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 IBM asked the question: How could the fullest potential of this
breakthrough be realized, and how could IBM create and capture a
significant portion of that value? They knew the answer was not by
relying on traditional internal processes and practices for R&D and
innovation. Advances in technology — especially digital technology and
the
increasing role of software
in products and services — are demanding that large, successful
organizations increase their pace of innovation and make greater use of
resources outside their boundaries. This means internal R&D
activities must increasingly shift towards becoming
crowdsourced, taking advantage of the wider
ecosystem of customers, suppliers, and entrepreneurs.
IBM, a company with a long and successful tradition of
internally-focused R&D activities, is adapting to this new world of
creating
platforms and enabling
open innovation.
Case in point, rather than keep Watson locked up in their research
labs, they decided to release it to the world as a platform, to run
experiments with a variety of organizations to accelerate development of
natural language applications and services. In January 2014 IBM
announced they were spending $1 billion to launch the
Watson Group, including a $100 million venture fund to support start-ups and businesses that are building Watson-powered apps using the “
Watson Developers Cloud.”
More than 2,500 developers and start-ups have reached out to the IBM
Watson Group since the Watson Developers Cloud was launched in November
2013.
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.”
IBM also had to make some bold structural moves in order to create an
organization that could both function as a platform as well as
collaborate with outsiders for open innovation. They carved out The
Watson Group as a new, semi-autonomous, vertically integrated unit,
reporting to the CEO. They brought in 2000 people, a dozen projects, a
couple of Big Data and content analytics tools, and a consulting unit
(outside of
IBM Global Services).
IBM’s traditional annual budget cycle and business unit financial
measures weren’t right for Watson’s fast pace, so, as Mike Rhodin told
me, “I threw out the annual planning cycle and replaced it with a
looser, more agile management system. In monthly meetings with
CEO Ginni Rometty,
we’ll talk one time about technology, and another time about customer
innovations. I have to balance between strategic intent and tactical,
short-term decision-making. Even though we’re able to take the long
view, we still have to make tactical decisions.”
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.
