THREE DIGITAL BUSINESS MODELS

Digital business models are obviously red-hot these days. Companies that built on them have grown massively and created enormous value. Apple doubled its market capitalization from 1 trillion to 2 trillion in just two year. Amazon made Jeff Bezos the richest man in the world. And if you look at the largest companies by value in the world today, nearly all of them have leveraged digital business models. Accenture shows that eight of the largest ten companies in the world today have been built on platform-business models, while only two companies were built on these business models in 2010 (Collins 2021). The World Economic Forum estimates that "70% of new value created in the global economy over the next decade will be based on digitally enabled platform business models."[1]

Lurking behind this enormous growth is a massive change and transformation of how value is created, captured and realized today and in the future (Collis 2021). We are still at the early stages of the Fourth Industrial Revolution where existing technologies like the internet and new emerging technologies mature at the same time and merge with humans’ physical lives. The possibilities of billions of connections, people connected by mobile devices, companies connected to companies with unprecedented processing power, storage capacity, and access to knowledge, are unlimited. Emerging technology breakthroughs in fields such as artificial intelligence, the Internet of Things, and quantum computing to mention a few create a massive multiplier that largely shifts value creation for companies from the supply side to the demand side (Schwab 2016).

Until today, value has been created by companies and brands on the supply side through performing activities differently along the value chain that create economies of scale through production efficiencies, as quantities produced increased, the unit cost of creating the product or service decreased. Configuration of the unique activities of the firm and exploiting these economies of scale created what is known as a sustainable competitive advantage. The diminishing return of this traditional form of value creation has been already called out by numerous thought leaders, most notably Rita McGrath (2013).

Today, new value and hence competitive advantage is also being created on the demand side, so-called demand side economies of scale. This is where the new technologies have a massive impact. Value creation is driven by efficiencies in networks of companies such as value networks, platforms or ecosystems, or networks among people like social or business networks, demand aggregation, software development and other phenomena that make bigger networks more valuable. They create three types of important demand-side effects: network effects, learning effects and viral effects (Joachimsthaler 2020). The value from these demand-side effects can be captured through digital business models which have become the most dominant form of driving new innovation and growth today.[2]

One type of digital business models are platform-based business models (Parker, Van Alstyne and Choudary 2016). These models enable interactions or exchanges between customers and/or third parties. Airbnb, Uber and GAFA or Google, Apple, Facebook and Amazon are often mentioned over and again. An example is Salesforce, the company offers the AppExchange marketplace that allows software developers to build and sell its software to Salesforce customers. There are more than one million developers that offer over 2,500 apps to its customers. Another example is Kloeckner Metal which offers a set of digital products and services, called Kloeckner Connect that streamline its supply chain of for example delivering hot-rolled steel to build a large Tesla plant in the Nevada desert or around Berlin, Germany. It also offers a marketplace of 30 third-party vendors offering complementary products.

I will describe several digital business models. Based on my analyses of several hundreds of applications of these models, I come to the conclusion that there are four factors that makes them successful. First is, there needs to be a clear identification of the problem they solve, the needs and challenges or jobs of customers, consumer or people that they solve, the solutions they enable, facilitate or improve or eliminate. Second is, the application needs to prove out the technology and the business model. This is about designing the business model and how it enables interactions that become the source of value creation. Third is, how to build the digital business model. This isn’t about technology anymore, it is about creating interactions between consumers, brands or participants, partners and stakeholders. Fourth and finally, there needs to be a mechanism, policy or governance structure that maximizes the interactions across all major participants and share value exchange so that value is created, captured, realized and also shared out fairly.

While digital business models are hugely successful, it shouldn’t surprise you that most digital business models also fairly often fail.[3] One major reason for the failure is the lack of understanding of how to brand digital business models. Hence, I will focus on this issue in this paper. THREE DIGITAL BUSINESS MODELS

