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Research Briefing

Unlocking Value as a Modular Producer: Three Key Mechanisms

Established companies can leverage three key mechanisms to develop revenue-generating modular producer offerings.
Abstract

An MIT CISR survey found that companies with a modular producer business model performed better relative to their industry than companies with an omnichannel or supplier business model. Given these benefits, we believe that in the next five years many large traditional companies will experiment with adding modular producer offerings to complement their established business models. This research briefing describes how two financial services companies, Munich Re and WeBank, have applied three key mechanisms—an agile organization, modular systems, and evidence-based decision making—to develop modular producer offerings. 

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MIT CISR research has shown that companies have a choice of four digital business models to create value and make money in the digital era.[foot]Peter Weill and Stephanie L. Woerner, What’s Your Digital Business Model?: Six Questions to Help You Build the Next-Generation Enterprise (Boston: Harvard Business Review Press, 2018), https://cisr.mit.edu/publication/whats-your-digital-business-model.[/foot] Companies that choose a modular producer business model[foot]S. L. Woerner, I. M., Sebastian, and P. Weill, “All Companies Need a Modular Producer Strategy,” MIT Sloan CISR Research Briefing, Vol. XIX, No. 2, February 2019, https://cisr.mit.edu/publication/2019_0201_ModularProducer_WoernerSebastianWeill. [/foot] provide innovative digitized products to the customers of ecosystem drivers and omnichannel companies—a digital strategy to grow reach via partners.[foot]I. M. Sebastian, P. Weill, and S. L. Woerner, “Three Strategies to Grow via Digital Partnering,” MIT Sloan CISR Research Briefing, Vol. XX, No. 5, May 2020, https://cisr.mit.edu/publication/2020_0501_DigitalPartneringStrategies_SebastianWeillWoerner.[/foot]

In a 2019 survey[foot]MIT CISR 2019 Top Management Teams and Transformation survey, N=1,311.[/foot] we found that companies with a modular producer business model performed better relative to their industry than companies with an omnichannel or supplier business model. In financial services, for example, modular producers had an average revenue growth of 14.9 percentage points and an average net margin of 9.6 percentage points above industry average—a significant premium.[foot]The quantitative analysis is based on the MIT CISR 2019 Top Management Teams and Transformation survey, N=1,311; financial services companies N=277. Financial services companies categorized based on dominant business model: ecosystem drivers 16%, modular producers 11%, omnichannel 12%, suppliers 61%. Financial services revenue growth percentage points above/below industry average: ecosystem drivers +24.3, omnichannel -9.3, suppliers -11.1; net profit margin: ecosystem drivers +16.6, omnichannel -2.1, suppliers -7.4. Net profit margin and revenue growth are compared to industry and are 5% mean trimmed to eliminate outliers. Self-reported net profit margin/revenue growth correlate significantly with actual profit margin/revenue growth at the p<.01 level. [/foot] Given these benefits, we believe that in the next five years many large traditional companies in financial services and beyond will experiment with adding modular producer offerings to complement their already successful established business models.

Three Mechanisms to Develop Modular Producer Offerings

In our interviews,[foot]In 2020–2021, we conducted forty interviews with executives in companies with ecosystem business models on value creation with partners.[/foot] companies described three mechanisms (i.e., sets of capabilities and practices) they found were crucial to enabling speed and flexibility in developing offerings for new partners, thereby mitigating risks such as not engaging directly with customers and depending on a partner to scale a product within an ecosystem:

  • An agile organization: Companies created agile structures based on business components. Leaders specified critical outcomes and responsibility and let agile teams innovate to drive speed.[foot]J. W. Ross, C. M. Beath, and R. R. Nelson, “The Digital Operating Model: Building a Componentized Organization,” MIT Sloan CISR Research Briefing, Vol. XX, No. 6, June 2020, https://cisr.mit.edu/publication/2020_0601_BuildingComponentizedOrganization_RossBeathNelson.[/foot]
  • Modular systems: These shared systems enabled teams to combine and recombine technology and data components to create new digital offerings for partners, and to generate value from operations for the company, decreasing time and cost.[foot]I. M. Sebastian, P. Weill, and S. L. Woerner, “Three Types of Value Drive Performance in Digital Business,” MIT Sloan CISR Research Briefing, Vol. XXI, No. 3, March 2021, https://cisr.mit.edu/publication/2021_0301_ValueinDigitalBusiness_SebastianWeillWoerner.[/foot]
  • Evidence-based decision making: Teams based decisions regarding partners and their partners’ customers on evidence—produced via sophisticated data and analytics capabilities—which helped improve products and customer experience.

