Episode Summary
In this episode of our predictive maintenance series, we take a step back and tackle something many sites skip: defining the problem before jumping into PdM.
Before selecting assets, installing sensors, or launching a pilot, maintenance and reliability teams need to be clear on what they’re actually trying to improve. Is the goal to reduce reactive work? Extend inspection intervals? Increase MTBF on key asset classes? Without alignment on the problem, PdM pilots often drift, expectations collide, and even good results can be misunderstood.
We talk through what a strong PdM problem statement looks like, share examples with clear metrics, and discuss how teams can align around success before any technology is introduced. We also address a common concern many sites raise: “We don’t even have good data.” The reality is that every site has signals to start from, even if they’re messy.
If you’re considering predictive maintenance or planning a pilot, this episode will help you start in the right place: clarity before technology.
Chapters
00:00 Introduction to Predictive Maintenance
01:57 Defining the Right Problem
08:19 Crafting a Clear Problem Statement
28:51 Data Challenges in Predictive Maintenance
34:09 Conclusion and Next Steps
Sound Bites
"Start with a problem, not just more data."
"Measure the impact over a realistic timeframe."
"Align your team and get buy-in early."
Keywords
predictive maintenance, problem statement, asset management, reliability, maintenance strategy, data quality, pilot projects, business outcomes
