Lean Six Sigma and Promoting Innovation

Authors

  • Douglas C. Montgomery


About 40 years ago, approximately about one in four US workers were in manufacturing; today, it is about one in ten. Only about 30% of current US GDP derives from manufacturing. The numbers in Europe are approximately comparable. This should not be a huge concern. In the early 1800s, about 70% of the US workforce was involved in agriculture, compared to less than 5% today. Yet, the agriculture productivity of the USA is unsurpassed.

Most of the really important work being done now and in the future will be done by knowledge workers. This includes new technology creation, the design and development of products and services based on this new technology, and improvements in productivity in existing technologies. This is the process of innovation. There are two kinds of innovation: breakthrough innovation that creates new technology and incremental innovation that improves existing technology to increase productivity, product function, and reliability. Energy, pharmaceuticals, transportation, and communications are examples of industrial sectors where breakthrough innovation will lead to economic growth and development. The automotive, electronics, chemical, and medical device industries often provide examples of incremental innovation.

Lean Six Sigma and the associated tools of quality technology should play a major role in this. Unfortunately, these tools are most often thought of in terms of their application to manufacturing. But many aspects of the Lean Six Sigma tool kit are essentially knowledge generation tools. Designed experiments are an obvious example. Well-planned, well-designed, correctly executed, and properly analyzed experiments are in my view one of the most powerful tools of innovation available to business organizations. Practitioners of Lean Six Sigma and quality professionals in general should position themselves to play a key role in the knowledge economy by thinking of themselves as innovation engineers.

How do we get the word out that Lean Six Sigma and the associated statistical techniques are an integral part of the general process of innovation? A good start is publicizing your successes. Lean Six Sigma projects often contain excellent case studies of innovation. Some ways to get a wider audience for these examples of innovation include the following:

  • Post a descriptive summary of the project and the key results on an internal company website where it will be seen by many fellow employees.
  • Participate in internal technical meetings and conferences that your organization conducts.
  • Give a presentation at a local chapter meeting of a professional society such as ASQ, INFORMS, the American Management Association, ENBIS, or the Institute of Industrial Engineers.
  • Present a paper at a regional meeting of a professional society, such as those listed above.
  • Give a presentation at a national meeting of a professional society. The ASQ, the American Statistical Association, and INFORMS have national meetings annually as well as some specialized conferences that are appropriate for these types of presentations such as the Fall Technical Conference and the Quality and Productivity Research Conference. INFORMS has a conference every year devoted to practice that could be an excellent venue.
  • Publish a case study paper describing how you successfully used Lean Six Sigma or other statistical techniques to achieve an innovative solution to an important business problem. Quality and Reliability Engineering International would be good outlet for many case studies; our interest is on case studies that illustrate the novel application of standard tools or the deployment of those tools in new or nontraditional settings, and the application of new techniques and methods.

There are other possibilities, such as contributing to a blog or writing for newsletters. The key idea here is to spread the word and advertise success. People outside of our community need to see the enormous potential for innovation in the techniques and methods that Lean Six Sigma and statistical tools have to offer.

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