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How Microsoft Became Innovative Again

• Behnam Tabrizi

Inside the cultural turnaround that helped the tech giant think like a startup.

How did Microsoft revive its culture of innovation? For years, the company has been written off for playing defense on its position in the tech world. But, as signaled by its partnership with OpenAI and its challenge to Google’s search supremacy, it has gone back on the offense. The about face was, at its core, a cultural shift, driven by CEO Satya Nadella. He drove this by inviting an existential moment when he stepped into the job, reconsidering the company’s purpose. Then, he laid out strategic changes that would enable the company to think more like a startup, and made business decisions that committed the company to this new direction.

For years now, observers of tech have written off Microsoft as a 20th-century phenomenon, fat and happy from its Windows monopoly. The tech giant hadn’t had a breakthrough innovation in decades. It was rich enough to be a fast follower, but too big and bureaucratic to lead in any market. Jeff Bezos was known to gesture east and admonish his Amazon colleagues not to become complacent like their Seattle neighbor.

• BT Behnam Tabrizi has been teaching “Leading Organizational Transformation” at Stanford University’s Department of Management Science and Engineering and executive programs for more than 25 years. An expert in organizational and leadership transformation, he has helped thousands of CEOs and leaders plan, mobilize, and implement innovative transformational initiatives. He has written ten books, most recently  Going on Offense : A Leader’s Playbook for Perpetual Innovation  (IdeaPress Publishing, August 2023). TabriziBehnam

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Product Management Practice Case Study: Microsoft

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Microsoft’s Marketing Mix (4Ps) Analysis

Microsoft Corporation’s marketing mix is a showcase of how rapid innovation combines with effective approaches to maintain a strong share of the market. An organization’s marketing mix or 4Ps (Product, Place, Promotion & Price) determines the strategies and tactics for implementing a marketing plan. In this case, Microsoft uses online technology and technological measures to protect digital products. As a major competitor in the computer hardware and software market, the company enjoys high revenues. However, competitive rivalry and related issues, as shown in Microsoft’s Five Forces analysis , threatens such market position. To ensure continued success in the global market, Microsoft must match its marketing mix with the characteristics of target markets worldwide.

An effective marketing mix (4Ps) enables Microsoft Corporation to maximize its sales revenues. However, an evolving marketing mix is necessary to maintain the company’s position in the computer hardware and software market.

Microsoft’s Products (Product Mix)

Microsoft started as a software developer. However, the business has since grown to include an increasing variety of products, as shown in this element of the marketing mix. Microsoft categorizes its products, also known as the product mix, as follows:

• Entertainment
• Cloud and other online services

Microsoft’s devices include hardware products, such as personal computers, tablets, and the Xbox. On the other hand, the company puts systems software or basic software under the Software category. For example, such software products include Microsoft 365 and Windows OS. In the Apps product line are other free and proprietary software products from the company, as well as from third parties. For example, these apps include Remote Desktop (from Microsoft Corporation) and the proprietary Drawboard PDF (from Drawboard). The company keeps a percentage of all revenues generated through sales of third-party apps on Microsoft online stores. The Games product line covers the Xbox games, Windows games, and related gaming software. In the Entertainment category, the company also keeps a percentage of all movies sold through its website. Cloud-based and other online services include Azure and online storage solutions. This element of Microsoft’s marketing mix reflects the increasing diversification of the company’s products. Such a condition is connected to Microsoft’s generic competitive strategy and intensive growth strategies , which emphasize growth by penetrating markets and providing attractive products.

Place/Distribution in Microsoft’s Marketing Mix

Microsoft Corporation needs to maximize its reach in the computer hardware and software market. In this element of the marketing mix, the locations or places for transacting with customers are considered. In the case of Microsoft, the following venues or places are used to distribute products:

• Official website
• Authorized sellers
• Microsoft Stores

Customers can access, purchase or download software products through Microsoft’s official website and online store. At present, this online place is a major avenue for the company’s revenues. In addition, the firm’s authorized sellers provide a direct approach to sales and marketing. These sellers, typically located in strategic commercial areas around the world, enable the company to reach target markets. On the other hand, Microsoft Stores are physical retail stores where customers can access a variety of the company’s products, such as smartphones and Xbox units. These stores, although limited in number, are another direct approach to marketing, enabling the company to enhance its brand image and improve customer experience. This element of the marketing mix shows an expanding reach in the global computer hardware and software market, thereby supporting efforts to capture every person as a customer, as highlighted in Microsoft’s mission statement and vision statement .

