WSJ: Efficiency Demands Predictive Maintenance – True or False?

Oct 12, 2022 | Leadership in Maintenance Articles, Resource Library, TRM Blog | 0 comments

John Q. Todd

Sr. Business Consultant/Product Researcher

Total Resource Management (TRM), Inc. 

Oh my… those few words recall all kinds of nightmarish scenarios involving spreadsheets, consultant’s reports, corporate messaging, and industry buzz words. It’s ok. We can talk it through. The strive for more and more efficiency cannot be ignored… the demand is too high!

We ran across an article written by the Wall Street Journal that inspired this post. Given that we work with clients who want to (or are being forced to!) use modern maintenance tools and techniques to increase their efficiency, we wanted to add to the conversation.

For your reference, here is the WSJ article:


Getting from point A to point B?

If you want to get from one place to another using the most efficient route, then you need information about the options you have. A particular route could be deemed efficient one day, but not the next. Maybe all routes are similarly efficient, but the cost varies considerably.

Take your typical travel planning application as an example. Using near-real time data, these apps point out your choices and let you know if your current route is still the most efficient. Or not… maybe you picked one that was less so, and in the end, it worked out the best for you!

You get to decide what “efficient,” means… the app uses its access to vast amounts of data to “predict,” how your trip there will progress.


Efficiency, efficiency, efficiency!

This is not a new call for anyone in the manufacturing world. While the roadblocks to achieving whatever level of efficiency continue to be varied, multi-faceted, and relentless, they are still just roadblocks that we either see coming… or not.

Efficient use of time, materials, and money are at the forefront of every single day in just about every business on the planet. Efficiently creating value in the eyes of your customers is what keeps you in business. Loose sight of efficiency and the business quickly suffers.


Predicting outcomes? How on earth does one do that?

We all remember the kid in school who everyone thought would turn out to be… well, you can fill in the blank. Many times, we have been proven to be correct! How did we know?

Easy… we had data to base our predictions upon. Perhaps it was qualitative vs. quantitative data, but it was data, nonetheless. We had something to start our observations and judgement with. Add this data set to the skepticism we felt from our parents when we brought that new friend from school by the house. We did well with our predictions!

Not so new really, but we have access to vast amounts of operational data, some coming directly from the equipment we maintain that help us make predictions. This data can be in the form of raw numbers that need to be crunched to make any sense of, but it can also be observational in nature… not by humans necessarily… that can give us insights.

There are rivers of data, often from a variety of directions and sources, available to maintenance operations today, as well as the software tools to make sense of it all. Only a few years ago they were the realm of the data scientist or reliability engineer. Lately these tools have become much more accessible to a wider audience, and some do predict real problems lurking in the dark.


Prediction reduces the unexpected

Back to the mapping application as we journey to the swanky restaurant. Our chosen path gives us a sense of how long it will take in addition to the miles to drive. What may be a few short miles can be quite the long period of time for many reasons. Just like driving in Los Angeles, it not the miles it’s the time it takes to travel those miles.

In our industry there are a growing number of tools available to ingest our data and provide a degree of prediction so we can make decisions and avoid troubles. Even if the result is along the lines of, “Seems like there are more and more anomalies coming from Pump A since before the rebuild,” it is a result that can prompt you to take a deeper look.

Sure, it would be nice if our new AI friend could tell the day or the hour of a failure… and some are coming close… but for now the tools do a far better job pointing us in an action direction that just what our parents inferred to us years ago.


By the numbers

If your organization is sounding the efficiency alarm, then we would hope that they have a number to work towards. Given a specified efficiency goal… let’s say a 1% decrease in downtime, then we can make use of tools and data to confirm (or not) that our maintenance operation is participating in the new wonderfulness.

It may seem an obvious statement, but there is significant value to being able to predict failures or reductions in output. These unfortunate events… as if fortune has anything to do with it… directly detract from your efficiency goals. Even better, if you can make a prediction… that truly is avoided, then you can apply that value to meeting the efficiency goals.


Wrap up

Where to start? Go ahead and search the internet for “predictive maintenance.” You will be presented with 120,000,000+ hits that should keep you busy for a while. (Lots of data to work with, right?) Everyone, (including us) will be touting their wares and methods to help you get started. Your challenge is to sort out who can truly help you get from point A to point B… and perhaps to point C, D, etc.

Make contact and let’s talk about the issues and/or goals you might have in the areas of predictive maintenance. You could discover that your organization does not need to venture into prediction, but perhaps simply refine your maintenance approach. Of course, you may find ways to take advantage of your data set to your benefit with simple tools readily available on your current systems. No matter where you are now TRM can help predict your path and potentially greatly reduce any roadblocks that you know are out there waiting for you.



John Q. Todd, Sr. Business Consultant / Product Researcher at TRM. Reach out to us at if you have any questions or would like to discuss deploying MAS 8 or Maximo AAM for condition-based maintenance/monitoring.




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