When plants compare planned versus reactive maintenance costs, they often only count direct labor and parts. That comparison understates the true cost of reactive work by a wide margin.
The costs that don't show up in the work order
Reactive maintenance carries costs that rarely get coded against the work order itself: expedited parts shipping, overtime labor, secondary damage to adjacent components, and lost production during unplanned downtime. A conservative rule of thumb across industrial operations puts total reactive cost at three to five times the equivalent planned work.
Why the gap persists
Most cost reporting is built around what's easy to capture in the CMMS or ERP — direct labor hours and issued parts — rather than the downstream production and quality impact that operations teams feel but rarely quantify. Without a connected view across maintenance, production, and finance data, the true cost of reactive work stays invisible to the people who could act on it.
Making the case for planned work
Building the business case for shifting toward planned maintenance means connecting three data sets that usually live in different systems: CMMS work order costs, production downtime records, and finance's cost-center actuals. Once that connection exists, the true cost differential between planned and reactive work becomes visible — and it's usually the single most persuasive number in a reliability improvement business case.
This is exactly the kind of cross-system reporting problem a well-built business intelligence layer is meant to solve, and it's often the first dashboard worth building once the underlying data model is in place.