Experimentation, Innovation and Technological Change

1. Stefan Thomke Harvard Business School Experimentation, Innovation and Technological Change Advancing Knowledge and the Knowledge Economy Washington, D.C. January 10, 2005

2. Today The Process, Economics and Management of Experimentation • Experimentation is critical to product development and needs to be managed explicitly (e.g., organization, process design choices, technology adoption). • New technologies (e.g., computer modeling and simulation) amplify the impact of experimentation and create the potential for higher R&D performance, product innovation and value creation for customers. • The integration of these new technologies have organizational, managerial and process implications for innovators.

3. Why Experimentation Matters to Learning by Doing and Innovation Source of uncertainty How can uncertainty be resolved? • Technical • Can it work? • Production • Can it be effectively produced? • Need • Does it address customer needs? • Market • Does the market size justify the resource investment? 1. Experimentation 2. “First Principles” 3. Experience

4. Technology Potential: The Changing Economics of Experimentation • New technologies (e.g., computer modeling/simulation, rapid prototyping) are making it easier than ever to conduct complex experiments quickly and cheaply. • Potential increases in efficiency and speed (e.g., substitution of costly prototypes with long build times). • New possibilities through “what-if” experiments that were previously too costly and impractical (e.g., simulation models in integrated circuits, flight simulators). • These technologies are being broadly adopted in many industries (e.g., automotive, semiconductors, pharmaceuticals) and professional fields (e.g., engineering, science, medicine).

5. Research Example: Crash Simulation and Modeling in Automotive R&D • 1982: Simulation model using CRASHMAS (3,000 finite elements). • Run time nearly three months. • No real significance in design decisions. • 2002: Simulation model of X5 using PAMCRASH (about 700,000 finite elements). • Run time less than 30 hours (at less than $10/hour). • Drives important design decisions. Source: BMW AG.

6. Technology-Performance Paradox: Empirical Findings from Car Industry • Large-scale empirical study of project performance drivers in global car industry (started in 1980s with Clark/Fujimoto) • Late 1990s: U.S. companies were leading in the deployment of sophisticated technologies (e.g., CAE, 3-D CAD). • But Japanese companies integrated these technologies more effectively into their development organizations by: • Earlier use of simulation that forces earlier problem-solving. • Having fewer organizational interfaces in order to accelerate experimentation and problem-solving cycles. • Using fewer functional prototypes; they are built rapidly for immediate feedback on design problems and solutions.

7. How Can Companies Unlock the Potential of New Technologies? • My research focused on what does and does not work when the value of experimentation is captured. • Large empirical studies, grounded field research, and analytical methods revealed a set of principles that are robust across companies and industries. • While some of the management principles seem intuitive, the reasons why companies do not follow them are complex and subtle. • These reasons can be understood through the lens of experimentation.

8. Unlocking the Potential: Principles for Managing Experimentation • Organizing for Rapid Iteration. • Organizing for rapid experimentation. • Fail early and often but avoid “mistakes”. • Manage projects as experiments. • Experimenting Early and Often. • Anticipate and exploit early information through front-loaded process. • Experiment frequently but do not overload your organization. • Integrate new and traditional technologies to unlock performance. • Shifting the Locus of Experimentation & Innovation (with Eric von Hippel, MIT).

9. Shifting Experimentation to Customers via Design Toolkits Traditional Model New Model: Reverse Information Flow Need Information (“What do I want”) Need Information (“What do I want”) Solution Information (“What is possible?”) Solution Information (“What is possible?”) Customers Customers Supplier Supplier “Innovation Toolkits” “User Research”

10. LSI Logic Founded in 1981: A Radical Approach Transforms Chip Design Focus Solution Information (“What is possible?”) Need Information (“What do I want”)

11. Customers design chips that are produced by LSI. User-friendly and integrated toolkit (using simulation and CAD technology). Traditional suppliers were reluctant to make tools available to markets (intellectual property). Fujitsu even refused to share its tools with US division. Shifting Design Locus: LSI’s Development Toolkit Source: LSI Logic.

12. From Design Toolkits to New Markets: The LSI Model

13. An Industry Transformation: Creating Value by Shifting the Locus of Design

14. BACK-UP

15. Industry Study of Product Development: Global Automotive Project at HBS • Background of research project: • 1980s: First study by Kim Clark and Takahiro Fujimoto; 29 car development projects; book published in 1991. • Early 1990s: Second study by Kim Clark, David Ellison and Takahiro Fujimoto; 27 projects; David’s thesis. • Late 1990s: Third study by Takahiro Fujimoto and myself (with support from Kim); 22 projects; new book project. • In the third study, companies answered about 400 questions per project, including on the use of new technologies (e.g., CAD, simulation, rapid prototyping).

16. Department A Department B Learning by Experimentation: Testing of Innovative “What-If” Ideas Interface(s) Design (new concepts) Analyze Data (modify understanding) Build Model (prototypes) Run Test (collect data) Iterations Learn

17. Global Automotive Study at HBS: Actual vs. Expected Engineering Hours Source: Global Automotive Development Study at HBS.

18. Global Automotive Study at HBS: Actual vs. Expected Development Time Source: Global Automotive Development Study at HBS.

19. The Pattern is Repeated: The Rise of Field Programmable Technologies

20. 30 years of in-house expertise on website (tools): $5 mill. cost. Potential customers can solve their own design problems. Helpline calls dropped >50%. 400 e-seminar for 8,000 potential customers per year. About one million visitors p.a. Automatic screening and tracking of potential customers. One third of new customers. Sales threshold dropped by more than 60%. Creating Value with Toolkits: Experiences at GE Plastics Source: GE Plastics.

21. Summary • Managing Experimentation: Experimentation is critical to product development and needs to be managed explicitly (e.g., organization, process choices, technology adoption). • The Changing Economics of Experimentation: New technologies (e.g., computer modeling and simulation) amplify the impact of experimentation and create the potential for higher R&D performance, product innovation and value creation for customers. • How to Unlock The Potential of New Technologies: Companies that master and integrate these technologies must change their processes, organization and management of innovation.

22. How “Best Practice” Moves Big Markets Out of Reach for Companies