I became a skeptic of overall equipment effectiveness (OEE) when I saw the performance on the midnight shift at a well-run plant nosedive. The low OEE was on the shift performance dashboard and attracted undue attention. Local plant management blamed maintenance, and the maintenance manager called me to support him.

An investigation showed that operations had decided one employee could operate a machine that regularly required two employees. In fact, sometimes they assigned one employee to operate two machines. Usually, one employee would keep the machine fed and cull out poor feedstock, while a second would remove the processed product and clear the jams that occurred every 10 minutes for about 30 seconds.

OEE was down to about 40 percent for equipment that usually achieved 70 to 80 percent. Further investigation revealed a wider batch-processing window than on the other shifts.

The bottom line was that the labor cost per unit processed was reduced by nearly 40 percent while meeting production timeframes. Operations really did not know the makeup of OEE, and instead of defending their numbers, they chose to cast blame.

For those who do not remember the OEE formula, for the required run window, it is:

Throughput performance percentage x quality performance percentage x uptime performance percentage = OEE (expressed as a percentage)

That is the quick two-penny version.

Who uses OEE? Hopefully, it is used by those who know what the three factors mean and how they are measured. My experience says there are various levels of OEE.

OEE was thought to be the miracle metric by some organizations, and a lot of management attention still is paid to the metric. I submit that the metric at a plant level means squat to the line operator — and plant level was the original use of OEE. Yet it is this operator and his or her maintenance technician that makes or breaks the company during the operating shift.

Could an OEE be developed that was a meaningful metric to the line machine operators? How about for the engineers and process developers who established equipment performance and line-balancing parameters? How about the supervisor who oversees a production of machines in series? How about the planners and schedulers? In other words, specific OEEs could be developed that represent the specific impacts various players have on the plant performance.

I’ll even go one further. How about the finance guys who watch the pennies? How about human relations?

Most companies recognize the importance of customers, employees, resources and the bottom-line budget performance. It not possible to separate them, yet each must be managed.

In the late 1990s, my old organization searched for a meaningful metric to gauge employee motivation and satisfaction with the workplace. The usual factors of safety, attendance, Equal Employment Opportunity (EEO) complaints and grievances were numbers that alone could not be individually correlated to performance.

As we moved out of the 1950s and into the enlightened times of the late 20th century, the old term KSA (knowledge, skills and abilities) did not seem to be the end-all when dealing with workers. We wanted them to no longer leave their brains at the front door. We wanted the whole person on the job. Empowerment, quality of working life, involvement, and the importing back into U.S. industry of Deming’s and Crosley’s quality concepts caused an upheaval in how management must view and treat the worker. Then came total productive maintenance, lean, Toyota, process management and a host of other programs.

The literature began to talk of employee talents, situational flexibility, learning organizations, systems thinking, self-direction and self-motivation. My organization categorized this as employee willingness. Yes, we hire a person that walks through the door with KSAs. What happens to his or her willingness or desire to produce to his/her finest? Can we measure that, and what do we need to help him or her walk out of the plant at the end of the day feeling satisfied?

I once had a manager who said that if we provide the right tools and timely, pertinent information, then employees will work. That means the organization exists to support the employee.

OK, so how does all of this hot air relate to OEE? It can be timely information. It can identify training and skill problems. It can indicate process and equipment problems. And, it is a barometer of employee willingness. Should, therefore, OEE be an analytical metric? Absolutely. Otherwise, throw it away.

The bottom line was that OEE became a top-level workforce metric for plant management. At the same time, all processing equipment produced (in real time) the OEE that the operators managed to gauge their performance and analyze problems. The biggest issue was to train supervisors and superintendents to use the same OEE as a diagnostic tool to help remove obstacles to operator performance.

The directors of HR were now held responsible for understanding OEE and how it should be viewed and used. It was no longer an “operations problem” but a plant-wide tool to recognize employee excellence.