group. Group members may also be assigned to implement a particular part of the solution based on their role in the decision making or because it connects to their area of expertise. Likewise, group members may be tasked with publicizing the solution or “selling” it to a particular group of stakeholders. Last, the group should consider its future. In some cases, the group will get to decide if it will stay together and continue working on other tasks or if it will disband. In other cases, outside forces determine the group’s fate.

“Getting Competent”

Problem Solving and Group Presentations

Giving a group presentation requires that individual group members and the group as a whole solve many problems and make many decisions. Although having more people involved in a presentation increases logistical difficulties and has the potential to create more conflict, a well-prepared and well-delivered group presentation can be more engaging and effective than a typical presentation. The main problems facing a group giving a presentation are (1) dividing responsibilities, (2) coordinating schedules and time management, and (3) working out the logistics of the presentation delivery.

In terms of dividing responsibilities, assigning individual work at the first meeting and then trying to fit it all together before the presentation (which is what many college students do when faced with a group project) is not the recommended method. Integrating content and visual aids created by several different people into a seamless final product takes time and effort, and the person “stuck” with this job at the end usually ends up developing some resentment toward his or her group members. While it’s OK for group members to do work independently outside of group meetings, spend time working together to help set up some standards for content and formatting expectations that will help make later integration of work easier. Taking the time to complete one part of the presentation together can help set those standards for later individual work. Discuss the roles that various group members will play openly so there isn’t role confusion. There could be one point person for keeping track of the group’s progress and schedule, one point person for communication, one point person for content integration, one point person for visual aids, and so on. Each person shouldn’t do all that work on his or her own but help focus the group’s attention on his or her specific area during group meetings (Stanton, 2009).

Scheduling group meetings is one of the most challenging problems groups face, given people’s busy lives. From the beginning, it should be clearly communicated that the group needs to spend considerable time in face-to-face meetings, and group members should know that they may have to make an occasional sacrifice to attend. Especially important is the commitment to scheduling time to rehearse the presentation. Consider creating a contract of group guidelines that includes expectations for meeting attendance to increase group members’ commitment.

Group presentations require members to navigate many logistics of their presentation. While it may be easier for a group to assign each member to create a five-minute segment and then transition from one person to the next, this is definitely not the most engaging method. Creating a master presentation and then assigning individual speakers creates a more fluid and dynamic presentation and allows everyone to become familiar with the content, which can help if a person doesn’t show up to present and during the question-and-answer section. Once the content of the presentation is complete, figure out introductions, transitions, visual aids, and the use of time and space (Stanton, 2012). In terms of introductions, figure out if one person will introduce all the speakers at the beginning, if speakers will introduce themselves at the beginning, or if introductions will occur as the presentation progresses. In terms of transitions, make sure each person has included in his or her speaking notes when presentation duties switch from one person to the next. Visual aids have the potential to cause hiccups in a group presentation if they aren’t fluidly integrated. Practicing with visual aids and having one person control them may help prevent this. Know how long your presentation is and know how you’re going to use the space. Presenters should know how long the whole presentation should be and how long each of their segments should be so that everyone can share the responsibility of keeping time. Also consider the size and layout of the presentation space. You don’t want presenters huddled in a corner until it’s their turn to speak or trapped behind furniture when their turn comes around.

• Of the three main problems facing group presenters, which do you think is the most challenging and why?
• Why do you think people tasked with a group presentation (especially students) prefer to divide the parts up and have members work on them independently before coming back together and integrating each part? What problems emerge from this method? In what ways might developing a master presentation and then assigning parts to different speakers be better than the more divided method? What are the drawbacks to the master presentation method?

Decision Making in Groups

We all engage in personal decision making daily, and we all know that some decisions are more difficult than others. When we make decisions in groups, we face some challenges that we do not face in our personal decision making, but we also stand to benefit from some advantages of group decision making (Napier & Gershenfeld, 2004). Group decision making can appear fair and democratic but really only be a gesture that covers up the fact that certain group members or the group leader have already decided. Group decision making also takes more time than individual decisions and can be burdensome if some group members do not do their assigned work, divert the group with self-centered or unproductive role behaviors, or miss meetings. Conversely, though, group decisions are often more informed, since all group members develop a shared understanding of a problem through discussion and debate. The shared understanding may also be more complex and deep than what an individual would develop, because the group members are exposed to a variety of viewpoints that can broaden their own perspectives. Group decisions also benefit from synergy, one of the key advantages of group communication that we discussed earlier. Most groups do not use a specific method of decision making, perhaps thinking that they’ll work things out as they go. This can lead to unequal participation, social loafing, premature decisions, prolonged discussion, and a host of other negative consequences. So in this section we will learn some practices that will prepare us for good decision making and some specific techniques we can use to help us reach a final decision.

Brainstorming before Decision Making

Before groups can make a decision, they need to generate possible solutions to their problem. The most commonly used method is brainstorming, although most people don’t follow the recommended steps of brainstorming. As you’ll recall, brainstorming refers to the quick generation of ideas free of evaluation. The originator of the term brainstorming said the following four rules must be followed for the technique to be effective (Osborn, 1959):

• Evaluation of ideas is forbidden.
• Wild and crazy ideas are encouraged.
• Quantity of ideas, not quality, is the goal.
• New combinations of ideas presented are encouraged.

To make brainstorming more of a decision-making method rather than an idea-generating method, group communication scholars have suggested additional steps that precede and follow brainstorming (Cragan & Wright, 1991).

• Do a warm-up brainstorming session. Some people are more apprehensive about publicly communicating their ideas than others are, and a warm-up session can help ease apprehension and prime group members for task-related idea generation. The warm-up can be initiated by anyone in the group and should only go on for a few minutes. To get things started, a person could ask, “If our group formed a band, what would we be called?” or “What other purposes could a mailbox serve?” In the previous examples, the first warm up gets the group’s more abstract creative juices flowing, while the second focuses more on practical and concrete ideas.
• Do the actual brainstorming session. This session shouldn’t last more than thirty minutes and should follow the four rules of brainstorming mentioned previously. To ensure that the fourth rule is realized, the facilitator could encourage people to piggyback off each other’s ideas.
• Eliminate duplicate ideas. After the brainstorming session is over, group members can eliminate (without evaluating) ideas that are the same or very similar.
• Clarify, organize, and evaluate ideas. Before evaluation, see if any ideas need clarification. Then try to theme or group ideas together in some orderly fashion. Since “wild and crazy” ideas are encouraged, some suggestions may need clarification. If it becomes clear that there isn’t really a foundation to an idea and that it is too vague or abstract and can’t be clarified, it may be eliminated. As a caution though, it may be wise to not throw out off-the-wall ideas that are hard to categorize and to instead put them in a miscellaneous or “wild and crazy” category.

Discussion before Decision Making

The nominal group technique guides decision making through a four-step process that includes idea generation and evaluation and seeks to elicit equal contributions from all group members (Delbecq & Ven de Ven, 1971). This method is useful because the procedure involves all group members systematically, which fixes the problem of uneven participation during discussions. Since everyone contributes to the discussion, this method can also help reduce instances of social loafing. To use the nominal group technique, do the following:

• Silently and individually list ideas.
• Create a master list of ideas.
• Clarify ideas as needed.
• Take a secret vote to rank group members’ acceptance of ideas.

During the first step, have group members work quietly, in the same space, to write down every idea they have to address the task or problem they face. This shouldn’t take more than twenty minutes. Whoever is facilitating the discussion should remind group members to use brainstorming techniques, which means they shouldn’t evaluate ideas as they are generated. Ask group members to remain silent once they’ve finished their list so they do not distract others.

During the second step, the facilitator goes around the group in a consistent order asking each person to share one idea at a time. As the idea is shared, the facilitator records it on a master list that everyone can see. Keep track of how many times each idea comes up, as that could be an idea that warrants more discussion. Continue this process until all the ideas have been shared. As a note to facilitators, some group members may begin to edit their list or self-censor when asked to provide one of their ideas. To limit a person’s apprehension with sharing his or her ideas and to ensure that each idea is shared, I have asked group members to exchange lists with someone else so they can share ideas from the list they receive without fear of being personally judged.

During step three, the facilitator should note that group members can now ask for clarification on ideas on the master list. Do not let this discussion stray into evaluation of ideas. To help avoid an unnecessarily long discussion, it may be useful to go from one person to the next to ask which ideas need clarifying and then go to the originator(s) of the idea in question for clarification.

During the fourth step, members use a voting ballot to rank the acceptability of the ideas on the master list. If the list is long, you may ask group members to rank only their top five or so choices. The facilitator then takes up the secret ballots and reviews them in a random order, noting the rankings of each idea. Ideally, the highest ranked idea can then be discussed and decided on. The nominal group technique does not carry a group all the way through to the point of decision; rather, it sets the group up for a roundtable discussion or use of some other method to evaluate the merits of the top ideas.

Specific Decision-Making Techniques

Some decision-making techniques involve determining a course of action based on the level of agreement among the group members. These methods include majority, expert, authority, and consensus rule. Table 14.1 “Pros and Cons of Agreement-Based Decision-Making Techniques” reviews the pros and cons of each of these methods.

Majority rule is a simple method of decision making based on voting. In most cases a majority is considered half plus one.

Becky McCray – Voting – CC BY-NC-ND 2.0.

Majority rule is a commonly used decision-making technique in which a majority (one-half plus one) must agree before a decision is made. A show-of-hands vote, a paper ballot, or an electronic voting system can determine the majority choice. Many decision-making bodies, including the US House of Representatives, Senate, and Supreme Court, use majority rule to make decisions, which shows that it is often associated with democratic decision making, since each person gets one vote and each vote counts equally. Of course, other individuals and mediated messages can influence a person’s vote, but since the voting power is spread out over all group members, it is not easy for one person or party to take control of the decision-making process. In some cases—for example, to override a presidential veto or to amend the constitution—a super majority of two-thirds may be required to make a decision.

Minority rule is a decision-making technique in which a designated authority or expert has final say over a decision and may or may not consider the input of other group members. When a designated expert makes a decision by minority rule, there may be buy-in from others in the group, especially if the members of the group didn’t have relevant knowledge or expertise. When a designated authority makes decisions, buy-in will vary based on group members’ level of respect for the authority. For example, decisions made by an elected authority may be more accepted by those who elected him or her than by those who didn’t. As with majority rule, this technique can be time saving. Unlike majority rule, one person or party can have control over the decision-making process. This type of decision making is more similar to that used by monarchs and dictators. An obvious negative consequence of this method is that the needs or wants of one person can override the needs and wants of the majority. A minority deciding for the majority has led to negative consequences throughout history. The white Afrikaner minority that ruled South Africa for decades instituted apartheid, which was a system of racial segregation that disenfranchised and oppressed the majority population. The quality of the decision and its fairness really depends on the designated expert or authority.

Consensus rule is a decision-making technique in which all members of the group must agree on the same decision. On rare occasions, a decision may be ideal for all group members, which can lead to unanimous agreement without further debate and discussion. Although this can be positive, be cautious that this isn’t a sign of groupthink. More typically, consensus is reached only after lengthy discussion. On the plus side, consensus often leads to high-quality decisions due to the time and effort it takes to get everyone in agreement. Group members are also more likely to be committed to the decision because of their investment in reaching it. On the negative side, the ultimate decision is often one that all group members can live with but not one that’s ideal for all members. Additionally, the process of arriving at consensus also includes conflict, as people debate ideas and negotiate the interpersonal tensions that may result.

Table 14.1 Pros and Cons of Agreement-Based Decision-Making Techniques

“Getting Critical”

Six Hats Method of Decision Making

Edward de Bono developed the Six Hats method of thinking in the late 1980s, and it has since become a regular feature in decision-making training in business and professional contexts (de Bono, 1985). The method’s popularity lies in its ability to help people get out of habitual ways of thinking and to allow group members to play different roles and see a problem or decision from multiple points of view. The basic idea is that each of the six hats represents a different way of thinking, and when we figuratively switch hats, we switch the way we think. The hats and their style of thinking are as follows:

• White hat. Objective—focuses on seeking information such as data and facts and then processes that information in a neutral way.
• Red hat. Emotional—uses intuition, gut reactions, and feelings to judge information and suggestions.
• Black hat. Negative—focuses on potential risks, points out possibilities for failure, and evaluates information cautiously and defensively.
• Yellow hat. Positive—is optimistic about suggestions and future outcomes, gives constructive and positive feedback, points out benefits and advantages.
• Green hat. Creative—tries to generate new ideas and solutions, thinks “outside the box.”
• Blue hat. Philosophical—uses metacommunication to organize and reflect on the thinking and communication taking place in the group, facilitates who wears what hat and when group members change hats.

Specific sequences or combinations of hats can be used to encourage strategic thinking. For example, the group leader may start off wearing the Blue Hat and suggest that the group start their decision-making process with some “White Hat thinking” in order to process through facts and other available information. During this stage, the group could also process through what other groups have done when faced with a similar problem. Then the leader could begin an evaluation sequence starting with two minutes of “Yellow Hat thinking” to identify potential positive outcomes, then “Black Hat thinking” to allow group members to express reservations about ideas and point out potential problems, then “Red Hat thinking” to get people’s gut reactions to the previous discussion, then “Green Hat thinking” to identify other possible solutions that are more tailored to the group’s situation or completely new approaches. At the end of a sequence, the Blue Hat would want to summarize what was said and begin a new sequence. To successfully use this method, the person wearing the Blue Hat should be familiar with different sequences and plan some of the thinking patterns ahead of time based on the problem and the group members. Each round of thinking should be limited to a certain time frame (two to five minutes) to keep the discussion moving.

• This decision-making method has been praised because it allows group members to “switch gears” in their thinking and allows for role playing, which lets people express ideas more freely. How can this help enhance critical thinking? Which combination of hats do you think would be best for a critical thinking sequence?
• What combinations of hats might be useful if the leader wanted to break the larger group up into pairs and why? For example, what kind of thinking would result from putting Yellow and Red together, Black and White together, or Red and White together, and so on?
• Based on your preferred ways of thinking and your personality, which hat would be the best fit for you? Which would be the most challenging? Why?

Influences on Decision Making

Many factors influence the decision-making process. For example, how might a group’s independence or access to resources affect the decisions they make? What potential advantages and disadvantages come with decisions made by groups that are more or less similar in terms of personality and cultural identities? In this section, we will explore how situational, personality, and cultural influences affect decision making in groups.

Situational Influences on Decision Making

A group’s situational context affects decision making. One key situational element is the degree of freedom that the group has to make its own decisions, secure its own resources, and initiate its own actions. Some groups have to go through multiple approval processes before they can do anything, while others are self-directed, self-governing, and self-sustaining. Another situational influence is uncertainty. In general, groups deal with more uncertainty in decision making than do individuals because of the increased number of variables that comes with adding more people to a situation. Individual group members can’t know what other group members are thinking, whether or not they are doing their work, and how committed they are to the group. So the size of a group is a powerful situational influence, as it adds to uncertainty and complicates communication.

