Welcome to the MIT CISR Research Briefing series. We publish monthly research briefings to share findings from our research.

MIT CISR provides academic research insights for business technology leaders. Our global research team studies high performing, complex companies, investigating topics related to digital transformation. More than seventy-five firms sponsor our work and participate in our consortium. 

To learn more and access more free research, visit our website at https://cisr.mit.edu.

MIT CISR Research Briefing Series—Audio Edition

Ina Sebastian reads MIT CISR's March 2021 research briefing, which she co-authored with Peter Weill and Stephanie Woerner. See the text version and related content at https://cisr.mit.edu/publication/2021_0301_ValueinDigitalBusiness_SebastianWeillWoerner.

Abstract: Companies can create new types of value in the digital era. In our research, we identified three types of value from digital business: value from operations, value from customers, and value from ecosystems. All three types of value were significant predictors of company performance, although their relative impacts varied. In this briefing, we describe the three types of value and show how they are captured in company performance. We then illustrate how two companies, Kaiser Permanente and Maersk, designed digital initiatives to create value from ecosystems—a new type of value for many large, traditional companies.

Three Types of Value Drive Performance in Digital Business

Barb Wixom reads MIT CISR's April 2021 research briefing, which she co-authored with Leslie Owens and Cynthia Beath. See the text version and related content at https://cisr.mit.edu/publication/2021_0401_DataHeartsMinds_WixomOwensBeath.

Abstract: Companies today are starting to walk the talk when it comes to treating data like a strategic firm asset—they are hiring chief data officers, and rolling out data literacy programs. This briefing describes what else is required for employees to believe that data can create value in new ways, that it can do so over and over and over again, and that everyone in the company can play a role. MIT CISR research indicates that leaders should build capabilities, optimize data monetization initiatives, and motivate pervasive data use, all of which can and should be measured.

Data Is Everybody’s Business

Barb Wixom reads MIT CISR's May 2021 research briefing, which she co-authored with Gabriele Piccoli. See the text version and related content at https://cisr.mit.edu/publication/2021_0501_DataLiquidity_WixomPiccoli.

This briefing introduces the concept of data liquidity, defined as the ease of data asset reuse and recombination. While data is inherently reusable and recombinable, an organization must activate these characteristics by creating strategic data assets and building out its data monetization capabilities. As the company’s strategic data assets become more highly liquid and their number grows, data is made increasingly available for conversion to value, and the company’s data monetization accelerates. Fidelity is an excellent example of a company that is actively creating highly liquid strategic data assets for use enterprise wide.

Build Data Liquidity to Accelerate Data Monetization

Ida Someh reads MIT CISR's July 2022 research briefing, which she co-authored with Barb Wixom and Cynthia Beath. See the text version and related content at https://cisr.mit.edu/publication/2022_0701_AIX_SomehWixomBeath.

Abstract: Four characteristics of AI—unproven value, model opacity, model drift, and mindless application—make it challenging to get stakeholders to trust AI solutions. As a result, organizations that strive to become AI-powered adopt practices to produce AI solutions that are trustworthy. Over time, these practices build AI Explanation (AIX) capability: an emerging enterprise capability that arises from practices AI teams use to build stakeholder confidence in AI solutions. In this briefing, we first describe AIX capability and four sets of practices used to build it. We then draw on a case study about the AI journey of Microsoft to illustrate examples of the practices that company has leveraged.

Building AI Explanation Capability for the AI-Powered Organization

Ina Sebastian reads MIT CISR's January 2025 research briefing, which she co-authored with Stephanie Woerner, Peter Weill, and Daniel Woerner. See the text version and related content at https://cisr.mit.edu/publication/2025_0101_DigitalSustainability_SebastianWoernerWeillWoerner.

Abstract: Sustainability is a cost of doing business for many companies today—but it is also an opportunity for creating value. Companies only achieve value, however, by embedding sustainability goals into company strategy and then developing capabilities to advance these goals. Our survey analysis suggested that there are four distinct strategic sustainability goals: compliance and efficiency, customer and investor reputation, new revenue, and company purpose. Companies in the research that pursued strategic sustainability goals beyond compliance and efficiency saw bottom-line impacts such as greater EBIT, more revenues from innovation, and improved customer experience.