Microsoft’s Promotion (Promotional Mix)

Microsoft’s concern in this element of the marketing mix focuses on effective communication strategies and tactics used to attract target customers. Considering the conditions of the computer hardware and software market, the strategies and tactics in Microsoft’s promotional mix are prioritized as follows:

• Advertising (most significant)
• Sales promotions
• Direct marketing
• Personal selling
• Public relations

Microsoft’s biggest promotion expense is on advertising, which enhances the company’s corporate image. In sales promotions, the firm uses discounts and other incentives to attract customers. For example, students can purchase the company’s products at discounted prices. On the other hand, the company uses direct marketing for sales deals with organizations, such as academic institutions. In personal selling, Microsoft Store sales personnel present products and their features to potential buyers. While the discounts also function as a public relations tactic, the company’s main public relations strategy is implemented through Microsoft grants, charity, and discounted solutions, such as for nonprofits. Donations and related activities are executed through this philanthropic arm. For example, the company donates computer hardware and software products to nonprofit organizations and provides financial support for programs that help at-risk youth. In this element of Microsoft’s marketing mix, advertising is the most important determinant of the company’s effectiveness in communicating with the target market. The other strategies and tactics satisfy stakeholders according to Microsoft’s corporate social responsibility and stakeholder management programs .

Prices & Pricing Strategy in Microsoft’s 4P

Price points affect the attractiveness and sales performance of Microsoft’s products. The company must apply suitable pricing approaches to ensure effectiveness in addressing concerns in this element of the marketing mix. Microsoft uses the following pricing strategies:

• Market-oriented pricing strategy
• Freemium pricing strategy
• Buy Only What You Use pricing strategy

In the market-oriented pricing strategy, Microsoft sets the prices of many of its products, based on market factors, such as competitors’ pricing and consumer demand. The company also uses the freemium pricing strategy, which involves offering a product for free, and requiring payment for additional functionality or features. For example, the Microsoft 365 cloud productivity suite is free to use on devices with a maximum screen size of 10 inches. Payment is required to use the suite on larger devices. This pricing strategy is advantageous because it allows customers to try Microsoft 365 free of charge, enabling the company to show the benefits of using the products in the suite. Moreover, Microsoft applies the “buy only what you use” pricing strategy for cloud services. This strategy involves fees based on how much the customer actually uses, instead of fees per device. The advantage of this pricing strategy is its ability to attract customers concerned about extra charges in using multiple computing devices. Thus, this element of the marketing mix shows that Microsoft has been reforming its pricing strategies to address changes in the computer hardware and software market, especially amid competition with other technology firms.

• De Ruyter, K., Keeling, D. I., Plangger, K., Montecchi, M., Scott, M. L., & Dahl, D. W. (2022). Reimagining marketing strategy: Driving the debate on grand challenges. Journal of the Academy of Marketing Science, 50 (1), 13-21.
• Kucuk, S. U. (2023). Digital Marketing Mix Modeling and Coordination. In Visualizing Marketing: From Abstract to Intuitive (pp. 273-291). Cham: Springer International Publishing.
• Microsoft Corporation – Cloud, Computers, Apps & Gaming .
• Microsoft Corporation – Form 10-K .
• Microsoft Corporation – Segment Information .
• Microsoft Education Store – Student Discounts & Deals .
• Mir-Bernal, P., & Sadaba, T. (2022). The ultimate theory of the marketing mix: A proposal for marketers and managers. International Journal of Entrepreneurship, 28 , 1-22.
• Reddy, T. N., Ghouse, S. M., & JS, R. K. (2023). Marketing Mix – Review of P. Research Journal of Humanities and Social Sciences, 14 (1), 55-58.
• U.S. Department of Commerce – International Trade Administration – Software and Information Technology Industry .
• Copyright by Panmore Institute - All rights reserved.
• This article may not be reproduced, distributed, or mirrored without written permission from Panmore Institute and its author/s.
• Educators, Researchers, and Students: You are permitted to quote or paraphrase parts of this article (not the entire article) for educational or research purposes, as long as the article is properly cited and referenced together with its URL/link.

How can you improve Microsoft Authenticator?

Product case study, ‍ describe the product ‍.

Microsoft Authenticator is a mobile app developed by Microsoft that adds an extra layer of security to your online accounts. It helps protect your accounts from unauthorized access by providing a secure way to verify your identity. The great thing about Microsoft Authenticator is that it adds an extra level of security without making the login process complicated. ‍