Access to information also influences a group. First, the nature of the group’s task or problem affects its ability to get information. Group members can more easily make decisions about a problem when other groups have similarly experienced it. Even if the problem is complex and serious, the group can learn from other situations and apply what it learns. Second, the group must have access to flows of information. Access to archives, electronic databases, and individuals with relevant experience is necessary to obtain any relevant information about similar problems or to do research on a new or unique problem. In this regard, group members’ formal and information network connections also become important situational influences.

The urgency of a decision can have a major influence on the decision-making process. As a situation becomes more urgent, it requires more specific decision-making methods and types of communication.

Judith E. Bell – Urgent – CC BY-SA 2.0.

The origin and urgency of a problem are also situational factors that influence decision making. In terms of origin, problems usually occur in one of four ways:

• Something goes wrong. Group members must decide how to fix or stop something. Example—a firehouse crew finds out that half of the building is contaminated with mold and must be closed down.
• Expectations change or increase. Group members must innovate more efficient or effective ways of doing something. Example—a firehouse crew finds out that the district they are responsible for is being expanded.
• Something goes wrong and expectations change or increase. Group members must fix/stop and become more efficient/effective. Example—the firehouse crew has to close half the building and must start responding to more calls due to the expanding district.
• The problem existed from the beginning. Group members must go back to the origins of the situation and walk through and analyze the steps again to decide what can be done differently. Example—a firehouse crew has consistently had to work with minimal resources in terms of building space and firefighting tools.

In each of the cases, the need for a decision may be more or less urgent depending on how badly something is going wrong, how high the expectations have been raised, or the degree to which people are fed up with a broken system. Decisions must be made in situations ranging from crisis level to mundane.

Personality Influences on Decision Making

A long-studied typology of value orientations that affect decision making consists of the following types of decision maker: the economic, the aesthetic, the theoretical, the social, the political, and the religious (Spranger, 1928).

• The economic decision maker makes decisions based on what is practical and useful.
• The aesthetic decision maker makes decisions based on form and harmony, desiring a solution that is elegant and in sync with the surroundings.
• The theoretical decision maker wants to discover the truth through rationality.
• The social decision maker emphasizes the personal impact of a decision and sympathizes with those who may be affected by it.
• The political decision maker is interested in power and influence and views people and/or property as divided into groups that have different value.
• The religious decision maker seeks to identify with a larger purpose, works to unify others under that goal, and commits to a viewpoint, often denying one side and being dedicated to the other.

In the United States, economic, political, and theoretical decision making tend to be more prevalent decision-making orientations, which likely corresponds to the individualistic cultural orientation with its emphasis on competition and efficiency. But situational context, as we discussed before, can also influence our decision making.

Personality affects decision making. For example, “economic” decision makers decide based on what is practical and useful.

One Way Stock – Tough Decisions Ahead – CC BY-ND 2.0.

The personalities of group members, especially leaders and other active members, affect the climate of the group. Group member personalities can be categorized based on where they fall on a continuum anchored by the following descriptors: dominant/submissive, friendly/unfriendly, and instrumental/emotional (Cragan & Wright, 1999). The more group members there are in any extreme of these categories, the more likely that the group climate will also shift to resemble those characteristics.

• Dominant versus submissive. Group members that are more dominant act more independently and directly, initiate conversations, take up more space, make more direct eye contact, seek leadership positions, and take control over decision-making processes. More submissive members are reserved, contribute to the group only when asked to, avoid eye contact, and leave their personal needs and thoughts unvoiced or give into the suggestions of others.
• Friendly versus unfriendly. Group members on the friendly side of the continuum find a balance between talking and listening, don’t try to win at the expense of other group members, are flexible but not weak, and value democratic decision making. Unfriendly group members are disagreeable, indifferent, withdrawn, and selfish, which leads them to either not invest in decision making or direct it in their own interest rather than in the interest of the group.
• Instrumental versus emotional. Instrumental group members are emotionally neutral, objective, analytical, task-oriented, and committed followers, which leads them to work hard and contribute to the group’s decision making as long as it is orderly and follows agreed-on rules. Emotional group members are creative, playful, independent, unpredictable, and expressive, which leads them to make rash decisions, resist group norms or decision-making structures, and switch often from relational to task focus.

Cultural Context and Decision Making

Just like neighborhoods, schools, and countries, small groups vary in terms of their degree of similarity and difference. Demographic changes in the United States and increases in technology that can bring different people together make it more likely that we will be interacting in more and more heterogeneous groups (Allen, 2011). Some small groups are more homogenous, meaning the members are more similar, and some are more heterogeneous, meaning the members are more different. Diversity and difference within groups has advantages and disadvantages. In terms of advantages, research finds that, in general, groups that are culturally heterogeneous have better overall performance than more homogenous groups (Haslett & Ruebush, 1999). Additionally, when group members have time to get to know each other and competently communicate across their differences, the advantages of diversity include better decision making due to different perspectives (Thomas, 1999). Unfortunately, groups often operate under time constraints and other pressures that make the possibility for intercultural dialogue and understanding difficult. The main disadvantage of heterogeneous groups is the possibility for conflict, but given that all groups experience conflict, this isn’t solely due to the presence of diversity. We will now look more specifically at how some of the cultural value orientations we’ve learned about already in this book can play out in groups with international diversity and how domestic diversity in terms of demographics can also influence group decision making.

International Diversity in Group Interactions

Cultural value orientations such as individualism/collectivism, power distance, and high-/low-context communication styles all manifest on a continuum of communication behaviors and can influence group decision making. Group members from individualistic cultures are more likely to value task-oriented, efficient, and direct communication. This could manifest in behaviors such as dividing up tasks into individual projects before collaboration begins and then openly debating ideas during discussion and decision making. Additionally, people from cultures that value individualism are more likely to openly express dissent from a decision, essentially expressing their disagreement with the group. Group members from collectivistic cultures are more likely to value relationships over the task at hand. Because of this, they also tend to value conformity and face-saving (often indirect) communication. This could manifest in behaviors such as establishing norms that include periods of socializing to build relationships before task-oriented communication like negotiations begin or norms that limit public disagreement in favor of more indirect communication that doesn’t challenge the face of other group members or the group’s leader. In a group composed of people from a collectivistic culture, each member would likely play harmonizing roles, looking for signs of conflict and resolving them before they become public.

Power distance can also affect group interactions. Some cultures rank higher on power-distance scales, meaning they value hierarchy, make decisions based on status, and believe that people have a set place in society that is fairly unchangeable. Group members from high-power-distance cultures would likely appreciate a strong designated leader who exhibits a more directive leadership style and prefer groups in which members have clear and assigned roles. In a group that is homogenous in terms of having a high-power-distance orientation, members with higher status would be able to openly provide information, and those with lower status may not provide information unless a higher status member explicitly seeks it from them. Low-power-distance cultures do not place as much value and meaning on status and believe that all group members can participate in decision making. Group members from low-power-distance cultures would likely freely speak their mind during a group meeting and prefer a participative leadership style.

How much meaning is conveyed through the context surrounding verbal communication can also affect group communication. Some cultures have a high-context communication style in which much of the meaning in an interaction is conveyed through context such as nonverbal cues and silence. Group members from high-context cultures may avoid saying something directly, assuming that other group members will understand the intended meaning even if the message is indirect. So if someone disagrees with a proposed course of action, he or she may say, “Let’s discuss this tomorrow,” and mean, “I don’t think we should do this.” Such indirect communication is also a face-saving strategy that is common in collectivistic cultures. Other cultures have a low-context communication style that places more importance on the meaning conveyed through words than through context or nonverbal cues. Group members from low-context cultures often say what they mean and mean what they say. For example, if someone doesn’t like an idea, they might say, “I think we should consider more options. This one doesn’t seem like the best we can do.”

In any of these cases, an individual from one culture operating in a group with people of a different cultural orientation could adapt to the expectations of the host culture, especially if that person possesses a high degree of intercultural communication competence (ICC). Additionally, people with high ICC can also adapt to a group member with a different cultural orientation than the host culture. Even though these cultural orientations connect to values that affect our communication in fairly consistent ways, individuals may exhibit different communication behaviors depending on their own individual communication style and the situation.

Domestic Diversity and Group Communication

While it is becoming more likely that we will interact in small groups with international diversity, we are guaranteed to interact in groups that are diverse in terms of the cultural identities found within a single country or the subcultures found within a larger cultural group.

Gender stereotypes sometimes influence the roles that people play within a group. For example, the stereotype that women are more nurturing than men may lead group members (both male and female) to expect that women will play the role of supporters or harmonizers within the group. Since women have primarily performed secretarial work since the 1900s, it may also be expected that women will play the role of recorder. In both of these cases, stereotypical notions of gender place women in roles that are typically not as valued in group communication. The opposite is true for men. In terms of leadership, despite notable exceptions, research shows that men fill an overwhelmingly disproportionate amount of leadership positions. We are socialized to see certain behaviors by men as indicative of leadership abilities, even though they may not be. For example, men are often perceived to contribute more to a group because they tend to speak first when asked a question or to fill a silence and are perceived to talk more about task-related matters than relationally oriented matters. Both of these tendencies create a perception that men are more engaged with the task. Men are also socialized to be more competitive and self-congratulatory, meaning that their communication may be seen as dedicated and their behaviors seen as powerful, and that when their work isn’t noticed they will be more likely to make it known to the group rather than take silent credit. Even though we know that the relational elements of a group are crucial for success, even in high-performance teams, that work is not as valued in our society as the task-related work.

Despite the fact that some communication patterns and behaviors related to our typical (and stereotypical) gender socialization affect how we interact in and form perceptions of others in groups, the differences in group communication that used to be attributed to gender in early group communication research seem to be diminishing. This is likely due to the changing organizational cultures from which much group work emerges, which have now had more than sixty years to adjust to women in the workplace. It is also due to a more nuanced understanding of gender-based research, which doesn’t take a stereotypical view from the beginning as many of the early male researchers did. Now, instead of biological sex being assumed as a factor that creates inherent communication differences, group communication scholars see that men and women both exhibit a range of behaviors that are more or less feminine or masculine. It is these gendered behaviors, and not a person’s gender, that seem to have more of an influence on perceptions of group communication. Interestingly, group interactions are still masculinist in that male and female group members prefer a more masculine communication style for task leaders and that both males and females in this role are more likely to adapt to a more masculine communication style. Conversely, men who take on social-emotional leadership behaviors adopt a more feminine communication style. In short, it seems that although masculine communication traits are more often associated with high status positions in groups, both men and women adapt to this expectation and are evaluated similarly (Haslett & Ruebush, 1999).

Other demographic categories are also influential in group communication and decision making. In general, group members have an easier time communicating when they are more similar than different in terms of race and age. This ease of communication can make group work more efficient, but the homogeneity may sacrifice some creativity. As we learned earlier, groups that are diverse (e.g., they have members of different races and generations) benefit from the diversity of perspectives in terms of the quality of decision making and creativity of output.

In terms of age, for the first time since industrialization began, it is common to have three generations of people (and sometimes four) working side by side in an organizational setting. Although four generations often worked together in early factories, they were segregated based on their age group, and a hierarchy existed with older workers at the top and younger workers at the bottom. Today, however, generations interact regularly, and it is not uncommon for an older person to have a leader or supervisor who is younger than him or her (Allen, 2011). The current generations in the US workplace and consequently in work-based groups include the following:

• The Silent Generation. Born between 1925 and 1942, currently in their midsixties to mideighties, this is the smallest generation in the workforce right now, as many have retired or left for other reasons. This generation includes people who were born during the Great Depression or the early part of World War II, many of whom later fought in the Korean War (Clarke, 1970).
• The Baby Boomers. Born between 1946 and 1964, currently in their late forties to midsixties, this is the largest generation in the workforce right now. Baby boomers are the most populous generation born in US history, and they are working longer than previous generations, which means they will remain the predominant force in organizations for ten to twenty more years.
• Generation X. Born between 1965 and 1981, currently in their early thirties to midforties, this generation was the first to see technology like cell phones and the Internet make its way into classrooms and our daily lives. Compared to previous generations, “Gen-Xers” are more diverse in terms of race, religious beliefs, and sexual orientation and also have a greater appreciation for and understanding of diversity.
• Generation Y. Born between 1982 and 2000, “Millennials” as they are also called are currently in their late teens up to about thirty years old. This generation is not as likely to remember a time without technology such as computers and cell phones. They are just starting to enter into the workforce and have been greatly affected by the economic crisis of the late 2000s, experiencing significantly high unemployment rates.

The benefits and challenges that come with diversity of group members are important to consider. Since we will all work in diverse groups, we should be prepared to address potential challenges in order to reap the benefits. Diverse groups may be wise to coordinate social interactions outside of group time in order to find common ground that can help facilitate interaction and increase group cohesion. We should be sensitive but not let sensitivity create fear of “doing something wrong” that then prevents us from having meaningful interactions. Reviewing Chapter 8 “Culture and Communication” will give you useful knowledge to help you navigate both international and domestic diversity and increase your communication competence in small groups and elsewhere.

Key Takeaways

• Every problem has common components: an undesirable situation, a desired situation, and obstacles between the undesirable and desirable situations. Every problem also has a set of characteristics that vary among problems, including task difficulty, number of possible solutions, group member interest in the problem, group familiarity with the problem, and the need for solution acceptance.

The group problem-solving process has five steps:

• Define the problem by creating a problem statement that summarizes it.
• Analyze the problem and create a problem question that can guide solution generation.
• Generate possible solutions. Possible solutions should be offered and listed without stopping to evaluate each one.
• Evaluate the solutions based on their credibility, completeness, and worth. Groups should also assess the potential effects of the narrowed list of solutions.
• Implement and assess the solution. Aside from enacting the solution, groups should determine how they will know the solution is working or not.
• Before a group makes a decision, it should brainstorm possible solutions. Group communication scholars suggest that groups (1) do a warm-up brainstorming session; (2) do an actual brainstorming session in which ideas are not evaluated, wild ideas are encouraged, quantity not quality of ideas is the goal, and new combinations of ideas are encouraged; (3) eliminate duplicate ideas; and (4) clarify, organize, and evaluate ideas. In order to guide the idea-generation process and invite equal participation from group members, the group may also elect to use the nominal group technique.
• Common decision-making techniques include majority rule, minority rule, and consensus rule. With majority rule, only a majority, usually one-half plus one, must agree before a decision is made. With minority rule, a designated authority or expert has final say over a decision, and the input of group members may or may not be invited or considered. With consensus rule, all members of the group must agree on the same decision.

