Operational metrics — like absorption costing and overall equipment effectiveness (OEE) — shape behavior not just in theory, but on the floor, hour by hour.
They tell teams what to prioritize, signal when something’s “working,” and often determine which efforts get praised or penalized. But what happens when those metrics reward output instead of outcomes? Or when hitting the target means missing the point?
In many manufacturing environments, that’s exactly what’s happening. Metrics like OEE, utilization, and cost per unit dominate dashboards, but they don’t reflect whether the work being done is actually needed. They reward volume, not flow. In doing so, they drive decisions that contradict customer demand
The outcome: Bloated inventories, delayed changeovers, hidden instability, and reactive management.
And the bigger the business gets, the more costly those consequences become. Keep reading to unpack why common production metrics backfire, how they create system-wide friction, and what to use instead to drive meaningful performance.
Are Output-Based Metrics Rewarding the Wrong Behavior?
For years, manufacturers have relied on familiar measurements like OEE, cost per unit, utilization, and absorption costing. But when those metrics drive decisions that contradict actual demand, the result is a system that appears efficient but struggles under the surface.
At a glance, OEE and cost-per-unit metrics seem objective. After all, machines are either running or they’re not, units are either being produced or they’re not. What these metrics leave out, however, is whether that production is needed.
OEE — short for overall equipment effectiveness — tracks machine availability, performance, and quality. Absorption-based accounting adds another layer of distortion, incentivizing plants to stay busy to “earn back” overhead regardless of what the customer actually needs. This kind of metric logic turns overproduction into a rational business decision.
In practice, both metrics push teams to prioritize output whether or not there’s actual demand. When OEE penalizes downtime, it discourages changeovers and preventive maintenance. When absorption costing treats every extra unit as a cost-saving asset, it turns overproduction into a financial strategy.
The result is more units, less flow, and a system that looks lean, but behaves the opposite.
Avoiding Changeovers Degrades Flow
Because changeovers are classified as downtime in metrics like overall equipment effectiveness, they become something to avoid. The unintended result is a system that resists responsiveness. Instead of making what’s needed, when it’s needed, operators are pushed to run large batches of a single product to protect the metric.
This creates the illusion of efficiency while quietly degrading responsiveness. Lead times stretch, finished goods pile up, and the production schedule becomes rigid and reactive. What looks like a smooth, efficient line is actually a system accumulating waste.
The more pressure there is to just “keep the machines running,” the less time there is for activities that actually protect flow — like maintenance, cleaning, or troubleshooting. At some point, the backlog of skipped care catches up. Quality slips, breakdowns spike, and the firefighting begins. All in the name of getting the best ROI.
“Are you going to drive your brand new Lexus around the block a couple hundred times just to get “utilization” out of your vehicle?” — Mark DeLuzio.
The problem isn’t that changeovers are wasteful, it’s that the overall equipment effectiveness metric misclassifies them. In a system aligned to TAKT time, changeovers are a normal part of matching supply with demand. They’re considered something to learn from, not hide from.
Metric Pressure Causes Local Optimizations
When the goal is to protect high OEE or absorb fixed costs, decisions tend to get made in isolation. Machines are kept running even when the downstream process is overwhelmed. Batches get larger to minimize changeovers, even if it means delaying the next product the customer actually needs.
In these conditions, local optimization becomes the norm. Each area, department, or shift tries to look good according to its metrics, even when those efforts make the system as a whole harder to manage. Flow suffers, coordination breaks down, and real problems get buried under a veneer of efficiency.
These siloed decisions pile up into bigger systemic issues. While leaders may add capacity or headcount to compensate, the core issue — conflicting incentives — remains.
But when the goal shifts from maximizing utilization to aligning with demand, those same systems and teams behave differently. Changeovers aren’t avoided, they’re streamlined. Inventory isn’t inflated, it’s kept light and moving. And improvement efforts aren’t disconnected from reality, they’re rooted in what the customer actually needs.
TAKT Time Aligns Work to Real Demand
Unlike OEE or absorption costing, TAKT time doesn’t measure how much can be produced. Rather, it reflects how much should be produced, based on actual customer demand.
By using TAKT time as a guiding metric, teams shift their focus from maximizing output to maintaining consistent, reliable flow. Because TAKT time makes problems visible, leaders can clearly see when, where, and why flow breaks down. It encourages small batches, synchronized work, and smoother handoffs between functions.
And, critically, this approach also removes the pressure to keep machines busy for the sake of the metric, freeing teams to focus on building capability rather than chasing efficiency illusions.
This changes how operations are managed. Instead of chasing efficiency at the local level, teams collaborate across the value stream to meet the rhythm of demand. Instead of padding inventory to hit accounting targets, they reduce waste by producing just what’s needed, when it’s needed — with higher quality and less friction.
The value of this shift compounds over time. Systems become more predictable, lead times shorten, and continuous improvement efforts yield real business results, not just better-looking metrics.
“TAKT time drives the right behaviors if you use it correctly.” — Mark DeLuzio.
Transitioning from Absorption Costing and Overall Equipment Effectiveness
Moving away from output-based metrics doesn’t mean abandoning measurement. It means measuring what matters.
While legacy metrics ask: How fast are we going? How busy are we? How much are we producing? Those aren’t the same as asking whether we’re creating flow, solving problems, or delivering value.
If the goal is real operational excellence, and not the appearance of it, it’s time to challenge the metrics that distort decision-making. That starts with reevaluating what “good performance” looks like.
TAKT time provides a baseline. From there, supporting metrics like first-pass yield, planned versus actual changeovers, and flow interruptions by cause can build a more complete picture based on responsiveness, not just activity.
Thankfully, none of this requires a full system overhaul. It starts with clarity: being honest about what current metrics are really incentivizing and having the discipline to replace them when they mislead. Because the real performance gains — the ones customers feel and the business benefits from — don’t come from running harder. They come from running smarter, in rhythm with real demand.
Metrics will always shape behavior. The question is whether they’re shaping the behaviors that actually help the system work.
