Does your company have an explicit innovation strategy? (Hint: It’s not the same as your corporate business strategy.) If not, you’re not alone, and perhaps it’s time to create one. This issue of Innovation Quarterly will help
IN THIS ISSUE:
Brief reviews of “Collective Disruption: How Corporations & Startups Can Co-Create Transformative New Businesses” by Michael Docherty and “Social Physics: How Good Ideas Spread-The Lessons from a New Science” by Alex Pentland
Gary Pisano’s recent article on innovation strategy in the June issue of Harvard Business Review (see our review here) raised a critical question: What is the relationship between a company’s business strategy and its innovation strategy?
One perspective on this issue comes from a little known, but arguably valuable, framework put forth by Ralph Stacey, a professor of management at Hertfordshire Business School, back in 1996, the Agreement-Certainty Matrix, shown above. In Stacey’s matrix, the two dimensions of Agreement and Certainty help companies assess the complexity of decisions about the opportunities and challenges they face.
If we put the Agreement-Certainty framework into a strategy context, the following ideas take shape:
Business Strategy is about managing agreement.
Henry Mintzburg, a renowned author and professor of management at McGill Univertsity, has said that one of the purposes of a business strategy should be to “formulate an integrated perspective, a vision, of where the organization should be heading,” A company’s business strategy and strategic planning process are important mechanisms companies use to get agreement and alignment on the current situation, where to go, and the alternatives and risks of action.
Innovation Strategy is about managing (un)certainty.
Certainty (and its counterpart – uncertainty) comes into play because many future states are inherently unknowable and, more importantly, non-probabilistic.  Companies often become paralyzed in the face of uncertainty, but uncertainty is inherent in the complex ecosystems they operate in. Uncertainty arises from the constant evolution of customer demand, from new technological possibilities and designs, from competitive surprises and from political, economic and social shifts. Managing this uncertainty is the defining purpose of an innovation strategy.Because the world is becoming more complex and uncertain, it makes sense to look at and deal with uncertainty as an end unto itself.
An innovation strategy is a company’s method to turn uncertainty into risks that companies are well suited to deal with. Defining an explicit innovation strategy that separates out the uncertainty factors and complements the company’s business strategy allows people within the company to explicitly discuss the uncertainties being faced and how to tackle them.
Managing uncertainty is a valuable end unto itself, and the Agreement-Certainty framework makes this explicit. Formulating a strategy for how the corporation will do this helps companies achieve clarity about a range of activities and priorities that will determine their future.
In terms of strategic thinking, a company needs both a business strategy for achieving agreement and an innovation strategy for managing uncertainty. Many companies today are creating an explicit innovation strategy separate and distinct from their corporate business strategy. It is a change that is needed as the world becomes more complex and uncertain.
More on the subject of Innovation Strategy, including a discussion of the necessary components, can be found on the Innovate-Innovation blog.
Risk and uncertainty are different. Risk refers to future states for which probabilities can be reasonably estimated. Uncertainty refers to future states for which a probability distribution cannot be reliably determined. See ‘Defining Risk and Uncertainty’ for a good discussion.
The innovation community is smart, vibrant and prolific. The following is a small selection of recent, insightful items that we’ve curated for you.
1. The Data Science Revolution by Eric Schmidt and Jared Cohen in Huffpost Blog
As computers evolve, we become liberated from tedious tasks. What will we do with all this “free time” and how will this liberating experience affect our lives?
According to Eric Schmidt, executive chairman of Google, “In the next 10 years, we believe that computers will move beyond their current role as our assistants, and become our advisors.”
Case in point is IBM’s Watson, the artificially intelligent (AI) computer. Recall its debut on game show Jeopardy in 2011, when it defeated the all-time champion, Ken Jennings. Today Watson is even more capable and already is being used in the medical field to improve diagnosis and treatment decision-making.
There are numerous other areas of our lives where an AI machine like Watson could make a huge, positive difference. Just think what city planners could do with this type of power to help solve daily problems or the benefits that company owners could reap by putting an AI on their Board (hint – this has already happened).
As the article concludes, “we will learn to build machines that go beyond executing tasks, and that will provide us with the kinds of insights that empower historic decision-making. It’s an exciting time to be alive.”