Clarifying Questions ‍

• What are the current pain points or challenges users are experiencing with Microsoft Authenticator?
• Are there any specific features or functionalities that users are requesting or suggesting for improvement?
• How does Microsoft Authenticator compare to similar authentication apps in terms of user satisfaction and adoption?
• What is the overall goal or vision for Microsoft Authenticator, and how does it align with the needs and expectations of the target user base?
• What is the feedback from security experts or industry professionals regarding the effectiveness and robustness of the app's security measures?
• Are there any upcoming changes or updates to the authentication protocols or standards that need to be implemented in Microsoft Authenticator?
• How can the user experience be enhanced to make the app more intuitive, user-friendly, and seamless in verifying identities?
• Are there any specific user segments or industries where Microsoft Authenticator is particularly popular or where it needs improvement?
• How can the app's compatibility with different platforms and devices be improved to ensure a broader reach and usability?
• What metrics or key performance indicators (KPIs) are being tracked to measure the success and effectiveness of Microsoft Authenticator, and are there any areas where the app is falling short? ‍

Define the Goal ‍

The primary goal of Microsoft Authenticator is to enhance the security of users' online accounts and protect them from unauthorized access. It aims to provide a reliable and convenient method of verifying users' identities during the login process. By adding an extra layer of security through two-factor authentication (2FA) or multi-factor authentication (MFA), Microsoft Authenticator helps users safeguard their personal information, sensitive data, and online transactions. It seeks to prevent unauthorized individuals from accessing accounts, even if they manage to obtain or guess the account password.

‍ Identify User Segments ‍

The user segments of Microsoft Authenticator can include:

General Users: This segment comprises individuals who use Microsoft Authenticator to secure their personal online accounts, such as email, social media, online banking, and e-commerce platforms.

Business Users: Organizations and their employees make up this segment. They use Microsoft Authenticator as part of their company's security policies to protect business accounts, access sensitive information, or enable secure remote access to company resources.

App Developers: This segment includes developers who integrate Microsoft Authenticator into their own applications to provide an additional layer of authentication and security for their users.

IT Administrators: This segment consists of IT professionals and system administrators responsible for managing security protocols and user access within organizations. They may use Microsoft Authenticator to enforce strong authentication measures and manage access control.

Security-Conscious Users: These users prioritize their online security and actively seek out solutions like Microsoft Authenticator to enhance the protection of their accounts and sensitive data.

Mobile-First Users: Users who heavily rely on mobile devices for their online activities and prefer the convenience of using a mobile app like Microsoft Authenticator for quick and easy authentication. ‍

List the Pain Points ‍

Here are some pain points that users across different segments may experience with Microsoft Authenticator:

Complexity of Setup: Users may find the initial setup process of linking Microsoft Authenticator to their accounts confusing or time-consuming, especially if they are not familiar with two-factor authentication or the app's interface.

Limited Account Compatibility: Some users may face challenges when trying to use Microsoft Authenticator with certain online accounts or services that do not support the app as a form of authentication.

Technical Issues: Users may encounter technical glitches, such as app crashes, delays in receiving push notifications, or difficulties syncing their accounts with Microsoft Authenticator.

Inconvenience of Multiple Apps: Users who rely on multiple authentication apps, including Microsoft Authenticator, may find it cumbersome to switch between different apps for verification, leading to a fragmented user experience.

Lack of Backup Options: Users may be concerned about the potential loss of access to their accounts if they lose or replace their device, especially if there are no reliable backup options available for their Microsoft Authenticator credentials.

Limited User Awareness: Some users may be unaware of the benefits and availability of Microsoft Authenticator as a security solution, resulting in low adoption rates and missed opportunities for enhanced account protection.

User Interface and Usability: Users may find the user interface of Microsoft Authenticator complex or not intuitive enough, making it difficult to navigate through settings or access desired features.

Compatibility Issues with Older Devices: Users with older mobile devices or operating systems may encounter compatibility issues or performance limitations when using Microsoft Authenticator.

Educational Resources: Users may struggle to find comprehensive and easily accessible educational resources or guides that explain the setup process, best practices, and troubleshooting tips for using Microsoft Authenticator effectively. ‍

List the solutions to the identified pain points ‍

Here are some potential solutions to address the pain points identified for Microsoft Authenticator:

Simplified Setup Process:

• Provide clear and concise instructions during the initial setup, guiding users through the process step-by-step.
• Offer in-app tutorials or interactive guides to help users understand how to link their accounts with Microsoft Authenticator.

Enhanced Account Compatibility:

• Collaborate with online service providers to increase the number of platforms and services that support Microsoft Authenticator as a form of authentication.
• Provide resources or APIs to facilitate easier integration of Microsoft Authenticator into third-party applications.

Improved Technical Stability:

• Regularly release updates to address technical issues, improve app performance, and resolve bugs reported by users.
• Implement robust testing and quality assurance processes to ensure a stable and reliable user experience.

Seamless Multi-App Integration:

• Explore partnerships or collaborations with other authentication apps to create a unified experience, allowing users to manage multiple accounts from a single app interface.
• Enable easy migration of account data from other authentication apps to Microsoft Authenticator.

