OEE Is Not Enough: What to Measure Instead of OEE Alone
DBR77 Team7 min read
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OEE is not enough because it measures how well a machine uses the time it was planned to run, not whether the plant makes the right products, on time, at the right cost. OEE can rise while delivery slips and stock grows. Keep OEE for finding losses on a line, and add a few measures beside it: output at the bottleneck, on-time delivery, first-pass yield, cost per good unit, changeover time and stability of maintenance. Six to eight measures on one scorecard are usually enough.
Many plants have made OEE their headline number. That is useful up to a point, then it starts to steer the wrong behavior.
What OEE is good at, and where it stops
OEE combines availability, performance and quality into one figure for a machine or line. Vorne notes that 85% is often called world class, based on 90% availability, 95% performance and 99% quality, and that most manufacturing companies have scores closer to 60%. The same page advises against comparing dissimilar processes with external OEE benchmarks and suggests focusing on the ability to improve.
OEE works best for tracking one line over time and showing which of the three losses to attack first. It does not cover:
- Time outside the plan. OEE uses planned production time as its base. Vorne's TEEP adds utilization, which is planned production time divided by all time. A line can have high OEE and run only one shift.
- What is being made. OEE does not ask whether the products were needed.
- The rest of the plant. OEE on one machine says nothing about the flow through the whole line or the cost of the result.
- OEE, line 1
- 62% to 71%
- On-time delivery
- Still 88%
- Finished goods
- Up by a third
- OEE
- Rewards long runs
- Stock days
- Punish making the wrong thing
Line 1 OEE rises from 62% to 71%, while on-time delivery stays at 88%.
Five ways OEE rises while results don't
Illustrative example: a packaging plant raises OEE on line 1 from 62% to 71% in one quarter. On-time delivery stays at 88%, and finished goods stock grows by a third. Here is how that happens.
- Longer runs, fewer changeovers. The team runs bigger batches to cut changeover loss. OEE rises. The plant now makes products weeks before customers need them.
- Overproduction. The Lean Enterprise Institute defines overproduction as producing more, sooner or faster than is required by the next process, and Taiichi Ohno called it the most grievous form of waste.
- The wrong line. Line 1 is not the bottleneck. The filler on line 2 is. Every minute gained on line 1 waits in front of line 2.
- Moving losses out of the base. Changeovers or short stops are reclassified as planned time. Availability improves on paper, and nothing changes on the floor.
- Quality hidden in rework. Parts that pass after rework are counted as good. The quality factor looks fine, and rework hours grow.
Each is what a team does when one number is the target.
Measures to add next to OEE
Each measure below catches something OEE misses; most plants need five or six of them.
| Measure | What it shows that OEE misses | Typical owner | Review |
|---|---|---|---|
| Output at the bottleneck | Whether the plant as a whole made more | Plant director | Every shift |
| On-time delivery to the customer | Whether the right products left on time | Head of planning | Daily |
| Schedule adherence | Whether the line ran what the plan asked for, in order | Shift lead | Every shift |
| First-pass yield | Good parts without rework or sorting | Quality manager | Daily |
| Cost per good unit | Labor, material, energy and scrap in each sellable part | Controlling | Monthly |
| Changeover time | Whether shorter changeovers allow smaller batches | Production engineering | Weekly |
| MTBF and MTTR | Whether stops are becoming rarer and shorter | Maintenance manager | Weekly |
| Finished goods and WIP days | Whether output is turning into stock | Plant director, controlling | Weekly |
| Safety incidents and near misses | Whether speed is costing safety | HSE manager | Daily |
Some measures pull against each other on purpose. OEE rewards long runs, while stock days and on-time delivery punish making the wrong thing. Changeover time links them: when changeovers get shorter, small batches stop hurting OEE. Schedule adherence connects to planning, the subject of Production Planning vs Reality: Why APS Plans Fail.
How to build a plant scorecard
A scorecard is a short list of measures that, together, show whether the plant is doing well. Five steps:
- Start from three or four plant goals, for example deliver on time, cut cost per unit, keep people safe, grow capacity without new machines.
- Pick one or two measures per goal. Keep the total at six to eight.
- Include one measure at the bottleneck. If the scorecard has no constraint measure, gains elsewhere will look like progress.
- Pair measures that pull against each other, such as OEE with stock days, or output with first-pass yield. A gain in one at the cost of the other shows at once.
- Write a definition card for each measure, with one formula, one data source and one owner; How to Build a Real-Time KPI System for Your Factory shows the card format.
Review the scorecard weekly at plant level, and let each line keep OEE as its working tool for losses. Change a target only when the goal behind it changes.
How this works in DBR77 IRIS
Most measures on a DBR77 IRIS scorecard come from the module that holds the record. IRIS MES supplies OEE, cycle times and counts. IRIS QMS tracks first-pass yield, defect rates and cost of poor quality. IRIS CMMS provides MTBF, MTTR and planned versus unplanned downtime. IRIS HSE adds lost-time incidents. Indicators that no module produces, such as energy per unit, are entered by hand or in a batch. IRIS KPI brings them together in scorecards with targets at plant, line and team level, and drill-down to shift and machine.
IRIS shows availability, performance and quality losses separately for each line, so the team can see which loss to work on first. People decide which actions go ahead, and a change can be tested first in a simulation with DBR77 DT.
When comparing systems, ask the vendor to build your scorecard from your own definitions during the demo. How to Evaluate a Plant Operating System lists more questions like that.
FAQ
Should we stop using OEE?
No. Keep it as the working tool for losses on each line. Stop using it alone as the plant's headline result.
What is a good OEE target?
One based on your own line's history and product mix. Vorne advises against comparing dissimilar processes with external benchmarks, and lines with many changeovers usually score lower.
Is TEEP better than OEE?
It answers a different question. TEEP shows how much of all calendar time is productive, which matters when deciding between more shifts and new equipment.
Conclusion
Compare your current KPI list with the measures above. If OEE has no partner measure, pair it with stock days or first-pass yield, and if nothing on the list sits at the bottleneck, add output there. Keep the total at six to eight, review it weekly at plant level, and let each line keep OEE for its own losses.
Sources
- Vorne, World-Class OEE
- Vorne, Calculate TEEP: Increase Equipment Utilization
- Lean Enterprise Institute, Overproduction