1) 'The Old Guard' who are extremely skeptical. They tend to be extremely dismissive of models and predictions, distrust anything but most basic analysis. If they can't do the analysis on an excel spreadsheet it's too complicated and "will never work". These people tend to be Engineers (mechanical and chem type) and Plant Operations roles. A lot of the time there is value in listening to there skepticism but they tend to be extremely conservative by nature (Fortran ort to be enough for anyone...).
2) 'The Optimists' people who think "big data" and "machine learning" is the panacea to every problem in our org. To these people a prediction is a good as a real measurement - they trust forecasting implicitly. They have probably read an article somewhere about machine learning but don't really grasp any of the intricacies. These people tend to be in logistics/accounting/finance type roles and a large part of my job tends to be spent in phone calls with these people explaining why their forecasts did not match the actual results.
3) 'The KPI guy' - usually a manager who is somewhat out of their depth who wants to distill everything he can into a single number which can be displayed on a dashboard. The end result is a dilbert-esque situation where the 'KPI guy' decides that to make his mark in the org he needs to come up with a new metric. You end up with the bizarre situation where people are discussing a 'super metric' made by combing other metrics into a single number. I also spend a lot of time on phone with these guys because they forget what undpin their super metrics and don't understand all the subtleties they've distilled out of the data by focusing so much on higher level metrics. They get angry when you question the value of their dashboard. Whenever someone starts talking about "Yield" "OEE" "DIFOT" good chance they are a 'KPI guy'
Most of my job is balancing out interactions between the three 'customers'. Tempering the optimists enthusiasm, reigning in the KPI guys and nudging the Old Guard.