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Milliman’s partnership with Microsoft results in sales pipeline growth and new customers like Phoenix Group

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The partnership between Milliman and Microsoft is strong on several fronts, and growing stronger. The success Milliman has seen with customers using Integrate, a Microsoft Azure-powered financial and risk management solution for global life insurance companies, “has motivated Milliman and Microsoft to increase collaboration across sales, marketing and product engineering, grow the pipeline for Integrate, and drive further transformational change in the insurance market,” said Paul Maher, Principal and Chief Technology Officer at Milliman.

“By jointly promoting and selling Integrate and Azure, we were able to help customers such as Phoenix Group take advantage of the scale and extensibility of the cloud.”

— paul maher, principal and cto of life technology solutions practice, milliman.

Maher continued: "Our strong relationship across Microsoft product engineering, marketing, and sales has helped Milliman amplify the benefits of Integrate. By jointly promoting and selling Integrate and Azure, we were able to help customers such as Phoenix Group take advantage of the scale and extensibility of the cloud.”

Phoenix Group, the largest insurance consolidator in the United Kingdom, turned to Milliman and Integrate for help. They had acquired dozens of companies, and almost as many modeling systems. Add to this the mountain of new insurance products and regulations, and the Phoenix actuaries simply could not keep pace.

Implementing Milliman’s Integrate solution resulted in dramatic improvements. More than 900 manual processes were reduced to 44, and the time it takes the company to produce quarterly data was cut from four months to just three days. By the end of three years, the savings generated had paid for the project three times over.

“By taking advantage of Azure and its associated services, Milliman has been able to accelerate the development and time-to-market of the Integrate solution,” Maher said. “Integrate clients are able to run large actuarial jobs on-demand year-round, benefiting from the Azure platform’s scale and extensibility in a pay-as-you-go business model.”

“It is without question that Milliman is changing the game with its leading-edge cloud solutions,” said Tony Jacob, managing director of worldwide insurance at Microsoft. “It’s a remarkable use of the cloud—not just in insurance, but in business. The considerable cost, time, and labor savings companies can realize with Integrate is unmatched. Microsoft values its partnership with Milliman and will continue to work together in helping insurers take on strategic actuarial systems and business transformation projects in the coming years.”

“By taking advantage of Azure and its associated services, Milliman has been able to accelerate the development and time-to-market of the Integrate solution.”

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AI in insurance: Supporting innovation in risk, data governance, and customer service

The present and future of ai in insurance, a microsoft whitepaper.

The present and future of AI in insurance

Supporting innovation in risk, data governance, and customer service

Insurance is a data-driven industry, and underwriters are quickly transforming into data scientists to keep up with their information. Intelligent tools like AI and machine learning are helping these professionals to innovate some of the most challenging problems in the industry, from modeling risk for underwriting to streamlined operations and responsive global customer support.

In the whitepaper  The present and future of AI in insurance: Supporting innovation in risk, data governance, and customer service , learn how insurance companies are using Microsoft Azure AI and machine learning to fuel their brilliant innovations impacting customers worldwide. Gain insight into the priorities of AI in this industry and learn more about how these priorities are playing out through real-world case studies.

In this whitepaper from Microsoft and Novarica  The present and future of AI in insurance: Supporting innovation in risk, data governance, and customer service , learn how insurance companies are using Microsoft Azure AI and machine learning to fuel their brilliant innovations impacting customers worldwide. Gain insight into the priorities of AI in this industry and learn more about how these priorities are playing out through real-world case studies.

Maurice Blackburn’s insurance claims assessments reduced from months to minutes, delivering faster client service

Hyperspeed: law firm uses ai to slice months off insurance claims, ai reduces time to assess superannuation disability insurance claims from months to minutes.

Maurice Blackburn Lawyers has rolled out an artificial intelligence-infused solution that cuts the time taken to assess a client’s entitlement to a superannuation disability insurance claim from months down to the span of the client’s initial phone call.

Developed by Microsoft partner, Arinco, the system saves time for the client while also freeing up the lawyers who would otherwise have their time taken up with combing through insurance policy fine print.

Maurice Blackburn’s insurance claim lawyers provide a no win, no fee service to clients and it’s imperative that the initial triage of claims is fast, inexpensive and accurate.

A ground-breaking solution developed using Azure Cognitive Search and Services uses AI to review life insurance policies to assess rapidly whether a claim has merit and should be pursued.

Maurice Blackburn’s General Manager Digital & Technology, Greg Emsley says it’s a very significant breakthrough for the law firm’s Superannuation and Insurance practice.

“The solution allows us to triage new claims, assess them for eligibility and then make that insight available directly to our insurance law claims team in a matter of seconds,” Mr Emsley says.

“The use of artificial intelligence allows us to extract only those aspects of the policy documents pertinent to the claims process, and then correlate that to a client’s specific event to quickly and confidently identify the cover in place for them at the time.

We are in the early stages of adoption, but the signs are that this will be very effective in reducing the time needed to serve our clients from months to minutes, and significantly improve the client experience in what can often be a traumatic period in their life. – Maurice Blackburn’s General Manager Digital & Technology, Greg Emsley

Maurice Blackburn’s National Manager of Operations for the Superannuation and Insurance team, Jason Brown agrees it will vastly improve the clients’ experience.

“Knowing what you’re entitled to is the first step in getting access to justice so by couplingAI with trained staffwe can provide clients with greater certainty more quickly.

“For many,  finding out whether you have a claim can now be as simple as a call to our office and we can start work on a claim virtually immediately and move it along quickly,” Mr Brown says

“Automating the process also means we can free up our team to spend more time with clients and make quicker decisions about how to proceed with claims”.

