Struggling to turn pilot projects into full-scale PdM success? You’re not alone.
We recently published a whitepaper on the five biggest barriers holding manufacturers back from digital transformation, including predictive maintenance (PdM) initiatives - and what it actually takes to overcome them.
This blog series breaks down each of those barriers in more detail, starting with what’s keeping teams stuck in reactive mode.
Want the full picture? Download the whitepaper here.
The barriers are real – and they’re not just technical.
Predictive maintenance is often promised as a game-changer: less downtime, reduced costs, and smarter asset decisions. But, why are so many manufacturers still stuck in reactive mode or paused at pilot stages? The interest is there. What’s holding teams back are deeply rooted technical, strategic, cultural, and financial challenges.
So, what’s the holdup?
Despite growing interest and increasing pressure to modernize, many manufacturers find themselves spinning their wheels. Promising pilots stall. Scaling proves elusive. And the benefits of predictive maintenance remain out of reach. That’s because the roadblocks aren’t always obvious or easy to solve. They’re embedded in the very fabric of how most operations are built and run.
The good news? For every barrier, there’s a practical fix. Here are the five most common – and costly – reasons PdM initiatives get stuck, along with how to get them moving again:
Many operational environments still depend on aging machines and software built before cloud computing or real-time data sharing were possible. These systems often trap valuable performance insights in isolated silos.
The Fix: Retrofitting with IoT sensors, middleware, and edge devices can unlock that data without overhauling your entire infrastructure.
Teams want to move fast. But without shared goals, clear KPIs, and buy-in from both IT and OT, even the most promising pilots can stall or fail to scale.
The Fix: Start with business outcomes, not just tech. Build a roadmap with measurable milestones and cross-functional alignment.
New platforms, tools, and training require investment. And without a quick, visible return, getting budget approval can be tough.
The Fix: Begin with high-impact use cases that can quickly demonstrate ROI on critical assets. Let early wins make the financial case for broader adoption.
PdM relies on more than hands-on expertise. it needs people who can interpret data, recognize trends, and work with advanced tools. Most maintenance teams weren’t trained for this shift.
The Fix: Invest in upskilling or partner with experts who can lead initial deployments and transfer knowledge along the way.
Technology is the easy part. People are harder. If frontline teams don’t see the benefit (or fear the change), they may resist or disengage. Silos between departments can create even more friction.
The Fix: Make change management a priority. Include operators early, celebrate quick wins, and show how PdM supports their success without replacing it.
The Bottom Line
Predictive maintenance is more than a tech upgrade. It’s a shift in mindset and operations. The path forward to Digital Transformation doesn’t have to be overwhelming.
Start small. Start with purpose. Scale what works.
Want to know where you stand?
Use our Predictive Maintenance Readiness Checklist to assess your organization’s progress - and explore the next steps.
Our whitepaper, “Addressing Barriers to Advanced Analytics and Predictive Maintenance,” offers an in-depth look at the five biggest blockers (and proven ways around them). Access the full resource here.