The design of an ecosystem should be driven by its core value proposition. The initial value blueprint should incorporate the minimum number of domains (types of participants or market sides) that are needed to provide this core value and expand over time. All examples of hybrid models that we know started either as a transaction ecosystem (Airbnb, Alibaba, LinkedIn) or as a solution ecosystem (Apple iOS, Android) and added further domains and offerings only once they were firmly established.
The value blueprint is the basis for assigning roles to the various players. A solution ecosystem is typically characterized by a core firm that orchestrates the offerings of several complementors, suppliers, and intermediaries (such as Better Place’s ecosystem in Exhibit 2). In transaction ecosystems, the orchestrator role is played by the owner of a central (mostly digital) platform that links producers and their suppliers with consumers.
The different roles have benefits and drawbacks. The orchestrator builds the ecosystem, encourages others to join, defines standards and rules, and acts as arbiter in cases of conflict. The broad scope of the role comes with the bulk of responsibility for ecosystem success and the sustained level of investment that is required to get the ecosystem going. The orchestrator is the residual-claim holder of the ecosystem. While it has a big influence on the distribution of the value created, it must also make sure that all relevant players earn a decent profit. In return, the orchestrator can keep the residual profit, which can be very high (Apple iOS, Microsoft Windows) but also negative for an extended period of time (Uber, Lyft). Orchestrators that fail in their responsibility to secure fair value sharing will sooner or later destroy their ecosystems.
Who should be the orchestrator?
In many business ecosystems, the assignment of the orchestrator role is clear. For example, in most transaction ecosystems the provider of the matching platform is the natural orchestrator, and the roles of producers and consumers are readily assigned. Similarly, some solution ecosystems are built on a technical platform that serves as the basis for orchestration, such as the console of a video game ecosystem or the operating system on a PC or smartphone.
You cannot unilaterally choose to be the orchestrator. You need to be accepted by the other players in the ecosystem.
However, as a new ecosystem emerges, the orchestrator role may be contested. Think of the competing smart-farming ecosystems that are currently being built by equipment manufacturers (John Deere), seed and crop protection providers (Bayer-Monsanto), and technology players (Alphabet). And who should be the orchestrator of an effective ecosystem for electronic health records: health insurers, providers, IT companies, or the government?
It is important to understand that you cannot unilaterally choose to be the orchestrator. You need to be accepted by the other players in the ecosystem. In this regard, there are four requirements for a successful orchestrator of a business ecosystem. First, the orchestrator needs to be considered an essential member of the ecosystem and control resources needed for its viability, such as a strong brand, customer access, or key skills. Second, the orchestrator should have a central position in the ecosystem network, with strong interdependencies with many other players and a resulting high need and ability for effective coordination. Third, the orchestrator should be perceived as a fair (or even neutral) partner by the other members, not as a competitive threat. And finally, the best candidate is likely to be the player with the highest net benefits from the ecosystem and thus a correspondingly high ability to shoulder the large upfront investments.
Most companies seem to strive for the orchestrator role because they fear being commoditized, losing direct access to customers, or being exploited by another orchestrator. However, being a supplier or complementor in a business ecosystem can be a very attractive role. Arguably, the biggest winners of the Californian gold rush in the mid-19th century were the suppliers of pots, pans, and Levi jeans. Similarly, suppliers and complementors can benefit from lower investment requirements and the opportunity to join the most attractive of several ecosystems. Or they can hedge their bets and participate in more than one ecosystem. In particular, if they provide important components that represent a bottleneck for the ecosystem, they can secure a substantial share of the overall profits.
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D.P. Hannah and K.M. Eisenhardt, “How firms navigate cooperation and competition in nascent ecosystems,” Strategic Management Journal, December 2018.
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D.P. Hannah and K.M. Eisenhardt, “How firms navigate cooperation and competition in nascent ecosystems,” Strategic Management Journal, December 2018.
An example of a highly successful complementor is Adyen, a Dutch payments company enabling global platforms to support all key payment methods around the world. At the time of writing, the company had a market cap of more than €25 billion, had more than doubled its stock price since its IPO in June 2018, and reported revenue growth of 41% in the first half of 2019 at an EBITDA margin of 57%. Arithmetic dictates that only a small minority of firms can be orchestrators. We are convinced that many incumbents would be well advised to put their strategic focus on finding attractive complementor or supplier roles.
How can the orchestrator motivate the other players?
