Modernizing Maintenance for Sustainable Productivity

The manufacturers closing the productivity gap are augmenting automation with maintenance operations that are data-driven, predictive and connected.

A pump fails on a Friday night. A technician shows up, diagnoses the problem from memory, fixes it in two hours, and goes home. No record of what he found. No documentation of what he did. No root-cause analysis data captured to better monitor and reduce future recurrence. 

That scenario plays out thousands of times a day across manufacturing. And most organizations have quietly accepted it as just how things work.

They shouldn’t. The gap between high-performing and average manufacturing operations is widening, and maintenance is at the center of it. According to the MaintainX 2026 State of Industrial Maintenance Report, which surveyed 2,234 maintenance and operations leaders across the U.S. and Canada, 79% of teams experienced the same or more unplanned downtime over the past year. The cost of that downtime is rising too. Thirty-nine percent of leaders saw downtime costs increase, driven by higher parts and shipping prices, rising labor costs, and accelerating wear on aging assets.

The problem isn’t that manufacturers lack good equipment or capable people. The problem is the operating model.

What ”Modernizing Maintenance” Actually Means

Modernizing maintenance means changing how decisions get made, how equipment is designed, how knowledge gets shared and how frontline work connects to the broader production system. Technology is the enabler, but the operating model, people and processes are the foundation.

Right now, most maintenance teams operate in relative isolation and can be perceived only as an indirect cost center to control. Work orders get managed through whiteboards, spreadsheets or legacy systems that don’t integrate with anything else. Asset history lives in the heads of veteran technicians and SMEs. When something breaks, the priority is getting the line back up, not operationalizing lessons learned.

That’s a sustainability and revenue durability problem. Over time, organizations that operate this way accumulate technical debt they can’t see: aging assets running past their productive lifecycle, recurring failures that never get root-caused/de-risked and a workforce carrying uncaptured institutional knowledge without mobile device-enabled lean standard work. 

The 2026 report makes the execution gap explicit. Despite 64% of leaders claiming to actively use preventive maintenance programs, half of all teams still dedicate less than 40% of their time to planned maintenance work. More advanced strategy isn’t translating into better execution. That gap is where productivity is lost.

The Knowledge-Transfer Gap Is the Real Crisis

Alongside aging infrastructure and budget pressure, skills gaps and labor shortages ranked among the top five maintenance challenges in the 2026 survey for the second consecutive year. Thirty-six percent of leaders cited labor shortages as a direct driver of increased downtime. Another 31% pointed to poor knowledge transfer or training.

Capturing tribal knowledge from veteran technicians is essential, but many manufacturers struggle to do so. A worker’s retirement could mean losing someone who knows that a particular pump always runs hot in summer, that a certain motor needs lubrication every six weeks regardless of what the manual says or and that the vibration in line three is a warning sign two days before a failure. When those workers retire, it doesn’t just leave an open position, it leaves a gap in the organization’s ability to keep equipment running reliably.

The challenge is solvable, but it requires treating knowledge capture as an operational priority. That means building documentation into workflows and making it easy for technicians to record what they did, what they found and what they would tell the next person who touches that asset.

Captured knowledge is endlessly valuable, but its value depends on its accessibility, searchability and connection to the assets and procedures people actually work with day to day.

From Reactive to Proactive: The Execution Problem

Most facilities sit on a spectrum. On one end, there purely reactive maintenance: fix something when it breaks. On the other, there are fully predictive operations with continuous monitoring, data-driven forecasting, and a collaborative reliability-centered culture. The majority of manufacturers are somewhere in the middle.

The 2026 data shows that more advanced maintenance approaches are gaining ground. Usage-based and condition-based maintenance have both moved up the list of programs leaders actively use. Nearly two-thirds of respondents (62%) say they are already using or piloting real-time equipment monitoring.

But adoption of better programs doesn’t automatically produce better results. Many organizations now operate with modern software platforms and still struggle with weak preventive maintenance programs, poor schedule compliance, inconsistent root cause analysis and limited planning capacity. The report puts it directly: Reliability results come from execution maturity, not system adoption alone.

That distinction matters more than most leaders acknowledge. Software is most effective when it supports integrated maintenance and operations fundamentals. This means pairing those tools with disciplined planning/scheduling, digital standard work, AI-driven knowledge capture and a culture that treats asset data as a strategic resource.

Why Execution Fails, and What Changes It

The gap between a well-designed operating model and one that actually works usually comes down to adoption. Frontline workers have seen plenty of initiatives that created more work without making their jobs easier, like digital processes that broke down under real shop floor conditions, or reporting requirements that felt more like surveillance than support.

The organizations that get this right start with the people doing the work. They design workflows and change management that fit the pace of the shop floor. They make it easier to work with a system vs. working around it, and they measure whether execution is actually improving.

The 2026 data reflects this shift in thinking. When leaders were asked how they plan to reduce unplanned downtime over the next 12 months, improving training quality and frequency ranked first (42%), ahead of replacing aging equipment (40%) and adopting new automation or technology (38%). Leaders are betting on enablement, not just infrastructure.

Connecting Maintenance to the Broader Strategy

Plant managers and operations leaders increasingly understand that maintenance isn’t a cost center to be minimized. It’s a lever for improved performance and strategic advantage.

The most competitive manufacturers manage assets the way financial organizations manage portfolios: with clear data on performance, risk and return. They know which assets are generating the most unplanned downtime. They know where to invest in condition monitoring and where basic preventive maintenance is sufficient. They make capital decisions based on evidence, not instinct.

The 2026 survey reflects growing investment appetite. Half of leaders expect their maintenance budget to increase over the next year. Among teams that experienced significantly more downtime, that figure jumps to 75%. Organizations that have been falling behind are committing real resources to catch up.

But more budget alone doesn’t close the gap. The organizations that will benefit most are the ones investing in connected systems, disciplined execution and the kind of knowledge infrastructure that makes expertise scalable across a workforce.

Manufacturing has never been a forgiving environment for organizations that stand still. The teams building the right foundation, the ones standardizing execution, capturing institutional knowledge and connecting frontline work to operational outcomes, will be in a very different position than those still running on clipboards and memory.

The gap is already opening. The question is which side of it you’re on.