Established companies pursuing new modular producer offerings have an advantage: they can leverage their existing business models—such as by drawing on established customer knowledge—to strengthen new offerings. Companies, particularly new ones, that pursue only modular producer models typically have little knowledge of the customers they serve, as offerings are delivered via partners’ platforms.

This research briefing describes how two financial services companies, Munich Re and WeBank, have applied the three mechanisms to create modular producer offerings. Munich Re built such offerings as part of the company’s digital transformation; WeBank has developed them from the company’s early days. Both companies have benefited from knowledge of customers to strengthen evidence-based decision making. Munich Re, a supplier of reinsurance to primary insurance companies (B2B), knows its customers well—which was a good foundation for new B2B2C modular producer offerings for these companies. WeBank was established by a powerful ecosystem driver, Tencent, and can draw on data models developed for use in WeBank’s other products in Tencent’s ecosystem.[foot]E. Loufield, D. Ferenzy, and T. Johnson, “Accelerating Financial Inclusion with New Data,” a joint report from the Center for Financial Inclusion at Accion and the Institute of International Finance, May 2018, page 14, https://www.iif.com/portals/0/Files/private/finewdata_cfi.pdf.[/foot] While the regulatory environments and economic contexts in which WeBank and Munich Re operate differ, each companies’ leverage of the three mechanisms to create modular producer offerings provides valuable insights.

Munich Re Develops its B2B2C Offerings

In 2016 the Munich, Germany-based global reinsurance company Munich Re[foot]This briefing case draws from N. O. Fonstad, and M. Mocker, “Munich Re: Building a Foundation for Innovative Offerings,” MIT Sloan CISR Working Paper No. 445, August 2020, https://cisr.mit.edu/publication/MIT_CISRwp445_MunichRe_FonstadMocker.[/foot] commenced a digital transformation to create new revenue-generating digital offerings, including building a foundation to provide dedicated expertise and a digital platform of shared services. By the end of 2019, more than seventy of the company’s innovation initiatives relied on this foundation, including those developing new B2B2C modular producer offerings. Munich Re was developing these offerings to help insurance companies, brokers, and other businesses provide better customer experience and increase revenues via improved rate-quote-bind insurance underwriting processes. For example, modular producer offerings MIRA Digital Suite and Realytix enabled automated risk assessment, and resulted in a faster insurance process—in the case of Realytix, reducing the time required from multiple days to ten minutes. Munich Re benefited from an increase in customers, and generated revenue via service fees and larger reinsurance contracts.

Munich Re created an agile organization to support the company’s innovation initiatives. A new Innovation Lab treated each initiative as a start-up, providing initiatives with staged funding, innovation processes, and workspace. To support the B2B2C innovation teams, in 2018 the IT organization created a new unit, Business Technology, to provide specialized talent such as initiative chief technology officers, developers, and security compliance experts. Between 2017 and 2019 Business Technology reduced the average length of projects by twenty to thirty percent, with some projects launched in as little as twelve weeks.

Business Technology created a modular system, a digital platform of shared services named Excite, to help the innovation teams simplify and speed up product development for modular producer offerings. As of 2020, Excite offered more than thirty reusable components (e.g., Submit Claim, Insurance Fraud Detection, Data Pipeline Services) to more than seventy innovation initiatives. The components were organized in three layers: digital front-end services, insurance services, and data- and analytics-related services supporting evidence-based decisions (such as for portfolio optimization).

Munich Re leveraged knowledge of its business customers for evidence-based decision making during development of new B2B2C offerings. In the initial stage of the innovation process, the company engaged with customers to understand how an opportunity for a new B2B2C offering could improve their customers' experience and generate revenue. For example, MIRA Digital Suite was developed to simplify insurance companies’ risk assessment regarding their customers with chronic conditions. The Excite team also used an evidence-based approach to grow the Excite platform, adding components gradually and learning what the innovation initiatives needed, and selling this as managed services to the initiatives. The Excite team measured success with faster time to market, improved customer experience, revenue growth, and cost savings. In 2020, Munich Re was evaluating the opportunity of extending its modular producer model to offer Excite as a revenue-generating platform.