Arinco used Microsoft Azure Cognitive Services to develop the AI-infused solution which in turn uses Azure Forms Recogniser to  accelerate business processes through automating information extraction.

Principal Consultant at Arinco, Chris Padgett says Azure was an ideal tool to deal with complex and lengthy policy information.

“These policy documents can be dozens, if not hundreds of pages long and dense with legal jargon.

“Using Forms Recogniser, we recognise content within these document files, extracting the key phrases from them as well as tabulated data, and then surface that to a business application used by the lawyer,” Mr Padgett says.

“Maurice Blackburn’s claims triage team don’t have to navigate their way through hundreds of pages of documentation to find these key sections and instead are presented with a  very readable, easy to navigate way to help them expedite a claim.”

While Arinco has structured this solution specifically to support insurance claims triage, the underlying framework, machine learning and AI could be applied across multiple industry sectors with tailored solutions spun up rapidly to meet specific requirements.

Microsoft Australia’s Chief Technology Officer, Lee Hickin says it’s rewarding to see the Azure suite employed creatively to improve business services.

“Cloud, data and AI are the trinity that deliver immense value to businesses in every sector.

“The array of Azure Cognitive Services means that these sorts of applications can be developed and deployed rapidly, supporting employees with tasks that would otherwise be time consuming, laborious and quite costly,” Mr Hickin says.

“The methodology that Arinco uses and its deep skills across the Microsoft Azure ecosystem can be brought to bear rapidly, driving real impact and measurable value for clients in multiple sectors.”

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MS Fabric enables an insurance services company take data-informed decisions, improve operational efficiency and ignite strategic innovation

Client business description.

Our US-based Insurance services client sought to elevate data-driven decision-making, operational efficiency, and innovation. They required a solution for data transformation, data warehousing, data visualization, and real-time analysis across diverse systems. Their mandate handling vast data volumes with precision, streamlining transformations, and delivering timely, accurate analysis.

Project Requirement

The client approached our team with several key business requirements:

Data Ingestion and Integration

Implement Azure Logic Apps to automate data integration, ensuring data consistency and reliability.

Data Transformation

Create a standardized data model to ensure consistency across the organization.

Data Warehousing

Deploy Azure Synapse Analytics (formerly SQL Data Warehouse) to store and manage structured data efficiently.

Real-Time Analysis

Implement Azure Stream Analytics to analyze data streams in real-time.

Data Visualization

Utilize Power BI for creating interactive dashboards and reports.

To address the client's objectives, we proposed a holistic solution leveraging Microsoft Fabric:

• Data Ingestion and Integration Azure Data Factory is used to ingest data from various sources, including customer databases, policy records, IoT devices, and external market data. Azure Logic Apps automate data integration processes, ensuring data consistency and reliability.
• Data Transformation Azure Databricks is employed for advanced data transformation and preparation. This includes data cleaning, normalization, and enrichment, resulting in high data quality. A standardized data model has been created, ensuring consistency and accuracy across the organization.
• Data Warehousing Azure Synapse Analytics (formerly SQL Data Warehouse) has been deployed to efficiently store and manage structured data. Data partitioning and indexing strategies have been implemented to optimize query performance.
• Real-Time Analysis Azure Stream Analytics is utilized to analyze data streams in real-time. This provides immediate insights into customer behavior, claims processing, and risk assessment. Custom alerts and automated actions are set up based on real-time analytics results, improving decision- making agility.
• Data Visualization Power BI is employed for creating interactive dashboards and reports, enabling the client to visualize data insights in real time. Stakeholders have access to real-time visualizations for informed decision-making.

Technology Used

Microsoft Fabric

The solution utilized the below technologies to extract, transform, visualize and deliver data-driven insights for strategic HR management and decision making.

• Data-Driven Decision-Making The client now has the capability for real-time data analytics and visualization, enabling data-driven decisions that enhance customer service and risk management.
• Operational Efficiency Streamlined data transformation processes and efficient data warehousing have resulted in reduced operational costs and increased efficiency.
• Innovation Opportunities Timely and accurate data insights open doors to innovative product offerings and improved customer experiences, ensuring the client's competitiveness in the market.
• Scalability Timely and accurate data insights open doors to innovative product offerings and improved customer experiences, ensuring the client's competitiveness in the market.
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Azure Files and Azure File Sync customer case studies

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Case study: Rand Mutual Assurance

In 1886, gold was discovered in Johannesburg, South Africa. This had a profound impact on the region as businesses and industries thrived around the newfound resource. One such business was Rand Mutual Assurance (RMA), an insurance company aimed at assuring that mine workers and their families were covered against the worst risks of the fledgling mining industry. Since then, RMA has expanded its coverage to include employees of metal engineering companies, and it has plans to expand even further in the coming years into additional sectors. Much of the company’s growth has come in the last two years, during which time RMA has increased its employee count from 200 to 500 full-time workers. RMA expects that number to double or triple again in the coming years as expansion into new markets continues. As this phase of rapid growth began, RMA saw the need for detailed, actionable insights regarding employee engagement and patterns of work. Of particular importance to CEO Jay Singh was the ability to uncover what habits and behaviors led to higher employee engagement and improved productivity. The existing system through which leaders could understand employee behavior relied on a single annual performance appraisal review. Administered by managerial staff, these appraisal reports determined employees’ developmental and promotional opportunities, transfer eligibility, and even the amounts they could expect as annual salary increases or bonuses. Managers lacked deep insight into employee engagement and company-wide patterns, and employees themselves wanted more visibility into the system. To improve the process and address the concerns of its workforce, RMA hired George Honiball as its new Talent Manager. Collaborating with Singh and the company’s IT leadership, Honiball helped identify Microsoft Workplace Analytics as the solution that best fit the company’s needs.