2. Innovators are Killing Us: Instead of reinventing housing or transit, they bring us companies like Airbnb and Uber by John Patrick Leary in Salon
Rarely do you hear the word “innovation” talked about as negatively as Leary does in this article. Some examples:
by Michael Docherty
Read by Brian Christian
One of the major business questions today is whether large corporations will successfully learn how to create disruptive new businesses, reinventing and even disrupting themselves along the way, or whether they are destined for the dust heap of history at the hands of nimble startups. Where some see the raging innovative disruption of industries as a battle between startups and large corporations, Michael Docherty sees the opportunity to succeed through collaboration. This means to leverage the strengths of both types of organizations – highly-motivated, fast-moving, risk-taking startups, supported by well-financed, talent-laden and influential corporations.
A plethora of empirical evidence exists that startups have an upper hand. Witness Uber, Netflix, Chobani and countless others. But there is also plenty of evidence that large organizations can learn to be disruptive and, in fact, do it repeatedly. Apple is a quintessential example, and the Fortune 500 is still populated by a number of 100-year old companies, many of which have reinvented themselves (General Electric, IBM). Others have created innovative new products and business models in a repeatable way (P&G, 3M, Corning and Johnson & Johnson, to name a few).
The movement among large corporations to become more nimble, serial creators of successful new businesses is in full bloom. Note the rapid market penetration of the Lean Startup,(1) Customer Discovery(2) and Business Model Canvas(3) methodologies promoted by Ries, Blank and Osterwalder. Or the plethora of conferences now dedicated to the topics of disruptive innovation, corporate venture capital and open innovation. Or the growth in consultancies in the past decade with a focus on strategic/disruptive/breakthrough innovation, including Innosight, Strategos, Docherty’s own Venture2, and, of course, The Inovo Group.
The prescriptions for corporations to become strategic innovators are expansive and growing. One can roughly divide this space into three categories: (1) opportunity discovery process (2) opportunity pursuit process (from concept to market adoption) and (3) mindset and culture change. Docherty’s contribution lies in the areas of opportunity pursuit process and mindset and culture change. He proposes that large corporations shed the idea that they need to go it alone and, instead, identify active startups — or fund new startups — with which they can co-create these transformative new businesses. This notion has obvious appeal; we all understand that 1+1=3 when complementary partners manage to play well together.
Docherty offers a range of suggestions for enabling corporate “elephants” to dance with startup “mice.” His suggestions will no doubt be helpful to those seeking success through the co-creation model. But it’s also fair to say that the book’s strength lies not in the novelty or ingenuity of these proposed frameworks. Rather it lies in the countless case stories, drawn from a wide range of corporate innovators and entrepreneurs, and the author’s sharp observations.
Docherty, as an astute explorer in the co-creation realm, has laid down a nice contour map of the geography to aid those that follow and to spark continued discussion.
by Alex Pentland
Read by Larry Schmitt
— Alex Pentland
In his book, Social Physics, Alex Pentland collects, codifies and enhances the science of social dynamics and communication. He defines Social Physics as “… a quantitative social science that describes reliable, mathematical connections between information and idea flow on the one hand and people’s behavior on the other.”
Pentland’s core hypothesis is that idea flow, of the right type, enhances innovation, creativity, social well-being and even the functioning of governments. The “right” type of idea flow is a flow that occupies a sweet spot between isolation (i.e. no external idea flow) and “echo chamber” (i.e. similar ideas shared only within a like-minded community). It is in this sweet spot where people are advancing their ideas, building on others’ ideas and challenging existing ideas, he argues, that the most creativity occurs. Where Pentland is strongest in his research and writing is in how to foster such an environment, a question that should concern any corporation or individual who is trying to innovate.
One item of note is that Pentland’s definition of an ‘idea’ is somewhat at odds with a ‘standard’ conception of what an idea is. He defines an idea as
Although he is consistent in his use of this definition it often leads to some strange formulations. The book also suffers from a high degree of self-promotion, and the egocentric writing style can be off-putting. Especially egregious is the presentation of foundational knowledge as if it were new. People have been looking at the social network effects of influence since 1969, when Frank Bass created the Bass diffusion model based, in part, on the work by Everett Rogers on the diffusion of innovation. Pentland’s oversight in acknowledging this rich history is a disappointment and results in it being difficult for the reader to place his work within a larger context.
Despite its flaws, the book provides interesting and valuable insights into the effects of social influence and dynamics that are only becoming more powerful in today’s connected world.