Let’s dive into the new digital business models with some practical examples. I categorize them into three classes or types: digital interface models, platform ecosystems, and interaction fields (Table 1). They represent three new ways of creating value for customers and other stakeholders by applying digital technologies. The Digital Interface Model The first model, the digital interface model, is pursued by companies that see opportunities to improve or simplify the way they interact with consumers or customers and create value, either through optimization along the value chain, streamlining their customers’ business processes, or removing frictions along the customer journey (Table 1). Typically, this involves creating more meaningful or more valuable direct interactions with customers or other stakeholders. Dominos Pizza is a great illustration of success with this model. It always stood for pizza delivery. Remember the slogan: “In 30 minutes or it is free”? Since the 1960s, the Michigan company optimized its operations and business processes, delivering on the promise of speed and convenience and a relatively simple and narrow set of needs of consumers: not the best pizza, not the most innovation around food but speed and convenience. Digital technology was a godsend for the company in this pursuit, and unlike its competitors, Dominos identified this problem and opportunity early on. Since the mid 2000s, channels or touchpoints of ordering digitally has increased steadily from desktop to mobile to texts with a pizza emoji or voice via Alexa. Dominos made it easier to order, with a good example being ‘zero click ordering’. All you need to do is open the app, and within 10 seconds your pizza is ordered (Ip and Loten 2020). Digital ordering importantly helps to track interactions with consumers and hence can have an impact on every aspect of operations, better understanding customers, better and different marketing, optimizing the franchisee system and enabling franchisees and delivery drivers to make money, while also optimizing speed and convenience of delivery or pickup for consumers. There is a huge volume of interactions that Dominos consistently learns from. It serves up to 3 million pizzas to 1 million customers a day. This changes how it markets and builds brands and how it is enabling, streamlining, and simplifying everything from internal operations to customer interfaces. Dominos has experienced steady growth of customers, and even more growth of its stock price, beating even Apple, Amazon, and Google. Only Netflix’s stock performed better (Del Rey and Molla 2018).

A digital interface model even can alter the entire brand promise and value proposition to consumers and create the next category disruptors. Roman and Franc Arnold started in 1985 with importing and reselling Italian high-end performance bike parts in Germany as Radsport Arnold GmbH. They rebranded to Canyon Bicycles in 2001 when they started manufacturing their own bikes, sold them online and delivered directly to customers. So, long before direct-to-consumer or DTC became popular in selling eyewear or mattresses or insurance, these brothers practiced it and perfected a model that made huge waves in the cycling industry. It offers high-end performance bikes directly at discount prices. Technology enables this value proposition at massive scale with sales in over 100 countries.

The digital interface that enabled Canyon’s success isn’t just a website, a cool design and a direct marketing model to acquire new customers. It also is the Perfect Position System (PPS) that enables mass customization or personalization, the perfect fit for the body, and the perfect frame size, and best combination of components. PPS isn’t just a typical configurator like those found on a car website, it is a continuous learning system of interactions that enables and changes many of the Canyon key business processes, optimizes the digital supply chain, and enables the new customer journey. No need to visit a bike shop, Canyon bikes are delivered directly to your home, and can be assembled as easily as an Ikea table, despite the high level of precision typically needed in assembly and fine-tuning of a high-performance bike for optimal rider comfort and achievement. Canyon and others who followed them have changed the industry, the role of the all-important middlemen especially the bike shops, and how value is created, and shared with consumers.

Ben & Jerry’s illustrates the same digital interface model, and shows that even manufacturers in the slow-to-adopt-digital traditional consumer packaged goods industry can leverage this type of business model and sell pints of ice-cream. It solves an incredibly simply need for a treat, fun and entertainment. It ships ice cream directly to your door ($9 shipping for order $99+), or gift packs for baby showers for example, or bundles of brands for certain moments of consumers’ daily life. Others like Pepsi via Snacks.com or PantryShop.com or Kraft Heinz via Heinz to Home further experiment with technology, logistics, marketing, service (Biscotti 2020).

A B2B example is Kloeckner Metal, a medium-sized steel metal trader that operates in an incredibly difficult trading environment: oversupply of steel due to imports from Asia, and enormous price pressure. The industry is old-fashioned, and not very efficient with long lead times, high inventory levels and incorrect deliveries.

In an effort to streamline its supply chain, Kloeckner created a range of digital products and services, collectively known as Kloeckner Connect. One is a tool called Part Manager which allows customers to make orders from any device, check on past orders, see what’s available in stock, and look through the entire Kloeckner offering catalog. Two other tools are called Direct and EDI. They add various functionalities that help customers to automate key processes at the interface with Kloeckner such as inventory tracking, writing purchase orders and paying invoices.