Several factors influence the decision-making process:

• Situational factors include the degree of freedom a group has to make its own decisions, the level of uncertainty facing the group and its task, the size of the group, the group’s access to information, and the origin and urgency of the problem.
• Personality influences on decision making include a person’s value orientation (economic, aesthetic, theoretical, political, or religious), and personality traits (dominant/submissive, friendly/unfriendly, and instrumental/emotional).
• Cultural influences on decision making include the heterogeneity or homogeneity of the group makeup; cultural values and characteristics such as individualism/collectivism, power distance, and high-/low-context communication styles; and gender and age differences.
• Scenario 1. Task difficulty is high, number of possible solutions is high, group interest in problem is high, group familiarity with problem is low, and need for solution acceptance is high.
• Scenario 2. Task difficulty is low, number of possible solutions is low, group interest in problem is low, group familiarity with problem is high, and need for solution acceptance is low.
• Scenario 1: Academic. A professor asks his or her class to decide whether the final exam should be an in-class or take-home exam.
• Scenario 2: Professional. A group of coworkers must decide which person from their department to nominate for a company-wide award.
• Scenario 3: Personal. A family needs to decide how to divide the belongings and estate of a deceased family member who did not leave a will.
• Scenario 4: Civic. A local branch of a political party needs to decide what five key issues it wants to include in the national party’s platform.
• Group communication researchers have found that heterogeneous groups (composed of diverse members) have advantages over homogenous (more similar) groups. Discuss a group situation you have been in where diversity enhanced your and/or the group’s experience.

Adams, K., and Gloria G. Galanes, Communicating in Groups: Applications and Skills , 7th ed. (Boston, MA: McGraw-Hill, 2009), 220–21.

Allen, B. J., Difference Matters: Communicating Social Identity , 2nd ed. (Long Grove, IL: Waveland, 2011), 5.

Bormann, E. G., and Nancy C. Bormann, Effective Small Group Communication , 4th ed. (Santa Rosa, CA: Burgess CA, 1988), 112–13.

Clarke, G., “The Silent Generation Revisited,” Time, June 29, 1970, 46.

Cragan, J. F., and David W. Wright, Communication in Small Group Discussions: An Integrated Approach , 3rd ed. (St. Paul, MN: West Publishing, 1991), 77–78.

de Bono, E., Six Thinking Hats (Boston, MA: Little, Brown, 1985).

Delbecq, A. L., and Andrew H. Ven de Ven, “A Group Process Model for Problem Identification and Program Planning,” The Journal of Applied Behavioral Science 7, no. 4 (1971): 466–92.

Haslett, B. B., and Jenn Ruebush, “What Differences Do Individual Differences in Groups Make?: The Effects of Individuals, Culture, and Group Composition,” in The Handbook of Group Communication Theory and Research , ed. Lawrence R. Frey (Thousand Oaks, CA: Sage, 1999), 133.

Napier, R. W., and Matti K. Gershenfeld, Groups: Theory and Experience , 7th ed. (Boston, MA: Houghton Mifflin, 2004), 292.

Osborn, A. F., Applied Imagination (New York: Charles Scribner’s Sons, 1959).

Spranger, E., Types of Men (New York: Steckert, 1928).

Stanton, C., “How to Deliver Group Presentations: The Unified Team Approach,” Six Minutes Speaking and Presentation Skills , November 3, 2009, accessed August 28, 2012, http://sixminutes.dlugan.com/group-presentations-unified-team-approach .

Thomas, D. C., “Cultural Diversity and Work Group Effectiveness: An Experimental Study,” Journal of Cross-Cultural Psychology 30, no. 2 (1999): 242–63.

Communication in the Real World Copyright © 2016 by University of Minnesota is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

How it works

For Business

Join Mind Tools

Article • 10 min read

The Problem-Definition Process

Developing the right solution.

By the Mind Tools Content Team

When we try to solve business problems, we can often pressurize ourselves to find solutions quickly.

The problem with this is that we can end up only partially solving the problem, or we can solve the wrong problem altogether, with all of the delay, expense, and lost business opportunity that goes with this.

The Problem-Definition Process helps you avoid this. In this article, we'll look at this process and we'll see how to apply it.

Dwayne Spradlin published the Problem-Definition Process in September 2012's Harvard Business Review . (We refer to this with permission.)

Spradlin was the President and CEO of Innocentive, an organization that connected organizations with freelance problem solvers. He developed the process over 10 years, while working with a community of more than 25,000 "problem solvers" such as engineers, scientists, and industry experts.

The process gives you four steps that help you better understand complex problems. These steps are:

• Establish the need.
• Justify the need.
• Understand the problem and its wider context.
• Write a problem statement.

The Problem-Definition Process encourages you to define and understand the problem that you're trying to solve, in detail. It also helps you confirm that solving the problem contributes towards your organization's objectives.

This stops you spending time, energy, and resources on unimportant problems, or on initiatives that don't align with your organization's overall strategy.

It also encourages you to fully define the problem and its boundaries. You can then use this information to justify the need for change, brief designers and contractors, and kick-off new projects successfully.

Use the Problem-Definition Process alongside tools such as Simplex and Hurson's Productive Thinking Model . These will guide you through the full problem-solving process .

Using the Problem-Definition Process

The four main steps in the Problem-Definition Process contain several smaller questions that, once answered, help you define and clarify the problem thoroughly.

Let's look at each step in more detail.

The process we present below is an adaptation of Spradlin's original model. We’ve included additional questions and sub-steps where appropriate.

1. Establish the Need

The first step is to identify why you need a solution to the problem. To do this, answer these questions:

a. What is the basic need? First, write your problem down in simple terms. Then, identify the basic need that you'll fulfill once you've solved the problem.

For example:

b. What is the ideal outcome? Next, identify the outcome that you want to see once you've implemented a solution.

Don't think of any particular solutions at this point – your aim is to visualize the result of a successful solution, not the solution itself.

It helps to be specific here: "Increase weekly sign-ups by 20 percent" is more useful than "Increase weekly sign-ups."

c. Who will (and won't) benefit? Finally in this step, identify all of the stakeholders who will benefit, both directly and indirectly, once you've solved the problem and reached your desired outcome. Write down who these people or groups are, and the advantages that they'll see.

Also consider who may be at a disadvantage if you solve the problem.

Tools like Impact Analysis and the Futures Wheel are useful here, as they help identify the possible consequences of a change.

As you work through the next steps of this process and get more of an understanding of your problem, you may find it useful to go back and refine your answers to previous questions.

2. Justify the Need

Once you understand the need for solving the problem, you must then justify why you should solve it. To do this, answer these questions:

a. Is effort aligned with your overall strategy? This problem, and the effort that you'll be putting into solving it, must align with your organization's strategic priorities , as well as its mission and values .

b. What benefits do we want, and how can we measure these? Identify what benefits your organization, as a whole, will see when you solve this problem, and think about how you can measure these in relation to its overall strategy and objectives. Be as specific as possible.

c. Are we likely to be able to implement a solution? Think about factors such as how you'll get support from stakeholders and decision-makers, and how you'll access the required resources and expertise. This may involve speaking with senior managers in your organization to understand what resources may be available.

3. Understand the Problem and Its Wider Context

In steps 1 and 2, you identified why you need a solution, and why it's important to your strategy and mission.

The three questions in this third step encourage you to look at the problem in more depth, and to look back into the past to see what you can learn from past efforts.

a. What's the cause? First in this step, make sure that you've identified all of the causes of your problem, using tools like CATWOE , Root Cause Analysis , Cause and Effect Analysis , Systems Diagrams , and Interrelationship Diagrams .

b. What solutions already exist? Have other people in your organization tried to solve this or a similar problem in the past? If so, what did they do? What worked and what didn't work?

Next you need to find out if people outside of your organization have already tried to do something about this problem. Widen your search to include trade journals, field studies, past research, competitors, industry experts, and your personal network.

Your goal is to look at what's been done already, and what hasn't worked, so that you don't waste time working on a solution that already exists, or working on a solution that's likely to fail.

c. What are the constraints? By now, you're starting to have a deeper understanding of the problem and how it relates to your organization. Now you can brainstorm factors that might prevent you from implementing a solution. (Use your answers from question c in step 2 to help with this.)

First, look at internal constraints. Will you have access to enough people, money, and other resources to solve this problem? Are there any stakeholders who might try to block your efforts? Are there any rules or procedures that you must follow? (For instance, a new website would need to align with your organization's brand guidelines.)

Next, look externally. Are there any government regulations or laws that might stall or block your solutions? Is the technology available?

d. What requirements must a solution meet? Write down the requirements that the solution must meet in order to solve the problem successfully. As part of this, also identify other factors that, while not essential for solving the problem successfully, would add value to the final solution. For example, you might want "quiet machinery," or a "database that you can access from anywhere with an Internet connection."

e. How will we define success? Identify how you'll define success once you've implemented a solution.

4. Write a Problem Statement

The final step is to pull together all of the information that you've gathered into a clear, comprehensive problem statement. This should provide a thorough overview of the problem, and outline a plan for how you will go about solving it.

If someone else (for example, a contractor, outside organization, or other department) will be tasked with solving the problem, also work through the following questions, and include the answers to these in your problem statement:

a. Which problem solvers should we use? Identify who, specifically, is best placed to help solve this problem. This could be a person, a team, or an outside firm.

b. What information and language should the problem statement include? The problem statement needs to be clear, specific, and understood by the people who should solve it. Avoid industry jargon , and make sure that it relates to its intended audience.

c. What do problem solvers need to produce? What will you or your organization need from them? For instance, will you need a comprehensive report, or a presentation on the proposed solution? Do you want a prototype? Is there a deadline? Spell the details out here.

d. What incentives do solvers need? This question addresses motivation. If an internal team will be working on the solution, how will they be rewarded? If an external team or firm will be addressing this problem, what incentives are you offering?

e. How will we evaluate the solutions? Who will be responsible for analyzing proposals, and what evaluation method will you use?

Dwayne Spradlin published the Problem-Definition Process in the September 2012 Harvard Business Review.

The process presents four steps that help you better understand complex problems. These four steps are:

The main advantage of using the process is that it helps you to define and understand the problem in detail, and helps you understand how important a problem is in relation to your organization's mission and strategy. From this, you can determine whether or not it's worth developing a solution.

Spradlin, D. (2012) 'Are You Solving the Right Problem?' Harvard Business Review . Available here . [Accessed November 8, 2018.]

You've accessed 1 of your 2 free resources.

Get unlimited access

Discover more content

The problem-solving process.

Looking at the Basic Problem-Solving Process to Help Keep You on the Right Track

Problem-Solving Sabotage

Tips to Make You Aware of Self-Sabotage Increasing Your Chance of a Positive Solution

Add comment

Comments (0)

Be the first to comment!

Team Management

Learn the key aspects of managing a team, from building and developing your team, to working with different types of teams, and troubleshooting common problems.

Sign-up to our newsletter

Subscribing to the Mind Tools newsletter will keep you up-to-date with our latest updates and newest resources.

Subscribe now

Business Skills

Personal Development

Leadership and Management

Member Extras

Most Popular

Newest Releases

SWOT Analysis

SMART Goals

Mind Tools Store

About Mind Tools Content

Discover something new today

How to stop procrastinating.

Overcoming the Habit of Delaying Important Tasks

What Is Time Management?

Working Smarter to Enhance Productivity

How Emotionally Intelligent Are You?

Boosting Your People Skills

Self-Assessment

What's Your Leadership Style?

Learn About the Strengths and Weaknesses of the Way You Like to Lead

Recommended for you

Essential negotiation skills.

Reaching an Agreement That Works for You

Business Operations and Process Management

Strategy Tools

Customer Service

Business Ethics and Values

Handling Information and Data

Project Management

Knowledge Management

Self-Development and Goal Setting

Time Management

Presentation Skills

Learning Skills

Career Skills

Communication Skills

Negotiation, Persuasion and Influence

Working With Others

Difficult Conversations

Creativity Tools

Self-Management

Work-Life Balance

Stress Management and Wellbeing

Coaching and Mentoring

Change Management

Managing Conflict

Delegation and Empowerment

Performance Management

Leadership Skills

Developing Your Team

Talent Management

Problem Solving

Decision Making

Member Podcast

Master the 7-Step Problem-Solving Process for Better Decision-Making

Discover the powerful 7-Step Problem-Solving Process to make better decisions and achieve better outcomes. Master the art of problem-solving in this comprehensive guide. Download the Free PowerPoint and PDF Template.

StrategyPunk

Introduction

Mastering the art of problem-solving is crucial for making better decisions. Whether you're a student, a business owner, or an employee, problem-solving skills can help you tackle complex issues and find practical solutions. The 7-Step Problem-Solving Process is a proven method that can help you approach problems systematically and efficiently.

The 7-Step Problem-Solving Process involves steps that guide you through the problem-solving process. The first step is to define the problem, followed by disaggregating the problem into smaller, more manageable parts. Next, you prioritize the features and create a work plan to address each. Then, you analyze each piece, synthesize the information, and communicate your findings to others.

By following this process, you can avoid jumping to conclusions, overlooking important details, or making hasty decisions. Instead, you can approach problems with a clear and structured mindset, which can help you make better decisions and achieve better outcomes.

In this article, we'll explore each step of the 7-Step Problem-Solving Process in detail so you can start mastering this valuable skill. You can download the process's free PowerPoint and PDF templates at the end of the blog post .

Step 1: Define the Problem

The first step in the problem-solving process is to define the problem. This step is crucial because finding a solution is only accessible if the problem is clearly defined. The problem must be specific, measurable, and achievable.

One way to define the problem is to ask the right questions. Questions like "What is the problem?" and "What are the causes of the problem?" can help. Gathering data and information about the issue to assist in the definition process is also essential.

Another critical aspect of defining the problem is identifying the stakeholders. Who is affected by it? Who has a stake in finding a solution? Identifying the stakeholders can help ensure that the problem is defined in a way that considers the needs and concerns of all those affected by it.

Once the problem is defined, it is essential to communicate the definition to all stakeholders. This helps to ensure that everyone is on the same page and that there is a shared understanding of the problem.

Step 2: Disaggregate

After defining the problem, the next step in the 7-step problem-solving process is to disaggregate the problem into smaller, more manageable parts. Disaggregation helps break down the problem into smaller pieces that can be analyzed individually. This step is crucial in understanding the root cause of the problem and identifying the most effective solutions.

Disaggregation can be achieved by breaking down the problem into sub-problems, identifying the contributing factors, and analyzing the relationships between these factors. This step helps identify the most critical factors that must be addressed to solve the problem.

A tree or fishbone diagram is one effective way to disaggregate a problem. These diagrams help identify the different factors contributing to the problem and how they are related. Another way is to use a table to list the other factors contributing to the situation and their corresponding impact on the issue.

