How to manage uncertainty in innovative projects
A week ago I finished the first full draft of my MSc thesis. The title is Managing uncertainty in innovative projects: The experimentation-driven approach. My basic argument is that uncertainty is essential for innovation - the more uncertain your project outcome is from the get-go, the more chances you have for creating something truly novel. Contrast this to a project where the outcome is a predefined target of e.g. increasing production line energy efficiency by 10%. Unfortunately, the way most projects are managed - even those that aim for novelty and innovation - the focus is on eliminating uncertainty, or simply ignoring its existence in the first place. (1)
Perhaps most interestingly, however, my research shows that even seemingly simple and mundane projects may contain uncertainties that cannot be planned for (i.e. they cannot be predicted beforehand), and those uncertainties can be very significant for the outcome of the project. I studied how an experimentation-driven approach to managing innovative projects can be used to uncover these uncertainties, as well as validate our existing claims and assumptions regarding the idea we are pursuing. The result? It works very well indeed.
In short, the experimentation-driven approach starts with an idea you want to develop, identifying the key assumptions regarding that idea, and coming up with creative ways to test those assumptions in practice. Key assumptions are those that can either make or break the idea. In the case of Zappos, which has grown to become the largest online shoe store, the key assumption in the beginning was "are customers willing to buy shoes online, without seeing and trying them on before purchase?" Where a business school educated MBA graduate would have approached this topic by spending hour after hour doing market research, crafting a business plan - which in itself is a fictitious document describing a reality that is definitely not going to happen - and carefully calculating cash flow potential, the founder of Zappos did something else: He went to a local shoe store, asked the owner if he could photograph the shoes and put those for sale online. If someone would make a purchase, he would then buy the shoes himself from the store and ship them to the customer. No IT systems, no warehouses, no marketing. Just a rudimentary website that helped validate the key assumption, without which there would be no business. And in the process he also learned a thing or two about what kind of payment options to offer, how to handle returns, how to do customer service and so on. (2, 3)
The basic assumption behind experimentation-driven innovation is that uncertainties cannot be resolved by planning. As a method it shifts the focus to learning as much as possible about your idea, quickly, while keeping costs low. Furthermore, when experimentation is the main tool, what you learn will be based on experience, not on assumptions. In other words, you get actual proof about the validity of your idea. This is especially true when your idea has anything to do with human behaviour as opposed to something that is purely mechanistic. For example, in one of the cases I studied a simple idea aimed to increase motivation and decision-making of employees lead also to increases in productivity, teamwork, trust between workers and the supervisors, and perhaps most surprisingly got the workers to proactively start taking ownership of and improving the internal work processes in the team. It might be too far off to say that none of these effects could not have been seen beforehand by thorough planning, but even so, without actually experimenting the idea there would have been little proof about them.
In fact, quite often it is simply less costly and much faster to do a hands-on experiment to see what happens instead of planning all the possible scenarios inside one's head. As my boss in the MIND research group has a habit of saying; "show, don't tell."
Perhaps the most interesting thing that has happened in the field of entrepreneurship research in the past 15 years is the work done by Saras D Sarasvathy from University of Virginia and her colleagues. She studied how expert entrepreneurs - meaning people who have built businesses with annual sales between $200 million and $6.5 billion - approach starting a new venture. And guess what? They pretty much use approaches similar to the experimentation-driven method, focusing on what they can do with their existing means, using low-cost ways to validate their key assumptions, and getting the first customers and other stakeholders on-board. In other words, they focus on acting instead of planning, control instead of prediction, and without risking what they cannot afford to lose. (4, 5)
It is becoming something of a cliche to say that the world is getting more and more complex, and that uncertainty is similarly increasing as a result. However, the advent of Big Data has not made us much better at uncovering uncertainties, especially in emerging contexts where there might not exist any data. This calls for a model of rational decision-making that is not rooted in the Newtonian worldview of clear cause-and-effect relationships and linear thinking. When it comes to creating something innovative, the focus needs to shift from emphasis on prediction to emphasis on control - meaning that you put your energy into what you can do, here and now, to develop your ideas and keeping options open so when uncertainties inevitably do happen, you are able to learn from them and adapt your approach.
The future is constantly being created and shaped by human action. It does not exist 'out there' to be predicted. And this means it is up to you to help create the kind of future you want.
References:
(1) Kline S. J., & Rosenberg N. (1986). An Overview of Innovation. In Landau, R., & Rosenberg, N. (Eds.) The Positive Sum Strategy: Harnessing Technology for Economic Growth, Washington: National Academy Press, 275-305.
(2) Sykes, H. B., & Dunham, D. (1995). Critical assumption planning: A practical tool for managing business development risk. Journal of Business Venturing, 10, 413-424.
(3) Hsieh, Tony (2010). Delivering Happiness: A Path to Profits, Passion, and Purpose. New York: Business Plus.
(4) Sarasvathy, Saras D. (2008). Effectuation: elements of entrepreneurial expertise. Cheltenham (UK): Edward Elgar Publishing.
(5) Dew, N., Sarasvathy, S., Read, S., & Wiltbank, R. (2009). Affordable loss: behavioral economic aspects of the plunge decision. Strategic Entrepreneurship Journal, Vol. 3, Iss. 2, 105-126.