A recurring challenge exists across the process industries, namely, how to integrate the data from ever-more complex sensors with the domain knowledge of what works in that process, borne out of vast experience.

Interestingly, a similar problem faces endurance sports, where a dizzying array of data can now be easily collected. Unfortunately, this has led to a situation in which the athlete is presented with masses of data but not necessarily the tools to understand what it is telling them about their performance.

In this talk, we explore how:

• JMP can simplify the preparation and analysis of training data, providing a route to testing long-held beliefs about what works.
• How JMP can streamline the exploration of time series curved data, allowing us to see the whole picture.
• How DOE can provide a convenient approach to testing a range of possible improvements.

Armed with this knowledge, we can now answer the question, “How best to operate this complex system?”