Discerning reality from perception

Workplace Analytics analyzes aggregated, de-identified metadata from everyday activities in Microsoft Office 365 to identify work patterns that impact productivity, collaboration, and employee engagement. Trusted cloud security and built-in privacy safeguards enable organizations to maintain compliance with industry and regional requirements.

RMA sees Workplace Analytics as an ideal tool to help the company optimize productivity by measuring the impact of meetings, employee networks, information silos, and more in order to uncover what is working best and replicate it. Because every department at RMA has a unique system for measuring transactional data, a quantifiable view of employee productivity can be highly impactful. “Often, the employees we think are high performers and those who turn out to be high performers are different,” says Honiball. “It’s important to be able to drill down into the information at the heart of performance. Workplace Analytics helps us unlock the hidden talent and potential within our workforce. It shows us the people doing wonderful work that we might have overlooked before.” Armed with actionable insights, managers can encourage positive work habits or course-correct departmental imbalances as they arise. And they can harness Workplace Analytics’ sister tool, Microsoft MyAnalytics—a personalized productivity assistant that delivers private insights about work habits directly to employees—to help people visualize their results and track how they change over time. RMA leaders are using these insights to drive business outcomes, fuel employee engagement, and simultaneously reduce the company’s reliance on annual performance appraisals. Thanks to the company’s use of Workplace Analytics, employee talent measurements are now triangulated through the use of multiple targeted sources. “Workplace Analytics helps us to identify the most important competencies of our top performers that contribute most directly to business success,” says Honiball. “This allows us to improve the performance of other employees by encouraging them to learn and practice these skills. We can also now more easily identify potential new hires that already possess these competencies, interests, and values.”

Gaining perspective

RMA aimed its initial use of Workplace Analytics to two key areas: enhancing internal departmental collaboration and understanding the impact of management transitions on team dynamics. In the information and communication technology (ICT) department, where poor internal communication, lack of ownership, and missed deadlines were contributing to an “us versus them” mentality between departmental employees and the rest of the business, RMA changed reporting lines. Under the new system, specialists report directly to subject matter experts, with the hoped-for result of improved accountability, quality assurance, and focus. Using Workplace Analytics, the company began measuring collaboration hours, the number of emails sent each day, the weekly span in which employees engaged in work, and how frequently each group of employees attended meetings. If leadership could use Workplace Analytics to determine which of these factors had contributed to possible failure, adjustments and improvements could be made.

Over in the Contact Center, a long-time manager was leaving the company. RMA wanted to understand the impact shifting leadership had on the team’s productivity. By tracking team collaboration hours during the departing manager’s last few months of employment, during the three-month search for his replacement, and upon the new manager’s arrival, the company would be able to visualize management’s influence upon a group of roles, along with the impact the changes had on team efficiency and effectiveness.

Acting on data-driven insights

As the weeks passed and data was analyzed, the ICT department and the Contact Center began to gather key insights. In ICT, employees who attended more face-to-face meetings and relied less on email interactions emerged as better collaborators, whether they were communicating inside the department or with key stakeholders across the business. Shorter meetings with fewer participants also contributed to improved performance. In response to these metrics, the general manager asked management staff to take an active role in establishing regular, shorter meetings with employees. On average, the department increased the number of meetings it held each week by 25 percent, with a significant 83 percent increase among system management employees. The result was a 22 percent improvement in internal ICT collaboration and a corresponding 21 percent increase in cross-departmental collaboration as employees built accountability and healthier relationships through more personal connections.

In the Contact Center, metrics showed that weekly collaboration hours increased by 30 minutes when the interim manager took over, and an additional 40 minutes once the new manager came onboard. Taken alone, this would have been a very good thing. But during the interim manager’s tenure, RMA saw a potentially detrimental three-hour-per-week spike in collaboration among Team Leads, the employees responsible for reporting to the manager. These individuals had taken on too many new tasks, and their increased collaboration hours were beginning to eat into their productivity. Sharing this insight with the incoming manager, RMA was able to stabilize Team Lead workloads, reducing their collaboration time by over an hour each week. The Contact Center also discovered a steady downward trend in collaboration among Service Consultants working in the field. For them, each new shift in management had resulted in a full hour of lost collaborative activities per week. With in-office collaboration improved, the new Manager turned his attention to these individuals, aiming to increase employee focus and the overall standard of customer service. “We really value our ability to see how well change is being implemented,” says Honiball. “We might have been able to replicate past leadership decisions before we used Workplace Analytics, but now we can accurately measure how employees respond to these decisions and both the effectiveness and impact of these changes.”

From knowledge to empowerment

In addition to insights focused on specific employee groups, RMA has used Workplace Analytics to affect large-scale change. Traditionally, the company’s individual departments have operated in silos. A year ago, cross-departmental collaboration was infrequent. By inputting historical data into Workplace Analytics, RMA identified the existing instances of cross-departmental collaboration and discovered they led to faster problem solving and more creative solutions. As a result, RMA implemented the Future Leaders Program, which brings in outside experts and encourages employees to reach across the departmental divide, identify organizational problems, and collaborate on innovative solutions that bring about positive change within the business. Now entering its second year, the program has been a resounding success. RMA has also begun to develop a series of policies designed to set employees up for success. These policies are not simply blanket companywide instructions, but career paths based on the practices of their own successful peers and broken down by department, employment level, and function to provide employees with a potential launch pad for their career plans. Employee adherence to these paths could in turn also improve the company’s customer experience, shortening claim resolution times and reducing the number of outbound calls that fall within inopportune hours. “Workplace Analytics has become a key factor in our ability to measure the effectiveness of internal change,” says Honiball. “I recommend it to any organization looking to implement change because you can tangibly measure the effectiveness of interactions over time.”