Disaggregation helps in breaking down complex problems into smaller, more manageable parts. It helps understand the relationships between different factors contributing to the problem and identify the most critical factors that must be addressed. By disaggregating the problem, decision-makers can focus on the most vital areas, leading to more effective solutions.

Step 3: Prioritize

After defining the problem and disaggregating it into smaller parts, the next step in the 7-step problem-solving process is prioritizing the issues that need addressing. Prioritizing helps to focus on the most pressing issues and allocate resources more effectively.

There are several ways to prioritize issues, including:

• Urgency: Prioritize issues based on their urgency. Problems that require immediate attention should be addressed first.
• Impact: Prioritize issues based on their impact on the organization or stakeholders. Problems with a high impact should be given priority.
• Resources: Prioritize issues based on the resources required to address them. Problems that require fewer resources should be dealt with first.

Considering their concerns and needs, it is important to involve stakeholders in the prioritization process. This can be done through surveys, focus groups, or other forms of engagement.

Once the issues have been prioritized, developing a plan of action to address them is essential. This involves identifying the resources required, setting timelines, and assigning responsibilities.

Prioritizing issues is a critical step in problem-solving. By focusing on the most pressing problems, organizations can allocate resources more effectively and make better decisions.

Step 4: Workplan

After defining the problem, disaggregating, and prioritizing the issues, the next step in the 7-step problem-solving process is to develop a work plan. This step involves creating a roadmap that outlines the steps needed to solve the problem.

The work plan should include a list of tasks, deadlines, and responsibilities for each team member involved in the problem-solving process. Assigning tasks based on each team member's strengths and expertise ensures the work is completed efficiently and effectively.

Creating a work plan can help keep the team on track and ensure everyone is working towards the same goal. It can also help to identify potential roadblocks or challenges that may arise during the problem-solving process and develop contingency plans to address them.

Several tools and techniques can be used to develop a work plan, including Gantt charts, flowcharts, and mind maps. These tools can help to visualize the steps needed to solve the problem and identify dependencies between tasks.

Developing a work plan is a critical step in the problem-solving process. It provides a clear roadmap for solving the problem and ensures everyone involved is aligned and working towards the same goal.

Step 5: Analysis

Once the problem has been defined and disaggregated, the next step is to analyze the information gathered. This step involves examining the data, identifying patterns, and determining the root cause of the problem.

Several methods can be used during the analysis phase, including:

• Root cause analysis
• Pareto analysis
• SWOT analysis

Root cause analysis is a popular method used to identify the underlying cause of a problem. This method involves asking a series of "why" questions to get to the root cause of the issue.

Pareto analysis is another method that can be used during the analysis phase. This method involves identifying the 20% of causes responsible for 80% of the problems. By focusing on these critical causes, organizations can make significant improvements.

Finally, SWOT analysis is a valuable tool for analyzing the internal and external factors that may impact the problem. This method involves identifying the strengths, weaknesses, opportunities, and threats related to the issue.

Overall, the analysis phase is critical for identifying the root cause of the problem and developing practical solutions. Organizations can gain a deeper understanding of the issue and make informed decisions by using a combination of methods.

Step 6: Synthesize

Once the analysis phase is complete, it is time to synthesize the information gathered to arrive at a solution. During this step, the focus is on identifying the most viable solution that addresses the problem. This involves examining and combining the analysis results for a clear and concise conclusion.

One way to synthesize the information is to use a decision matrix. This involves creating a table that lists the potential solutions and the essential criteria for making a decision. Each answer is then rated against each standard, and the scores are tallied to arrive at a final decision.

Another approach to synthesizing the information is to use a mind map. This involves creating a visual representation of the problem and the potential solutions. The mind map can identify the relationships between the different pieces of information and help prioritize the solutions.

During the synthesis phase, remaining open-minded and considering all potential solutions is vital. To ensure everyone's perspectives are considered, it is also essential to involve all stakeholders in the decision-making process.

Step 7: Communicate

After synthesizing the information, the next step is communicating the findings to the relevant stakeholders. This is a crucial step because it helps to ensure that everyone is on the same page and that the decision-making process is transparent.

One effective way to communicate the findings is through a well-organized report. The report should include the problem statement, the analysis, the synthesis, and the recommended solution. It should be clear, concise, and easy to understand.

In addition to the report, a presentation explaining the findings is essential. The presentation should be tailored to the audience and highlight the report's key points. Visual aids such as tables, graphs, and charts can make the presentation more engaging.

During the presentation, it is essential to be open to feedback and questions from the audience. This helps ensure everyone agrees with the recommended solution and addresses concerns or objections.

Effective communication is vital to ensuring the decision-making process is successful. Stakeholders can make informed decisions and work towards a common goal by communicating the findings clearly and concisely.

The 7-step problem-solving process is a powerful tool for helping individuals and organizations make better decisions. By following these steps, individuals can identify the root cause of a problem, prioritize potential solutions, and develop a clear plan of action. This process can be applied to various scenarios, from personal challenges to complex business problems.

Through disaggregation, individuals can break down complex problems into smaller, more manageable parts. By prioritizing potential solutions, individuals can focus their efforts on the most impactful actions. The work step allows individuals to develop a clear action plan, while the analysis step provides a framework for evaluating possible solutions.

The synthesis step combines all the information gathered to develop a comprehensive solution. Finally, the communication step allows individuals to share their answers with others and gather feedback.

By mastering the 7-step problem-solving process, individuals can become more effective decision-makers and problem-solvers. This process can help individuals and organizations save time and resources while improving outcomes. With practice, individuals can develop the skills to apply this process to a wide range of scenarios and make better decisions in all areas of life.

7-Step Problem-Solving Process PPT Template

Free powerpoint and pdf template, executive summary: the 7-step problem-solving process.

The 7-Step Problem-Solving Process is a robust and systematic method to help individuals and organizations make better decisions by tackling complex issues and finding practical solutions. This process comprises defining the problem, disaggregating it into smaller parts, prioritizing the issues, creating a work plan, analyzing the data, synthesizing the information, and communicating the findings.

By following these steps, individuals can identify the root cause of a problem, break it down into manageable components, and prioritize the most impactful actions. The work plan, analysis, and synthesis steps provide a framework for developing comprehensive solutions, while the communication step ensures transparency and stakeholder engagement.

Mastering this process can improve decision-making and problem-solving capabilities, save time and resources, and improve outcomes in personal and professional contexts.

Please buy me a coffee.

I'd appreciate your support if my templates have saved you time or helped you start a project. Buy Me a Coffee is a simple way to show your appreciation and help me continue creating high-quality templates that meet your needs.

7-Step Problem-Solving Process PDF Template

7-step problem-solving process powerpoint template.

Xpeng SWOT Analysis: Free PPT Template and In-Depth Insights (free file)

Unlock key insights into Xpeng with our free SWOT analysis PPT template. Dive deep into its business dynamics at no cost.

Strategic Insights 2024: A SWOT Analysis of Nestle (Plus Free PPT)

Explore Nestle's strategic outlook with our SWOT analysis for 2024. This PowerPoint template highlights key areas for growth and challenges.

2024 Business Disruption: Navigating Growth Through Shaping Strategy

Discover the importance of being a shaper in 2023's business ecosystem. Shaping strategy, attracting a critical mass of participants, and finding the right strategic path to create value.

Samsung PESTLE Analysis: Unveiling the Driving Forces (Free PPT)

Download our comprehensive guide: Samsung PESTLE Analysis (Free PPT). Discover the strategic insights & driving forces shaping Samsung's future.

A descriptive phase model of problem-solving processes

• Original Paper
• Open access
• Published: 09 March 2021
• Volume 53 , pages 737–752, ( 2021 )

Cite this article

You have full access to this open access article

• Benjamin Rott   ORCID: orcid.org/0000-0002-8113-1584 1 ,
• Birte Specht 2 &
• Christine Knipping 3  

7263 Accesses

18 Citations

Explore all metrics

This article has been updated

Complementary to existing normative models, in this paper we suggest a descriptive phase model of problem solving. Real, not ideal, problem-solving processes contain errors, detours, and cycles, and they do not follow a predetermined sequence, as is presumed in normative models. To represent and emphasize the non-linearity of empirical processes, a descriptive model seemed essential. The juxtaposition of models from the literature and our empirical analyses enabled us to generate such a descriptive model of problem-solving processes. For the generation of our model, we reflected on the following questions: (1) Which elements of existing models for problem-solving processes can be used for a descriptive model? (2) Can the model be used to describe and discriminate different types of processes? Our descriptive model allows one not only to capture the idiosyncratic sequencing of real problem-solving processes, but simultaneously to compare different processes, by means of accumulation. In particular, our model allows discrimination between problem-solving and routine processes. Also, successful and unsuccessful problem-solving processes as well as processes in paper-and-pencil versus dynamic-geometry environments can be characterised and compared with our model.

Similar content being viewed by others

Competencies for Complexity: Problem Solving in the Twenty-First Century

Naturalising Problem Solving

The Noble Art of Problem Solving

Avoid common mistakes on your manuscript.

1 Introduction

Problem solving (PS)—in the sense of working on non-routine tasks for which the solver knows no previously learned scheme or algorithm designed to solve them (cf. Schoenfeld, 1985 , 1992b )—is an important aspect of doing mathematics (Halmos, 1980 ) as well as learning and teaching mathematics (Liljedahl et al. 2016 ). As one of several reasons, PS is used as a means to help students learn how to think mathematically (Schoenfeld, 1992b ). Hence, PS is part of mathematics curricula in almost all countries (e.g., KMK, 2004 ; NCTM, 2000 , 2014 ). Accordingly, PS has been a focus of interest of researchers for several decades, Pólya ( 1945 ) being one of the most prominent scholars interested in this activity.

Problem-solving processes (PS processes) can be characterised by their inner or their outer structure (Philipp, 2013 , pp. 39–40). The inner structure refers to (meta)cognitive processes such as heuristics, checks, or beliefs, whereas the outer structure refers to observable actions that can be characterised in phases like ‘understanding the problem’ or ‘devising a plan’, as well as the chronological sequence of such phases in a PS process. Our focus in this paper is on the outer structure, as it is directly accessible to teachers and researchers via observation.

In the research literature, there are various characterisations of PS processes. However, almost all of the existing models are normative , which means they represent idealised processes. They characterise PS processes according to distinct phases, in a predetermined sequence, which is why they are sometimes called ‘prescriptive’ instead of normative. These phases and their sequencing have been formulated as a norm for PS processes. Normative models are generally used as a pedagogical tool to guide students’ PS processes and to help them to become better problem solvers. The normative models in current research have mostly been derived from theoretical considerations. Nevertheless, real PS processes look different; they contain errors, detours, and cycles, and they do not follow a predetermined sequence. Actual processes like these are not considered in normative models. Accordingly, there are almost no models that guide teachers and researchers in observing, understanding, and analysing PS processes in their ‘non-smooth’ occurrences (cf. Fernandez et al. 1994 ; Rott, 2014 ). Our aim in this paper, therefore, is to address this research gap by suggesting a descriptive model.

A descriptive model enables not only the representation of real PS processes, but also reveals additional potential for analyses. Our model allows one systematically to compare several PS processes simultaneously by means of accumulation, which is an approach that to our knowledge has not been proposed before in the mathematics education community. In Sect.  6 , we show how this approach can be used to reveal ‘bumps and bruises’ of real students’ PS processes to illustrate the practical value of our descriptive model (Sect.  5.3 , Fig.  5 ). We show how our model allows one to discriminate problem-solving processes from routine processes when students work on tasks. We illustrate how differences between successful and unsuccessful processes can be identified using our model. We also reveal how students’ PS processes, working in a paper-and-pencil environment compared to working in a digital (dynamic geometry) environment , can be characterised and compared by means of our model.

Our descriptive model is based on intertwining theoretical considerations, in the form of a review of existing models, as well as on a video-study researching the processes shown by mathematics pre-service teachers working on geometrical problems.

2 Theoretical background

In this section, we first describe and compare aspects of existing models of PS processes (which are mostly normative) to characterize their potential and their limitations for analysing students’ PS processes (2.1). We then discuss why looking specifically at students’ PS processes in geometry and in dynamic geometry contexts is of particular value for developing a descriptive model of PS processes (2.2).

2.1 Models of problem-solving processes

Looking at models from mathematics, mathematics education, and psychology that describe the progression of PS processes, we find phase models, evolved by authors observing their own PS processes or those of people with whom the authors are familiar. So, the vast majority of existing PS process models are not based on ‘uninvolved’ empirical data (e.g., videotaped PS processes of students); they were actually not designed for the analysis of empirical data or to describe externally observed processes, which emphasises the need for a descriptive model.

2.1.1 Classic models of problem-solving processes

Two ‘basic types’ of phase models for PS processes have evolved in psychology and mathematics education. Any further models can be assigned to one or the other of these basic types: (1) the intuitive or creative type and (2) the logical type (Neuhaus, 2002 ).

Intuitive or creative models of PS processes originate in Poincaré’s ( 1908 ) introspective reflection on his own PS processes. Building on his thoughts, the mathematician Hadamard ( 1945 ) and the psychologist Wallas ( 1926 ) described PS processes with a particular focus on subconscious activities. Their ideas are most often summarised in a four-phase model: (i) After working on a difficult problem for some time and not finding a solution ( preparation ), (ii) the problem solver does and thinks of different things ( incubation ). (iii) After some more time—hours, or even weeks—suddenly, a genius idea appears ( illumination ), providing a solution or at least a significant step towards a solution of the problem; (iv) this idea has to be checked for correctness ( verification ).

So-called logical models of PS processes were introduced by Dewey ( 1910 ), describing five phases: (i) encountering a problem ( suggestions ), (ii) specifying the nature of the problem ( intellectualization ), (iii) approaching possible solutions ( the guiding idea and hypothesis ), (iv) developing logical consequences of the approach ( reasoning (in the narrower sense) ), and (v) accepting or rejecting the idea by experiments ( testing the hypothesis by action ). Unlike in Wallas’ model, there are no subconscious activities described in Dewey’s model. Pólya’s ( 1945 ) famous four-phase model—(i) understanding the problem , (ii) devising a plan , (iii) carrying out the plan , and (iv) looking back —manifests, according to Neuhaus ( 2002 ), references to Dewey’s work.

Research in mathematics education mainly focuses on logical models for describing PS processes, following Pólya or more recent variants of his model (see below). This is due to the fact that PS processes of the intuitive or creative type might take hours, days, or even weeks to allow for genuine incubation phases, and PS activities in the context of schooling and university teaching are mostly shorter and more contained. Therefore, we focus on logical models. In the following, we compare prominent PS process phase models that emerged in the last decades (see Fig.  1 ).

