In my previous post, we looked at how stakeholders and organizational structures influence decisions about what data is collected and exposed for use. If you haven’t seen machine data before, that post might have felt a little abstract and some things might have felt contradictory (e.g. how does one look at the events before a failure without any sensor data?). For people who prefer concrete details and real examples, this post is for you.

This post will be the first of two that discusses how organizational dynamics, stakeholder incentives, and the goals of the business drive decisions about what data is collected and why. What is discussed is relevant to companies trying to do predictive maintenance on industrial and commercial machines, but it applies to other industries as well.