Backup and Recovery Options:

• Implement secure backup and recovery mechanisms, such as cloud synchronization or account recovery codes, to help users regain access to their accounts if they switch devices or lose their device.

Increased User Awareness:

• Launch targeted marketing campaigns to raise awareness about the benefits of Microsoft Authenticator, highlighting its ease of use and enhanced security features.
• Collaborate with online service providers to promote Microsoft Authenticator as a recommended authentication method.

Improved User Interface and Usability:

• Conduct user research and usability studies to identify pain points in the app's user interface and implement design improvements for enhanced intuitiveness.
• Provide customizable settings to allow users to personalize their app experience based on their preferences.

Compatibility with Older Devices:

• Optimize app performance for older mobile devices and operating systems to ensure a smooth experience for users with legacy devices.

Comprehensive Educational Resources:

• Develop comprehensive guides, FAQs, and video tutorials within the app and on the Microsoft Authenticator website to educate users about setup, best practices, and troubleshooting steps.
• Offer responsive customer support channels to address user queries and provide timely assistance. ‍

Use Prioritization Metrics to prioritize the solutions according to factors such as feasibility and ease of usage ‍

Let's use the MOSCOW prioritization framework to prioritize the solutions for Microsoft Authenticator:

• Simplified Setup Process: This is a crucial solution to ensure a seamless onboarding experience for users.

Should-Have:

• Enhanced Account Compatibility: Improving compatibility with popular online services will expand the usability and value of Microsoft Authenticator.

Could-Have:

• Seamless Multi-App Integration: While valuable for users managing multiple accounts, this solution can be prioritized lower as it addresses a specific use case.
• Backup and Recovery Options: Although important for user convenience, it can be prioritized lower as users can still use Microsoft Authenticator without these options.

Won't-Have:

• Increased User Awareness: While important for long-term success, this solution can be deprioritized initially to focus on improving the existing user experience.
• Improved User Interface and Usability: Enhancing the user interface and usability can be considered later once critical issues are addressed.
• Compatibility with Older Devices: This solution can be deprioritized if usage data indicates a smaller user base on older devices.
• Comprehensive Educational Resources: While valuable for user education, it can be addressed in later iterations once the core functionality is improved.
• By using the MOSCOW prioritization framework, you can focus on the must-have and should-have solutions first, ensuring the core functionality and essential improvements are prioritized. This approach allows for a more efficient allocation of resources and prioritizes solutions that have the highest impact on user satisfaction and security.
• Simplified Setup Process: A crucial solution to ensure a seamless onboarding experience for users.
• Improved Technical Stability: Ensuring a stable and reliable app experience is essential for user satisfaction and trust.

Define Metrics to measure the performance ‍

Adoption Rate: Measure the percentage of users who have successfully set up and linked their accounts with Microsoft Authenticator. This metric reflects the effectiveness of the simplified setup process and user onboarding experience.

Account Compatibility: Track the number of online services and platforms that have integrated Microsoft Authenticator as a supported authentication method. This metric indicates the progress in expanding the compatibility of Microsoft Authenticator with popular services.

App Stability: Monitor the frequency of app crashes, bug reports, and user complaints related to technical issues. Lowering these occurrences signifies improved app stability and reliability.

User Satisfaction: Conduct user surveys or collect feedback to gauge user satisfaction with Microsoft Authenticator. This metric helps assess the overall user experience and the effectiveness of implemented solutions.

Usage Patterns: Analyze usage data to understand how often users engage with Microsoft Authenticator, such as the frequency of login requests and approvals. This data can provide insights into user behavior and the value they derive from the app.

App Ratings and Reviews: Monitor user ratings and reviews on app stores or other platforms. Positive ratings and favorable reviews indicate user satisfaction and appreciation for the improvements implemented.

Support Requests: Track the number of support requests or inquiries related to account compatibility, setup process, technical issues, or other pain points. A decrease in support requests indicates successful resolution of user pain points.

Conversion Rate: If applicable, measure the percentage of users who switch from other authentication apps to Microsoft Authenticator. This metric demonstrates the success of the seamless multi-app integration solution.

Return on Investment (ROI): Assess the impact of the implemented solutions on user adoption, user satisfaction, and overall app performance to determine the ROI of the efforts invested in improving Microsoft Authenticator.

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Responsible Use of Technology: The Microsoft Case Study

In collaboration with the Markkula Center for Applied Ethics at Santa Clara University, USA

The World Economic Forum Responsible Use of Technology project aims to provide practical resources for organizations to operationalize ethics in technology. This White Paper, with its focus on Microsoft Corporation, highlights tools and processes that facilitate responsible technology product design and development. The document is the first in a series that seeks to investigate how companies have begun to incorporate ethical thinking into the development of technology. Its lessons can help organizations advance their own responsible innovation practices, and may even inspire others that have created new methods in pursuit of ethical technology to share their work, either in this series or elsewhere.