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Home / Case Studies / HELLA

HELLA drives productivity with modern document collaboration solution for SharePoint with Avanade

Published on July 11, 2018

A global professional services company providing IT consulting and services focused on the Microsoft platform with artificial intelligence, business analytics, cloud, application services, digital transformation, modern workplace, security services, technology and managed services offerings.

In today’s high-paced business environment, having easy access to documents on time and from multiple locations is critical for decision making. It has a tremendous effect on increasing employee efficiency and effectiveness, impacting the company’s bottom line in a positive way. HELLA, an international automotive supplier, noticed that their system wasn’t enabling access to all the information they needed. They decided to simplify an overly complex, high-risk document management system.

As one of the leading automotive suppliers in Europe, with a specialty in lighting and electronics, HELLA’s sales force operates in 125 locations across 35 countries. And like all sales forces, HELLA’s needs to be fast and efficient. “HELLA operates globally with its clients, and everyone in our global sales team and associated business units should not only get on time access to documents across locations but also work collaboratively on the documents to ensure faster decision making” said Andreas Geiger, Head of Global Sales Excellence (GSE) at HELLA. Geiger also understood that previous client and document management solutions made life difficult for its global sales team. Valuable customer information was being spread out across multiple stand-alone servers, each with its own folder structure and naming conventions. Information was also frequently shared via email and thus, there was a need to optimize the entire document management and sharing process. This situation also made the tracking of information quite challenging for the sales people, who had to collate and manage hundreds of technical and legal documents each time an opportunity would arise.

It was clear that a strong document management solution was needed — one that could integrate seamlessly with Salesforce.com, HELLA’s core sales system. Because Avanade had intimate experience with both Salesforce.com and Microsoft’s SharePoint platform, HELLA selected Avanade as its strategic partner to design and deliver a new cloud first solution. “We were very confident Avanade had the expertise to get the job done. We were extremely confident all the way,” said Nico Götzel, the GSE project manager who worked with Avanade for this change.

Avanade designed a cloud-based, end-to-end document management system that integrated their SharePoint Online instance with their legacy Salesforce.com customer management tool. With it, HELLA’s sales team can now automatically create a central repository for documents when starting a new opportunity, as well as collaborate with others and access much needed information, regardless of geographic location in a fast and unfettered way. “Today, all the data for customers is in a single space, making it quite easy and accessible for sales,” said the HELLA executive.

Everyone is happy we no longer have to rely on the old system. And we are all really happy with the [SharePoint] solution and the cooperation with Avanade.

By empowering sales team members to easily create, edit and track all the documents needed for their opportunities, the new document management system is improving productivity, reducing IT headaches and delivering transparency by acting as a single source of truth for customer information. The new solution “pays for itself” in time savings alone, according to HELLA.

Notably, HELLA’s GSE head said that the solution is already driving a positive return on investment. “We’ve measured the time saving improvements and this project will save hundreds of thousands of Euros a year, so it pays for itself,” Götzel reported. Another major win has been the modern capabilities and engagement this new solution is bringing to HELLA’s digital workforce. Employees no longer need to rely on others to find crucial customer information and documents. “It’s a huge relief,” he said. “Everyone is happy we no longer have to rely on the old system. And we are all really happy with the solution and the cooperation with Avanade.”

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April 22, 2024 | by samantha varner.

To download this IT Resource Management Case Study, simply click the button below.

A well-respected, publicly traded national insurance provider that offers personal home and auto, business, and life insurance was struggling with its prior resource management platform’s inability to help them conduct proper analysis due to lacking reporting features. Brian, the insurer’s IT (Information Technology) Resource Manager, knew that his team of more than 1,500 employees needed a more robust platform to help facilitate resource capacity management. His team also needed a solution to help plan the hundreds of projects they manage, facilitate career development, and hiring decisions. As a Resource Management Certified Professional© who completed professional certification for resource managers with The Resource Management Institute, Brian recognized the need for a quicker resource management solution that was easier to use and could help them manage a growing department and numerous resource managers.

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The ghosts of ‘Wintel’: What leaders can learn from the diverging paths that made Microsoft a $3 trillion powerhouse and flatlined Intel

Steve Jobs wasn’t accustomed to hearing “no.” But that was the answer from Paul Otellini, CEO of Intel . 

It was 2006, and Intel, the global king of computer chips, was bringing in record revenue and profits by dominating the kinds of chips in hottest demand—for personal computers and data centers. Now Jobs wanted Intel to make a different type of chip for a product that didn’t even exist, which would be called the iPhone.

Otellini knew chips for phones and tablets were the next big thing, but Intel had to devote substantial capital and its best minds to the fabulously profitable business it already possessed. Besides, “no one knew what the iPhone would do,” he told The Atlantic seven years later, just before he stepped down as CEO. “There was a chip that they were interested in, that they wanted to pay a certain price for and not a nickel more, and that price was below our forecasted cost. I couldn’t see it.”

Otellini, who died in 2017, was a highly successful CEO by many measures. But if that decision had gone the other way, Intel might have become a chip titan of the post-PC era.  Instead, it gave up on phone chips in 2016 after losing billions trying to become a significant player. As he left the company, Otellini seemed to grasp the magnitude of his decision: “The world would have been a lot different if we’d done it.”

