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Is your “OEE” providing the results that you were expecting?


Overall equipment effectiveness (OEE). Somehow became one of the most critical key performance indicators (KPIs) of operations management. Although some critics about this KPI, I want to mention something even before those critics.


Why are there so many fake OEE numbers?


OEE should have some rules to function as a KPI like any KPIs. Unfortunately, it is left wild with many fake numbers. I am not saying we need some punishment system. But I feel like something is missing. Some things are driving this OEE to become useless, just like many KPIs.



1. Simple rule. OEE can NOT exceed 100%.

Very often, I observe machine that is performing OEE above 100%. Many might think this is not their problem because they never seem close to 100% of an OEE. That is because, most likely, they are observing the average OEE for the month or the week. I am not looking at an average of some period. I am looking at the speed of the equipment.

The speed of the equipment should be the baseline of the capacity. OEE should be calculated based on the “best” rate. Unfortunately, this “best” speed is a subjective decision. I have been to factories that defined OEE based on historical average output. It was performing at OEE 90%, but that meant they were performing below what they were doing before. In one meeting, they were like heroes. On another, they got bashed. Why such a discrepancy? If I ask them to use the best speed, they will protest because “the number will look bad.” Well, the factory is in bad condition. Why not show that it is terrible?

Best “speed” can change. You can install different components on the machine, and the best speed can improve. Yet, you hardly ever see them change the standard of calculating the “best” rate. They will tell that they need to validate, but this will take forever. On the other hand, there are cases where they decide to lower the standard rate without any good problem-solving. This change happens faster than the speed of light.

One key point of discussion is how do you see problems (variations and fluctuations) in operations? Many believe that we will always have those. That’s why we need to calculate and make allowances in capacity, speed, and resources. Since there are allowances, the people need to live with the problem. Problem-solving is an option. Toyota thinks the other way around. They know they can eliminate the problem and stop a problem from happening again. Because of this, they do not allow allowances. It should immediately stop. And then, when a problem occurs, it is the manager’s responsibility to respond, not the people because they don’t have time. And what is essential is that problem solving is a must. Of course, issues happen, and we need to keep extra resources. But those additional resources are preserved separately, not kept inside every process. And the use of these additional resources is connected to immediate problem-solving.

The objective of OEE is not to show big numbers. It is to show the condition of the equipment. It should reflect the actual status and connect to problem-solving and improvement activities. The KPI becomes useless when the allowances and insurances between the measurement baseline and the proper capacity. What is essential is to develop this eye to find the gap on the shop floor. At least for OEE calculation, the theoretical capacity is back of envelope level calculations.

The problem here is not those who hide the capacity. It is the fear against punishment they get for low numbers. If your people think that “honesty doesn’t pay here,” OEE is just another game.


2. Are we allowed to talk about the problem? The real problem?

The problem above or any cases, we are not allowed to talk about the real problem. We have to talk about what allowed us to discuss. There was a plant that highlighted that changeover is the biggest problem. We worked on changeover time reduction. But the total time on changeover continued to grow. It wasn’t like we were reducing the batch size and intentionally doing frequent changeovers to level the flow. Instead, we stopped in the middle of production units causing more chaos. The truth was that the plant was changing over to cover the material shortages. They were not allowed to mention that unstable material supply is the biggest problem. There is this belief that manufacturing flexibility means production covering whatever supply issues. The true functionality of “Production control & logistics” is not planning production based on material availability. It is to level the demand and prepare the supply chain to protect it. After several negotiations in the above case, the purchasing manager agreed that they had a problem and said the supplier was the problem. So they requested the supplier to conduct the five-why analysis. The analysis came back. Nobody read it but accepted it. The conclusion said, “we have to make sure the customer order correctly.” Finally, they admitted that material supply is a big issue.

Inside an organization, there is some power balance. If we don’t pay attention, the weaker will be blamed for a problem. In the case of operations, the operators and the suppliers are easy victims. Blaming the stakeholders never leads to a good solution. Most likely, after a considerable effort to change, you repeat the same problem. We need to look at the process. And to look at the proper process, we need to be allowed to talk about the real problem.