These tools, most of them built using off-the-shelf software, had a huge and almost immediate impact. Kloeckner can now interact more quickly and transparently with customers. They can learn better about their needs and goals, which helped to reduce inventory levels, which in turn cut costs and improved margins (Gunther McGrath and McManus 2020).

One up from streamlining order processing, Kloeckner launched an ecommerce platform for its own customers, which was followed by a third-party marketplace, which included a number of 30 third-party vendors offering complementary products. Other B2B examples of this strategy can be found elsewhere (Hagui and Wright 2021).

The net effect of optimizing, streamlining and removing of frictions along the supply chain or customer’s business processes leads to more frequent, and more real-time interactions with customers. From there, it is possible to expand to new customers, or new products and services.

The digital interface model is merely a transitory model. It primarily enables data-enabled learning effects which attract new customers which in turn provides even more data that enables more learning through the application of analytics and machine learning or AI technology. In the process, it significantly changes the way a company or brand goes to market, from marketing, sales to customer service. The Platform Ecosystem Model The second model, the platform ecosystem model, is today very popular and often discussed (Parker, Van Alstyne and Choudary 2016). This too is just transitory because it does not optimize interactions among platform or ecosystem participants. As the name suggests, ecosystems are networks of partners or participants that provide a broader and well-defined value proposition or brand promise, solving more complex and adjacent customer needs or wants. The most often used example is Airbnb. At its core, Airbnb matches hosts or anyone that has a spare room available with travelers or guests. There are a number of services to address consumer needs that are adjacent to accommodation from cleaning, property management, to financing services. Airbnb also offers experiences, adventures, and restaurant bookings by ecosystem partners. Today and just over 11 years since its founding, it has over 150 million users or renters with over seven million rooms listed in over 100,000 cities, across 220 countries and regions worldwide. Airbnb is also worth over $100 billion.

How did Airbnb do it in just a decade? It is simple. It created a new market, the home-sharing market. What is difficult is, it made it easy and simple to rent out a spare room in your home, and it build a platform and brand that consumer or renters started to trust for a stay in a stranger’s home. The early days of Airbnb, though weren’t easy at all. It needed to convince homeowners to list their properties on Airbnb instead of Craig’s List for example. As Airbnb got the listings, it searched for renters on Facebook to match up. Facebook provided additional information about the renters which helped foster a sense of trust with owners. As its its user base grew, it benefited from two major effects of digital platform businesses: first is the network effect, and second is the power of marginal cost. Network effects describe how the consumer value of a product changes when the number of consumers of the same product or complementary products changes (Drewel et al 2020). The more properties Airbnb lists on its website, the more valuable the site becomes for renters and the more renters there are, the more valuable Airbnb becomes for home owners. Airbnb also benefits from the fact that digital platforms benefit from the marginal costs that trend toward zero. That is, for Airbnb to list an additional property, its costs are minimal, while an traditional hotel like Marriott or Hyatt needs to invest in land, architecture, construction and building out of new rooms, and services, and more.

The Airbnb story plays out right now again in the fitness market. Peloton is creating a market for at-home fitness and exercise. Unlike Airbnb, though, it got its start with a premium and quality product, the stationary bike. Today, Peloton essentially brings studio fitness into the home. Because its bikes come digitally equipped with touch screens and sensors, it can deliver workouts to its community of over five million members, led by some world’s most elite instructors such as for example Cody Rigsby, a former dancer and beloved Peloton superstar or the Uber popular fitness buff Jess Sims in an Uber engaging way. Unlike Airbnb, this also creates direct network effects on both sides of the platform, when members interact with each other and compete, or when instructors compete against each other for members. What both Airbnb and Peloton have in common is that every single core interaction is measured, captured and analyzed which helps Airbnb and Peloton to learn an enormous amount about how to increase host performance or instructor performance, and how to increase Airbnb member experience or Peloton rider experience. Ecosystem partners are merely nodes in a network that is powered by data, analytics and technology but the interactions are not reciprocal. Ecosystem partners are mostly suppliers or contributors to the Peloton value proposition. That is, instructors or hosts or other ecosystem participants that create value have a lot less access to the data, the volume of interactions, than Airbnb or Peloton has. This also means that the value creation through interactions isn’t shared equally with ecosystem partners.