World Economic Forum reports may be republished in accordance with the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Public License , and in accordance with our Terms of Use .

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Change management case study

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An organization was implementing a replacement of an old legacy system. This system supported a call center where about 400 order takers entered orders that they received from customers over the phone.

During the planning for the project, no major changes were defined for the call center. The organization decided not to include the order takers in the implementation project directly. Instead, it worked with a group of business analysts who were anchored in the IT department. Earlier system changes had negatively affected order taker performance measures and, as a result, individual cash commissions. Because of those earlier experiences, everyone expected the order takers to offer lots of resistance to any kind of system or process change. Therefore, project management thought that it would be easier to wait until late in the project to include that group of users.

When the project was barely into the build phase, rumors about the new system started to spread from other departments to the order taker teams. The Sales department VP brought a couple of order takers into an improvised demo. The demo went poorly, partly because the demo data was unrelatable and partly because the department VP performed the demo after little or no preparation or practice. The unintended outcome was affirmation of the order takers' impression that the order taking process in the new system would be slower and involve more effort than in the legacy system.

The concerns and rumors almost turned into a revolt. Several key senior supervisors and team leads openly talked about going to a nearby competitor. This competitor was actively using these rumors to approach team members.

At this point, the project sponsor brought in a change manager. The change manager suggested two workstreams. The first stream consisted of the traditional assessments and planning across the organization. Then, given the late stage and the damage that had already been done, a second stream was immediately started to address the call center problem head-on.

The change manager immediately arranged sessions where the company president addressed the whole company, including the call center. They explained why it was critically important for the company to implement a new system and how this system would ensure a significant competitive advantage in the market. The president outlined a bright future for the company, with many other changes than just the system, including new product lines and modern workplace options. During these sessions, individuals in the call center also had a chance to voice their concerns that were related to the earlier changes.

A work group that represented all levels in the call center was set up, and a senior supervisor who was highly regarded and respected by their peers was reassigned as a liaison between the business analysts and the call center. Measures were defined for efficiency, and a plan was made for ensuring that commissions were calculated fairly during the transitional phase. The order takers were able to define some pain points in the legacy system, primarily related to alternative products. All these activities were communicated clearly and repeatedly.

There were still individuals who resisted, especially in the call center supervisor team. Although some general excitement was generated, it seemed as if this small group could turn individuals back against the changes.

The change manager asked a consultant from the implementing partner to arrange for a voluntary round of practice sessions and a contest for the order takers. They wanted to see who could take the most simulated orders in the new system. This time, a test setup that had real data was used. The president supported the contest, and donated not only a weekend at the corporate lodge for the winner and their family but also a symbolic cash prize for the winner and the two runners-up.

The outcome was stunning. More than 50 order takers signed up. After only a few hours of practice, the order takers who took part were largely able to match the legacy system in effectiveness, thanks especially to order copying functionality that didn't exist in the old system. During the practice sessions, the order takers noticed that they could search for products by using both internal and external stock keeping units (SKUs) and product names. They also noticed that the system could prompt them with suggestions for alternative products, whereas the old system required that they look up products in a binder.

In the face of these results, the small group of supervisors who had been resisting lost their argument. A few did eventually leave the company, but an increase in efficiency quickly balanced that loss. The connection between the call center and the IT department continued and eventually brought on more momentous changes, now driven by suggestions from the call center.

The traditional change management workstream also provided results. Sessions to define outcomes and measures found large differences in expectations, a high level of complexity and risk, and a low level of transformation maturity.

Directly after the assessments and discussions, department VPs and senior managers replaced the business representatives who were originally assigned to the project team, to ensure proper representation and decision-making efficiency.

The project sponsor realized the complexity and risk, and also the company's poor readiness. Therefore, they brought in a management consultant who specialized in the areas of warehouse management and supply chain management to help the project team.

Overall, the project was a remarkable success.

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Manufacturing for tomorrow: Microsoft announces new industrial AI innovations from the cloud to the factory floor

Apr 17, 2024 | Kathleen Mitford, CVP, Global Industry

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After years of uncertainty from supply chain disruption and increased customer expectations, to changes in consumer demand and workforce shortages, manufacturing remains one of the most resilient and complex industries. Today, we are witnessing the manufacturing industry enter a transformative era, fueled by AI and new AI-powered industrial solutions. This AI-driven shift is prompting many organizations to fundamentally alter their business models and re-evaluate how to address industry-wide challenges like data siloes from disparate data estates and legacy products, supply chain visibility issues, labor shortages, and the need for upskilling employees, among others.  AI is more than just an automation tool, it’s a catalyst for innovation, efficiency and sustainability. AI innovation creates an opportunity to help manufacturers enhance time-to-value, bolster operations resilience, optimize factory and production costs and produce repeatable outcomes.

