By Mike Sheahan, Vice President for Transformance Advisors
A Powerful Tool
Overall Equipment Effectiveness, or OEE, is a powerful performance measurement derived from three elements: availability, performance, and quality. Measuring OEE is a best practice and very common in organizations leveraging common improvement programs such as Six Sigma or Lean Transformation.
Combining availability, performance, and quality provides a clear representation of how a process is operating. Yes, you read that correctly. While “equipment” is in the name, it’s really about the entire process for producing a product or providing a service. The equipment is just one component. Consider a few examples:
- A shortage, of test chemicals, means a blood analysis machine will sit idle – low availability
- Poor training, of a new employee, leads to the assembly line running at a slow pace – poor performance
- Lack of calibration, on a measurement tool, causes defects to “escape” from an inspection process – a quality disaster
While availability, performance, and quality are all important, bringing all three together in one overall measurement is half of the magic of OEE. Chasing one element, just to hit a number, will often lead to problems with the other elements. The other half of the magic is tracking OEE to show progress, identify issues which need to be investigated, finding the root cause of those issues, and eliminating those root causes.
Using OEE, as a performance measurement, requires an understanding of each element and how they work together.
Let’s look closer at availability, performance, and quality.
Availability
Availability is the amount of time a piece of equipment is running divided by the amount of time it should be running. Is the equipment available when it is supposed to be?
Let’s say a hospital plans to use an operating room for 15 hours per day. Due to various reasons, the room can only be used 13.5 hours per day. The availability of the operating room is 13.5 divided by 15 or 90%.
A number of reasons could be causing availability to be less than planned:
- Shortage of people
- Unplanned maintenance
- Shortage of supplies
The calculation for availability is clear, but that doesn’t mean it’s easy. One of the main challenges with availability is agreeing on what counts as “available”. Some organizations calculate the available time based on every minute the machine was available to run. Others calculate it based on how much time the staff was also available to run it. A machine is rarely running off to a meeting or taking a break for lunch. The same cannot be said about the people who operate the machine.
Many process improvement enthusiasts presume any machine should be available 24 hours a day and 7 days a week. This grandiose approach might feel good. But, it does reduce the effectiveness of OEE as a performance measurement. The staff at a restaurant cannot run the pizza oven 24 hours a day. The restaurant is only open 12 hours a day and there is no business reason to run 24 hours a day.
The last thing you want is a performance measurement which drives the wrong behavior. When it comes to availability, you want people to focus on why equipment was not running when it was supposed to be. You don’t want people finding creative ways to run machines 24 hours a day – when that is not the goal.
Performance
Performance is actual run rate divided by the ideal run rate. Is the equipment performing, as it is supposed to, when it is running?
Let’s say our operating room should take 45 minutes per operation – the ideal run rate. During the 13.5 hours when the operating room is staffed and running, the total batches should be (13.5 * 60) = 810 minutes / 45 minutes per = 18 operations completed per day. If we take 54 minutes per operation and only complete 15 a day, then the performance of the operating room is 15 divided by 18 or 83%.
A number of reasons could be causing performance to be less than ideal:
- Lack of training
- Delayed maintenance
- Poor instructions
As with availability, the calculation for performance is straight forward math. One of the main challenges is setting the “ideal run rate.” A few people advocate a machine should be expected to run at the maximum speed provided in the original specifications from the manufacturer. However, these original specifications might have been developed for an entirely different application.
The foundation of performance should reflect how the a machine behaves in the specific process under ideal conditions. Do not muddy the waters by basing an ideal run rate on limited data, such as the fastest operator, or on a process which hasn’t been standardized. Identify the ideal conditions and what the run rate should be when operators are following the standard operating procedures and work instructions.
The last thing anyone needs is a performance measurement which promotes dangerous behavior just to hit some fictitious engineering standard. You don’t want people running equipment too fast and causing a danger to themselves and others. Just as you would not want a surgeon rushing through an operation to hit some number dreamed up by the supplier of the tool used for the procedure.
“You cannot mandate productivity; you must provide the tools to let people become their best.”
– Steve Jobs
Quality
Quality is the products, or services, which meet standards without rework or any other alterations. This is also known as “first pass yield”.
One possible way to see quality in a operating room is in how many operations where a complete success. Let’s say 14 of the 15 operations were a complete success. The quality of the operating room is 14 divided by 15 or 93%.
A number of reasons could be causing quality, or first pass yield, to be less than perfect:
- Failure to follow directions
- Worn parts on equipment
- Poorly calibrated instruments
Beyond someone not counting accurately, defining quality is a challenge for many. An analysis commissioned by the National Quality Forum identified 1,367 quality measurements – used by 48 state and regional healthcare systems. Knowing exactly what is required for a first pass yield is easier said than done.
Many organizations rely upon rejection and rework to sort out poor quality. They often ignore these first pass failures in the official measurement. Claims of 99% or 100% quality often signal it’s time to look much closer at what is being reported.
A quality measurement is only valuable if it is reporting the true situation with an emphasis on first pass yield. Finding products, or services, which don’t meet the standard on the first try serves up those golden nuggets for root cause analysis and continuous improvement.
Overall Equipment Effectiveness = Availability * Performance * Quality
Bring It Home
In our operating room example, we have found:
- Availability = 13.5 divided by 15 or 90%
- Performance = 15 divided by 18 or 83%
- Quality = 14 divided by 15 or 93%
I suspect you can see where this is going!
The overall equipment effectiveness is 90% times 83% times 93% which equals 69%.
This operating room can be relied on to perform as expected 69% of the time. The rest of the time, there will be an issue with availability, performance, or quality. Beyond the potential for poor patient outcome, the hospital and our entire healthcare system is slowed by unnecessary waste and aggravation.
OEE paints a vastly different picture from other performance measurements which don’t include all three elements.
Employee Engagement
Healthcare workers have enough to do without worrying about the equipment they rely on to care for patients. When a machine fails, someone’s work gets more complicated. They have to stop to repair it, wait for someone else to repair it, or find another one they can use instead.
Consider if equipment failure, or lack of supplies, is a common occurrence. How do healthcare workers feel going into work every day knowing the struggles they will face?
Imagine the operating room team who goes into work knowing all the equipment and supplies they need will be available. Then imagine the team who faces breakdowns, or supply shortages, as part of the routine. Which team will be more engaged? Which team will have members looking to go work someplace else?
An availability rate of 90% doesn’t sound so bad – until the performance rate and quality rate are also considered. Then, it becomes clear, there is some sort of issue 31% of the time. That’s awful.
Overall Equipment Effectiveness Summary
While “equipment” is in the name, it’s really about the entire process for producing a product or providing a service. The equipment is just one component. Combining availability, performance, and quality provides a clear representation of how a process is operating.
Think of the last time you were at a restaurant and there was a delay. You may have wondered if the stove broke, was there a shortage of some ingredient, or did the staff up and quit. An OEE measurement would track the effectiveness of the process and not just measure what was going on with the stove.
Mike Sheahan
Mike Sheahan is on the Board of Advisors for Transformance Advisors and is also President Emeritus of the ISCEA International Standards Board. He is a former president of the Association for Supply Chain Management and a well-recognized leader in the field.
Mike is instrumental in helping Transformance Advisors define and maintain the body of knowledge associated with each of our certification programs and the other credentials we offer. His experience spans top-tier companies such as ABB, Caterpillar, and ConAgra where he helped them with technology assessments, project management, and supply chain improvement initiatives.
Beyond work, Mike enjoys international travel, exploring national parks, and supporting micro-breweries.
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