Measuring Overall Equipment Effectiveness: How Productive Is Your Shop – and Does OEE Measure It Meaningfully?

Theoretically, Overall Equipment Effectiveness (OEE) measures capacity versus output to show you how much of the time you’ve allocated to production actually produces the desired result: finished parts that pass quality control. The idea is that you can benchmark OEE to compare shifts, see if you measure up to industry standards or find out if your performance has changed – for better or worse – over time. Many shop owners believe they can establish a baseline OEE measurement and recalculate OEE periodically to evaluate progress toward efficiency. Unfortunately, the metric’s meaning isn’t a simple answer to the question, “Are we as efficient as we can be?” Misapplied, an OEE score can lead to some dangerous generalizations that actually decrease your efficiency.

The math behind OEE can be simple. Multiply the number of defect-free pieces by the minimum amount of time required to manufacture one part. Divide the result by the total amount of time allocated to production. The outcome is Fully Productive Time spent making good parts at full speed with no downtime. Other, more-complex OEE calculations further break down loss by type, including availability, performance or quality.

On the shop floor, OEE looks like a great way to help operators and programmers understand gaps between expected and actual output so they can improve performance accordingly. But that’s the problem with OEE: It looks objective because it involves a mathematical calculation. Like many math-based measures, however, OEE makes assumptions about what constitutes productivity and fails to consider the vast differences between different types of shops.

It’s also important to remember that no single OEE score is ideal for every type of production workflow. You may see an 85% score widely mentioned as a target for highly efficient shops, but that figure is meaningless without context. Myriad factors influence its attainability, from the types of parts you produce to the size of your part runs.

For example, in a shop that dedicates its machines to making thousands or even millions of the same parts every year, the OEE score should be close to – but not quite – 100%. No shop can sustain full capacity productively all the time, and everyone needs time for proactive maintenance. Conversely, a job shop that produces a diverse mixture of short runs with individual setups could not come close to that high OEE score, and probably couldn’t reach the 85% mark.

OEE time eaters

Ultimately, many shops treat OEE like a report, not as a basis for action, and fail to recognize that OEE is not the answer to a question. Instead, it’s a source of questions you can ask yourself on the path to greater productivity. Remember that measurement for its own sake creates a data trap that doesn’t move you toward actionable information. Instead, look for answers.

The important metrics to evaluate are the bottlenecks in production. If you’re using a machine monitoring system, you capture measurements of performance and can see where they bog down. If some of your machines didn’t run as productively as they could, did they suffer a breakdown? Were they too slow? Were they loading and unloading, or were too few people available to run them? Were you out of tools or waiting for raw materials? Did a job require a machining program that wasn’t completely written?

Ultimately, two facts truly stand out, especially if you decide to measure OEE. First, if you want to increase productivity, you need to figure out what aspect you’re increasing. That’s because an unquantified demand doesn’t give operators an actionable target for their output. Second, trying to increase production too much can be counterproductive, especially in shops with a high-mix, low volume workflow. In those cases, operators may be tempted to tackle easy jobs – or those that don’t require a change in setup – before more-complex jobs and those with shorter deadlines. That kind of “cherry picking” makes short-term statistics look good at the expense of longer-term productivity.

As you look for ways to streamline and support your workflow, keep OEE in mind as an interesting statistic that may offer relevant insights, if you use it correctly and measure it as a way to find your production bottlenecks. In the long run, it can be just as counterproductive to criticize yourself for your current OEE score as to praise yourself for it.


Depending on your workflow, OEE may not be the best measure of your shop’s efficiency. These alternatives may help you gauge where you can improve.


Many shops wind up with a mixture of small projects that finish up ahead of schedule and bigger ones that run late. That could be a sign that your operators complete easy projects first to boost their output, rather than tackling work in the order it needs to reach the customer. This is why it’s important to encourage the right kind of productivity, not just staying busy.


When you communicate your priorities to your staff, give them specific targets to hit instead of merely encouraging everyone to “get more done.” Without actionable objectives, you’re unlikely to reach your overall goals.


If you’re concerned about running out of work, you may encourage your sales reps to accept any and all jobs that come your way, regardless of whether they really fit your strengths. Trying to do too much can leave you constantly running behind – and disappointing customers.


To increase your efficiency, you need to find the bottlenecks in your production. Many of those occur when things change – a job moves from one machine to another, a machine needs a new setup, and so on.


Efficiency is everyone’s business. Ask your entire staff to question the status quo, look for ways to improve – and keep track of anything that looks like an opportunity to streamline how you approach your work.

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