Ahead of Hannover Messe , one of the world’s largest manufacturing innovation events, Microsoft is announcing new AI and data solutions for manufacturers to help unlock innovation, enable intelligent factories, optimize operations and enhance employee productivity. The manufacturing industry has been incredibly resilient over the last decade and the infusion of new AI solutions signifies a critical transformation in this vital industry.

Unlock innovation and fuel the next generation of intelligent factories with data and AI

Manufacturing is one of the most data-intensive industries, generating an average of 1.9 petabytes worldwide every year, according to McKinsey Global Institute. And most of this data goes unused, leaving many valuable insights untapped. According to Gartner ® Research, “Generative AI will transform the manufacturing industry to a level previously not available, by providing new insights and recommendations based on data and actionable information.” [1] In this era of AI, the importance of data continues to grow as organizations realize they are only scratching the surface of what’s possible.

To help customers leverage their data and insights, today, we are announcing the private preview of manufacturing data solutions in Microsoft Fabric, and copilot template for factory operations on Azure AI . These solutions help manufacturers unify their operational technology and information technology (IT) data estate and accelerate and scale data transformation for AI in Fabric, our end-to-end analytics SaaS-based platform. Copilot template for factory operations helps manufacturers to create their own copilots for front-line workers utilizing the unified data. Front-line employees can use natural language to query the data for knowledge discovery, training, issue resolution, asset maintenance and more. For example, if a factory plant manager wants to understand why a machine is breaking, they can query the copilot to get insights and resolve the issue in just days, instead of weeks.

As part of our private preview, Intertape Polymer Group (IPG) uses Sight Machine’s Manufacturing Data Platform to continuously transform data generated by its factory equipment into a robust data foundation for analyzing and modeling its machines, production processes and finished products. IPG is now using Sight Machine’s Factory CoPilot, a generative AI platform with an intuitive natural language chat interface, powered by the Microsoft Cloud for Manufacturing and the copilot template for factory operations on Azure AI. This tool facilitates the team’s ability to rapidly gather insights and direct work on production lines which previously operated like black boxes. Instead of working through manual spreadsheets and inaccessible data, all teammates including production, engineering, procurement and finance have better information to drive decisions on products and processes throughout the plant improving yield and reducing inventory levels.

Also in private preview, Bridgestone is partnering with Avanade to confront production challenges head-on, focusing on critical issues related to production disruptions and scheduling inefficiencies, like yield loss, which can escalate into quality issues. As a private preview customer collaborating with Avanade, Bridgestone aims to harness the power of manufacturing data solutions in Fabric and the copilot template for factory operations. Their goal is to implement a natural language query system that enables front-line workers, with different levels of experience, with insights that lead to faster issue resolution. The team is excited to establish a centralized system that efficiently gathers and presents critical information from various sources and facilitates informed decision-making and enhances   operational agility across Bridgestone’s production ecosystem.

Creating more resilient operations and supply chains

A robust data strategy must span from cloud to the shop floor to enable the level of scale and integration that will help manufacturers accelerate industrial transformation across all operations. However, gathering OT data and integrating the data into multiple solutions is not an easy task for manufacturers. Production is complex, and their sensors, machines and systems are highly varied. Each site is unique and ensuring the right data is being shared with the right person at the right time is onerous and costly. Unfortunately, these scale and integration hurdles also block the enterprise from scaling AI solutions across every shop floor or gaining global visibility across all their sites.

With this in mind, Microsoft recently launched the adaptive cloud approach , including Azure IoT Operations . Our adaptive cloud is a framework to modernize edge infrastructure across operations, like factories, to take advantage of a modern, composable and connected architecture for your applications. Our adaptive cloud approach creates the level of scale needed to repeat AI solutions across production lines and sites. Putting the adaptive cloud approach into practice, Azure IoT Operations leverages open standards and works with Microsoft Fabric to create a common data foundation for IT and OT collaboration. To find out more about our adaptive cloud approach and Azure IoT Operations, visit our Azure Blog .

Looking to increase global operational efficiency, Microsoft’s customer Electrolux Group, developed a single platform to build, deploy and manage several key manufacturing use cases. Their platform’s goal is to capture all manufacturing data, contextualize it and make it available for real time decision-making across all levels of the organization within a scalable infrastructure. To enable this, Electrolux Group is adopting a full stack solution from Microsoft that leverages the adaptive cloud approach, including Azure IoT Operations. Using this approach, Electrolux Group is looking to reduce overhead from multiple vendors, a consistent and simple way to deploy and manage multiple use cases at a site, and then the ability to scale those solutions to multiple sites with simple and consistent fleet management.