Different phase models of problem-solving processes

2.1.2 Recent models of problem-solving processes

In Fig.  1 , different models are presented (for more details see the appendix). These build on and alter distinct aspects of Pólya’s model, especially envisioned phases and possible transitions between these phases. They mark this distinction by using different terminology for these nuanced differences in the phases. The models by Mason et al. ( 1982 ), Schoenfeld ( 1985 , Chapter 4), and Wilson et al. ( 1993 ; Fernandez et al. 1994 ) are normative; they are mostly used for teaching purposes, that is, to instruct students in becoming better problem solvers. Compared to actual PS processes, these models comprise simplifications; looking at and analysing students’ PS processes requires models which are suited to portray these uneven and cragged processes.

In several studies, actual PS processes are analysed; however, only a few of these studies use any of these normative models that describe the outer structure of PS processes. Even fewer studies present a descriptive model as part of their results. Some of the rare studies that attempt to derive such a model are presented in more detail in the appendix; their essential ideas are presented below (Artzt & Armour-Thomas, 1992 ; Jacinto & Carreira, 2017 ; Yimer & Ellerton, 2010 ).

2.1.3 Comparing models of problem-solving processes

In this section, we compare the previously mentioned as well as additional phase models with foci on (a) the different types of phases and (b) linearity or non-linearity of the portrayed PS processes. Figure  1 illustrates similarities and differences in these models, starting with those of Dewey ( 1910 ) and Pólya ( 1945 ) as these authors were the first to suggest such models. Schoenfeld ( 1985 ) and Mason et al. ( 1982 ) introduced this discussion to the mathematics education community, referring back to ideas of Pólya. Then, we discuss those of Wilson et al. ( 1993 ), and Yimer and Ellerton ( 2010 ), as examples of more recent models in mathematics education.

Different types of phases

The presented models comprise three, four, or more different phases. However, we do not think that this number is important per se; instead, it is interesting to see which activities are encompassed in these phases of the different models and in the extent and manner in which they follow Pólya’s formulation, adopt it, or go beyond his ideas. In Fig.  1 , we indicated Pólya’s phases with differently patterned layers in the background.

Dewey’s ( 1910 ) model starts with a phase (named “suggestions”) in which the problem solvers come into contact with a problem without already analysing or working on it. Such a phase is seldom found in phase models in the context of mathematics education. In mathematics though this phase at the beginning is typical and important, as Dewey already pointed out. In the context of teaching, on the other hand, PS mostly starts with a task handed to the students by their teachers. Analysing and working on the problem is expected right from the beginning; this is part of the nature of the provided task. So, in educational research the phase of “suggestions” is rarely mentioned, as it normally does not occur in students’ PS processes.

“Understanding the problem”, Pólya’s ( 1945 ) first phase, is comparable to the second phase (“intellectualization”) of Dewey’s model. In this phase, problem solvers are meant to make sense of the given problem and its conditions. Such a phase is used in all models, though often labelled slightly differently (see Fig.  1 for a juxtaposition). Artzt and Armour-Thomas, ( 1992 ) facing the empirical data of their study, differentiated this phase of “understanding the problem” into a first step, where students are meant to apprehend the task (“understanding”), and a second step, where students are actually expected to comprehend the problem (“analysing”); a similar differentiation is presented by Jacinto and Carreira ( 2017 ) into “grasping, noticing” and “interpreting” a problem.

The next two phases incorporate the actual work on the problem. Pólya describes these phases as “devising” and “carrying out a plan”. Especially the planning phase encompasses many different activities, such as looking for similar problems or generalizations. These two phases are also integral parts of the models by Wilson et al. ( 1993 ), and Yimer and Ellerton ( 2010 ) (see Fig.  1 ), or Jacinto and Carreira ( 2017 , there called “plan” and “create”). Mason et al. ( 1982 ) chose to combine both phases, calling this combined phase “attack”. According to their educational and research experience, they noted that both phases cannot be distinguished in most cases; therefore, a differentiation would not be helpful for learning PS and describing PS processes. Schoenfeld ( 1985 ), on the contrary, further differentiated those phases by splitting Pólya’s second phase into a structured “planning” (or “design”) phase and an unstructured “exploration” phase. When “planning”, one might adopt a known procedure or try a combination of known procedures in a new problem context. However, when known procedures do not help, working heuristically (e.g., looking at examples, counter-examples, or extreme cases) might be a way to approach the given problem in “exploration” (Schoenfeld, 1985 , p. 106). According to Schoenfeld, exploration is the “heuristic heart” of PS processes.

The last phase in Pólya’s model is “looking back”, the moment when a solution should be checked, other approaches should be explored, and methods used should be reflected upon. This phase is also present in other models (see Fig.  1 ). In their empirical approach, Yimer and Ellerton ( 2010 ), for example, differentiated this phase into two steps, namely, “evaluation” (i.e., checking the results), which refers to looking back on the recently solved problem, and “internalization” (i.e., reflecting the solution and the methods used), which focuses on what has been learnt by solving this problem and looks forward to using this recent experience for solving future problems. Jacinto and Carreira ( 2017 ) used the same “verifying” phase as Pólya, but added a “disseminating” phase for presenting solutions, as their final phase.

Other researchers (see the appendix) came to insights similar to those of these researchers, using slightly different terminologies when describing these phases or combinations of these phases.

Sequence of phases: linear or non-linear problem-solving processes

Other important aspects are transitions from one phase to another, and how such transitions occur. The graphical representations of different models in Fig.  1 not only indicate slightly different phases (and distinct labels for these phases), but also illustrate different understandings of how these phases are related and sequenced.

There are strictly linear models like Pólya’s ( 1945 ), which outline four phases that should be passed through when solving a problem, in the given order. Of course, Pólya as a mathematician knew that PS processes are not always linear; in his normative model, however, he proposed such a stepwise procedure, which has often been criticised (cf. Wilson et al. 1993 ). Mason et al. ( 1982 ) and Schoenfeld ( 1985 ) discarded this strict linearity, including forward and backward steps between analysing, planning, and exploring (or attacking, respectively) a problem. Thereafter, PS processes linearly proceed towards the looking back equivalents of their models. Wilson et al. ( 1993 ) presented a fully “dynamic, cyclic interpretation of Polya’s stages” (p. 60) and included forward and backward steps between all phases, even after “looking back”. The same is true for Yimer and Ellerton ( 2010 ), who included transitions between all phases in their model.

As we illustrate later, transitions from one phase to another reflect also characteristic features of routine and non-routine processes in general, and can be also distinctive for students’ PS processes in traditional paper-and-pencil environments compared to Dynamic Geometry Software (DGS) contexts. Our descriptive model of PS processes, which we present in Sect.  5 , also evolved by comparative analyses of students’ PS processes in both learning contexts. Thus, we comment briefly in 2.2 on what existing research has found in this respect so far.

2.2 Problem solving in geometry and dynamic geometry software

Overall, geometry is especially suited for learning mathematical PS in general and PS strategies or heuristics in particular (see Schoenfeld, 1985 ). Notably, many geometric problems can be illustrated in models, sketches, and drawings, or can be solved looking at special cases or working backwards (ibid.). Additionally, the objects of action (at least in Euclidean geometry) and the permitted actions (e.g., constructions with compasses and ruler) are easy to understand. Therefore, in our empirical study (see Sect.  4 ), we opted for PS processes in geometry contexts, knowing that other contexts could be equally fruitful.

One particular tool to support learning and working in the context of geometry, since the 1980s, is DGS, which is characterised by three features, namely, dragmode, macro-constructions, and locus of points (Sträßer, 2002 ). With these features, DGS can be used not only for verification purposes, but also for guided discoveries as well as working heuristically (e.g., Jacinto & Carreira, 2017 ). However, as Gawlick ( 2002 ) pointed out, to profit from such an environment, students—especially low achievers—need some time to get accustomed to handling the software. Comparing DGS and paper-and-pencil environments, Koyuncu et al. ( 2015 ) observed that in a study with two pre-service teachers, “[b]oth participants had a tendency toward using algebraic solutions in the [paper-and-pencil based] environment, whereas they used geometric solutions in the [DGS based] environment.” (p. 857 f.). These potential differences between PS processes in paper-and-pencil versus DGS environments are interesting for research and practice. Therefore, we compared students’ PS processes in these two environments in our empirical study.

3 Research questions

With regard to research on PS processes, it is striking that there is only a small number of studies, often with a low number of participants, that present and apply a descriptive model of PS processes. Further, the identified models are not suited for comparing PS processes across groups of students, but can only describe cases. Last but not least, in most empirical studies, the selection of phases that are included, and the assumption of (non-)linearity, are not discussed and/or justified. In all these respects, we see a research gap. Contributing to filling this gap was one of the motivations for the study presented here. Based on the existing research literature, we formulated two main research questions:

What elements of the already discussed PS process models can be used for a descriptive model? In particular, what is necessary so that such a descriptive model enables

a recognition of types of phases and an identification of phases in actual PS processes as well as

an identification of the sequence (i.e., the order, linear or non-linear) of phases and transitions between phases?

Can the model be used to describe and discriminate among different types of PS processes, for example

routine and non-routine processes,

successful and not successful processes, or

paper-and-pencil vs. DGS processes?

These questions guided our study and the motivation for developing a descriptive model of PS processes. Next, we present the methodology, before we discuss results of our empirical study and present our model.

4 Methodology

In a previous empirical study, we looked at PS processes of pre-service teacher students in geometry contexts. The data in this study were enormously rich and challenged us in their analyses in many ways. Existing PS models did not allow us to harvest fully this rich data corpus and we realised that with respect to our empirical data, we needed a descriptive model. So we formulated the research questions listed above in order to explore the potential and necessary extensions of the existing normative PS process models. We changed our perspective and focused on the development of an empirically grounded theoretical model. We required an approach that would allow us to mine the data of our empirical study and to provide a conceptualisation that could be helpful for further research on students’ problem-solving processes. The methodological approach we used is described in the following.

4.1 Our empirical study

About 250 pre-service teacher students attended a course on Elementary Geometry , which was conceived and conducted by the third author at a university in Northern Germany. The course lasted for one semester (14 weeks); each week, a two-hour lecture for all students as well as eight 2-h tutorials for up to 30 students each, supervised by tutors (advanced students), took place. Four tutorials (U1, Ulap2, U3, and Ulap4) were involved in this study: in U1 and U3 the students worked in a paper-and-pencil environment, in Ulap2 and Ulap4 the students used laptop computers to work in a DGS environment. (The abbreviations consist of U, the first letter ‘Uebung’, German for tutorial, with an added ‘lap’ for groups which used laptop computers as well as an individual number.) Students worked on weekly exercises, which were discussed in the tutorials. In addition, over the course of the semester, in groups of three or four, the students worked on five geometric problems in the tutorials (approx. 45 min for each problem), accompanied by as little tutor help as possible. In this paper, we focus on these five problems. See the appendix for additional information regarding the organisation of our study.

The five problems were chosen so that students had the opportunity to solve a variety of non-routine tasks, which at the same time did not require too much advanced knowledge that students might not have.

For each of the five problems, two groups from each of the four tutorials were observed. Each problem was therefore worked on by four groups with and four groups without DGS (minus some data loss because of students missing tutorials or technical difficulties). The collected data were videos of the groups working on these problems ( processes ), notes by the students ( products ), as well as observers’ notes. Overall, 33 processes (15 from paper-and-pencil as well as 18 from DGS groups) from all five problems, with a combined duration of 25 h, were analysed. For space reasons, we cannot discuss all five problems in detail here. Instead, we present three of the five problems here; the other two can be found in the appendix.

4.1.1 The problems

Regarding the ‘Shortest Detour’ (Fig.  2 , top), as long as A and B are on different sides of the straight line, a line segment from A to B is the shortest way. When A and B are on the same side of g , an easy (not the only) way to solve this problem is by reflecting one of the points, e.g. A , on g and then constructing the line segment from the reflection of A to B , as reflections preserve lengths.

Three of the five problems used in our study

Part a) of the ‘Three Beaches’ problem (Fig.  2 , bottom), finding the incircle of an equilateral triangle, should be a routine-procedure as this topic had been discussed in the lecture. Students working on part b) of this problem needed to realize that in an equilateral triangle, all points have the same sum of distances to the sides (Viviani’s problem). This could be justified by showing that the three perpendiculars of a point to a side in such a triangle add up to the height of this triangle, for example by geometrical addition or by calculating areas.

Like Problem (4), Problem (3) (Fig.  2 , middle) contained an a)-part which is a routine task—finding the circumcircle of a (non-regular) triangle—and a b)-part that constitutes a problem for the students.

These tasks were chosen because they actually represented problems for our students, and expected PS processes appeared neither too long nor too short for a reasonable workload by students and for our analyses. Further, the problems covered the content of the accompanying lecture, and the problems could be solved both with and without DGS.

Differences between working with and without DGS: With DGS many examples can be generated quickly, so that an overview of the situation and the solution can be obtained in a short time. For the justifications, however, with and without DGS, students had to reflect, think, and reason to find appropriate arguments.

4.2 Framework for the analysis of the empirical data

For the analyses of our students’ PS processes, we used the protocol analysis framework by Schoenfeld ( 1985 , Chapter 9) with adaptations and operationalizations by Rott ( 2014 ), following two phases of coding.

Process coding: With his framework, Schoenfeld ( 1985 ) intended to “identify major turning points in a solution. This is done by parsing a [PS process] into macroscopic chunks called episodes” (p. 314). An episode is “a period of time during which an individual or a problem-solving group is engaged in one large task […] or a closely related body of tasks in the service of the same goal […]” (p. 292). Please note, the term “episode” refers to coded process data, whereas “phase” refers to parts of PS models. Schoenfeld (p. 296) continued: “Once a protocol has been parsed into episodes, each episode is characterized” using one of six categories (see also Schoenfeld, 1992a , p. 189):

Reading or rereading the problem.

Analysing the problem (in a coherent and structured way).

Exploring aspects of the problem (in a much less structured way than in Analysis).

Planning all or part of a solution.

Implementing a plan.

Verifying a solution.

According to Schoenfeld ( 1985 ), Planning-Implementation can be coded simultaneously.

The idea of episodes as macroscopic chunks implies a certain length, thus individual statements do not comprise an episode; for example, quickly checking an interim result is not coded as a verification episode. Also, PS processes are coded by watching videos, not by reading transcripts (Schoenfeld, 1992a ).

Schoenfeld’s framework was chosen to answer our first research question, for two reasons. (i) The episode types he proposed cover a lot of the variability of phases also identified by us (see Sect.  2.1.3 ). (ii) Coding episodes and coding episode types in independent steps offers the possibility of adding inductively new types of episodes.