Ecosystem orchestrators face the additional challenge of motivating the required partners to commit and contribute to the ecosystem. Ron Adner identified two important risks for the feasibility of an emerging ecosystem: co-innovation risk and adoption risk.
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Ron Adner, The Wide Lens, Penguin Group, 2012
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Ron Adner, The Wide Lens, Penguin Group, 2012
Co-innovation risk stems from the fact that developing a new or substantially improved value proposition is typically associated with high risks for the individual required innovations. In the case of a business ecosystem, these individual risks multiply because of the interdependence of the different components. The probability of technical success of an ecosystem solution equals the mathematical product of the probability of success of all required components, which can be very small if just one factor is small.
This co-innovation risk is particularly relevant for solution ecosystems, where the failure of one critical component is sufficient for the entire ecosystem to fail. For example, in early 2000, Nokia and Sony Ericsson started a race to bring to market the first 3G mobile phone capable of video streaming. Nokia had forecast that by 2002 more than 300 million mobile handsets would be connected to the internet. The actual number was 3 million; 300 million was reached in 2008, six years later. Nokia became a victim of co-innovation risk: While Nokia was fast to the market and could sell its first 3G handset in 2002, before Ericsson, other actors in the ecosystem still had to develop solutions to fully enable video streaming, such as formatting software to fit TV images on small phones, router innovations allowing mobile phone operators to know which customer signed up for which plan, and digital rights management to ensure copyright protection for content owners. Before these innovations were established, 3G video streaming could not be viable, rendering the device largely useless.
Assessing co-innovation risk is important to evaluate the overall probability of success of the ecosystem, but also to identify the bottleneck components that need most attention and support. Intel understood this challenge when the company designed its ecosystem and created the Intel Architecture Lab to drive architectural progress on the PC system and to stimulate and facilitate innovation on complementary products.
Even if co-innovation risk seems limited, there is another challenge related to the value blueprint: adoption risk. Because of the high interdependencies in a business ecosystem, all contributors to the overall solution need to be ready, willing, and able to participate and invest in the ecosystem. A single instance of rejection is enough to break the entire adoption chain. For example, Better Place finally failed in spite of a compelling value proposition because it could not secure the participation of one important group of partners in its ecosystem, the car manufacturers. It got Renault on board by guaranteeing volume and placing an order of 100,000 cars, four years before it had a single customer. But Renault ultimately was Better Place’s only car manufacturing partner.
How can you evaluate critical partners’ incentives to participate? Partners are more likely to commit if they score high on the following criteria:
- High relative profit increase from participation
- High competitive risk from non-participation
- Limited investments required for participation
- Limited risk from participation
- Existing capabilities to build on
If some critical players show a high adoption risk, you may need to reflect this in your ecosystem design with incentives for participation. Incentives need not be only monetary; they can, for instance, also include access to customers or data. Ron Adner mentions digital cinema projectors as an example. The value proposition for replacing analog films and projectors by digital counterparts was generally compelling: higher resolution, better protection from piracy, and significant savings in the value chain. The cost of producing a conventional film was $2,000 to $3,000 per print, costing $7.5 million for a release shown on 3,000 screens. Regardless of these advantages, adoption risk proved to be very high for cinemas because the investment costs were prohibitive relative to the benefits. Despite efficiency gains, higher quality for consumers, and more flexibility regarding the offering, cinemas saw no need to adopt digital projectors on a large scale. Only once the film studios established a financing scheme in which they shouldered the initial outlay for the projector, and studios shared the benefits by paying a virtual print fee per digital film screened (covering ~80% of the cinema investment costs), were the incentives for adoption high enough to establish the new technology on a broader scale.
Step 3: What should be the initial governance model of your ecosystem?
How open should the ecosystem be?
Ecosystem governance is an important design choice because it creates an indirect form of control appropriate to the complexity and dynamism of an ecosystem. It establishes the standards, rules, and processes that define an ecosystem’s formal or informal constitution. Governance needs to balance two requirements for ecosystem success: value creation (rules of collaboration to co-create value as an ecosystem) and value sharing (rules and processes for splitting the value among ecosystem players).
The single biggest governance question for an emerging ecosystem is its degree of openness. Questions in three areas must be answered:
- Access. Which individual partners will be allowed to participate in the ecosystem? Which requirements do they have to fulfill in order to get access to the platform and its resources?
- Participation. To what extent are ecosystem partners invited to shape the ecosystem? What is the scope, detail, and strictness of the rules governing this? Who decides how the value created is distributed among partners?