Supply chain disruption is not new; however, its complexity and the rate of change are outpacing organizations’ ability to address issues. Manufacturers are under pressure to prevent and minimize disruptions, and as a result, almost 90% of supply chain professionals plan to invest in ways to make their supply chains more resilient. To support our customers, we’re announcing the upcoming preview of a traceability add-in for Dynamics 365 Supply Chain Management that will allow businesses to increase visibility into their product genealogy through the different steps of the supply chain. Traceability will also help businesses track events and attributes throughout supply chain processes and will provide an interface to query and analyze data.

Empowering front-line workers with AI tools to improve productivity,and job satisfaction

To enable intelligent factory operations, an empowered and connected workforce is key. According to the latest Work Trend Index , 63% of front-line workers do repetitive or menial tasks that take time away from more meaningful work. Additionally, 80% of front-line workers think AI will augment their ability to find the right information and the answers they need. From the office to the factory floor to the field, we are building solutions to address the unique challenges manufacturers face — by helping streamline front-line operations, enhance communication and collaboration, improve employee experience and strengthen security across shared devices.

Today we’re introducing new capabilities for Copilot in Dynamics 365 Field Service that help service managers and technicians efficiently find information, resolve issues while keeping customers updated at every step, and help summarize their work. Generally available, field service managers can interact with Copilot to find pertinent information about work orders using natural language in their flow of work in the Dynamics 365 Field Service web app. Additionally, available in public preview, front-line workers can configure and customize the fields Copilot uses to generate summaries within Dynamics 365 Field Service.

To further streamline collaboration among field service managers, technicians, and remote experts, Dynamics 365 Field Service users with the Field Service app in Teams can now share links to work orders that automatically expand to provide key details. This capability is generally available starting today. Should technicians need additional assistance from remote experts to resolve issues, they can simply access Dynamics 365 Remote Assist capabilities in the flow of work in Microsoft Teams with anchored spatial annotations even if the camera moves.

Microsoft ecosystem and partnerships in the era of AI

These new industry innovations in data and AI are strengthened through the Microsoft Cloud for Manufacturing, which enables organizations to accelerate their data and AI journey by augmenting the Microsoft Cloud with industry-relevant data solutions, application templates and AI services. The Microsoft Cloud for Manufacturing brings the best of Microsoft and our partners to jointly accelerate the digital transformation in manufacturing.

Microsoft is a trusted co-innovation partner committed to working with enterprises to unlock the true potential of AI solutions and transform the industry.​ Our offerings can also be customized by an unmatched global ecosystem of trusted partners. This year, we’re proud to have the following valued partners demonstrate at our Hannover Messe booth: Accenture, Annata, Ansys, Avanade, AVEVA, Blue Yonder, Bosch, CapGemini, Cognite, Connected Cars DK, DSA, HERE Technologies, Hexagon, Netstar, NVIDIA, o9 Solutions, PTC, Rockwell Automation, SAP, Syntax, Sight Machine, Siemens, SymphonyAI, Tata Consultancy Services (TCS), Threedy, ToolsGroup and Tulip Interfaces.

We look forward to seeing you at the Microsoft Booth in Hall 17 Stand G06, where you can join guided tours, and speak with manufacturing and industrial experts from around the world.

[1]   Gartner®, GenAI use-case prism for manufacturing, By Ellen Eichhorn, Sohard Aggarwal, July 2023. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.

Tags: AI , Copilot for Dynamics 365 , Generative AI

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Home / Microsoft Copilot Scenario Library / Finance departmental guidance / Build a business case

Finance scenario: Build a business case

Potential benefits.

Reduce spend

Access data more efficiently across systems

Using Copilot to build a business case

1. define opportunityfor investment.

Ask Copilot to create a project brief from emails and other company documents.

Support efficient review and understanding of the issues that need to be addressed with the investment.

2. Gather project information

Meet with the production team to learn about the various options available and gather financial information for the business case.

Copilot in Teams

Help ensure a productive meeting by using Copilot to suggest questions and clarify what people said. Use the recap for a summary and action items.

3. Gather financial data

Pull data from the financial system using a plug in built with Copilot Studio to estimate past cost of sales and revenues by year.

Copilot Studio

Copilot in Excel

Reduce the effort required to pull information from financial systems.

4. Meet with chief economists

Get the latest economic forecast from the economist team to estimate future pricing and cost of materials. Organize the information in a table in Excel and use Copilot to produce charts showing trends in the data.