After parsing a PS process into episodes, we coded the episodes with Schoenfeld’s categories (deductive categories), but also generated new episode types to characterize these episodes (inductive categories). While coding, we observed initial difficulties in coding the deductive episodes reliably; especially differentiating between Analysis and Exploration episode types was difficult (as predicted by Schoenfeld, 1992a , p. 194). We noticed that Schoenfeld’s ( 1985 , Chapter 9) empirical framework referred to his theoretical model of PS processes (ibid., Chapter 4) which was based on Pólya’s ( 1945 ) list of questions and guidelines. Recognizing an analogy between Schoenfeld’s framework and Pólya’s work (see Fig.  1 ), we were able to operationalize their descriptions in a coding manual (see Rott, 2014 ).

When the deductive episode types did not fit our observations, we inductively added a new episode type. This happened three times. Especially in the DGS environment, where students showed behaviour that was not directly related to solving the task, new types of activities occurred. For example, students talked about the software and how to use it. This kind of behaviour was coded by us as Organization . When it took students more than 30 s to write down their findings (without developing any new results or ideas), this episode was coded as Writing . Discussions about things which were not related to mathematics, but for example daily life, were coded as Digression . These codings were used only when activities did not align with numbers 2–6 of Schoenfeld’s list.

This coding of the videotapes was done independently by different research assistants and the first author. We then applied the “percentage of agreement” ( P A ) approach to compute the interrater-agreement as described in the TIMSS 1999 video study (Jacobs et al. 2003 , pp. 99–105), gaining more than P A  = 0.7 for parsing PS processes into episodes and more than P A  = 0.85 for characterizing the episode types. More importantly, every process was coded by at least two raters. Whenever those codes did not coincide, we attained agreement by recoding together (as in Schoenfeld’s study, 1992a , p. 194).

Product coding : To be able to compare successful and unsuccessful PS processes, students’ products produced in the 45-min sessions were rated. Because the focus was on processes, product rating finally was reduced to a dichotomous right/wrong coding without going into detail regarding students’ argumentations (these will be analysed and the results reported in forthcoming papers). Rating was done independently by a research assistant and the first author with an interrater-agreement of Cohen’s kappa > 0.9. Differing cases were discussed and recoded consensually.

5 Results of our empirical study and implications for our descriptive model

In this section, we briefly illustrate results of our data analyses, which underline the need to go beyond existing models. We summarize key findings of our empirical study and illustrate how these have contributed to the development of our descriptive model of PS processes. After this, we highlight how answering our research questions based on our theoretical and empirical analyses contributes to the development of our descriptive model. Finally, we present and describe our descriptive model.

5.1 Sample problem-solving processes and codings to illustrate the procedure of analysis

To illustrate our analyses and codings of students’ PS processes, we present three sample processes, the first two in detail and the third one only briefly. The first two were paper-and-pencil processes and stem from the same group of students, belonging to parts a) and b) of the ‘Three Beaches’ problem. The third process shows a group of students working on the ‘Shortest Detour’ problem with DGS. Our codings of the different episodes are highlighted in italics .

5.1.1 Group U1-C, Three Beaches (part a))

After reading the Three Beaches problem (00:25–01:30), the three students of group C from tutorial U1 try to understand it. They remember the Airport problem in which they had to find a point with the same distance to all three vertices of a triangle and they try to identify the differences between both problems. The students wonder whether they should again use the perpendicular bisectors of the sides of the triangle or the bisectors of the angles of the triangle ( Analysis , 01:30–05:05). They agree to use the bisectors of the angles and construct their solutions with compasses and ruler. One of the students claims that in the case of an equilateral triangle, perpendicular and angle bisectors would be identical and convinces the others by constructing a triangle and both bisectors with compasses and ruler ( Planning-Implementation , 05:05–06:05). Finally, the students verify their solution by discussing the meaning of the distance from a point to the sides of a triangle, as they initially were not sure how to measure this distance (06:05–07:40). Even though the Analysis episode was quite long (see Fig.  3 ), this part of the task was actually not a problem for the students as they remembered a way to solve it.

Process codings of the group U1-C, working on the ‘Three Beaches’ problem

5.1.2 Group U1-C, three beaches (part b))

After reading part b) of the problem (07:45–07:55), the students discuss whether the requested point is the same as in a) ( Analysis , 07:55–10:25). They agree to try out and construct a triangle each, place points in it, draw perpendiculars to the sides, and measure the distances. One student asks whether it is allowed to place the point on a vertex and thus have two distances become zero ( Exploration , 10:25–15:30). After this, the students discuss the meaning of distance, particularly the meaning of a distance related to a side of a triangle. They agree that any point on a side, even the vertex, would satisfy the condition of the problem, thus being a suitable site for the ‘house’ ( Analysis , 15:30–16:40). The students wonder why the distance from one vertex to its opposing side (the height of the triangle) is as large as the sum of the distances from the centre of the incircle (from part a)). They remember that the angle bisectors intersect each other in a ratio of 1/3 to 2/3. Thereafter, they continue to place points in their triangles (not on sides) and measure their distances. They finally agree on the [wrong] hypothesis that any point on the angle bisectors is a point with a minimal sum of the distances to the sides; other points in the triangle would have a slightly larger sum [because of inaccuracies in their drawings]. They realize, however, that they cannot give any reasons for their solution ( Exploration , 16:40–32:30). The codings are represented in Fig.  3 (right).

5.1.3 Group Ulap2-TV, shortest detour

Ulap2-TV working on the shortest detour problem (Fig.  4 ) is an example of a process with more transitions. The students solve the first case of the problem ( A and B on different sides of g ) within 5 min ( Planning-Implementation , Verification ) and then explore the second case ( A and B on the same side of g ) for more than 17 min before solving the problem.

Process coding of the group Ulap2-TV, working on the ‘Shortest Detour’ problem

We selected these three PS processes from our study, as they are examples of our empirical data in several aspects: They illustrate both learning environments (paper-and-pencil and DGS), they incorporate all types of episodes (except for Digression ) and, therefore, all types of phases discussed in the PS research literature, and they include linear and cyclic progressions (see below). The routine process (Three Beaches, part a)) is rather atypical as the students take a lot of time analysing the task, before implementing routine techniques ( Planning-Implementation ). The two PS processes (Three Beaches, part b) and Shortest Detour) are typical for our students, spending a lot of time in Exploration episodes. In the DGS environment, we see that the students take some time to handle the software ( Organization ). Compared to free-hand drawings in paper-and-pencil environments, the students in the DGS environment need to think about constructions ( Planning ) before exploring the situation.

5.2 From theoretical models and empirical results to a descriptive model of problem-solving processes

In the following, the coded episodes from all 33 PS processes of our empirical study are used to answer the first research question. What parts or phases of the established models are suited to describe the analysed processes? Which transitions between phases can be observed? The systematic comparison of PS models from the literature (Sect.  2.1.3 ) is the theoretical underpinning of answering these questions. This process aims at generating a descriptive process model suitable for representing students’ actual PS processes.

5.2.1 Different types of episodes that are suited to describing empirical processes

Within the observed processes, all of Schoenfeld’s episode types could be identified with high interrater agreement. Thus, based on our data, we saw no need to merge phases like Understanding and Planning , even though some models suggest doing so.

More specifically, structured approaches of Planning could be differentiated from unstructured approaches which we call Explorations as suggested by Schoenfeld ( 1985 , Chapters 4 & 9) (in 6 out of 33 non-routine processes, both Exploration and Planning were coded).

Furthermore, in some processes, Planning and Implementation episodes can be differentiated from each other (as suggested by Pólya, 1945 ); there are, however, processes in which those two episode types cannot be distinguished as the problem solvers often do not announce their plans (as predicted by Mason et al. 1982 ). In those PS processes, these two episode types are merged to Planning-Implementation (as done by Schoenfeld as well).

Verification episodes are rare, but can be found in our data. As our students do not show signs of trying to reflect on their use of PS strategies, we decided not to distinguish this episode type into ‘checking’ and ‘reflection’.

Incubation and illumination could not be observed in our sample. This was expected as the students did not have the time to incubate.

Altogether, the following theoretically recorded phases could be identified in our empirical data and are part of our model: understanding (analysis), exploration, planning, implementation (sometimes as planning-implementation), and verification.

5.2.2 Transitions between phases: linearity and non-linearity of the processes

Apart from the phases that occur, the transitions between these phases are of interest. Transitions have been coded between nearly all possible ordered pairs of episode types. If the phases proceed according to Pólya’s or Schoenfeld’s model ( Analysis → Exploration → Planning → Implementation → Verification ), we consider this as a linear process. If phases are omitted within a process but this order is still intact we regard this process still as ‘linear’. In contrast, a process is considered by us as non-linear or cyclic, if this order is violated (e.g., Planning → Exploration ). We also checked whether non-linear processes are cyclic in the sense of Wilson et al. (backward steps are possible after all types of episodes), or whether they are cyclic in the sense of Schoenfeld and Mason et al. (backward steps only before Implementation ).

The first sample process (Three Beaches, part a) illustrates a strictly linear approach as in Pólya’s model, represented in the descending order of the time bars (Fig.  3 , left). The second example (Three Beaches, part b) shows a cyclic process as after the first Exploration , an Analysis was coded (Fig.  3 , right). The third example (Shortest Detour) starts in a linear way; then, after a first Verification , the students go back to Planning-Implementation and Exploration episodes. Thus, overall, their process is cyclic (and not in a way that would fit Schoenfeld’s model as the linear order is broken after a Verification ).

We checked all our process codings for their order of episodes (see Table 1 ). In our sample, a third of the processes are non-linear; thus, a strictly linear model is not suited to describing our students’ PS processes.

5.3 Deriving a model for describing problem-solving processes

Using the results of our empirical study as described in Sects.  5.1 and 5.2 , our findings result in a descriptive model of PS processes. We consider this model as an answer to our first research question. We identified phases from (mostly normative) models in our data, then empirically refined these phases, and took the relevance of their sequencing into account as illustrated in Fig.  5 .

Descriptive model of problem-solving processes

In our descriptive model (see Fig.  5 ), we distinguish between structured ( Planning ) and unstructured ( Exploration ) approaches in accordance with the model of Schoenfeld ( 1985 ). It is also possible to differentiate between explicit planning ( Planning and Implementation coded separately) as well as implicit planning, which means (further) developing a plan while executing it ( Planning and Implementation coded jointly), as suggested by Mason et al. ( 1982 ). Our descriptive model combines ideas from different models in the literature. Furthermore, linear processes can be displayed (using only arrows that point downwards in the direction of the solution) as can non-linear processes (using at least one arrow that points upwards). Therefore, with this model, linear and non-linear PS processes can explicitly be distinguished from each other. Please note that we use ‘(verified) solution’ with a restriction in brackets, as not all processes lead to a verified or even correct solution. Our model is a model of the outer structure as it describes the observable sequence of the different phases.

In the following, we illustrate how far our descriptive model can also respond to our second research question. We use it to describe, as well as to distinguish different types of PS processes.

6 Using our descriptive model to analyse problem-solving processes

Below, we illustrate how our descriptive model (Fig.  5 ) can be used to analyse and compare students’ PS processes. We first reconstruct different processes of student groups and then propose a new way to represent typical transitions in students’ PS processes.

6.1 Representing students’ problem-solving processes

In contrast to the process coding by Schoenfeld, which contains specific information about the duration of episodes, our analyses are more abstract. We focus on the empirically found types of episodes and transitions between these episodes. This is done following Schoenfeld ( 1985 ), who emphasised: “The juncture between episodes is, in most cases, where managerial decisions (or their absence) will make or break a solution” (p. 300). Focusing on the transitions between episodes is one important characteristic that distinguishes different types of PS processes. Using our descriptive model allows one to do this.

For each process, the transitions between episodes can be displayed with our model (Fig.  5 ). In the following, we consider only the five content-related episode types, but not Reading , Organization , Writing , and Digression, as activities of the latter types of episodes do not contribute to the solution and they are not ordered as in Pólya’s or Schoenfeld’s phases.

For example, the routine process of group U1-C (Three Beaches, part a), see Sect.  5.1 ), starts with an Analysis , followed by a merged Planning-Implementation and a Verification or, in short: [A,P-I,V]; thereafter, this process ends. This means, there are four different transitions in this process indicated by arrows: Start → A, A → P-I, P-I → V, and V → End. Thus, in Fig.  6 (left), these transitions are illustrated with arrows. In this case, these transitions each occur only once, which is indicated by a circled number 1.

Translation from Schoenfeld codings to a representation using the descriptive model; the circled numbers indicate the number of times a transition occurs

The second example (U1-C, Three Beaches, part b)) consists of the following episodes: Analysis–Exploration–Analysis–Exploration [A,E,A,E]. This means that there are five transitions in this process: Start → A, A → E, E → A, A → E, and E → End (see Fig.  6 , middle). Please notice that the transition A → E is observed twice.

The final example shows group Ulap2-TV (Shortest Detour), which starts with a Planning-Implementation and proceeds through [P-I,V,P,E,P-I,V] with a total of seven transitions, two of which are P-I → V (ignoring Organization and Writing , Fig.  6 , right).

This reduction to transitions, neglecting the exact order and the duration of episodes, enables one to do a specific comparison of processes and an accumulation of several PS processes (e.g., from all DGS processes, see Sect.  6.2 ). The focus is now on transitions and how often they happen, which indicates different types of PS processes as shown below. This ‘translation’ from the Schoenfeld coding to the representation in our descriptive model has been done for all 33 processes. The directions of the arrows indicate from which phase to which the transitions are occurring, e.g., from analysis to planning; the numbers on the arrows show how often these transitions were coded (they do not indicate an order).

The three selected processes already show clearly different paths, for example, linear vs. cyclic (see Sect. 2.2.4).

6.2 Characterizing types of problem-solving processes by accumulation

Students’ PS processes can be successful or non-successful or conducted in paper-and-pencil or DGS contexts. Looking at different groups of students simultaneously can be fruitful, as such accumulations allow one to look at patterns in existing transitions. Our descriptive model allows one to consider several processes at once, via accumulation.

Representations of single processes, as presented in Fig.  6 and in the boxes in Fig.  7 , can be combined by adding up all coded transitions (which would be impossible with time bars used by Schoenfeld). For such an accumulation, we count all transitions between types of episodes and display them in numbers next to the arrows representing the number of those transitions. For example, six of the processes in the outer boxes start with a transition from the given problem to Planning , while one process begins with an Analysis . This is shown in the centre box by the numbers 6 and 1 in the arrows from the given problem to Planning and Analysis , respectively (see Fig.  7 for the combination of all processes regarding task 3a). Arrows were drawn only where transitions actually occurred in this task. Looking at the arrows that start at the ‘given problem’ or that lead to the ‘(verified) solution’, one can see how many processes were accumulated. All episode types (small boxes) must have the same number of transitions towards as well as from this episode type.