Meantime, some 800 miles north, in Seattle, Microsoft was struggling to find its role in a tech world dominated by the internet, mobile devices, social media, and search. Investors were not impressed by its efforts. No one could have foreseen that years later, a few key decisions would set the company up as an AI powerhouse and send its stock soaring. There was a time not so long ago that Microsoft and Intel were both atop the tech world. They were neither competitors nor significant customers of each other, but what New York University’s Adam Brandenburger and Yale’s Barry Nalebuff deemed “complementors.” Microsoft built its hugely profitable Windows operating system over the years to work on computers that used Intel’s chips, and Intel designed new chips to run Windows (hence “Wintel”). The system fueled the leading tech product of the 1990s, the personal computer. Microsoft’s Bill Gates became a celebrity wonk billionaire, and Intel CEO Andy Grove was Time ’s 1997 Man of the Year.

Since then their paths have diverged sharply. Microsoft in 2000 was the world’s most valuable company, and after losing that distinction for many years, it’s No. 1 again. Intel was the world’s sixth most valuable company in 2000 and the largest maker of semiconductors; today it’s No. 69 by value and No. 2 in semiconductors by revenue, far behind No. 1 TSMC (and in some years also behind Samsung ).

A Fortune 500 CEO makes thousands of decisions in a career, a few of which will turn out to be momentous. What’s easy to explain in hindsight—that Microsoft would be at the forefront of AI, that Google would become a behemoth, that Blockbuster would fade into obscurity—is never preordained. Often the fateful decisions are identifiable only in retrospect. Nothing more vividly illustrates this than the parallel stories of Microsoft and Intel. The case study of what went right and wrong at those two giant corporations offers a master class in business strategy not just for today’s front-runners at the likes of Google, Open AI, Amazon , and elsewhere—but also for any Fortune 500 leader hoping to survive and thrive in the coming decade.

Wintel’s origin story

The two companies were founded a mere seven years apart. Intel’s founders in 1968 included Robert Noyce, coinventor of the computer chip, and Gordon Moore, who had written the seminal article observing that the number of transistors on a chip doubled every year, which he later revised to two years—Moore’s law, as others later called it. Andy Grove was employee No. 3. All three are still regarded as giants of the industry.

Bill Gates famously dropped out of Harvard to cofound Microsoft with Paul Allen, a childhood friend. They were excited by the prospects of creating software for a new concept, the personal computer, also called a microcomputer. They launched Microsoft in 1975. 

The two companies’ paths crossed when IBM decided in 1980 to produce a PC and wanted to move fast by using existing chips and an existing operating system developed by others. It chose Intel’s chips and Microsoft’s operating system, profoundly transforming both companies and the people who ran them. IBM’s size and prestige made its design the industry standard, so that virtually all PCs, regardless of manufacturer, used the same Intel chips and Microsoft operating system for decades thereafter. As PCs swept America and the world, Intel and Microsoft became symbols of technology triumphant, glamour, success, and the historic bull market of 1982 to 2000.

Then everything changed.

The reign of Gates and Grove peters out

In October, 2000, Fortune ran an article with an illustration depicting Gates and Grove as monumental Egyptian sphinxes. The headline: “Their Reign Is Over.”

The reasoning: “Gates and Grove attained hegemony by exploiting a couple of key choke points in computer architecture—the operating system and the PC microprocessor,” the article explained. “But in the new, more diverse IT world wired together by universal internet protocols, there are no such obvious choke points to commandeer.”

Thus began a multiyear identity crisis for both companies. Intel’s PC chips and Microsoft’s PC operating system and applications remained bountifully profitable businesses, but both companies and their investors knew those were not the future. So what was? And who would lead this new era?

In January of 2000, Gates stepped down as CEO after 25 years, and Steve Ballmer, Microsoft’s president and a college friend of Gates, took his place; Gates remained chairman. Two days later, Microsoft’s stock rocket ran out of fuel. On that day the company’s market value hit $619 billion, a level it would not reach again for almost 18 years.

Grove was no longer Intel’s CEO in 2000, having handed the job to Craig Barrett, a longtime company executive, in 1998. But as Intel’s visionary and most successful CEO, Grove remained an important presence as chairman of the board. His health was becoming an issue; he had been diagnosed with prostate cancer in 1995, and in 2000 he was diagnosed with Parkinson’s disease. Intel’s stock roared until August, when the company’s market value peaked at $500 billion. It has never reached that level since.

But most significantly, 2000 was the year that the internet began to seem like it just might make Wintel irrelevant. 

At Intel, Barrett responded with acquisitions, many of which were in telecommunications and wireless technology. In concept, that made great sense. Cell phones were going mainstream, and they required new kinds of chips. “Craig tried to very aggressively diversify Intel by acquiring his way into new businesses,” says David Yoffie, a Harvard Business School professor who was on Intel’s board of directors at the time. “I would say that was not his skill set, and 100% of those acquisitions failed. We spent $12 billion, and the return was zero or negative.”

In the lean years after the dotcom balloon popped, Barrett continued to invest billions in new chip factories, known as fabs, and in new production technologies, so Intel would be well positioned when demand rebounded. That is a hint to one of the most important lessons of the Wintel saga and beyond: Protecting the incumbent business, even in a time of transition, is almost impossible to resist. That course usually sounds reasonable, but it holds the danger of starving the company’s future. As the great management writer Peter Drucker said: “If leaders are unable to slough off yesterday, to abandon yesterday, they simply will not be able to create tomorrow.” 