An example of an existing company or incumbent that transformed into a platform ecosystem is Intuit who evolved from a software company toward a platform ecosystem that provides seven million small businesses, one million self-employed individuals, and 44 million consumers with a range of financial and business management solutions including taxes, payroll, merchant payment processing, and financing. The products are QB Cash, QB Commerce, Payments & Capital, and Payroll & Time Tracking. One day it realized that it isn’t really about the incredible software like QuickBooks or TurboTax, the products that solve the problem of consumers, but it is more importantly about the services such as accounting services that solves consumers’ financial or tax challenges, and lets people get on with their lives, gives them time back, etc. So, it built a platform ecosystem that consists of developers, accountants, called ProAdvisors, and customers. QuickBooks Live is an open platform that matches accountants with small business customers. Intuit ensures that accountants are well-trained to service the needs of small businesses. Intuit also develops software that improves accountant’s workflows. It also manages a large number of developers that built applications for the QuickBooks platform. These include PayPal, Shopify, Square, and Bill.com. Its app store offers more than a thousand of third-party apps.

Intuit benefits greatly from network effects, more accountants attract more small businesses to QuickBooks. The more experience the independent accountants gain with QuickBooks, the more likely they recommend QuickBooks, and small businesses buy its software. A larger pool of small businesses in turn attracts more accountants, and the less likely accountants use other software. Intuit also has enormous opportunities to expand serving adjacent or complementary needs of small businesses related to whatever a business needs to grow and scale. It could offer insurance products, or additional HR services in competition with ADP, and so much more. It could easily embed additional financial services products and offer banking as a service by expanding its relationship with Stripe Treasury or Stripe Capital, for example. It could drive new innovation and growth for small business larger than 100 employees beyond QuickBooks Advanced which offers full-service accounting capabilities. It could provide access to more providers of services to small businesses. This would make a perfect case study for the theory of the inverted firm, where innovation takes place in the network rather than within the traditional organizational boundaries of the firm (Parker, Van Alstyne, and Jiang 2017). Alibaba B2B Marketplace and Network Effects A very different platform ecosystem is the B2B marketplace Alibaba. It is the largest B2B wholesale platform in the world, a two-sided marketplace that connects over 165,000 suppliers to over 10 million buyers in over 190 countries and regions. It provides all major functionalities of a marketplace on both sides, to source parts to produce the final goods, buy finished products to resell or to find items needed to operate the business.[4] These include digital tools such as CRM, AliSourcePro for lead generation, market and analytics tools, and comprehensive order management. Through an integrated, and highly interdependent set of entities or participants, it offers additional services from financing, to marketing (Alimama) to logistics (Cainiao). Their purpose or problem statement that they solve is to deliver on the original Alibaba mission from its founding in 1999: “To make it easy to do business anywhere.” Then, there is the eWTP, the global trade network. It has built hubs and free-trade zones in Rwanda, Ethiopia, Belgium or Malaysia, and two cities in China that enables small-to-medium-sized businesses to participate in global commerce, since 2016.

The success of Alibaba B2B marketplace comes from how it configured the business model in terms of the interactions, architecture and governance rules or policies (Van Alstyne 2019). On a daily basis, Alibaba receives over 300,000 inquiries from growing base of buyers and sellers. This creates an enormous amount of rich data and exchanges, and volumes of interactions which powers the network effect: the value for buyers and sellers increases as more companies or people buy or sell on Alibaba. Unlike Amazon which uses the data to gain insights into what products it can offer under an Amazon private label, Alibaba does not compete with its customers. It focuses intensively on interaction velocity between sellers and buyers themselves to gain deeper knowledge and insights toward its goal of making it easy to do business.[5] It removes frictions by developing industry-specific or vertical tools, or by providing value-added services that are shared which makes the platform more valuable to both sellers and buyers, instead of becoming merely a means to disrupt existing businesses or incumbents.