Centre rectangle: Accumulation of seven different group processes regarding task 3a)

To show the usability of our model, we distinguish between working on routine tasks and on problems in Sect.  6.2.1 ; thereafter, the routine processes are not further considered.

6.2.1 Routine vs. non-routine processes

In our study, two sub-tasks (3a) and 4a)) were routine tasks in which the students were asked to find special points in triangles. If we look at the accumulations of those processes in our model, clear patterns emerge: There are no Exploration episodes at all, either in the seven processes of task 3a) (Fig.  8 , left) nor in the eight processes of tasks 4a) (Fig.  8 , middle). Instead, there are Planning and/or Implementation episodes in all 15 processes. In some of those processes, Planning and Implementation can clearly be coded as two separate episodes. In other processes, it is not possible to discriminate between these episode types as two distinct episodes in the empirical data (see Fig.  8 ).

Accumulation of seven processes for the routine task 3a) (left) and eight processes for task 4a) (middle), 15 processes in total (right)

Most processes (12 out of 15) show no need for analysing the task but start directly with Planning and/or Implementation . Even though there are five Verification episodes, these verifications are often only short checking activities with no reflection in the sense of Pólya; however, the length and quality of an episode cannot be seen in the model. Additionally, all of these 15 processes are linear (as can be seen by the arrows, which point only downwards).

In contrast to these routine tasks, non-routine processes are often non-linear and contain at least one Exploration episode. In Fig.  9 , in direct comparison to Fig.  8 , the seven PS processes of problem 3a) (left), the eight PS processes of problem 3b) (middle), and an accumulation of the 15 PS processes (right) are shown. Overall, in these 15 processes, 17 Exploration episodes were coded, which can be seen in Fig.  9 (right): 4 processes start with an Exploration ; 12 times there is an Exploration after an Analysis episode; and once after Planning-Implementation .

Accumulation of seven processes for problem 3b) (left) and eight processes for problem 4b) (middle), 15 problem-solving processes in total (right)

In Fig.  10 (right), an accumulation is given of all 33 PS processes of all five problems. The differences of the routine and the PS processes (e.g., the latter containing Exploration episodes and being cyclic) can be seen by comparing Figs.  8 and 9 .

Accumulation of transitions in problem-solving processes, paper-and-pencil (left) vs. DGS (middle); all problem-solving processes (right)

6.2.2 Successful and unsuccessful problem-solving processes

One of Schoenfeld's ( 1985 ) major results was the importance of self-regulatory activities in PS processes. Schoenfeld was not able to characterize successful PS processes; however, he identified characteristics of processes that did not end in a verified solution. The unsuccessful problem solvers were most often those who missed out on self-regulatory activities (i.e., controlling interim results or planning next steps); they engaged in a behaviour that Schoenfeld called “wild goose chase” and that he described this way:

Approximately 60% of the protocols were of the type [...], where the students read the problem, picked a solution direction (often with little analysis or rationalization), and then pursued that approach until they ran out of time. In contrast, successful solution attempts came in a variety of shapes and sizes—but they consistently contained a significant amount of self-regulatory activity, which could clearly be seen as contributing to the problem solvers’ success. (Schoenfeld, 1992a , p. 195)

We made similar observations looking at the processes of our students; several of them, who did not show any signs of structured actions or process evaluations, were not able to solve the tasks. Thus, to test if this observation was statistically significant, we had to operationalize the PS type “wild goose chase”, as Schoenfeld had provided no operational definition for this phenomenon. A process is considered by us to be a “wild goose chase”, if it consists of only Exploration or Analysis & Exploration episodes, whereas processes that are not of this type contain planning and/or verifying activities (only considering content-related episode types). In our descriptive model, by definition, wild goose chase processes look like the process manifested by U1-C (Three Beaches, part b) (Fig.  6 , middle).

To check if the kind of behaviour in these processes is interrelated with success or failure of the related products (see Sect.  4.2 ), a chi-square test was used (because of the nominal character of the process categories, no Pearson or Spearman correlation could be calculated). The null hypothesis was ‘there is no correlation between the PS type wild goose chase and (no) success in the product’.

The entries in Table 2 consist of the observed numbers of process–product combinations; the expected numbers assuming statistical independence (calculated by the marginal totals) are added in parentheses. The entries in the main diagonal are apparently higher than the expected values. The test shows a significant correlation ( p  < 0.01) between the problem solvers’ behaviour and their success. Therefore, the null hypothesis can be rejected, there is a correlation between showing wild goose chase-behaviour in PS processes and not being successful in solving the problem.

6.2.3 Paper-and-pencil vs. DGS environment processes

Looking at the processes of the non-routine tasks indicates that the tasks were ‘problems’ for the students, as these processes showed no signs of routine behaviour (see Sect.  6.2.1 ). Instead, we see many transitions between different episodes and the typical cyclic structure of PS processes. Comparing accumulations of all 15 paper-and-pencil with all 18 DGS PS processes, we see some interesting differences, which our model helps to reveal (see Fig.  10 ). The time the students worked on the problem was set in the tutorials and, therefore, identical in both environments and in all processes. At the end of this paper, we discuss three aspects that our comparisons revealed; more detailed analyses are planned for forthcoming papers.

We coded more transitions in DGS than in paper-and-pencil processes (73 transitions in 18 DGS processes, in short: 73/18 or on average 4 transitions per DGS process compared to 52/15 or 3.5 transitions per paper-and-pencil process). If transitions are a sign of self-regulation (Schoenfeld, 1985 ; Wilson et al. 1993 ), our students in the DGS environment seem to better regulate their processes (please note that Organization episodes are not counted here; including them would further add transitions to DGS processes). However, there might be more transitions (and thus episodes) in DGS processes because of having more time for exploring situations and generating examples, which does not take as much time as in paper-and-pencil processes.

We see more Planning (and Implementation ) episodes in DGS than in paper-and-pencil processes (9/18 or Planning in 50% of the DGS processes compared to 2/15 or 13% in paper-and-pencil processes). Using Schoenfeld’s conceptualization of Planning and Exploration episodes, the DGS processes seem to be more structured—especially since there are less Exploration episodes in DGS than in paper-and-pencil processes (17/18 compared to 21/15), even though there are more episodes in the DGS environment (see above). There seems to be a need for students in the DGS environment to plan their actions, especially when it comes to complex constructions that cannot be sketched freehandedly as in the paper-and-pencil environment. Considering the success of the students (6 solutions in the DGS environment compared to 3 in the paper-and-pencil environment), this hypothesis is supported. As already existing research indicates, better regulated PS processes should be more successful. Please note that successful solutions cannot be obtained by stating only correct hypotheses, which would favour the DGS environment; solutions coded as ‘correct’ had to be argued for.

We double checked our codings to make sure that this result was not an artefact of the coding, that the students actually planned their actions, not only using the DGS (which was coded in Organization episodes). This result could be due to our setting, as our student peer groups had only one computer and thus needed to talk about their actions. In future studies, it should be investigated if this phenomenon can be replicated in environments in which each student has his or her own computer.

We also observed more Verification episodes in DGS compared to paper-and-pencil processes (7/18 or 39% compared to 2/15 or 13%). There could be different reasons for this observation, e.g., students not trusting the technology, or just the simplicity of using the dragmode to check results compared to making drawings in the paper-and-pencil environment.

The results of using our descriptive model for comparisons of PS processes appear to be insightful. The purpose of this section was to illustrate these insights and the use of our empirical model of PS processes. Accumulating PS processes of several groups is a key to enabling comparisons such as the ones presented.

7 Discussion

The goal of this paper was to present a descriptive model of PS processes, that is, a model suited to the description and analyses of empirically observed PS processes. So far, existing research has mainly discussed and applied normative models for PS processes, which are generally used to instruct people, particularly students, about ideal ways of approaching problems. There exist a few, well accepted, models of PS processes in mathematics education (Fig.  1 ); however, these models only partly allow represention of and emphasis on the non-linearity of real and empirical PS processes, and they do not have the potential to compare processes across groups of students. For the generation of our descriptive model of PS processes, following our first research question, (1) the existing models were compared. It turned out that similarities and fine differences exist between the current normative models, especially regarding the phases of PS processes and their sequencing. We identified which elements of the existing models could be useful for the generation of a descriptive model, linking theoretical considerations from research literature with regard to our empirical data. Analysing PS processes of students working on geometric problems, we observed that distinctive episodes (esp. the distinction between Planning and Exploration ) and transitions between episodes, were essential. Classifying the episodes was mostly possible with the existing models, but characterising their transitions and sequencing required extension of the existing models, which resulted in a juxtaposition of components for our descriptive phase model (e.g., allowing us to code, separately or in combination, Planning-Implementation or to regard the (non-)linearity of processes).

Our generated descriptive model turned out not only to provide valuable insights into problems solving processes of students, but also with respect to our second research question, (2), to compare, contrast, and characterise the idiosyncratic characteristics of students’ PS processes (using Explorations or not, linear or cyclic processes, including Verification and Planning or not). Our developed descriptive model can be used to analyse processes of students ‘at once’, in accumulation, which allowed us to group and characterise comparisons of students’ processes, which was not possible with the existing models. As demonstrated in Sect.  6.2 , our model further allows one to distinguish students’ PS processes while working on routine versus problem tasks. Applying our descriptive model to routine tasks, we detected linear processes, whereas in problem tasks cyclic processes were characteristic. Furthermore, in routine tasks, no Exploration episodes could be coded. Most of the students expressed no need for analysing the task but started directly with Planning and/or Implementation.

Our descriptive model also allows one to recognize a type of PS behaviour already described by Schoenfeld ( 1992a ) as “wild goose chases”. Our data illustrated that wild goose chase processes are statistically correlated with unsuccessful attempts at solving the given problems.

In addition, our descriptive model indicated differences between paper and pencil and DGS processes. In the latter context, students showed more transitions, more Planning (and Implementation ), and more Verification episodes. This result revealed significantly different approaches that students embarked on when working on problems in paper and pencil or DGS environments. These findings might indicate that in the DGS environment in our study, students better regulated their processes (cf. Schoenfeld, 1985 , 1992b ; Wilson et al. 1993 )—a hypothesis yet to be confirmed.

A limitation of our study might be the difficulty of the problems given to our students; only 9 of 33 processes ended with a correct solution. In future studies, problems should be used that better differentiate between successful and unsuccessful problem solvers. Also, our descriptive model has so far been grounded only in university students’ geometric PS processes. Even though geometry is particularly suited for learning mathematical PS in general and heuristics in specific (see Schoenfeld, 1985 ), other contexts and fields of mathematics might highlight other challenges students face. Further empirical evidence is needed to see how far our model is also useful and suitable to describe other contexts with respect to specifics of their mathematical fields. Following some of our ideas and insights, Rott ( 2014 ) has already conducted such a study: fifth graders working on problems from geometry, number theory, combinatorics, and arithmetic. Similar results as in the study presented here, were seen and indicate the value of our descriptive model. More research in this regard is a desideratum.

Regarding teaching, using our model can be helpful to discuss with students on a meta-level these documented distinct phases of PS processes, transitions between them, and the possibility of going back to each phase during a PS process. This might help students to be aware of their processes, of different ways to gain a solution and justification, and to be more flexible during PS processes. More reflection on this aspect is also a desideratum for future research.

Change history

12 march 2021.

ESM was added

Artzt, A., & Armour-Thomas, E. (1992). Development of a cognitive-metacognitive framework for protocol analysis of mathematical problem solving in small groups. Cognition and Instruction, 9 (2), 137–175.

Article   Google Scholar  

Dewey, J. (1910). How we think . D C Heath.

Book   Google Scholar  

Fernandez, M. L., Hadaway, N., & Wilson, J. W. (1994). Problem solving: Managing it all. The Mathematics Teacher, 87 (3), 195–199.

Gawlick, T. (2002). On Dynamic Geometry Software in the regular classroom. ZDM, 34 (3), 85–92.

Google Scholar  

Hadamard, J. (1945). The psychology of invention in the mathematical field . Princeton University Press.

Halmos, P. R. (1980). The heart of mathematics. The American Mathematical Monthly, 87 (7), 519–524.

Jacinto, H., & Carreira, S. (2017). Mathematical problem solving with technology: The techno-mathematical fluency of a student-with-GeoGebra. International Journal of Science and Mathematics Education, 15, 1115–1136.

Jacobs, J., Garnier, H., Gallimore, R., Hollingsworth, H., Givvin, K. B., Rust, K. et al. (2003). Third International Mathematics and Science Study 1999 Video Study Technical Report. Volume 1: Mathematics . National Center for Education Statistics. Institute of Education Statistics, U. S. Department of Education.

KMK. (2004). Beschlüsse der Kultusministerkonferenz. Bildungsstandards im Fach Mathematik für den Mittleren Schulabschluss [Educational standards in mathematics for secondary school leaving certificates] . Wolters Kluwer.

Koyuncu, I., Akyuz, D., & Cakiroglu, E. (2015). Investigation plane geometry problem-solving strategies of prospective mathematics teachers in technology and paper-and-pencil environments. International Journal of Mathematics and Science Education, 13, 837–862.

Liljedahl, P., Santos-Trigo, M., Malaspina, U., & Bruder, R. (2016). Problem solving in mathematics education . ICME Topical Surveys.

Mason, J., Burton, L., & Stacey, K. (1982). Thinking mathematically . Pearson.

NCTM. (2000). National Council of Teachers of Mathematics. Principles and standards of school mathematics . NCTM.

NCTM. (2014). Principles to actions. Ensuring mathematical success for all . NCTM.

Neuhaus, K. (2002). Die Rolle des Kreativitätsproblems in der Mathematikdidaktik [The role of the creativity problem in mathematics education] . Dr. Köster.

Philipp, K. (2013). Experimentelles Denken. Theoretische und empirische Konkretisierung einer mathematischen Kompetenz [Experimental thinking] . Springer.

Poincaré, H. (1908). Science et méthode [Science and method] . Flammarion.

Pólya, G. (1945). How to solve it . Princeton University Press.

Rott, B. (2014). Mathematische Problembearbeitungsprozesse von Fünftklässlern—Entwicklung eines deskriptiven Phasenmodells [Problem-solving processes of fifth graders: Developing a descriptive phase model]. Journal für Mathematik-Didaktik, 35, 251–282.

Schoenfeld, A. H. (1985). Mathematical problem solving . Academic Press.

Schoenfeld, A. H. (1992a). On paradigms and methods: What do you do when the ones you know don’t do what you want them to? Issues in the analysis of data in the form of videotapes. The Journal of the Learning Sciences, 2 (2), 179–214.

Schoenfeld, A. H. (1992b). Learning to think mathematically: Problem solving, metacognition, and sensemaking in mathematics. In D. A. Grouws (Ed.), Handbook for research on mathematics teaching and learning (pp. 334–370). MacMillan.

Sträßer, R. (2002). Research on dynamic geometry software (DGS)—An introduction. ZDM, 34 (3), 65.