‘We screwed it up’

At Microsoft in the 2000s, “it was not at all obvious what would happen with the shape and volume of PCs, with operating system margins, or the future of applications like Word or Excel,” says Ray Ozzie, a top-level Microsoft executive from 2005 to 2010. “There was significant internal debate at Microsoft and in the industry on whether, in the future, the PC was dead, or if it would continue to grow and thrive.” Maybe Word, Excel, and those other applications that resided on your hard drive would move to the internet, like Google Docs, introduced in early 2006. In that case Microsoft would need a new business model. Should it develop one? Some executives thought so. But no one knew for sure.

During this period, Microsoft was hardly a model of corporate innovation, and succumbed to what often happens when successful companies are disrupted. Ozzie explains: “When you are rolling in resources and there are multiple existential threats, the most natural action to protect the business is to create parallel efforts. It’s more difficult to make a hard opinionated choice and go all in. Unfortunately, by creating parallel efforts, you create silos and internal conflict, which can be dysfunctional.”

As competing teams fought for primacy, Microsoft missed the two most supremely profitable businesses since the PC era: search and cell phones. Those misses were not fatal because Microsoft still had two reliable, highly profitable businesses: the Windows operating system and the Office suite of apps. But in Drucker’s terms, those were yesterday businesses. Investors didn’t see substantial tomorrow businesses, which is why the stock price went essentially nowhere for years. Missing search and cell phones didn’t threaten Microsoft’s existence, but it threatened Microsoft’s relevance and importance in a changing world, which could eventually damage the company’s appeal among investors and the world’s best employees. The reasons for those crucial misses are instructive.

In 2000 Google was an insignificant internet search startup with no clear business model, but it had an inkling that selling advertising could be profitable. We know how that turned out: Google’s 2023 ad revenue was $238 billion. The model was entirely foreign to Microsoft, which made tons of money by creating software and selling it at high prices. Charging users nothing? Selling ads? Microsoft had never run a business at all like Google’s. By the time Google’s model had proved itself, Microsoft was hopelessly far behind. Today its Bing search engine has a 3% market share across all platforms worldwide, says the StatCounter web-traffic analysis firm. Google’s share is 92%.

Microsoft’s failure in cell phones was, in a large sense, similar—the company didn’t fully grasp the structure of the business until it was too late. The company assumed the cell phone industry would develop much like the PC industry, in which sellers like Dell combined Intel’s chips and Microsoft’s software in a final product. But Apple’s starkly different iPhone business model, in which it designs its own chips and writes its own software, was an enormous hit. The other big winner in the industry, Google’s Android smartphone operating system, likewise ignored the PC model. Instead of selling its operating system, Google gives it away to phone makers like Samsung and Motorola. Google makes money by putting its search engine on every phone and by charging app makers a fee when users buy apps.

Bill Gates acknowledges that Microsoft’s miss in cell phones was life-changing for the company. Looking back on his career in 2020, he said: “It’s the biggest mistake I made in terms of something that was clearly within our skill set.”

Intel also lost the mammoth cell phone opportunity, and in a similar way. It couldn’t adapt. Intel understood the opportunity and was supplying chips for the highly popular BlackBerry phone in the early 2000s. The trouble was, Intel hadn’t designed the chips. They were designed by Arm, a British firm that designs chips but doesn’t manufacture them. Arm had developed a chip architecture that used less power than other chips, a critical feature in a cell phone. Intel was manufacturing the chips and paying a royalty to Arm.

Understandably, Intel preferred to make phone chips with its own architecture, known as x86. Paul Otellini decided to stop making Arm chips and to create an x86 chip for cell phones—in retrospect, “a major strategic error,” says Yoffie. “The plan was that we would have a competitive product within a year, and we ended up not having a competitive product within a decade,” he recalls. “It wasn’t that we missed it. It was that we screwed it up.”

Groping for a megatrend

Just as 2000 was a turning point for Intel and Microsoft, so was 2013. Broadly they were in the same fix: still raking in money from the businesses that made them great; getting into the next big opportunities too late or unsuccessfully; groping for a megatrend they could dominate. Their stock prices had more or less flatlined for at least a decade. Then, in May 2013, Paul Otellini stepped down as Intel’s CEO. In August, Steve Ballmer announced he would step down as Microsoft’s CEO.

Succession is the board of directors’ No. 1 job, more important than all its other jobs combined. The stakes are always high. How the Intel and Microsoft boards handled their successions, nine months apart, largely explains why the two companies’ storylines have diverged so dramatically.

Under Otellini’s successor, Brian Krzanich, Intel kept missing new-chip deadlines—ironically failing to keep up with Moore’s law even as competitors did so—and lost market share. The company gave up on smartphone chips. After five years as CEO, Krzanich resigned abruptly when an investigation found he had had a consensual relationship with an employee. CFO Bob Swan stepped in as CEO, and the production troubles continued until, by 2021, for the first time in Intel’s existence, its chips were two generations behind competitors’. Those competitors were Taiwan’s TSMC and South Korea’s Samsung.

In crisis mode, Intel’s board brought back Pat Gelsinger, an engineer who had spent 30 years at Intel before leaving for 11 years to be a high-level executive at EMC and then CEO of VMware . As Intel’s CEO he has announced an extraordinarily ambitious and expensive plan to reclaim the company’s stature as the world leader in chip technology.

Microsoft’s board spent almost six months finding Ballmer’s successor under worldwide scrutiny. At least 17 candidates were publicly speculated upon. British and Las Vegas bookies offered odds on the eventual winner; Satya Nadella, who recently marked 10 years as CEO, was a 14-to-1 long shot. 