3. Data entry is an act of management

Today, advances in information technology allow us to quickly enter OEE data, such as the reason for the downtime. Many believe that having many entry points will help and ask the operators to select the reasons. But the question is it accurate? Often I don’t see an operator in front of a machine but registered as “changeover” or “missing material.” The night shift was struggling to make an output. The data just showed “no order.” As I came in at night with the plant manager to observe, a group of people walked back with cigarettes. The last person to come back with the cigarettes was the shift leader, who made the data entry.

These problems are not just related to people issues. There was a factory that was struggling with “quality” issues. They lost 30% (about 100 units) due to quality issues. I counted defects reworks and summed up ten units on the shop floor. It wasn’t like Toyota, where they stop when they have quality problems. They have expensive conveyors and robots to flush all defects into repair stations. So why are we losing ninety units without an explanation? The truth was that nobody knew about what was happening. Because they don’t know, they tied all losses to quality. It was clear that the management never observed the shop floor. So we observed. After an hour of observation, the plant manager said something was “strange.” I explained that the line has twenty stations, but the total work-in-process (WIP) stock was eighteen. The system controlled the WIP. But nobody knows why the WIP was less than the total number of stations. As we took out this control, the output recovered. In many cases, we simply don’t know what is happening.

The truth is that this act of data entry is the act of management. Many management actions depend on the judgment made at the data entry. In Toyota, they install “Andon” so when a problem happens, the problem grabs the manager’s attention. The manager will look into the problem and take action. Then, register what happened. Many companies are implementing such data entry without careful consideration. They “dance” with biased data—a significant amount of organizational effort with limited results.

At the time of data entry, two actions need to be highly effective. First, the corrective action to the problem needs to be perfect. Second is the registration of accurate reason. Both of these actions require a high level of training. The first action requires a high level of diagnosis and work skills. The second requires a fair mindset. The judgment of self-responsibility (自責) and external responsibility (他責) is crucial. Without proper training and environment, we tend to blame the others or the weaker spots in the organizations.


4. Why did your "old" KPIs not deliver the results you were expecting?

Most companies have the motivation to implement the OEE. That is because the old KPIs, “capacity,” “output,” “cost,” did not deliver the results that you were expecting. But just because you implement this new KPI, you still have to manage these old ones. After some time, the OEE also does not necessarily deliver the results you expect.

Why did those old KPIs not work for your company? And, did you solve the root cause of the problem?

What is the objective of the KPIs? Should we use those to punish the people? Should that fear become the driving force in your organization? I believe not. I think the KPI is, for first, a self-reflection trigger. Second, those are communication tools inside an organization. The leader will use the KPIs to guide the people toward the vision. They still come to the shop floor since it is not the KPI that is important. It is the action and thinking of people that is important.

After all, OEE is not a magic or radically new idea. It is actual output divided by the theoretical capacity, which we know is not defined. OEE divide into Availability, Performance, and Quality. Yet, any registration of these downtimes is a judgment by someone. Managers still need to be on the shop floor. The OEE does not change the fact that managers need to be on the shop floor to have the capability to see opportunities exist inside capacity. The most likely reason why the “old” KPIs did not work is because of this reason, the management is not on the shop floor, and they don’t know about it. OEE doesn’t solve that problem.


5. “What is the point of chacing OEE when you are allowed to have a process that is 100% waste?”

The above was a comment from a TPS coach, which touched the truth. Many will instantly react that it is impossible to have a piece of equipment that is 100% waste. But there are cases where they repeat inspections or a robot that move a component from conveyor to conveyor. No rule says how much waste we can have to calculate OEE.

OEE does not originate in TPS. It came from Total productive maintenance (TPM). TPS requires great maintenance, and therefore TPM is fantastic thinking. But OEE could contradict TPS. I will talk about this more in a separate post.



After all, OEE is not a magic KPI. It is just a KPI. An organization can use to improve or kill yourself. After all, managers need to be on the shop floor.

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