WeBank Develops its Auto Loan Offering

The Shenzhen, China based digital-only bank WeBank,[foot]This case study is based on two interviews one of the authors conducted with executives at WeBank in 2021 and public sources.[/foot] the online banking affiliate of Tencent Holdings Ltd., is the first privately-owned bank in China, established in 2014.[foot]In 2020, WeBank served 270 million retail customers and 1.88 million small and micro enterprise customers; see “2020 Annual Report,” WeBank, April 30, 2021, https://stdd.webankcdn.net/epss/upload/www/pdf/annual_report_2020.pdf. Tencent owns a 30 percent stake in WeBank. Rick Carew and Juro Osawa, “Tencent Affiliate WeBank Looks to Raise Around $1 Billion,” The Wall Street Journal, November 18, 2015, https://www.wsj.com/articles/tencent-affiliate-webank-looks-to-raise-around-1-billion-1447836592.[/foot] Tencent Holdings is also owner of the WeChat super app.[foot]A super app is a digital ecosystem that bundles multiple functionalities into one platform offering a range of services and using one payments wallet at the core. Super apps are prevalent in Asia and Latin America.[/foot] WeBank provides the consumer loan product Weilidai, and payment services from and to bank accounts as part of Weixin Wallet within Weixin, the WeChat product for the Chinese market.[foot]WeChat and Weixin are distinct but interoperable apps; WeBank provides services to the Weixin ecosystem (but not the WeChat ecosystem) as part of Weixin Wallet, the mobile wallet service within the Weixin app. Weixin and WeChat’s monthly active users combined total 1.25 billion; see “Tencent Announces 2021 Second Quarter and Interim Results,” Tencent, August 2021, https://static.www.tencent.com/uploads/2021/08/18/236f212d95d7402bacdbdf904a6b2b65.pdf. For more information on super app wallets, see Jixun Foo, “The Key to Super App Success Is a Super Wallet,” Fortune, October 8, 2021, https://fortune.com/2021/10/08/the-key-to-superapp-success-is-a-super-wallet/. [/foot] That WeBank established key mechanisms—an agile organization, modular systems, and evidence-based decision making—at the company enables it to experiment with also distributing loans in other ways. For example, WeBank offers an SME loan product in its app and a consumer auto loan product on partners’ platforms.

The auto loan product Weichedai (“micro car loan” in Mandarin) is a modular producer product. WeBank provides loan options to customers of its partners—online used car retailers—through the partners’ mobile apps or websites. WeBank partners on Weichedai with the majority of major online used car retailers in China (e.g., nationwide online used car dealer Uxin Group[foot]“Company Profile,” Uxin Group, https://ir.xin.com/company-profile.[/foot]) and has grown to cover 31 provinces and 660 cities. The product offers easy online application, a quick automated approval process, and flexible repayment. The Weichedai product teams’ core strength is their ability to deliver the product via different ecosystem partners at high speed and low cost, leveraging the three key mechanisms as follows.

WeBank is an agile organization. Weichedai product teams include embedded business, technical, and compliance professionals. These teams execute projects from the beginning of a partnership discussion through implementation, checking in with cross-functional enterprise teams such as compliance, IT security, data governance, and financial planning at key points. With this process design, the teams have in some cases reduced the time to launch embedded loan products from two months to as little as ten days.

WeBank product teams leverage modular systems based on a micro-core design. Micro cores—i.e., functional business blocks—are modules that can be bundled together via APIs when developing a new product. The Weichedai auto loan product combines modules for loan application, eKYC (electronic Know Your Customer), and fraud check with data and other components.

Evidence-based decision making is pervasive at WeBank. The company uses more than six hundred in-house data models, including those developed for use in its consumer lending product Weilidai in the Weixin ecosystem, to make evidence-based decisions on loans in a fully automated evaluation process with over one thousand variables. Weichedai product teams continuously test new features in limited releases and leverage an enterprise-wide big data platform that provides analytics tools for product performance, customer acquisition, user experience, and risk management. The Weichedai teams work with potential partners, evaluating their daily traffic, online and offline operations (producing different types of fraud risks), data collection methods, and the types of data available for risk modeling to determine if they are a good fit.

Synchronization of the Three Mechanisms

At Munich Re and WeBank, all three mechanisms are crucial to creating innovative modular producer offerings that can plug into any ecosystem. Agile teams depend on readily available modules and data to adapt, innovate, and scale new modular producer offerings. In a large traditional company, developing the three mechanisms and synchronizing them typically requires a digital transformation. But many companies have efforts well underway creating these mechanisms, positioning them to experiment with modular producer offerings. We urge these companies to explore how they can build on their already successful established business models to unlock new value as a modular producer.

© 2021 MIT Sloan Center for Information Systems Research, Sebastian and Fonstad. MIT CISR Research Briefings are published monthly to update the center's patrons and sponsors on current research projects.

About the Authors

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Nils O. Fonstad, Research Scientist, MIT Sloan Center for Information Systems Research (CISR)

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