Business Value from Digital Sustainability

Barb Wixom reads MIT CISR's February 2025 research briefing, which she co-authored with Nick van der Meulen and Cynthia Beath. See the text version and related content at https://cisr.mit.edu/publication/2025_0201_DataMonetizationImpact_vanderMeulenWixomBeath.

Abstract: While organizations generally recognize data’s potential to drive business value, many still struggle to realize substantial financial returns from their data monetization strategies. Beyond selecting a strategy, we identified a more critical differentiator for success: data monetization impact. This briefing explores the strategy-specific practices that enable organizations to achieve this impact on strategic business outcomes, providing guidance for leaders seeking to maximize the return on their investments in data initiatives. 

Maximizing Returns from Data Monetization Strategies

Stephanie Woerner reads MIT CISR's March 2025 research briefing, which she co-authored with Peter Weill, Jennifer S. Banner, and James Moore. See the text version and related content at https://cisr.mit.edu/publication/2025_0301_SavvyBoardsUpdate_WeillWoernerBannerMoore

Abstract: In 2019, MIT CISR published findings from our research on the digital savviness of company boards that showed 24 percent of boards were digitally savvy and had associated performance premiums. In 2024, we repeated the 2019 board analysis with current companies and found that having a digitally savvy board based on our original criteria was no longer differentiating. However, updating the criteria to account for newer technologies produced results similar to the original analysis. In this briefing we compare the results of these two studies, share insights from interviews of non-executive board directors, and explore how companies use board committees to help manage their work.

Digitally Savvy Boards: AI Update

Barb Wixom reads MIT CISR's April 2025 research briefing, which she co-authored with Nick van der Meulen and Cynthia Beath. See the text version and related content at https://cisr.mit.edu/publication/2025_0401_DataProductMindset_WixomVanderMeulenBeath.

Abstract: Today, by adopting a product mindset for data, organizations hold people accountable for the payoff of data investments over time. Data assets and data solutions represent two distinct types of “data products.” Organizations can use three sets of product management practices to more effectively generate returns from their data assets and data solutions: practices for satisfying data consumers, practices for setting prices, and practices for sustaining profits. This briefing illustrates these practices using examples from information businesses.

Shifting to a Product Mindset for Data

Stephanie Woerner reads MIT CISR's May 2025 research briefing, which she co-authored with Peter Weill. See the text version and related content at https://cisr.mit.edu/publication/2025_0501_DigitalPlatformDesigns_WoernerWeill.

Abstract: People use the term “digital platform” to mean lots of different things—an internal business capability, a business model, a technology, a business service, or a mindset, among other things. To help executives discuss, design, and manage digital platforms, we studied platform designs. We identified four dominant digital platform designs—platform as a service (PaaS), multisided marketplace, internal platform, and X as a service (XaaS)—and found that companies that effectively managed one or more of the designs had above-average financial performance. In this briefing, we describe the designs and share the financial performance of companies using each design.

Top-Performing Companies Reuse Four Digital Platform Designs

Ina Sebastian reads MIT CISR's June 2025 research briefing, which she co-authored with Stephanie Woerner and Peter Weill. See the text version and related content at https://cisr.mit.edu/publication/2025_0601_ANZInstitutionalPlatformTransformation_SebastianWoernerWeill.

Abstract: As business models become more AI-enabled, strategically designing, evolving, and reusing platforms that reflect a company’s core capabilities is key to driving growth and innovation. This briefing examines the platform transformation of ANZ Institutional, a division of the Australia and New Zealand Banking Group Limited (ANZ). By building robust, scalable internal platforms and connecting them to deliver revenue-generating digital services, ANZ Institutional redefined how it creates and delivers value—doubling its return on equity (ROE) between 2016 and 2024.

Platform-Enabled Business Transformation at ANZ Institutional

Martin Mocker reads MIT CISR's July 2025 research briefing, which he co-authored with Ina Sebastian. See the text version and related content at https://cisr.mit.edu/publication/2025_0701_MonetizingExDPs_MockerSebastian.

Abstract: To gain additional value from their digital platforms, some companies open them to external developers via APIs, thereby creating external developer platforms (ExDPs). Many companies struggle to monetize ExDPs, though. This briefing compares two distinct approaches to monetizing ExDPs: build-on, in which external developers create complementary solutions on top of the company’s platform; and build-in, in which external developers integrate capabilities  from the company’s platform into their own freestanding applications, often combined with data from other companies’ ExDPs. Using case studies of Salesforce and Schneider Electric, this briefing explores the distinct value, requirements, and outcomes of each approach to guide companies in selecting their ExDP monetization strategy.