- Commitment. What level of ecosystem-specific investments and co-specialization is required? Is exclusivity demanded or are partners allowed to multihome in competing ecosystems?
In practice, we can observe successful ecosystems with very different levels of openness, from rather restrictive (Nespresso) to managed (video games) to very open (Airbnb). For example, the Chinese company Haier chooses a rather open approach toward access to its emerging “internet of food” ecosystem, which tries to integrate players from the appliance, food, health care, home furniture, logistics, and even entertainment industries to create a comprehensive customer solution from buying to cooking, eating, storing, and cleaning. As Zhang Ruimin, chairman of the Haier group, put it, “We want to build an energetic rainforest rather than a structured walled garden.”
On the other hand, Sony experienced the peril of an open governance model when introducing its e-reader. Alarmed by piracy in the music industry, publishers were extremely concerned to protect their rights around books. Sony did not manage to establish a governance model to address this concern. Therefore, Amazon could conquer the e-book market as a late entrant by establishing the Kindle as a very closed platform that loaded content only from Amazon and precluded users from transferring books to any other device or to a printer.
In some sectors, ecosystems compete on their degree of openness. For example, Android broke the dominance of Apple iOS as a mobile operating system with a very open governance model, while Facebook overcame the weaknesses of Myspace’s open model by being initially very selective about who it allowed to join and establishing the double-opt-in “friending” feature.
How can you find the right level of openness for your ecosystem? The decision must optimize the tradeoff between the advantages of a more open setup and of a more closed setup. Open ecosystems can benefit from faster growth, particularly during launch. They enable greater diversity of participants and variety of offerings and encourage decentralized innovation. Open ecosystems tend to use the market to guide their development; partners join and leave and adjust their offers as customer demand and technologies evolve.
How can you find the right level of openness for your ecosystem? The decision must optimize the tradeoff between the advantages of a more open setup and of a more closed setup.
On the other hand, open ecosystems are difficult to control and are thus best suited for products and services with limited downside and relatively low cost of failure. In case of high failure costs, and a corresponding need to limit the downside, a closed ecosystem may be the better solution. It allows for a more deliberate design of the ecosystem and for closer control of partners and of the quality of the offering. Moreover, a more closed ecosystem helps the orchestrator capture value by, for example, charging for access.
The right level of openness for a given ecosystem will depend on the relative importance of the individual factors, such as growth versus quality, decentralized versus coordinated innovation, and speed versus consistency of co-evolution. Competition with other existing or emerging ecosystems in the same sector can also play a role, because a new ecosystem needs to find a differentiated positioning, such as the degree of openness.
We have seen many ecosystems start with a rather closed governance model in order to establish high quality and open up later. For example, the Q&A platform Quora started as an invite-only ecosystem that targeted prominent technology entrepreneurs. By building this dense and exclusive network of experts, Quora was able to develop an inventory of high-quality content that then made it easy to attract a broader audience when the platform later opened up. However, there are also examples of ecosystems that start as open to gain traction and become more closed later, such as the knowledge ecosystems investigated by Järvi and her colleagues.
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K. Järvi et al., “Organization of knowledge ecosystems: Prefigurative and partial forms,” Research Policy, October 2018.
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K. Järvi et al., “Organization of knowledge ecosystems: Prefigurative and partial forms,” Research Policy, October 2018.
We have seen many ecosystems start with a rather closed governance model in order to establish high quality and open up later.
What should the orchestrator control?
As an orchestrator, you face an additional design question: What do you want to do yourself and what do you want to encourage complementors to do? A starting point may be your own assets and capabilities. However, as Hannah and Eisenhardt observe, “Perhaps in complex strategic settings like ecosystems, strategy is more consequential than initial capabilities.”
Good ecosystem strategy may be to identify and occupy potential innovation or capacity bottlenecks that can become an important source of value. Successful orchestrators claim important system control points that allow them to capture their fair share of value. For example, Nest decided to engage in alarm and monitoring itself because these are essential functionalities for controlling the home. Apple pre-installs Apple Maps on the iPhone in an attempt to oust Google Maps. And Google uses its Google Play store to control the otherwise very open Android ecosystem.
There are, of course, many other initial governance questions. For example, when designing a transaction ecosystem, the platform orchestrator must decide whether the matching of producers and consumers should be done by algorithm (Uber) or by users (Facebook); whether pricing should be based on rules and algorithms (LendingClub) or on offer and negotiation (eBay); and whether curation should be done by platform editors (Wikipedia), user feedback (Airbnb), or algorithms (Google Search). These decisions depend on the specific context and get at the heart of the ecosystem’s operating model, value creation mechanism, and differentiation.