Collaborate effectively across teams / functions (e.g., legal, transportation) in a secure way. Use data for decision making in meetings and discussion.

5. Produce summary report

Once the case flow analysis is complete use Copilot to turn the project brief into a set of slides for the executive presentation. Then add in the financial information.

Copilot in PowerPoint

Improve the quality of your presentations by using Copilot to revise content and organize the slides using Excel data.

6. Stress test the business case

Use Copilot to test some options for the business case and identify the largest variances.

Speed analysis by using Copilot to add formulas columns and create charts.

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50 Product Management Case Studies

We often wonder what kind of process other product teams have created, planned, and most importantly, how they have implemented it. That is why we at Producter have compiled 50 different case studies for you.

a year ago   •   4 min read

We often wonder what kind of process other product teams have created, planned, and most importantly, how they have implemented it.

That is why we at Producter have compiled 50 different case studies for you.

Brought to you by Roadmape

1- Rules of Flow for Product Management: an AirBnB Case Study

“Engagement” is a term that is so overused in product management that it has almost lost its meaning. So often I’ve heard from teams, “We’ll measure the success of this test with engagement,” which could mean anything from feature click-through to bounce to we-aren’t-really-sure-this-will-drive-conversion-so-we’re-hedging-our-bet. Underneath, the reason this term has been co-opted and jargonized is that genuine, productive engagement can be ramped toward long-term customer loyalty. And loyalty pays off: a loyalty increase of 7% can boost lifetime profits per customer by as much as 85%, and a loyalty increase of 3% can correlate to a 10% cost reduction ( Brand Keys ).

2- The Psychology of Clubhouse’s User Retention (...and churn)

3- Netflix Q1 ’21 Subscriber Growth Miss: Can We Avoid Another One?

As a data analyst supporting a mobile subscription business , Netflix’s Q1 ’21 subscriber growth miss is a classic example of when I would get called for recommendations to prevent a miss in the future. I thought this would make an interesting case study to discuss my approach to finding insights to drive subscriber growth. Sadly I’m not a Netflix employee and will be limited to publicly available data but the wealth of information on the Internet about Netflix is sufficient to generate insights for this case study.

4- Amazon Go Green

As part of the Design Challenge from productdesign.tips, our team came together to find ways for Amazon to encourage more sustainability on their e-commerce platform. As with any unsolicited design project, the challenge comes with a lack of access to application analytics and technical feasibilities. Nonetheless, the question remains: How might we design checkout screens for an e-commerce app to help people recycle the goods they buy?

5- Quora Case Study – The Wonderful World of Quora

Quora has become a substantive resource for millions of entrepreneurs and one of the best sources for Business to Business market. Majorly used by writers, scholars, bloggers, investors, consultants, students this Q/A site has much to offer in terms of knowledge sharing, connection building and information gathering.

6- Building a product without any full-time product managers

Jambb is an emerging social platform where creators grow their communities by recognizing and rewarding fans for their support. Currently, creators monetize fan engagement through advertisements, merchandise, and subscriptions, to name a few. However, this only represents 1% of fans, leaving the other 99% (who contribute in non-monetary ways) without the same content, access, and recognition that they deserve.

8- What if you can create Listening Sessions on Spotify

Summary: The project was done as a part of a user experience design challenge given to me by a company. I was given the brief by them to work on a feature of Spotify and I spent around 25–30 hours on the challenge in which I went through the entire process, from the research to testing.

9- Redesigned Apple Maps and replicated an Apple product launch for it

Quick-fire question; what is the single most important and widely used feature in a phone — asides from texting and instant messaging friends, coworkers and family? Maybe you guessed right, perhaps this feature is so integrated into your life that you didn’t even think about it — either way, it is your phone’s GPS. It is reasonable to say that GPS technology has changed society’s lives in ways we never could’ve imagined. Gone are the days of using physically printed maps and almanacks, when we now have smartphones with navigation apps. Since the launch of the iPhone and the App Store, consumers have been able to use different apps for their personal navigation needs. Everyone has a preference, and apps have come out to try and address every need.

10- Intuitive design and product-led growth

In 2018, Miro was hardly a blip on the radar in the Design world. Fast forward two years, and suddenly Miro is solidly the number one tool for brainstorming and ideation.

Click below to see the complete list 👇

Producter is a product management tool designed to become customer-driven.

It helps you collect feedback , manage tasks , sharing product updates , creating product docs , and tracking roadmap .

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What is customer segmentation, learnings about product development strategy in 2022, keep reading, boost product management with slack: a comprehensive guide to producter's slack integration, mastering the art of product management: 10 essential strategies for success, what is user research.

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 + Machine Learning , Azure AI , Azure AI Services , Azure AI Studio , Azure OpenAI Service , Best practices

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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