I am working in a field where researches try to get insight about a complex process. I will give an example to demonstrate this. Let's say, we are attempting to get the most efficient and cost effective energy input for a large and complex data center. Assume, there are hundreds of things that people measure right now (temperature, humidity, location, number of employees, demand, holidays, failover requirements, impact of human error, impact of different feedback loops in a system etc etc.). The result of such efforts is presented like: if the mean daily temperature is above 30 degrees Celsius, one may need 5% more energy input required for cooling.
Problem
The metrics collected are all diverse with no apparent middle ground to link them together. For example, it's difficult to link temperature data with impact of human error, despite the fact they both influence the process.
Question
Can I use measure theory to get a common ground for all this metrics? I am thinking to define measurable space, sigma algebras and measures.