Excerpt from Rath & Strong’s Six Sigma Leadership Handbook (Wiley, 2003)

 Chapter 11- Design for Six Sigma

DFSS in the Context of Existing Design Process

Companies that are already heavily invested in formalizing their new product development process often struggle as to how they should align the two methodologies. Two fundamental choices emerge: 

·                     Adding tools from the DFSS toolbox to the existing process

·                     Abandoning the existing process

In reality, the outcome of both methods does not differ that much. Even when the existing approach to new product development is abandoned completely, the company must still adopt some of the existing tools and methods to the DFSS roadmap to ensure that all of the competencies and skills required are represented in the new process. And picking and choosing tools from the DFSS toolbox to complement the existing approach makes good sense, but requires an upgrade of the management approach to manage the process. Both options work, and only a gap analysis of the existing process can show what approach to choose. The important difference between DFSS and the current process is not so much the tools being used, although the DFSS toolkit can offer some powerful statistical methods; the main difference lies in how the entire process is managed to ensure that the outcome is “on target with minimum variation.”

The twenty points that follow summarize the crucial lessons leaders should keep in mind when embarking on the DFSS journey.

DFSS – Twenty Points for Leaders

1. Conduct a formal evaluation of how effectively your organization develops and launches new product and services.

2. Treat the implementation of DFSS in exactly the same way you would a capital investment, focusing on costs versus benefits and Return on Investment.

3. Your organization probably does not have the data to indicate how well, or badly, the current development process is performing. Be prepared to invest in process management and measurement as a precursor to DFSS.

4. Measure your investment in DFSS over a three- to five-year period.

5. Implementing DFSS is hard work; as such there is a strong incentive not to do it. Reward behavior change, not just results.

6. Remove unnecessary bureaucracy.

7. Resource for success: DFSS projects are more complicated than DMAIC projects, so plan accordingly.

8. The training and coaching support required for DFSS is greater than for DMAIC, so plan accordingly.

9. Be prepared to radically review your resource requirements for development projects in order to reflect the change in emphasis from reaction to prevention.

10. Educate all your key stakeholders in the fundamentals of Six Sigma; you cannot introduce DFSS in a vacuum.

11. Do not build your DFSS initiative around specialists: use cross-functional teams from the start.

12. Include customers and suppliers in new product and service development projects.

13. Train your customers and suppliers in the philosophy of DFSS and the use of its tools and techniques.

14. Consider using DFSS initially for new process design: the projects are easier and can be completed much faster.

15. Select your DFSS Black Belts even more carefully than your DMAIC Black Belts. Ensure they are well trained and deploy them over a period of two to three years.

16. Create opportunities for your DFSS Black Belts to work on specific elements of the DMAIC process. Assign them small starter projects that can be completed in a relatively short time frame to learn the tools instead of hitting them with a huge first-time project that will take years to complete.

17. Resist the temptation to cherry- pick from the DFSS toolbox in order to bolster your traditional development process. DFSS is as much about leadership, management, and culture as it is about tools and techniques.

18. Don’t neglect creativity: one creative idea can transform your future.

19. There are multiple interpretations of what listening to the customer means. Beware of superficial efforts and insist on actual data.

20. Insist that your development teams produce the data to demonstrate at all phases of the DMADV process that they are “on target with minimum variation.”

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