1. Let the Data Lead. Don’t assume you know where the savings are. Gut feel only goes so far, and in the end you will need to back everything up with good data.
2. Encourage Your Data to Be Challenged. If you are working with a data set that points to savings opportunities, it has got to stand the test of the end customers. Otherwise, they will not believe it which means they will not participate in your study. Let them challenge your data, then prove that it is valid. Sometimes customers point out factors that you are not thinking about that will make your study better!
3. Test Your Assumptions. At some point you are going to have to perform value analysis assessments to validate the reasons why a utilization overrun is occurring. Talk to your internal experts, visit the departments to visually validate and see the product(s) in question in action. See it with your own eyes whenever possible!