Platform ecosystems are often viewed as open platforms that enable others to become ecosystem partners. In reality, though, the orchestrator of the platform typically exerts enormous control in terms of who can participate in value creation, how value is created, captured and shared if at all, as is well known in the Apple and Amazon ecosystems, for example (Danzinger 2021). Platform ecosystems aren’t really about collaboration. They are about competition and disruption. Platform ecosystem also serve relatively well-defined needs and challenges that the platform orchestrators deem of value and worthy to create economic value for themselves. And as it has been shown in every example, the value that is created through interactions, captured by data and other value exchanges, isn’t shared among ecosystem partners equally. Whether it is the case of Airbnb or Intuit or Peloton the value is captured primarily by the orchestrator of the platform ecosystem. The Interaction Field Model The third model, the interaction field model, has emerged in recent years across a range of industries from agriculture, healthcare, retail, automotive and to consumer product categories such as cosmetics or petfood.[6] This model is the next evolution from platform ecosystems and solves for some of the ills of the digital interface model and the platform ecosystem model (Joachimsthaler 2020). Unlike platform ecosystems that solve fairly narrow and complementary needs of customers or that remove major frictions on two or more sides of a marketplace, the interaction field model solves for broad, new needs, rising customer expectations, and complex challenges for customers, but also the industry or even society at large. These broader market needs or challenges are often, latent or unarticulated, unstructured and not yet well-defined.

Interaction field companies are about collaboration, participation and engagement, not just about competition and disruption.

To illustrate this with a familiar example, consider Tesla. This company isn’t just about selling electric cars or solving for the well-defined needs of car ownership to jobs to be done such as commuting to work or taking kids to soccer training during weekends, while minimizing CO2 emissions. This alone would be a massive undertaking as a startup company that also challenges the automobile incumbency because success here requires building enormous capabilities along the automotive manufacturing and supply chain, including orchestrating a well-functioning ecosystem of suppliers of components such as for example batteries that are provided by Panasonic. Yet, Tesla’s aspiration is much bigger, beyond even car ownership, solving for large societal challenges like CO2 emissions, making the world less dependent on fossil fuel, or industry-wide challenges like reducing the incidence of highway deaths or specific consumer challenges such as reducing the costs of car ownership.[7] In short, Tesla enables new mobility for consumers while addressing some of the most intractable challenges of multiple industries, particularly the automotive, consumer electronics and energy industries.

A second major aspect of interaction field models is that they solve unique, unarticulated or latent and complex challenges and customer or societal needs. This requires often multiple platform ecosystems that are empowered by interactions and that deeply integrate into the workflows or daily life of consumers. Consider again Tesla as a simple example. Tesla offers solar panels for your home and a Powerpack battery for your garage so that you can generate and store energy for all your needs (your home or your car), or sell excess energy back to the grid. It is unlikely that consumer ever thought of generating their own electricity and making a business of selling energy back to the grid. This is what I mean by unarticulated consumer needs.

Tesla also powers a car-sharing platform ecosystem. It offers the Tesla network that allows you to make your Tesla car available to other drivers, when you don’t need it. And it builds a charging station network so that you can drive any distance with Tesla cars (Bhargava, Boehm, and Parker 2021). Moreover, any mile you drive with a Tesla creates an enormously valuable record of data because Tesla’s have more sensors on their cars than any other car on the road, which is uploaded to the cloud, and analyzed with the objective to improve the Autopilot which enables semi-autonomous driving, and hence the prospect of significantly lowering traffic accidents, and related societal hardships and pains.

Interaction field models then have a very different organizing structure than the previous two models. The interactions and data exchanges in the nucleus (Tesla owners sharing driving data or excess energy from solar panels) typically feed multiple but different platforms and ecosystems (charging stations, the electrical grid, the Zipcar-like car sharing service, Tesla Owner Clubs, etc.) that are wide open for all participants and that serve a broad range of diverse needs or requirements. Because these interactions aren’t just limited to ecosystem partners, the interaction field model solves for many more market inefficiencies than platform ecosystems. An example is Ant Group which is the largest fintech company in the world. Ant Group: An Open But Tightly Interlocking System At the core of Ant Group is the payment service Alipay which was started by Alibaba in 2003 as a means to provide a secure way of handling online payments via some sort of escrow service.[8] Alipay became hugely successful serving over 1.3 billion consumers (up from 450 million in 2016), and 80 million small businesses (Tudor-Ackroyd and Bray 2020). Alipay powers several different financial services platform ecosystems such as lending, wealth management, and even health insurance.

