Having lived in Texas I was always amused by the sayings. Most of the time they were polite and humorous ways to flag stupidity or make a point. So with that I will use some popular sayings to relay some best practices in a Predictive Maintenance project.
All hat and no cattle
A lot of companies start their predictive maintenance efforts with their current big iron vendors. I shake my head every time an IBM commercial comes on. You can’t buy a smarter planet or Watson but you sure can spend a lot of money on consultants who know very little about your business and try to build it on your dime. If you want to outsource your data center or fund a big consulting engagement then call a big iron company. If you want to get results quickly then find a company who has some industry experience in improving maintenance and is willing to spend some time with you understanding the business. At the very least include a few companies in your initial evaluation. You will learn more and be able to sort the fact from fiction.
When all you have is a hammer every thing looks like a nail.
This saying was popularized by the psychologist, Abraham Maslow, in the 60’s. Everyone has heard it. If you hire a consulting or outsourcing company to help with your predict analytics project don’t be surprised when the answer is “we need to study this more and bring in more people”. When you hire a company who specializes in cloud infrastructure or building data lakes to help with predictive analytics don’t be surprised when they tell you “you need a data lake first.” Nothing wrong with spending a lot of money on consulting or building a data lake it just does little to solve your maintenance problems. When your problem is improving maintenance you need a solution designed to improve maintenance. When you start a project for Predictive Maintenance make the project about maintenance results, which is what my next saying is about.
“Be careful how you make your bed because you have to sleep in it.”
This is an old saying and it is something my grandmother actually said to me as I was leaving home after graduating college. My reaction was “yeah whatever grandma” but in hindsight I realize that my grandmother gave me a mighty snippet of southern country wisdom. In projects involving predictive analytics this should be the tagline. A lot of projects go well but some don’t. The difference is how the project is planned. It’s called Predictive Maintenance – the word “predictive” is an adjective to the noun “maintenance”. The subject is maintenance! Make the project about maintenance. If you focus on what predictive analytics can do for your maintenance processes you are off to a good start. If you focus on predictive analytics as the subject you are off to my next saying:
A long road to a small house
This one simply means a lot of work for nothing. If you ask a data scientist what success means they will start off on algorithms, prediction accuracy, recall rates, etc. If you ask a maintenance manager what success means he or she will answer in availability or return on asset. What are the metrics for your predictive maintenance project – if you hear words like precision, recall, accuracy you are on a “long road to a small house”. Let me give you an example. A predictive model has been built to flag a problem that will cause a locomotive to fail but it is only correct one out of ten times. The data scientist would likely dismiss this as a failure. However if you go to the maintenance manager and tell him to perform this ten minute test on certain locomotives the next time they come in for planned maintenance and that for every ten you check you will prevent one catastrophic line of road failure, watch him smile. That is a big win or as they say in Texas, In high cotton.