Overall Labor Effectiveness = (Standard hours/Work hours) * Productivity %
Overall Labor Effectiveness (OLE) is a Key Performance Indicator (KPI) that measures the Utilization, Performance, and Quality of the workforce and its impact on productivity. However, in Spindle, we focus on the Utilization and Performance to calculate this metric.
- The Utilization component of OLE is determined by the percentage of time an employee spends making effective or measurable contributions in Standard tasks that have a target. In Spindle, this is the amount of the employees Standard hours divided by their Work hours. (Standard hours/(Spindle Hours - Lunch - Break))
- The Performance component of OLE is determined by the productivity percentage of the employee. In Spindle, we use the employee's productivity percentage. (Actual Pieces/Target Pieces)
An easy way to calculate your facility's Overall Labor Effectiveness (OLE) is as follows:
- From the Analysis Page, convert the Time Format to Decimal to make for easy calculation.
- Determine the total amount of Standard hours
- Determine the total amount of Spindle Hours - Lunch Hours - Break Hours
- Determine the overall Productivity. Any overall efficiency exceeding 100% will be reduced to 100% to perform the calculation.
- Overall Labor Effectiveness = (Standard hours/(Spindle Hours - Lunch - Break) * Productivity %
The below example is intended to further demonstrate the importance of OLE:
Your facility just installed Spindle and sees a nearly instant improvement in production efficiency. The employees are producing at a faster rate, thus the product is being processed and completed sooner during the day. This is typically due to the live feedback they're now receiving via the Spindle Displays throughout the facility.
However, when this happens the only way to truly reap the benefits of this improvement is to either (1) reduce hours or (2) increase volume without increasing hours. If volume remains the same, and hours remain the same, then the increased efficiency is nothing more than a number, and will likely not yield any true return.
This is where OLE comes in and why it's such an important KPI. In the above example, as efficiency increases and hours remain the same, the only option for the employees to do is to log into Non-Standard tasks (i.e. Cleaning, Material Handling, etc.) that are not measured against a target. When this happens, OLE remains the same, since it's essentially a comparison of Efficiency vs. