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Ecosystems are the reality of the market today — whether organizations want them or not. Organizations set out to build platforms that they control and expand, but the messy reality of modern interconnected businesses is that often an ecosystem of diverse participants will emerge, and an organization will be forced to participate or lose its place in the market. The better you acknowledge that reality, the better placed you are to compete.
The key difference between a platform and an ecosystem is control. An organization can create and run a platform, which gives them control over who can participate. But a company can only loosely set standards for an ecosystem, and participants may emerge spontaneously. Like a biological ecosystem, a technology ecosystem involves competition and ‘survival of the fittest.’ This means symbiotic, parasitic and predatory behavior, as well as a continuing need to adapt or perish. There are limited resources — often economic, but sometimes something such as “consumer attention” — and the struggle for these fuels interaction, innovation and evolution. Signals here include:
Consumers make purchasing decisions based on how your product fits in their ecosystem. Misunderstanding your position in the ecosystem can lead to poor business outcomes, while knowing when to share or ‘let go’ can create a source of competitive advantage.
For example, for years car manufacturers were investing to build proprietary platforms, These platforms failed for two reasons. First, drivers don’t think about their car as a closed platform; they just want their maps and music playlists to work. Second, auto manufacturers don’t have the specialization required to build world-class entertainment or mapping experiences, and always provided worse alternatives to the Spotify and Google Maps of the world. Consumers ultimately don’t care about their car manufacturer’s proprietary platform, they just want to be able to extend their most important and personal ecosystem — their phone — into the car.
The lesson here is that enterprises that play to their core strengths, and make sure their offerings are built to interact with surrounding ecosystems that are evolving holistically, will be best placed to win over customers and succeed in the emerging business environment.
A good example of an ecosystem is the online travel industry, comprising travel aggregator sites, airlines, hotels, lodging, and ground transport providers. Airlines would prefer that consumers book travel directly on their platforms where they can control branding and offer other products such as credit cards — but consumers often prefer to use aggregators so they can compare prices between airlines and work out details such as the entire cost of their trip. Airlines have responded by incorporating more of the overall ecosystem into what they provide — for example, the Delta Airlines mobile app now allows you to book an Uber or Lyft directly. While the aggregator might label itself a ‘platform business,’ we would argue that aggregators actually enable ecosystems in which an airline can derive a lot of business value from being a participant. Airlines are now learning how important it is to provide accurate data to other ecosystem participants, especially corporate travel management services. To take one example, one airline’s prices were not being correctly loaded into the ThoughtWorks corporate booking system. Rather than driving fliers to book on the airline’s website directly, it simply caused them to choose another airline!
Business API as product. Having a product focus, which includes deliberate thinking about how others will consume your APIs, will be key to competing for a spot in both existing and emerging ecosystems. Treating an API as a product requires the creation of other assets such as documentation and support offerings in order to encourage other organizations to adopt it. Like any other product, APIs require investment in understanding and responding to customer needs to keep them relevant and high-quality.
ML platforms. To speed deployment of machine learning into production, and to accelerate the training and management of ML models, many companies are creating ML platforms that can provide end-to-end capabilities such as data management; feature engineering; model training, evaluation, and governance; explainability; AutoML; and promotion between environments.
Proliferation of industry-wide open standards. We’re seeing a growing number of industry-specific standards that can help drive better interoperability between companies. Examples are GS1 barcode standards like Global Trade Item Numbers (GTIN) for product IDs, and the Fast Healthcare Interoperability Resources (FHIR) standard for the healthcare industry. There are also government-wide initiatives to encourage interoperability to give consumers more portability, such as the Open Banking initiative in the UK.
… actively strive to build systems that are part of larger ecosystems, which will allow them to reach customers that they couldn’t access otherwise. Combined with the fact that enterprises will be able to leverage technology created by others instead of struggling to build everything themselves, the evolving nature of platforms is a win-win proposition.
