Innovation and experimentation are vital to the longevity of any organization, says Stefan H. Thomke in his new book Experimentation Matters: Unlocking the Potential of New Technologies for Innovation. In this interview, Thomke, an associate professor of technology and operation management at Harvard Business School, discusses how businesses can sidestep the often prohibitive costs and time-consuming trials of experimentation by implementing new technologies.
Wendy Guild: We've all heard the old saw, "If it ain't broke, don't fix it." How dangerous is stasis to an organization and what are some of the possible negative consequences of remaining stagnant?
Stefan Thomke: Competitive environments and technologies are constantly changing, which creates both wonderful opportunities to innovate and grave threats if we fail to respond to such changes. For example, my book shows that product and service development is changing; creating the potential for higher R&D performance, innovation, and value creation for customers. The choice is simple: Organizations can either ignore these changes or take action and tap into this new potential.
Q: What are the first steps in assessing which management practices and processes in an organization could benefit from experimentation?
It is important to understand that experimentation matters to managing change and uncertainty.
A: It is important to understand that experimentation matters to managing change and uncertainty at four different levels: technical (can it work?), production (can it be produced?), need (does it address customer needs?), and market (is it big enough to justify the investment?). So managers need to assess at which level the uncertainty and opportunity for innovation is the greatest. For example, a set of well-designed business experiments can address new and unknown markets. In contrast, running experiments where early product prototypes are shown to customers can address need uncertainty.
Q: How should organizations respond when experiments fail?
A: We need to appreciate that new knowledge comes as much from failure as it does from success. Innovators learn from failure: Understanding what doesn't work may be at least as important as understanding what does, provided these failures are revealed early in a project and are swiftly reexamined. Learning from failure is a boon at this point: Few resources have been committed and decision making is flexible, meaning that other approaches can themselves be tested. Thus, experiments that result in failure should not be viewed as failed experiments.
Q: New experimentation technologies are helping to reduce the time and cost of innovation. What are some of the new "star" technologies and how can the average business integrate them in order to conduct low-cost, rapid testing?
We need to appreciate that new knowledge comes as much from failure as it does from success.
A: Rapid advances in technology are changing the economics of experimentation and are triggering fundamental changes in R&D processes and performance in such fields as integrated circuit design, automotive development, and pharmaceutical drug discovery. Computer modeling and simulation, rapid prototyping, and combinatorial technologies drive down the marginal cost of experimentation and allow companies to create more learning more rapidly, provided that managers can capture that potential. My book provides a roadmap of how the average business can take advantage of these new technologies.
Q: How can businesses shift experimentation to their customers?
A: The final chapter of my book explores how this can be done. Essentially, I show how some companies have abandoned their efforts to understand exactly what products their customers want and have instead equipped them with tools to design and develop their own new products, ranging from minor modifications to major new innovations. The user-friendly tools, often integrated into a "toolkit" package, deploy new technologies (e.g., computer simulation and rapid prototyping) to make innovation faster, less expensive and, most importantly, better, as customers run "what-if" experiments themselves. A variety of industries have started to use this approach.