Consider for example its lending business division called CreditTech which operates multiple platform ecosystems and products, Huabei and Jiebei which are credit products for consumers, and MYBANK which focuses on small to medium-sized businesses. It started as Alibaba’s Microloans business in 2010, when traditional banks in China used to loan to only large businesses in the millions of dollars. Most Chinese small businesses could not afford to borrow above the minimum of one-million-dollar loans, requiring a credit history and adequate documentation. Most Chinese businesses would have had a difficult time to qualify. The same challenges that small business faces, also exist for consumers who lack a credit history, with only a small percentage of Chinese carrying credit cards.

Ant solved that by building the microloan business (lending below $160,000) that is underwritten by partner banks. Today, the business involves over 100 banks and trust companies and a larger network of market makers that enable this business to process ever smaller loans, as small as $50 dollars in less time than it takes to summon an Uber car in NYC. Ant uses algorithms with more than 3,000 variables powered by AI and machine learning technologies (Zeng 2018). It calls the model “3-1-0”: fill out the application in less than 3 minutes, obtain approval in 1 second, with zero manual intervention (Ant Group 2020). Its success can be attributed to a decision in 2012 when it merged its Microloans business with Alipay to form Ant Group. This gave Ant’s loan division access to the rich and massive data it gathered through Alipay high-volume interactions, and its other businesses. As Ant’s algorithms improved and as the volume of interactions increased, and as the quality of the data exchanges also increased through enormous learning effects, it built a virtuous and self-reinforcing cycle of expanding its customer base of loan takers, which make its algorithms even more accurate, which brought in even more loan takers, thus expanding its consumer base to loans as small as $50, approved in seconds. Today, Ant makes more money on loans than on Alipay transactions. Imagine this with a platform ecosystem like Airbnb, it would mean, Airbnb makes more money on the cleaning services or property management than on matching supply and demand of accommodations on its platform. Beyond the loan products, Ant further expanded into a broader range of services.

Two examples are the platform ecosystems for its wealth management services, Ant Fortune, and the healthcare plan Xiang Hu Bao. Ant Fortune’s most well-known product is the Yu’e Bao, which translates into: left-over balance. Ant Fortune’s goal though is not a product push. The overarching goal of the platform is to allow financial services to work directly with customers, provide content, and to form an online community to discuss wealth management options (Wei 2017). Ant initially struck a joint venture with Vanguard to offer highly customized services for investors based on their investment objectives, time horizon, and risk preferences. Today, all Chinese mutual funds managers are on the platform which helps Ant, like with lending, to extend services to smaller business investors essentially democratizing wealth management.

Ant has become a tightly interlocking and self-perpetuating system of traditional businesses, platforms and digital ecosystems. It is an open and comprehensive interaction field powered by the nucleus of exchanges on Alipay which shares its data, and interactions seamlessly. The system of multiple platforms and ecosystems deeply integrates into the lives of small businesses, and consumers too.[9] It creates value not just at the core as in platform ecosystems, but it creates value across the entire interaction field, at the core, or the nucleus, at the ecosystem level with multiple platforms, and at the market level, delivering on its overall business purpose or vision: to build the future digital infrastructure of services, and thereby bring about constant and incremental changes that are beneficial to the world. Value creation and value capture shifts to the demand side.

It offers now a very broad range of services and a lot more is to come, given this broad vision. Eight out of every 10 Ant customers use at least three of its five services. For consumers like for businesses, it has become an essential way from paying for a water bottle at the kiosk around the corner to financing the inventory of retail store. Ant is an open system that even invites its competitors, over 100 banks, 60 insurance companies and 40 wealth management companies and brokerages use Ant. In total over 40 million companies connect.

Unlike western fintech companies, who see traditional banks and financial services as competition to be disrupted, Ant builds on collaboration, participation and engagement with traditional banks and financial services, partnering with them to underwrite the services. Whether it is the lending or the wealth management business, Ant delivers on the promise of its name, “empowering all the little but industrious, antlike companies.” In the process, it benefited from enormous learning effects, network effects, and viral effects, solving a broad set of needs in China that didn’t have easy solutions. Ant has a significant effect on the growth of the economy. John Deere: From Agriculture to the Global Food Interaction Field Another example of an interaction field model comes from John Deere. You would be forgiven if you immediately think of the colors green and yellow on a John Deere tractor now. Tractors and combines and other agricultural equipment have been at the core of the business for decades and help farmers in their daily work from preparation of soil, sowing, adding manure and fertilizers, irrigation, harvesting and storage. John Deere’s true colors however empower much more today. It powers a digital network, the nucleus which is called MyJohnDeere that enables farmers to share data like soil conditions and farm operations data. A host of technologies - including weather monitoring sensors, telemetry, AI and machine learning – collect, aggregate, analyze the field data and share them with farmers. This enables farmers to monitor crops in real-time, improve yield, reduce farming costs, identify water irrigation issues, and reduce water use and other resources.