Nadella has arguably been the best corporate succession choice, regardless of industry, in years or perhaps decades. Under his leadership the stock finally broke out of its 14-year trading range and shot upward, rising over 1,000%. Microsoft again became the world’s most valuable company, recently worth $3.1 trillion. Gelsinger, with just over three years in the job, can’t be fully evaluated; industry experts wonder if he’ll be Intel’s Nadella. But both CEOs offer useful examples of how to move a company from the past to the future.

Nadella orchestrated Microsoft’s dramatic turnaround by taking an outsider’s look at the company and making big changes with little drama. He began by making Office apps (Word, Excel) compatible with Apple iPhones and iPads—heresy at Microsoft, which regarded Apple as an archenemy. But Nadella realized the two companies competed very little, and why not let millions more people rely on Office apps? The move sent a message to the company and the world: The Microsoft culture’s endemic arrogance would be dialed down considerably. Interoperating with other companies could now be okay.

That was largely a new business model at the company, with many more to follow. For example, Nadella bought LinkedIn , a player in social media, which Microsoft had entirely missed, and later bought GitHub, a repository of open-source code, which Microsoft had previously despised. Both deals and several others have been standout successes. 

More broadly, Nadella brought a new leadership style for a new environment. In a company known for vicious infighting that could paralyze action, he settled long-running debates over major projects. For example, in 2016 he sold the Nokia cell phone business that Microsoft had bought a year before he became CEO, acknowledging that the company had lost the battle for phones. “People don’t quite grok why things have blossomed under Satya,” says a former executive. “His superpower is to make a choice, eliminate conflict, and let the business blossom.”

At Intel, Gelsinger also introduced culture-defying changes. The company had risen to dominance by designing leading-edge chips and manufacturing them with industry-leading skill. Amid that intense pride, the idea of creating a separate foundry business—manufacturing chips designed by others—was anathema. Yet under Gelsinger, Intel has created a new foundry business while also relying more on other foundries, including TSMC, the world’s largest chipmaker, for some of its own chips—a double shock to the culture. 

Getting a long-established company with a titanium-strength culture to adopt seemingly strange business models as Nadella and Gelsinger did can be painfully hard. Often only a new CEO can bring the openness necessary to make it happen. The same problem arises when a company needs to update its corporate strategy. Microsoft had been seeking and debating the next big thing for years, but Nadella saw that the company didn’t need to find a potentially huge new future-facing business. It already had one: Azure, its cloud computing service. Amazon Web Services was and is the industry leader, but Azure has grown to a strong No. 2 because Nadella has given it abundant capital and some of the company’s brightest workers. He also made an unorthodox investment in OpenAI, creator of ChatGPT, commiting $13 billion to the company starting before it was famous. Now Azure offers its customers OpenAI technology. In Drucker’s terms, it’s a big, thriving tomorrow business. 

Gelsinger changed Intel’s strategy even more radically. He bet heavily and successfully on billions of dollars from the U.S. government. Via the CHIPS and Science Act, Intel could receive up to $44 billion in aid for new U.S. chip factories the company is building in coming years. “As I like to joke, no one has spent more shoe leather on the CHIPS Act than yours truly,” he tells Fortune. “I saw an awful lot of senators, House members, caucuses in the different states. It’s a lot to bring it across the line.” 

A key insight is that for a major company with a history of success, like Microsoft and Intel, moving beyond an outmoded strategy and fully embracing a new one is traumatically difficult and sometimes impossible. For years both companies tried and failed to do it. A related insight: Doing it is easier for Nadella and Gelsinger because they have the advantage of being “insider outsiders,” leaders with deep knowledge of their organization but without heavy investment in its strategy; Nadella was working on Azure, not the Windows operating system or Office apps, long before he became CEO, and Gelsinger’s 11-year absence from Intel gave him license to rethink everything.

A larger lesson is that, in the stories of these two great companies, succession is the most important factor. Considering that Microsoft on the whole has fared better than Intel over the past 24 years, it’s significant that over that period, Microsoft has had only two CEOs and Intel has had five. Most people study the CEO when explaining a company’s performance, but they should first examine those who choose the CEO, the board of directors.

Looking back at these stories, asking “what if” is irresistible. What if Paul Otellini had said yes to Steve Jobs? What if any of Intel’s or Microsoft’s CEOs had been someone else? What if Intel, under a different CEO, had developed a successful GPU, the kind of chip that powers today’s AI engines (it tried)—would you ever have heard of Nvidia? Bill Gates said in 2019, “We missed being the dominant mobile operating system by a very tiny amount.” What if that tiny amount had shifted slightly? Whose phone would you be using today? 

It’s all endlessly tantalizing but of course unknowable. The value of looking back and asking “what if,” is to remind us that every day leaders are creating the future—and neglecting their duty if they don’t learn from the past.

5 lessons from the Wintel case study:

1. Success can be a company’s worst enemy. The great management writer Peter Drucker said every company must “abandon yesterday” before it can “create tomorrow.” But in a successful company, every incentive pushes leaders to protect yesterday. Intel and Microsoft struggled for years to create their tomorrows. 2. Leaders must be open to business models that seem strange. Whether giving away software or manufacturing chips designed by others as a separate business, both Microsoft and Intel faced competitors doing things differently.  3. Get everyone on the same page. Debate is healthy up to a point, but at Microsoft it continued far too long until Nadella became CEO and set clear priorities. At Intel a series of CEOs backed differing solutions to its declining business, which prolonged a muddled strategy.  4. Succession is the board’s No. 1 job, more important than all its other jobs combined. Everyone knows it, but some boards still do their job poorly. If they make a mistake, none of the other lessons matter. Considering that Microsoft has come through the past 24 years better than Intel, it may be significant that Microsoft has had only two CEOs in that period while Intel has had five. 5. Failure isn’t fatal. The Wintel story is a pointed reminder that all companies, including the best, suffer failures and fall into crises. There are no exceptions. The leaders of any company, even the grandest, must always be ready to engage the skills of organizational rescue, and know that even that can be part of greatness.