Two Approaches to Monetizing External Developer Platforms

Stephanie Woerner reads MIT CISR's August 2025 research briefing, which she co-authored with Ina Sebastian, Peter Weill, and Evgeny Káganer. See the text version and related content at https://cisr.mit.edu/publication/2025_0801_EnterpriseAIMaturityUpdate_WoernerSebastianWeillKaganer.

Abstract: Last year, MIT CISR introduced a four-stage enterprise AI maturity framework to help leaders identify how to create value from AI (artificial intelligence) technology. A new MIT CISR survey has found that enterprises today are making significant progress in their AI maturity, with the greatest financial impact seen in the progression from stage 2, where enterprises build pilots and capabilities, to stage 3, where enterprises develop scaled AI ways of working. In this briefing we describe how enterprises mature from piloting AI to scaling it, illustrated by case studies of the Guardian Life Insurance Company of America and Italgas Group.

Grow Enterprise AI Maturity for Bottom-Line Impact

Nick van der Meulen reads MIT CISR's September 2025 research briefing, which he co-authored with Ida Someh, Barb Wixom, and Cynthia Beath. See the text version and related content at https://cisr.mit.edu/publication/2025_0901_DataDemocracy_VanderMeulenSomehWixomBeath.

Abstract: Many organizations fail to realize value from their data investments, with only an average of 28 percent of employees drawing on reusable data assets. This briefing positions as a solution establishing a data democracy: an organizational state where all employees have data access, skills, motivation, and guidance for strategic use. We present a framework showing how specific connecting structures, such as centers of excellence and cross-functional teams, can amplify democratization practices. By intentionally designing this organizational state, leaders can increase the use of their organization’s available data assets, achieve greater employee empowerment, and maximize financial returns on their data investments.

Mobilize Your Data Democracy

Ina Sebastian reads MIT CISR's October 2025 research briefing, which she co-authored with Peter Weill, Stephanie Woerner, and Gayan Benedict. See the text version and related content at https://cisr.mit.edu/publication/2025_1001_BizModelsAIEra_WeillSebastianWoernerBenedict.

Abstract: MIT CISR anticipates that rapid advancements in AI will drive business model evolution over the next decade, and we propose that business models in the AI era will become increasingly outcome oriented and enabled by autonomous AI. In this briefing, we draw on our research from 2013 to 2025 involving 2,378 companies to describe how digital business models have developed over the last twelve years, and introduce a framework for AI-driven, real-time business models. We illustrate how companies have begun exploring these new business models with a case study of One New Zealand.

Business Models in the AI Era

Stephanie Woerner reads MIT CISR's January 2021 research briefing, which she co-authored with Peter Weill and Andrea Patricia Diaz Baquero. See the text version and related content at https://cisr.mit.edu/publication/2021_0101_HelloDomains_WeillWoernerDiaz.

Abstract: For decades, companies have thought of themselves as operating in industries such as banking, retail, and energy. In contrast, most customers seek to fulfill specific needs—business customers might aim to manage their energy consumption, and consumers might navigate getting an education. We call these different customer problems and opportunities domains. Digital technologies, and new business models such as ecosystems, provide an opportunity to rethink how to solve your customers’ needs in each of their important domains. In this briefing, we share our first efforts at identifying the key domains, scope the size of the opportunity, and provide examples.

Hello Domains, Goodbye Industries

Stephanie Woerner reads MIT CISR's February 2021 research briefing, which she co-authored with Peter Weill. See the text version and related content at https://cisr.mit.edu/publication/2021_0201_PathwaysUpdate_WoernerWeill.

Abstract: In 2017 we first observed how almost every big old company was on a digital transformation journey, many without a playbook. We described the goal of business transformation—to become Future Ready—and four pathways we identified in our research that companies can follow to outperform their industry. In understanding how companies successfully get to Future Ready, we pinpointed four significant, disruptive changes common to all of the pathways, which we call “explosions.” In this briefing we update the research and highlight what we have learned over the last four years.

Update on the Four Pathways to Future Ready

A research center at the MIT Sloan School of Management, MIT CISR helps executives meet the challenge of leading dynamic, global, and information-intensive organizations.

Building AI Explanation Capability for the AI-Powered Organization

MIT CISR

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