Overall Labor Effectiveness: Extending the principles of OEE to the workforce
Overall Labor Effectiveness (OLE) is a new key performance indicator that measures the cumulative effect of availability, performance, and quality—but for individuals or teams of people. The ability to measure the interdependency of these attributes is especially important in the workforce. Focused improvement on any one workforce metric, such as utilization—without considering other consequences like performance or quality—can have unintended consequences elsewhere in the plant.
OEE measures the cumulative effect of availability, performance and quality of a machine, providing insight to
Overall Labor Effectiveness (OLE) is a new key performance indicator that measures the cumulative effect of availability, performance, and quality—but for individuals or teams of people. The ability to measure the interdependency of these attributes is especially important in the workforce. The workforce, potentially the most flexible of all manufacturing resources,s all impact a manufacturer’s ability to leverage the rest of its plant. And focused improvement on any one workforce metric— such as utilization—without considering other consequences like performance or quality can have unintended consequences elsewhere in the plant.
OLE expands on the ideas of OEE by quantifying, diagnosing, and predicting not only the performance of the workforce and its influence on production, but the connection between the employees and the resources needed to expand production. OLE also is similarll in one place.
Breaking down OLE: How to measure workforce performance
The OLE equation is the sum of three workforce factors on productive output: availability, performance, and quality. Here is a summary of how these factors are determined.
Employee absenteeism is major factor in determining and meeting production benchmarks. Excused and unexcused absences, illness, and other issues of availability can determine whether a factory’s workforce and equipment are being properly utilized.
Scheduling the right employees at the right time—every time—also impacts production levels. Factories with specialized equipment often need employees with special certifications that are highly skilled, and can operate the machines at different times.
Indirect time with material delays, shift changeover, idle time, and machine downtime also contribute to a breakdown in the production process.
Analyzing these factors can help manufacturers develop attendance, leave, and absence management policies, in addition to scheduling deliveries of materials and products to keep the production chain moving. Examining OLE data may prompt a manufacturer to hire temporary help to account for seasonal or unpredictable demand—or schedule proper lead time for the arrival of materials so workers don’t leave their stations to obtain the materials themselves.
How long it takes for a manufacturer to produce and deliver product
An example of the performance component can be something as simple as a lack of technicians available to set up equipment for the following day’s production, or an employee that hasn’t been trained to operate a specific machine.
The quality component of OLE comes into play if employees are following instructions and processes, and using tools properly. By establishing the right output levels, supervisors can focus attention on producing a quality product, while avoiding high levels of rework and waste.
OLE: the results
The ability of OLE to show the cause and effect of workforce factors in relation to profitability is the key result. OLE has the ability not only to determine workforce performance through availability, performance, and quality; but it also shows how changes made to improve one area could negatively impact another. An example could be a policy where one area of production receives incentive pay for creating more output. The result overloads the equipment, causing it to be replaced and stopping production altogether.
While all three categories are critical, availability is one area where manufacturers with in-place workforces can leverage to consistently provide and schedule the right mix of employees to enhance the number of productive workforce hours.
OLE shows how investments in training, root cause insights, and predictive measures with the workforce can increase profits. By building on the OEE model, OLE
Gregg Gordon is global practice leader for manufacturing, with Kronos, Inc ., a supplier of workforce management solutions.
- Events & Awards
- Magazine Archives
- Oil & Gas Engineering
- Salary Survey
- Digital Reports
Annual Salary Survey
After almost a decade of uncertainty, the confidence of plant floor managers is soaring. Even with a number of challenges and while implementing new technologies, there is a renewed sense of optimism among plant managers about their business and their future.
The respondents to the 2014 Plant Engineering Salary Survey come from throughout the U.S. and serve a variety of industries, but they are uniform in their optimism about manufacturing. This year’s survey found 79% consider manufacturing a secure career. That’s up from 75% in 2013 and significantly higher than the 63% figure when Plant Engineering first started asking that question a decade ago.