Remember when IBM’s “Watson” computer competed on the TV game show “Jeopardy” and won? Most people probably thought “Wow, that’s cool,” or perhaps were briefly reminded of the legend of John Henry and the ongoing contest between man and machine. Beyond the media splash it caused, though, the event was viewed as a breakthrough on many fronts. Watson demonstrated that machines could understand and interact in a natural language, question-and-answer format and learn from their mistakes. This meant that machines could deal with the exploding growth of non-numeric information that is getting hard for humans to keep track of: to name two prominent and crucially important examples,
- keeping up with all of the knowledge coming out of human genome research, or
- keeping track of all the medical information in patient records.
So how does it work? First, with multiple business models. Mike Rhodin, IBM’s senior vice president responsible for Watson, told me, “There are three core business models that we will run in parallel.
- The first is around industries that we think will go through a big change in “cognitive” [natural language] computing, such as financial services and healthcare. For example, in healthcare we’re working with The Cleveland Clinic on how medical knowledge is taught.
- The second is where we see similar patterns across industries, such as how people discover and engage with organizations and how organizations make different kinds of decisions.
- The third business model is creating an ecosystem of entrepreneurs. We’re always looking for companies with brilliant ideas that we can partner with or acquire. With the entrepreneur ecosystem, we are behaving more like a Silicon Valley startup. We can provide the entrepreneurs with access to early adopter customers in the 170 countries in which we operate. If entrepreneurs are successful, we keep a piece of the action.”
More and more, organizations will need to make choices in their R&D activities to either create platforms or take advantage of them.
Those with deep technical and infrastructure skills, like IBM, can shift the focus of their internal R&D activities toward building platforms that can connect with ecosystems of outsiders to collaborate on innovation.
The second and more likely option for most companies is to use platforms like IBM’s or Amazon’s to create their own apps and offerings for customers and partners. In either case, new, semi-autonomous agile units, like IBM’s Watson Group, can help to create and capture huge value from these new customer and entrepreneur ecosystems.