Developing Tomorrow’s Information Systems Today
Innovation ecosystems afford great opportunities for information scientists and professionals to develop next-generation information systems.
In a reflective essay published in the Atlantic, Ben Shneiderman, the founding director of the UMD Human-Computer Interaction Lab, criticizes the long-held view that basic research drives applied research. Instead, he proposes that breakthrough discoveries and innovations often come from the interactions of basic and applied research embedded in large development projects. Shneiderman’s ecological model of research and development resembles a new way to organize innovations in the digital economy — innovation ecosystems.
An innovation ecosystem is a loosely coupled set of people and organizations involved in the creation and adoption of innovations — new processes, products, and services. For example, app developers, accessory makers, content suppliers, and consumers join Apple’s iOS ecosystem in which they co-create and/or adopt innovative products and services made available via the iPhones and iPads. The participants of an ecosystem are loosely coupled because they are free to join or leave the ecosystem without losing their autonomy and, while in the ecosystem, they don’t have to follow orders like the employees in a traditional hierarchical company. Rather, their relationships mimic those among different species in a natural ecosystem.
Various types of ecosystems have become a popular model to organize innovations across the digital economy. In addition to the product ecosystems exemplified by Apple’s iOS ecosystem, service ecosystems center around core services such as those offered by Uber. Business ecosystems such as those orchestrated by Amazon may each include multiple product or service ecosystems. Entrepreneurial ecosystems usually consist of diverse players such as government agencies, universities, and investors that shape the new ventures in specific geographic regions such as the Silicon Valley. More broadly, an entire category of product or technology can form a category ecosystem such as the mobile ecosystem and cloud computing ecosystem.
Why are innovation ecosystems so popular? Widespread digitization has broken monolithic product architecture into pieces that different players can make separately and then integrate into a coherent package for the customers to buy. This division of labor and integration of efforts, both enabled by digital technologies, have made it possible to innovate with ecosystems. Further, it is often desirable to innovate in ecosystems because digital technologies have become inexpensive and scalable. Moreover, sometimes it is even necessary to innovate in ecosystems due to Joy’s Law, famously put by Sun Microsystems’ co-founder Bill Joy: “Most of the bright people don’t work for you — no matter who you are. [So] you need a strategy that allows for innovation occurring elsewhere.” One such strategy is to tap the unlimited creativity and unique skills that autonomous participants bring to an ecosystem.
The possibility, desirability, and necessity of the ecological model for innovation can explain not only the popularity but also the exceptional successes of notable ecosystems led by Amazon, Alibaba, Google, Tencent, and so on. The value co-created and wealth accumulated by the players in any of these ecosystems far exceed those in any single company. Yet, these exceptional successful ecosystems are exceptions rather than the norm. Most ecosystems struggle to even get started. Some, such as the Symbian ecosystem for smartphones, achieved an early momentum but then collapsed. A closer look at failed ecosystems reveals that an ecosystem’s success may be cursed: As a growing ecosystem attracts more participants, they add complexity and risks to the ecosystem, which can cause the ecosystem to collapse.
Nevertheless, it may be possible to overcome this curse. On one hand, the sponsor of an ecosystem should carefully control the memberships, actions, and interactions of the ecosystem’s participants, using tools such as application programming interface (API) and software development kit (SDK). On the other hand, ecosystem participants should carefully determine their own actions and interactions with others. For example, whether to join or leave an ecosystem is an important decision for a company to make as it defines its own boundaries. All of these decisions rely on relevant information. Hence, the sustainability and success of innovation ecosystems depend on effective information management.
A promising field is widely open for information scientists and professionals to develop the information systems to support innovation ecosystems. Foremost, ecosystems are largely invisible without physical presences. Nonetheless, the data about an innovation ecosystem can be found from multiple sources such as the trade press, scientific publications, patents, consultants’ reports, social media, etc. Visual analytic tools may be employed to help decision makers visualize an ecosystem, including the actors and their relationships and interactions in the ecosystem. Since no ecosystem stands alone, the visualization of multimodal and multilayer networks of actors may help understand the interactions among ecosystems of the same or different types.
In 1994 Lucas and Baroudi speculate: “The organization of the future may not be an organization at all.” As digitization renders traditional, hierarchical organizations inadequate, ecosystems have become “the organization of the future” to manage innovations in the digital age. This ecological model of innovation affords great opportunities for information scientists and professionals to develop the next-generation information systems now.
This blog is based primarily on the following publication:
- Wang, P. 2021. “Connecting the Parts with the Whole: Toward an Information Ecology Theory of Digital Innovation Ecosystems,” MIS Quarterly (45:1), pp. 397–422.