We will address the question of ecosystem governance in more detail in a future article in this series.
Step 4: How can you capture the value of your ecosystem?
What should you charge?
When the basic setup of the business ecosystem is defined, the next big design step is to find a way to translate the benefits that the ecosystem creates for its customers into value for its participants. Monetization is one of the biggest challenges of the ecosystem orchestrator, which must balance three competing objectives: maximizing the size of the total pie; enabling all important domains (groups of participants) of the ecosystem to earn enough profit to ensure their ongoing participation; capturing its own fair share of the value.
To achieve this, the orchestrator must design not only the value proposition for the customer but also the value-sharing model, by defining the value proposition for each group of relevant stakeholders. At the same time, the orchestrator must make sure to own critical control points, such as access to the customer, products with many interfaces, or critical services.
In solution ecosystems, value capture is typically rather straightforward because the solution that the ecosystem creates can be sold as a product or service. The orchestrator can in addition capture value from complementary products or services through access fees, licensing fees, revenue shares, or sales of value-added products or services to complementors. For example, Apple takes 30% of revenues for all apps sold through its App Store, and Nespresso takes a license fee from machine makers such as Krups, Breville, and De’Longhi.
Transaction ecosystems offer many more options for capturing value. The orchestrator can charge for access, for example, with a general access fee to the platform, an enhanced access fee for producers for better targeted messages or interactions with particularly valuable users, premium access fees for consumers, or enhanced curation fees for users who are willing to pay for guaranteed quality. The orchestrator can also charge for usage in the form of a transaction fee, either a fixed fee per transaction or a percentage of the transaction price. In addition, the orchestrator can charge for supplementary products or services (such as invoicing, payments, insurance), or it can monetize the ecosystem indirectly through advertising revenues.
Whom should you charge?
The second critical question of value capture is whom to charge. Again, the orchestrator has a number of choices, such as charging all participants, charging only one side of the market while subsidizing the other side, or charging most users the full price while subsidizing selected marquee users or particularly price-sensitive users.
Our analysis showed that mispricing on one side of the platform is a key reason for failure, in particular in the launch phase (see the next section). For example, Table8, a platform for last-minute reservations in sold-out restaurants, failed because it charged the wrong side of the market. The company learned the hard way that few guests were willing to pay $20 or more for a reservation in a high-profile restaurant. Competitors like OpenTable that charged restaurants for their reservation service turned out to be more successful. Similarly, eBay had to learn that its established model of charging users to list products and services did not work in China because the practice discouraged sellers to set up online shops, whereas Taobao offered a cost-free system that was financed solely by advertisements.
How can you find the right monetization strategy for a given business ecosystem? In general, monetization should be designed so that it does not stifle the growth of the ecosystem but instead encourages and incentivizes participation and thus fosters network effects. This can be achieved, for example, by charging for transactions rather than access, subsidizing the side of the market that is less willing to participate, or offering rebates for increased usage and rewards for inviting others to join the network. A good starting point is to identify the participants with the highest willingness to pay and charge them according to the net excess value they derive from the ecosystem.
In general, monetization should be designed so that it does not stifle the growth of the ecosystem but instead encourages and incentivizes participation and thus fosters network effects.
Moreover, monetization should be used to overcome bottlenecks in the ecosystem and to encourage innovation by, for example, subsidizing bottleneck players and offering better terms for new products. Of course, the pricing strategy of an ecosystem can change over time. Many platforms initially subsidize one or both sides of the market to overcome the chicken-or-egg problem during launch. However, most of them realize that it is difficult to transition from free to fee and that they need to offer new, additional value to justify the change.
Step 5: How can you solve the chicken-or-egg problem during launch?
What does it take to achieve critical mass?
Many ecosystems fail during the launch phase because they cannot solve the chicken-or-egg problem of sufficient participation of both buyers and sellers/producers. They do not achieve the critical mass to secure network or data flywheel effects, whereby scale begets further scale. An analysis of 57 ecosystems in 11 sectors across geographic markets by the BCG Henderson Institute found that half of the investigated ecosystems never took off.