Wallas, G. (1926). The art of thought . C.A. Watts & Co.

Wilson, J. W., Fernandez, M. L., & Hadaway, N. (1993). Mathematical problem solving. In P. S. Wilson (Ed.), Research ideas for the classroom: High school mathematics (pp. 57–77). MacMillan.

Yimer, A., & Ellerton, N. F. (2010). A five-phase model for mathematical problem solving: Identifying synergies in pre-service-teachers’ metacognitive and cognitive actions. ZDM - The International Journal on Mathematics Education, 42, 245–261.

Download references

Open Access funding enabled and organized by Projekt DEAL.. Open Access funding enabled and organized by Projekt DEAL.

Author information

Authors and affiliations.

Universität zu Köln, Köln, Germany

Benjamin Rott

Universität Oldenburg, Oldenburg, Germany

Birte Specht

Universität Bremen, Bremen, Germany

Christine Knipping

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Benjamin Rott .

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file 1 (PDF 172 KB)

Rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Rott, B., Specht, B. & Knipping, C. A descriptive phase model of problem-solving processes. ZDM Mathematics Education 53 , 737–752 (2021). https://doi.org/10.1007/s11858-021-01244-3

Download citation

Accepted : 18 February 2021

Published : 09 March 2021

Issue Date : August 2021

DOI : https://doi.org/10.1007/s11858-021-01244-3

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Mathematical problem solving
• Descriptive process model
• Find a journal
• Publish with us
• Track your research

• school Campus Bookshelves
• menu_book Bookshelves
• perm_media Learning Objects
• login Login
• how_to_reg Request Instructor Account
• hub Instructor Commons
• Download Page (PDF)
• Download Full Book (PDF)
• Periodic Table
• Physics Constants
• Scientific Calculator
• Reference & Cite
• Tools expand_more
• Readability

selected template will load here

This action is not available.

3.3: Creative Problem-Solving Process

• Last updated
• Save as PDF
• Page ID 62756

LEARNING OBJECTIVES

By the end of this section, you will be able to:

• Describe the five steps in the creative problem-solving process
• Identify and describe common creative problem-solving tools

Creativity can be an important trait of an entrepreneur. In that discussion, we learned about creativity’s role in innovation . Here, we will look in more depth at creativity’s role in problem-solving . Let’s first formally define creativity as the development of original ideas to solve an issue. The intent of being an entrepreneur is to break away from practical norms and use imagination to embrace quick and effective solutions to an existing problem, usually outside the corporate environment.

The Steps of the Creative Problem-Solving Process

Training oneself to think like an entrepreneur means learning the steps to evaluating a challenge: clarify, ideate, develop, implement, and evaluate (Figure 3.3.1).

Step 1: Clarify

To clarify is the critical step of recognizing the existence of a gap between the current state and a desired state. This can also be thought of as having need awareness , which occurs when the entrepreneur notes a gap between societal or customer needs and actual circumstances. Clarifying the problem by speaking with clients and developing a detailed description of the problem brings the specifics of a problem to light. Failure to identify the specifics of a problem leaves the entrepreneur with the impossible task of solving a ghost problem, a problem that is fully unknown or unseen. To establish and maintain credibility, an entrepreneur must clarify the problem by focusing on solving the problem itself, rather than solving a symptom of the problem.

For example, a farm could have polluted water, but it would not be enough to solve the problem only on that farm. Clarifying would involve identifying the source of the pollution to adequately tackle the problem. After gaining an understanding of a problem, the entrepreneur should begin to formulate plans for eliminating the gap. A fishbone diagram, as shown in Figure 3.3.2, is a tool that can be used to identify the causes of such a problem.

In the case of our water pollution example, a fishbone diagram exploring the issue might reveal the items shown in Figure 3.3.3.

Step 2: Ideate

To ideate is the step of the creative problem-solving process that involves generating and detailing ideas by the entrepreneur. After collecting all information relevant to the problem, the entrepreneur lists as many causes of the problem as possible. This is the step in which the largest variety of ideas are put forth. Each idea must be evaluated for feasibility and cost as a solution to the problem. If a farm does not have clean water, for example, the entrepreneur must list causes of toxic water and eliminate as many of those causes as possible. The entrepreneur must then move forward investigating solutions to bring the water back to a safe state. If, say, nearby livestock are polluting the water, the livestock should be isolated from the water source.

Step 3: Develop

To develop is the step in which the entrepreneur takes the list of ideas generated and tests each solution for feasibility. The entrepreneur must consider the cost of each idea and the obstacles to implementation. In the preceding example, adding a chemical to the water may not be a feasible solution to the farmer. Not every farmer wants additional chloride or fluoride added to the water due to the effect on both humans and livestock. These tradeoffs should be addressed in the feasibility assessment. The farmer might prefer a filtration system, but the cost of that solution might not be practicable. The entrepreneur should identify and assess alternative solutions to find one that is most cost-effective and feasible to the customer.

Step 4: Implement

To implement is the step in which the solution to the problem is tested and evaluated. The entrepreneur walks through the planned implementation with the client and tests each part of the solution, if a service, or thoroughly tests a developed good. The entrepreneur implements the solution and goes through a structured system of follow-up to ensure the solution remains effective and viable. In the water example, the solution would be reducing runoff from toxic insecticides by adding prairie strips, buffers of grass, and vegetation along banks of streams.

Step 5: Evaluate

To evaluate is the step in which the final solution is assessed. This is a very important step that entrepreneurs often overlook. Any fallacy in the implementation of the product or service is reassessed, and new solutions are implemented. A continual testing process may be needed to find the final solution. The prairie strips, buffers of grass, and vegetation along banks of streams chosen in the farming water example should then be analyzed and tested to ensure the chosen solution changed the content of the water.

ARE YOU READY?

Implementing Creative Problem Solving

Removing waste is a problem, and it can also present an entrepreneurial opportunity. Try to examine ways in which waste products that you usually pay to have hauled away can now generate revenue. Whether it’s recycling aluminum cans or cardboard, or garbage that could be used to feed animals, your task is to come up with solutions to this entrepreneurial-oriented problem.

• Try following the first step of the creative problem-solving process and clearly identify the problem.
• Next, gather data and formulate the challenge.
• Then, explore ideas and come up with solutions.
• Develop a plan of action.
• Finally, note how you would evaluate the effectiveness of your solution.

Using Creativity to Solve Problems

Entrepreneurs are faced with solving many problems as they develop their ideas for filling gaps, whether those opportunities involve establishing a new company or starting a new enterprise within an existing company. Some of these problems include staffing, hiring and managing employees, handling legal compliance, funding, marketing, and paying taxes. Beyond the mundane activities listed, the entrepreneur, or the team that the entrepreneur puts in place, is indispensable in maintaining the ongoing creativity behind the product line or service offered. Innovation and creativity in the business are necessary to expand the product line or develop a groundbreaking service.

It is not necessary for the entrepreneur to feel isolated when it comes to finding creative solutions to a problem. There are societies, tools, and new methods available to spur the creativity of the entrepreneur that will further support the success and expansion of a new enterprise. 14 Learning and using entrepreneurial methods to solve problems alleviates the stress many startup owners feel. The entrepreneur’s creativity will increase using collaborative methodologies. Some entrepreneurial collaborative methodologies include crowdsourcing, brainstorming, storyboarding, conducting quick online surveys to test ideas and concepts, and team creativity activities.

Crowdsourcing

Professor Daren Brabham at the University of Southern California has written books on crowdsourcing and touts its potential in for-profit and not-for-profit business sectors. He defines it simply as “an online, distributed problem-solving and production model.” 15 Crowdsourcing involves teams of amateurs and nonexperts working together to form a solution to a problem. 16 The idea, as cbsnews.com’s Jennifer Alsever has put it, is to “tap into the collective intelligence of the public at large to complete business-related tasks that a company would normally either perform itself or outsource to a third-party provider. Yet free labor is only a narrow part of crowdsourcing's appeal. More importantly, it enables managers to expand the size of their talent pool while also gaining deeper insight into what customers really want. The challenge is to take a cautionary approach to the ‘wisdom of the crowd,’ which can lead to a ‘herd’ mentality.” 17

LINK TO LEARNING

Read this article that discusses what crowdsourcing is, how to use it, and its benefits for more information.

This new business prototype, similar to outsourcing, features an enterprise posting a problem online and asking for volunteers to consider the problem and propose solutions. Volunteers earn a reward, such as prize money, promotional materials like a T-shirt, royalties on creative outlets like photos or designs, and in some cases, compensation for their labor. Before proposing the solution, volunteers learn that the solutions become the intellectual property of the startup posting the problem. The solution is then mass-produced for profit by the startup that posted the problem. 18 The process evolves into the crowdsourcing process after the enterprise mass produces and profits from the labor of the volunteers and the team. Entrepreneurs should consider that untapped masses have solutions for many issues for which agendas do not yet exist. Crowdsourcing can exploit those agendas and add to the tools used to stimulate personal creativity. This type of innovation is planned and strategically implemented for profit.

For example, Bombardier held a crowdsourced innovation contest to solicit input on the future of train interiors, including seat design and coach class interior. A corporate jury judged the submissions, with the top ten receiving computers or cash prizes. Companies are often constrained, however, by internal rules limiting open source or external idea sourcing, as they could be accused of “stealing” an idea. While crowdsourcing outside of software can be problematic, some products such as MakerBot’s 3D printers, 3DR’s drones, and Jibo’s Social Robot have used developer kits and “makers” to help build a community and stimulate innovation from the outside.

WORK IT OUT

A Crowdsourced Potato Chip

In an effort to increase sales among millennials, PepsiCo turned to crowdsourcing to get new flavor ideas for their Lay’s potato chips (called Walker’s in the UK). Their 2012 campaign, “Do Us a Flavor,” was so successful that they received over 14 million submissions. The winner was Cheesy Garlic Bread, which increased their potato chip sales by 8 percent during the first three months after the launch.

• What are some other products that would work well for a crowdsourced campaign contest?
• What items wouldn’t work well?

Amazon’s Mechanical Turk is an online crowdsourcing platform that allows individuals to post tasks for workers to complete. In many instances, these tasks are compensated, but the payment can be less than one dollar per item completed. Mechanical Turk is one of the largest and most well-known crowdsourcing platforms, but there are a number of other more niche ones as well that would apply to smaller markets. In the case of innovation contests and outsourced tasks from corporations, those tasks may be hosted internally by the corporation.

Brainstorming

Brainstorming is the generation of ideas in an environment free of judgment or dissension with the goal of creating solutions. Brainstorming is meant to stimulate participants into thinking about problem-solving in a new way. Using a multifunctional group, meaning participants come from different departments and with different skill sets, gives entrepreneurs and support teams a genuine chance to suggest and actualize ideas. The group works together to refine and prototype potential solutions to a problem.

Brainstorming is a highly researched and often practiced technique for the development of innovative solutions. One of the more successful proponents of brainstorming is the United Nations Children’s Fund (UNICEF). UNICEF faces unique problems of solving resource problems for mothers and children in underdeveloped nations. See how UNICEF practices brainstorming to solve problems including child survival, gender inclusion, refugee crises, education, and others.

The setting for a brainstorming session should remain as informal and relaxed as possible. The group needs to avoid standard solutions. All ideas are welcome and listed and considered with no censorship and with no regard to administrative restrictions. All team members have an equal voice. The focus of brainstorming is on quantity of ideas rather than on the ideal solution provided in every suggestion. A classic entrepreneurial brainstorming activity, as popularized by business software developer Strategyzer, is known as the “silly cow” exercise. Teams come up with ideas for new business models pertaining to a cow, with the results often outrageous, ranging from sponsored cows to stroking cows for therapeutic release. Participants are asked to identify some aspect of a cow and develop three business models around that concept in a short time period, typically two minutes or fewer. The activity is designed to get creative juices flowing.

Watch this video from ABC’s Nightline that shows how IDEO designed a new shopping cart for an example of a design process that involves brainstorming.

Storyboarding

Storyboarding is the process of presenting an idea in a step-by-step graphic format, as Figure 3.3.4 shows. This tool is useful when the entrepreneur is attempting to visualize a solution to a problem. The steps to the solution of a problem are sketched and hung in graphic format. Once the original graphic is placed, images of steps working toward a solution are added, subtracted, and rearranged on a continual basis, until the ultimate solution emerges in the ultimate graphic format. For many years, entrepreneurs have used this process to create a pre-visual for various media sequences.

Team Creativity

Team creativity is the process whereby an entrepreneur works with a team to create an unexpected solution for an issue or challenge. Teams progress through the same creative problem-solving process described already: clarify, ideate, develop, implement, and evaluate. The main advantage of team creativity is the collaboration and support members receive from one another. Great teams trust in other team members, have diverse members with diverse points of view, are cohesive, and have chemistry.

Team members should work in a stress-free and relaxing environment. Reinforcement and expansion of ideas in the team environment motivates the team to continually expand horizons toward problem solution. A small idea in a team may spark the imagination of a team member to an original idea. Mark Zuckerberg, co-founder of Facebook, once said, “The most important thing for you as an entrepreneur trying to build something is, you need to build a really good team. And that’s what I spend all my time on.” 19

ENTREPRENEUR IN ACTION

Taaluma Totes 20

Young entrepreneurs Jack DuFour and Alley Heffern began to notice the beautiful fabrics that came from the different countries they visited. The entrepreneurs thought about what could be done with the fabrics to create employment opportunities both in the country from which the fabric originated and in their home base of Virginia. They decided to test producing totes from the fabrics they found and formed Taaluma Totes (Figure 3.3.5). DuFour and Heffern also wanted to promote the production of these fabrics and help underserved populations in countries where the fabric originated maintain a living or follow a dream.

The team continued to test the process and gathered original fabrics, which they sent to Virginia to create totes. They trained individuals with disabilities in Virginia to manufacture the totes, thus serving populations in the United States. The entrepreneurs then decided to take 20 percent of their profits and make microloans to farmers and small business owners in the countries where the fabric originated to create jobs there. Microloans are small loans, below $50,000, which certain lenders offer to enterprising startups. These startups, for various reasons (they are in poor nations, at the poverty level), can’t afford a traditional loan from a major bank. The lenders offer business support to the borrower, which in turn helps the borrower repay the microloan. The microloans from Taaluma are repaid when the borrower is able. Repayments are used to buy more fabric, completing Taaluma’s desire to serve dual populations. If the process proved unsuccessful, the co-owners would revise the process to meet the plan’s requirements.

DuFour and Heffern now have fabrics from dozens of countries from Thailand to Ecuador. The totes are specialized with features to meet individual needs. The product line is innovated regularly and Taaluma Totes serves a dual purpose of employing persons with disabilities in Virginia and creating employment for underserved populations in other countries.