Stefan Thomke, an authority on the management of innovation, is the William Barclay Harding Professor of Business Administration at Harvard Business School. He has worked with global firms on product, process, and technology development, organizational design and change, and strategy.
Since joining the Harvard faculty in 1995, Professor Thomke has taught and chaired numerous MBA and executive courses on innovation management, R&D strategy, product & service development, and operations, both at Harvard Business School and in individual company programs around the world. He is chair of the Executive Education Program Leading Product Innovation, which helps business leaders in revamping their innovation systems for greater competitive advantage. Professor Thomke is currently on the core faculty of the General Management Program (GMP) and has previously taught in the Advanced Management Program(AMP). He has also chaired and taught in numerous senior executive leadership programs around the world. Previously, he was faculty chair of the MBA Required Curriculum, faculty co-chair of the doctoral program in Science, Technology and Management, and chair of HBS executive education in India. He is the recipient of numerous awards, including the Apgar Award for Innovation in Teaching at HBS and a HBR McKinsey Award Finalist.
Professor Thomke's research and writings have focused primarily on the process, economics, and management of business experimentation in innovation. He is a widely published author with more than one hundred articles, cases and notes published in books and leading journals such as California Management Review, Harvard Business Review, Journal of Product Innovation Management, Management Science, Organization Science, Research Policy, Sloan Management Review, Strategic Management Journal and Scientific American. He is also author of the books Experimentation Matters: Unlocking the Potential of New Technologies for Innovation (Harvard Business School Press, 2003) and Managing Product and Service Development (McGraw-Hill/Irwin, 2006).
Professor Thomke was born and grew up in Calw, Germany. He holds Bachelor and Masters degrees in Electrical Engineering, Masters degrees in Operations Research and Management (MBA equivalent), and a Ph.D. degree in Electrical Engineering and Management from the Massachusetts Institute of Technology (MIT) where he was awarded a Lemelson-MIT doctoral fellowship for invention and innovation research. Professor Thomke was also awarded honorary degrees in Economics (Doctorate from the HHL Leipzig Graduate School of Management) and Arts (Masters from Harvard University). Prior to joining the Harvard University faculty, he worked in electronics and semiconductor manufacturing and later was with McKinsey & Company in Germany where he served clients in the automotive and energy industries.
Contact information: Harvard Business School, Soldiers Field, Morgan Hall 489, Boston, MA 02163 (U.S.A.); Telephone: +1 (617) 495-6569; Fax: +1 (617) 496-4059, E-mail: t@hbs.edu.
For a very detailed biography, see Curriculum Vitae (Additional Information section).
In the fast-moving digital world, even experts have a hard time assessing new ideas. Case in point: At Bing a small headline change an employee proposed was deemed a low priority and shelved for months until one engineer decided to do a quick online controlled experiment--an A/B test--to try it out. The test showed that the change increased revenue by an astonishing 12%. It ended up being the best revenue-generating idea Bing ever had, worth $100 million. That experience illustrates why it's critical to adopt an "experiment with everything" approach, say Kohavi, the head of the Analysis & Experimentation team at Microsoft, and Thomke, an HBS professor. In this article they describe how to properly design and execute A/B and other controlled tests, ensure their integrity, interpret results, and avoid pitfalls. They argue that if a company sets up the right infrastructure and software, it will be able to evaluate ideas not only for improving websites but also for new business models, products, strategies, and marketing campaigns--all relatively inexpensively. This will help it find the right path forward, especially when answers aren't obvious or people have conflicting opinions.
by Stefan Thomke and Jim Manzi (HBR McKinsey Award Finalist)
The data you already have can't tell you how customers will react to innovations. To discover if a truly novel concept will succeed, you must subject it to a rigorous experiment. In most companies, tests do not adhere to scientific and statistical principles. As a result, managers often end up interpreting statistical noise as causation—and making bad decisions. To conduct experiments that are worth the expense and effort, companies need to ask themselves several questions: Does the experiment have a clear purpose? Managers must figure out exactly what they want to learn in order to determine if testing is the best approach. Have stakeholders made a commitment to abide by the results? Are they willing to walk away from a project if the findings suggest they should? Is the experiment doable? The complexity of the variables in a business experiment and their interactions can make it difficult to determine cause-and-effect relationships. Choosing the right sample size is important. How can we ensure reliable results? Randomized field trials, "blind" tests, and big data can help. Have we gotten the most value out of the experiment? Conducting the experiment is just the beginning. Use the data to assess which components of a new initiative might have the highest ROI or the markets where it is most likely to be successful.
Many companies approach product development as if it were manufacturing, trying to control costs and improve quality by applying zero-defect, efficiency-focused techniques. While this tactic can boost the performance of factories, it generally backfires with product development. The process of designing products is profoundly different from the process of making them, and the failure of executives to appreciate the differences leads to several fallacies that actually hurt product-development efforts. In this article, the authors, an HBS professor and a consultant, expose these misperceptions and others. They look at six dangerous myths: 1) High utilization of resources will make the department more efficient; 2) Processing work in large batches will be more economical; 3) Teams need to faithfully follow their development plan, minimizing any deviations from it; 4) The sooner a project is started, the sooner it will be finished; 5) The more features a product has, the better customers will like it; and 6) Projects will be more successful if teams "get them right the first time." The authors explain the negative effects these "principles" have when applied to product development, offer practical guidelines on overcoming them, and walk readers through a visual tool that will help them keep projects on track.
Every company's ability to innovate depends on a process of experimentation whereby new products and services are created and existing ones improved. But the cost of experimentation is limiting. New technologies—including computer modeling and simulation—promise to lift that constraint by changing the economics of experimentation. They amplify the impact of learning, creating the potential for higher R&D performance and innovation and new ways of creating value for customers. In this book, Stefan Thomke argues that to unlock such potential, companies must not only understand the power of new technologies for experimentation, but also fundamentally change their processes, organization, and management of innovation. He shows why experimentation is so critical to innovation, explains the impact of new technologies, and outlines what managers must do to integrate them successfully.