When we looked deeper into the successes and failures, we noticed many misunderstandings regarding ecosystem launch. First, despite the paramount importance of network effects in many business ecosystems, first-mover advantages are often overestimated. It is not about being the first in the market, but being first with a complete solution. The Apple iPod was not the first digital music player, but it was the first to offer a comprehensive solution by combining the hardware product with the iTunes music management software.
Second, the size of the network should be measured not by vanity metrics, such as the number of members, but by the number of interactions or transactions, which is how business ecosystems create value. Most network effects are “local” (not only in a geographical sense), so network density may be a more important driver of value for users than network size.
Third, it is not only about the quantity of participants but about the right participants (such as the most attractive restaurants for an online booking platform like OpenTable) in the right proportions (such as a balanced number of drivers and riders for a ride-hailing ecosystem like Uber). Identity and culture are important success factors for a business ecosystem, and it is difficult to change them once they are established. Ecosystem growth is thus strongly path dependent, and the selection of early members and the sequence of attracting members can have a big impact. You can even experience negative network effects from attracting “bad” users, as Chatroulette, the random video chat platform, experienced with its “naked-hairy-men problem.”
What is the minimum viable ecosystem?
An important consideration to increase the odds of a successful launch is to start with a minimum viable ecosystem (MVE), a term coined by Ron Adner.
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Ron Adner, The Wide Lens, Penguin Group, 2012.
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Ron Adner, The Wide Lens, Penguin Group, 2012.
In the traditional approach to launching a new product, the fully developed value proposition of the product is demonstrated in a trial pilot with limited commercial scale before the broad rollout of the product. By contrast, a minimum viable ecosystem initially focuses on a basic value proposition (the core transaction) but demonstrates its commercial viability at scale, directly establishing a dense network of partners and customers. Over time, the MVE can expand its value proposition in a series of staged expansions.
To quickly get to critical mass and build a dense network, many successful ecosystems we observed initially constrained themselves by geography.
To quickly get to critical mass and build a dense network, many successful ecosystems we observed initially constrained themselves by geography. For example, Airbnb first focused on New York, and even as the company started its international expansion in 2011, it focused on creating critical mass in just a few markets. Similarly, OpenTable conquered one city at a time, following the rule of thumb that once 50 to 100 concentrated restaurants in a city subscribed, enough consumers would use the platform.
On the other hand, many failed ecosystems expanded too quickly. For example, Better Place may have been able to overcome the chicken-or-egg problem if it had focused on its two core markets, Israel and Denmark, where it achieved early success. However, the company moved too quickly to establish toeholds and run pilots in a wide range of new locations and ran out of money before it could secure the critical level of sales volumes to attract and retain partners—most important, automakers.
Other failed ecosystems completely ignored the MVE concept and launched an offering that was too broad rather than focusing on the core transaction. For example, Club Nexus, an early social network created in 2001, allowed students to chat, send emails, post events, buy and sell goods, and post images and articles. The complexity of features made the platform difficult to use and weakened the strength of its network. Facebook learned from this failure and started with only very simple profiles and allowed users to view only other people who went to the same school.
Which side of the market should you focus on?
In solution ecosystems, the main challenges are typically on the complementor side: convincing partners to commit to and invest in an unproven business opportunity. It helps if the orchestrator credibly demonstrates its own commitment through a large upfront investment in the ecosystem, as Microsoft did when it entered the video game console market in committing to sell the Xbox at a low price to convince game developers that there would be demand for their products. In addition, Microsoft subsidized some marquee developers to join the ecosystem. The orchestrator can make it easier to join by providing free or subsidized tools and services for complementors. Some orchestrators even sign conditional contracts with complementors and/or customers obliging them to join the ecosystem if it gets enough members of the other group to participate. If this does not work, the orchestrator can still develop or buy some of the required complements itself to kick-start the ecosystem. For example, Apple launched the iPhone with a number of applications that it developed in-house, including a web browser, mail, contacts, calendar, photos, videos, and iTunes.
Transaction ecosystems have an even larger number of levers at their disposal to kick-start the platform. Sometimes they can build on the existing infrastructure or customer base of a linear business model, as Amazon did when it opened its established e-commerce system to external producers and launched Amazon Marketplace. Or they can piggyback on an existing transaction ecosystem, like PayPal did on eBay’s online auction platform.
