I saw a post from Michel Baudin, Is OEE a Useful Key Performance Indicator? I don’t think it is. A few years back I wrote a blog about OEE and how it is very unclear as to what is really happening in a facility. It violates nearly every rule as to what is a clear and relevant metric.
Michel’s post started out with a bit from Jeffrey Liker’s post about OEE. This is the piece I found interesting from Jeffrey Liker:
Ignacio S. Gatell questions whether companies using OEE really understand it, can explain it clearly to their customers, and understand what it means to compare OEE as a KPI across plants. He questions whether even plant managers understand how it is calculated and what it means.
The only good argument for OEE is that at a macro-level in a plant it provides a high level picture of how your equipment is functioning.
I have to agree with Liker’s statement. OEE is good for a macro level idea of what is happening but you can’t understand what is happening without splitting it up into the components. Seems like Michel Baudin is thinking the same thing.
It is an overly aggregated and commonly gamed metric that you can only use by breaking it down into its constituent factors; you might as well bypass this step and go straight to the factors.
This is one of those blogs that gives me some of my sanity back. OEE seems to be so entrenched in “good business practices” it is hard to get people to move away from it. I get a lot of looks like I am completely crazy when I bring up my point of view. Thanks, Jeffrey and Michel. I see I’m not the only one now.
During some recent blog reading, I was spurred to think about a past situation when a company I worked for was buying new equipment and how WRONG this decision was.
I had been with the company for about four weeks when I heard about a capital expenditure my director had just approved to buy nine more of a patented machine. My company owned the patent. That would give us a total of 99 of these machines.
First question I asked, “Why are we buying more of these machines?”
The response was a typical one, “We they need more capacity because we are meeting the demand.”
I didn’t ask anymore questions at that point. I decided to go and see for myself. This was easy because the corporate offices we were in was part of the main manufacturing building. I had to walk about 100 yards.
During my observations I found two things:
- The overall OEE of the 90 machines was around 35-40% when it was running.
- At anytime I never saw more than 50 of the 90 machines running. This was because we never had enough people to run all the machines.
After a few hours of direct observation, it was clear there was no understanding of what was really going on.
First, attack changeovers and downtime to get the OEE of the machine up to the 75% range.
Second, why buy more machines if we can’t staff them?!
By my calculations, if the OEE was raised to the 75% range, not only would we not have to buy more machines we could get ride of about 20-25 machines we already had. That would mean our current staffing would be pretty close to what we needed.
I presented this to my new boss and the director, but by this time it was too late. The money had been cut and were pretty much crated and on the road to our facility.
This is why companies should question any new capital expenditures. Companies should be maintaining and using what they have first. The OEE should be at least 70% if not higher before considering adding more capacity through spending.
Do not make any decisions about capital expenditures until the current state is thoroughly understood. The best way to do that is to go and see for yourself.
A very common metric that is tossed around in the lean world is Overall Equipment Effectiveness (OEE). A couple of weeks ago I posted a blog about clear and relevant metrics and used OEE as an example of how it is not very clear or relevant to the people doing the work. There is another hang up with OEE. People become so focused on OEE that it starts to hinder flow.
When transforming the thinking of an area, people can latch onto OEE very easily because it is very silo’ed or machine focused. The metric focuses on how much the machine is up and how efficient it is with its time and materials. On the surface, this is all great. So how does this hinder flow?
When creating flow we want to eliminate/reduce the work-in-process (WIP) between processes. Once the machines are reliable we might try to create a work cell with several machines. When creating the work cell it may be necessary to slow one of the machines down to match the pace of another machine.
If the focus is on OEE and not flow, the report will show the machine that was slowed down not being very efficient and cause the OEE to drop. When this happens a traditional thought process would be to insert more work in order to keep the machine running at full speed. When this happens, the extra work inserted into the processes causes a jam up of the work trying to flow through the cell. This will cause lead times to increase and WIP to build back up between the processes.
The ideal state is to get the work flowing without stopping as much as possible. Make the 80% of the work that is the norm flow and learn how to manage the other 20%. If the 80% can flow with no effort, it means less work for the supervisors and managers because now they are not worrying about the 80% only the 20%, which is better than worrying about all 100% and managing the WIP it brings.
I know it sounds like I am against OEE but I’m not. It can be a beneficial metric when used properly. Like analyzing one single piece of equipment that is the constraint in a process in order to increase the capacity of the entire process or flow.
We shouldn’t focus on the equipment. We should focus on the flow of the product. The product should flow like a river.