• To take a "teach by example" approach, using real, sequential case studies from the business world to motivate and illustrate topics and make them memorable. 

• To present the "big picture" (i.e., overall approaches to operational improvement) first so that participants will understand why they need statistical thinking and methods and what these tools can do for them. 

• To demonstrate that statistical thinking and methods are key to operational improvement, by utilizing the powerful information contained in data. 

• To address the fact that most real operational applications occur in a dynamic process, rather than a static population. Assumes a "dynamic process" rather than "static population" context for data throughout the course. 

• To teach and illustrate fundamental concepts, such as the importance of a process viewpoint, the omnipresence of variation, the need for understanding, quantifying, and reducing variation, how to integrate individual tools into an overall approach to improvement, the value of good data, and the need to integrate data with subject matter knowledge. 

• To relegate calculation to the computer, freeing participants to develop their understanding of the concepts behind the proper application of statistical methods. 

• To develop learning and practical skills in data analysis by involving participants directly in applying material to real problems.

Programme Outline