If this is not possible, the critical question is which side of the market to focus on initially in order to build critical mass. Most ecosystem orchestrators that we analyzed focused first on building supply, and they used various levers to do so. Some seeded and subsidized one side of the market. For example, Uber initially guaranteed drivers $40 per hour as long as they kept the app running and maintained an acceptance rate of 70%. Some attracted supply by providing free or subsidized tools and services (Airbnb), subsidizing marquee producers to join the platform (Twitter), or creating an initial offering by acting as a producer themselves (Quora, Reddit). An interesting strategy can be to create standalone value for one side first. For example, OpenTable started by building a suite of software tools for restaurants to replace their manual booking process, which created the technical preconditions and a loyal base of suppliers for their online booking platform.
The critical question is which side of the market to focus on initially in order to build critical mass.
Supply-constrained ecosystems should not shy away from more traditional levers. Most successful food delivery platforms, for instance, started by hiring a field sales force that simply walked into restaurants during their downtime and talked to owners to convince them to join their ecosystem. Many ride-hailing platforms used referrals to incentivize existing suppliers to bring new suppliers to the platform.
Some transaction ecosystems are not supply-constrained and should focus on growing the demand side. For example, TaskRabbit quickly had thousands of people on the waitlist to provide services, while it turned out to be more difficult to build demand. The company deliberately constrained supply by charging an application fee and processing background checks in order to increase the quality of the offering and thus attract demand.
Other ecosystems follow a zigzag strategy to bring on both sides of the market at once. For example, Alibaba worked hard on getting Chinese suppliers and foreign buyers on board simultaneously when it first launched. YouTube also pushed participation by both sides simultaneously and alternated between strategies to get more people to upload and more people to view. The Japanese firm Recruit, which builds ecosystems to reinvigorate mature service markets, deploys what it calls its Ribbon Model to alternate between building supply and building demand.
And finally, some successful platforms use context-dependent creative and even devious tricks to overcome the chicken-or-egg problem. Twitter achieved its breakthrough by traditional push marketing with a big-bang event at the 2007 South by Southwest (SXSW) tech festival. Airbnb, instead of building supply from scratch, used readily available information on property owners who wanted to rent out their properties from Craigslist, a popular online classified website. And Uber launched Operation SLOG (Supplying Long-term Operations Growth) to aggressively attract drivers from rival ride-hailing service Lyft.
We conclude that successfully launching a business ecosystem is a big challenge that requires more than a strong initial design. It takes persistence, deep pockets, and sometimes the willingness to follow unusual and creative approaches that may not be financially sustainable, in order to kick-start the ecosystem. However, if the ecosystem is to be viable in the long run, it also needs to be designed for evolvability.
Step 6: How can you ensure evolvability and the long-term viability of your ecosystem?
How can you scale the ecosystem?
In contrast to most traditional business models, many business ecosystems have the potential not only for supply-side economies of scale but also for demand-side economies of scale and the resulting positive feedback loops. In particular, demand-side scale effects enable many ecosystems to grow quickly and exhibit winner-takes-all or at least winner-takes-most characteristics (at least for some time). However, some ecosystems have only limited demand- and supply-side economies of scale. And many ecosystems have failed because they did not solve the scalability challenge.
Demand-side economies of scale make networks more attractive to users as more users participate in the ecosystem. They can be based on direct (same-side) or indirect (cross-side) network effects. More traditional market-building instruments, such as a strong brand, can reinforce these network effects. Demand-side economies of scale are larger for ecosystems with global business models (travel booking platforms) than for multi-local ecosystems (food delivery platforms), where the network effects are limited to small local clusters. Moreover, an ecosystem may experience negative network effects and declining quality from growing the network, for example, if it becomes increasingly difficult to find the best match in a growing transaction ecosystem. Such negative network effects can be limited through effective (and scalable) curation using data, algorithms, and social feedback mechanisms.
Supply-side economies of scale can be based on falling fixed or variable costs. They are particularly strong in many digital ecosystems, which are frequently characterized by asset-light business models (Airbnb achieved a dominant position in the hospitality market without owning a single hotel), low-to-zero marginal cost (no significant effort of serving an additional customer on the Amazon Marketplace), and increasing returns on data (more effective matching of riders and drivers on a growing ride-hailing platform). Supply-side scale effects can be limited by sticky costs, for example, if competition between ecosystems requires ongoing high marketing and recruiting investments (food delivery platforms) or if a fast rate of technological innovation requires ongoing high research and development expenses (ride-hailing). Moreover, the rising cost of complexity and quality control may counterbalance positive scale effects as the network grows.
We suggest a simple matrix to analyze the scalability position of your ecosystem. (See Exhibit 3.)