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AI study guide: The no-cost tools from Microsoft to jump start your generative AI journey

By Natalie Mickey Product Marketing Manager, Data and AI Skilling, Azure

Posted on April 15, 2024 4 min read

The world of AI is constantly changing. Every day it seems there are new ways we can work with generative AI and large language models. It can be hard to know where to start your own learning journey when it comes to AI. Microsoft has put together several resources to help you get started. Whether you are ready to build your own copilot or you’re at the very beginning of your learning journey, read on to find the best and free resources from Microsoft on generative AI training.

Build intelligent apps at enterprise scale with the Azure AI portfolio

Azure AI fundamentals

If you’re just starting out in the world of AI, I highly recommend Microsoft’s Azure AI Fundamentals course . It includes hands on exercises, covers Azure AI Services, and dives into the world of generative AI. You can either take the full course in one sitting or break it up and complete a few modules a day.

Learning path: Azure AI fundamentals

Course highlight: Fundamentals of generative AI module

Azure AI engineer

For those who are more advanced in AI knowledge, or are perhaps software engineers, this learning path is for you. This path will guide you through building AI infused applications that leverage Azure AI Services, Azure AI Search, and Open AI.

Course highlight: Get started with Azure OpenAI Service module

Let’s get building with Azure AI Studio

Imagine a collaborative workshop where you can build AI apps, test pre-trained models, and deploy your creations to the cloud, all without getting lost in mountains of code. In our newest learning path , you will learn how to build generative AI applications like custom copilots that use language models to provide value to your users.

Learning path: Create custom copilots with Azure AI Studio (preview)

Course highlight: Build a RAG-based copilot solution with your own data using Azure AI Studio (preview) module

Dive deep into generative AI with Azure OpenAI Service

If you have some familiarity with Azure and experience programming with C# or Python, you can dive right into the Microsoft comprehensive generative AI training.

Learning path: Develop generative AI solutions with Azure OpenAI Service

Course highlight: Implement Retrieval Augmented Generation (RAG) with Azure OpenAI Service module

Cloud Skills Challenges

Microsoft Azure’s Cloud Skills Challenges are free and interactive events that provide access to our tailored skilling resources for specific solution areas. Each 30-day accelerated learning experience helps users get trained in Microsoft AI. The program offers learning modules, virtual training days, and even a virtual leaderboard to compete head-to-head with your peers in the industry. Learn more about Cloud Skills Challenges here , then check out these challenges to put your AI skills to the test.

Invest in App Innovation to Stay Ahead of the Curve

Challenges 1-3 will help you prepare for Microsoft AI Applied Skills, scenario-based credentials. Challenges 4 and 5 will help you prepare for Microsoft Azure AI Certifications, with the potential of a 50% exam discount on your certification of choice 1 .

Challenge #1: Generative AI with Azure OpenAI

In about 18 hours, you’ll learn how to train models to generate original content based on natural language input. You should already have familiarity with Azure and experience programming with C# or Python. Begin now!

Challenge #2: Azure AI Language

Build a natural language processing solution with Azure AI Language. In about 20 hours, you’ll learn how to use language models to interpret the semantic meaning of written or spoken language. You should already have familiarity with the Azure portal and experience programming with C# or Python. Begin now!

Challenge #3: Azure AI Document Intelligence

Show off your smarts with Azure AI Document Intelligence Solutions. In about 21 hours, you’ll learn how to use natural language processing (NLP) solutions to interpret the meaning of written or spoken language. You should already have familiarity with the Azure portal and C# or Python programming. Begin now!

Challenge #4: Azure AI Fundamentals

Build a robust understanding of machine learning and AI principles, covering computer vision, natural language processing, and conversational AI. Tailored for both technical and non-technical backgrounds, this learning adventure guides you through creating no-code predictive models, delving into conversational AI, and more—all in just about 10 hours.

Complete the challenge within 30 days and you’ll be eligible for 50% off the cost of a Microsoft Certification exam. Earning your Azure AI Fundamentals certification can supply the foundation you need to build your career and demonstrate your knowledge of common AI and machine learning workloads—and what Azure services can solve for them. Begin now!

Challenge #5: Azure AI Engineer

Go beyond theory to build the future. This challenge equips you with practical skills for managing and leveraging Microsoft Azure’s Cognitive Services. Learn everything from secure resource provisioning to real-time performance monitoring. You’ll be crafting cutting-edge AI solutions in no time, all while preparing for Exam AI-102 and your Azure AI Engineer Associate certification . Dive into interactive tutorials, hands-on labs, and real-world scenarios. Complete the challenge within 30 days and you’ll be eligible for 50% off the cost of a Microsoft Certification exam 2 . Begin now!

Finally, our free Microsoft AI Virtual Training Days are a great way to immerse yourself in free one or two-day training sessions. We have three great options for Azure AI training:

• Azure AI Fundamentals
• Generative AI Fundamentals
• Building Generative Apps with Azure OpenAI Service

Start your AI learning today

For any and all AI-related learning opportunities, check out the Microsoft Learn AI Hub including tailored AI training guidance . You can also follow our Azure AI and Machine Learning Tech Community Blogs for monthly study guides .

• Microsoft Cloud Skills Challenge | 30 Days to Learn It – Official Rules
• https://developer.microsoft.com/en-us/offers/30-days-to-learn-it/official-rules#terms-and-conditions

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