Why traditional manufacturing metrics can get you lost
An early operations mentor taught me this lesson as a Plant Manager: manufacturing doesn’t get the privilege of deciding what it works on. For a long time, I didn’t fully understand the advice.
As a new Plant Manager, I had a hard time getting product to the dock in the order it needed to be. We were releasing work orders with reasonable lead times and in the proper order, but something was happening that was throwing everything out of whack as the product moved through the facility. That something was the way we used earned standard hours, and the daily, weekly, and monthly targets we were taught to relentlessly push operations to hit.
The map that lied
I get the concept. Assign a value to each operation (a time and cost standard) on a work order traveler and clock it through when the op completes. For our reporting purposes, earned hours were simply quantity completed multiplied by the standard time. Across a month that meant thousands of earned standard hours (ESH) in each department. Targets were set by historical throughput. 1,500 ESH per day x 21 workdays… easy. Divide ESH by labor hours for productivity and clocked hours for efficiency. Here is the problem; when you apply that method in practice and when the time standards are not accurate and maintained, every ops leader is going to reorder the product to maximize the metric.
- This product already earned its hours and needs rework – push it aside
- This operation takes twice as long as the credit I earn – push it aside
- This operation has no standard time – push it aside
- This takes half as long as the credit I earn – pull it forward
- The customer is screaming about late parts – pull them forward
- The margin is great on these parts and we need them to hit bonus – pull them forward
- These parts aren’t due yet but prop up the P&L – pull them forward, use OT if necessary
Every decision made sense locally. Collectively, they were disastrous. I couldn’t get things to the dock in the right order because each operations lead was reshuffling the manufacturing order to hit their daily numbers and avoid getting a tongue lashing by the operations leadership above them.
Here’s the part that I didn’t fully connect until I became a Controller: ESH isn’t just a shop floor scoreboard, it’s baked directly into how the plant’s profitability gets reported. The plant’s performance measures and accounting system could make local efficiency look favorable even when the resulting production mix was bad for the business. Hit your ESH targets and the P&L looks strong for the period. Miss them and someone above you is explaining a margin gap to corporate. So every ops leader on my team wasn’t chasing an arbitrary number. They were responding rationally to the number leadership told them mattered – the number that bolstered the one line on the income statement that senior leadership watched like a hawk. That’s the trap.
The performance measurement and accounting method together were quietly rewarding local optimization: make your operation’s variance look good this month, regardless of whether the product you pushed forward or pushed aside was the right one for the plant to be building. Scholars have been writing about this exact distortion since the 1980s, but living it on a plant floor made it real. We weren’t measuring whether the hikers were actually completing the trail. We were measuring whether each hiker’s individual pace looked good on paper, and calling that progress.
Who got left behind?
That kind of optimization doesn’t stay contained to one department. When everyone on the trail is watching their own pace instead of the map, the group doesn’t arrive together, and the people waiting for them start making decisions of their own to compensate. The damage from chasing ESH didn’t stop at my operations leads reshuffling work orders. It rippled out to everyone who depended on the plant actually being where it said it would be.
- How did that affect purchasing? They could never seem to align raw material deliveries with the plan. They were always chasing stockouts, expediting product, and getting barked at by Ops. In response to unreliable production plans, they bought more than necessary and had it delivered earlier to protect against the next unplanned outage.
- How did that affect customers? Customers were calling left and right demanding recovery plans. Their delivery cadences were aligned with aircraft production lines, and they couldn’t absorb supply fluctuations from our facility without incurring steep penalties. Their response was to overbuy and build buffer. The bullwhip effect once again. Now we were building products that weren’t truly needed by some customers and not building the needed product for other ones.
- How did that impact employees? Turnover and a loss of valuable experience. Employee turnover carries costs well beyond recruiting a replacement. You lose experience, productivity, and team stability while recruiting and onboarding someone new. Those who can leave and find better employment do. Recruitment costs go up as sign-on and retention bonuses become necessary. Word gets out in the community on social media that you aren’t a good place to work, applications slow, and candidate quality diminishes.
Getting the map right
ESH isn’t the villain here, using it alone is. Throughput, in the sense that actually matters to a business, isn’t quantity times standard, it’s the rate at which the plant converts raw material into cash the customer is actually willing to pay for, on the timeline they need it. Ripping out standard costing isn’t realistic, it’s deeply embedded in how manufacturers plan, measure, and report performance. The answer isn’t to eliminate ESH. It’s to stop asking it to tell the whole story.
Here are a few conditions that will keep ESH from being the type of trap I experienced:
- Keep the standards current. Most of the gaming I described started with stale or missing time standards. An operation with no standard, or a wildly wrong one, is an invitation to reorder around it. Standards need a defined maintenance cadence, not a set-it-and-forget-it approach.
- Never let ESH stand alone. If you want a single number that’s harder to game, track throughput against the committed product mix and delivery dates so hitting the number on the wrong product mix shows up as a problem instead of a win. If your work order travelers use milestone operations, the ERP scheduler can project when parts should reach those milestones. Build reporting around whether the committed mix is reaching those milestones when expected.
- Measure the mix, not just the total. Aggregate department ESH hides the kind of push-forward, push-aside behavior that wrecked my dock. Measure earned hours against the specific product mix you committed to customers that period. Hours earned on the wrong product mix should not automatically count as a win.
- Don’t tie compensation to ESH in isolation. The moment a bonus threshold depends on a single number, that number will get managed instead of the business.
The trail ahead
None of this makes ESH useless, it makes it incomplete. A metric that only tells you how fast someone’s moving, without telling you whether they’re headed the right direction, will eventually get you lost, no matter how good the pace looks on paper. The plant I described didn’t have a discipline problem or a talent problem. It had a measurement problem. If you’re staring at strong efficiency numbers and a shop floor that still feels chaotic, you’re probably not measuring what you think you’re measuring.
Here is the lesson again: manufacturing doesn’t get the privilege of deciding what it works on.
If it seems insurmountable, Trail Guide can help. Give us a call.