The nucleus powers a second layer of the interaction field, called the ecosystem. These are the interactions with seed or crop manufacturers or fertilizer companies, software developers, technology suppliers and other stakeholders that directly affect farm productivity. Unlike in a platform ecosystem model where the orchestrator controls the interaction flows of data and exchanges, this is an open architecture where data are shared so that the ecosystem partners can apply their expertise, knowledge and experience to benefit farmers and other participants. This requires careful design of rules and policies of sharing of knowledge and data.

Part of the ecosystem are other platforms. For example, the Farmers’ Business Network is a B2B marketplace that enables price transparencies and lowers farmers’ seed costs or Farmobile which is an independent company that analyzes farm data. The ecosystem partners solve for some needs such as water irrigation that have been intractable in agriculture forever.

The third layer, called market makers, consists of entities that exert influence on value creation in the interaction field. They create value because they drive strongly interaction velocity, that is the volume and quality of data, interactions and exchanges among all the participants in the interaction field. The nucleus and ecosystem participants share data with government agencies such as the USDA, academic research centers or even competing tractor companies such as New Holland or Kubota who could share standards that reduce the costs of deploying and operating technologies. Collaborations with the USDA informs policy decisions to improve healthy food production or set objectives that eventually affect farmers through regulations and subsidies. This solves for larger needs beyond agriculture, namely the availability of healthy food options for consumers through the global food system.

CONCLUSIONS I described three digital business models that have proven to drive enormous new growth, innovation, and value creation for companies over the last decade. These models have emerged so rapidly and scaled so fast that they created some of the largest companies in the world today. I hope that this article has shed some new light on the models and encourages companies and brands to adopt some of the learnings from these early successes in driving new value creation. AUTHOR Erich Joachimsthaler, founder & CEO of the global brand strategy and business transformation firm Vivaldi and author of The Interaction Field: The Revolutionary New Way to Create Shared Value for Businesses, Customers, and Society, PublicAffairs 2020. ej@vivaldigroup.com

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[1] World Economic Forum, Shaping the Future of the Digital Economy and New Value Creation, https://www.weforum.org/platforms/shaping-the-future-of-digital-economy-and-new-value-creation [2] There are many sources that document the growth and success of these digital business models (e.g., Joachimsthaler 2020). See also: Holger Schmidt for an update: https://www.theoriginalplatformfund.de/blog/plattformokonomie-wachst-um-1-6-billionen-dollar, accessed July 26, 2021. [3] Three recent studies by two leading consultancies, BCG and McKinsey showed that failure to build a platform or digital ecosystem hovers around 85% or more (Pidun, Reeves, and Schuessler, 2020). Annabelle Gawer and Michael Cusumano—celebrated academics and two of the original platform theorists—found that of more than 250 platforms they studied, 80% failed (Cusumano, Gawer, and Yoffie 2019). [4] https://seller.alibaba.com/businessblogs/px53308i-alibabacom-vs-aliexpress-what-are-the-differences [5] Interaction velocity happens when both the quantity and quality of interactions across the network increases. [6] Various names have emerged business models similar to interaction field models such as Super Platforms (Lang et al. 2019), Super Apps (Towson 2018), Platforms of Platforms (Thompson 2020) or Ecosystem 2.0 (Chung et al. 2020). [7] Today, it is fashionable to talk about purpose, but years ago, a management theorist called these goals BHAGs, or Big Hairy Audacious Goals: https://www.jimcollins.com/concepts/bhag.html [8] Alipay processes payments between any two users, whether they’re shoppers and small businesses, roommates, or street performers and commuters. [9] Ant also has an enormous successful consumer business. Over 80% of all Chinese consumers use its core payment service Alipay.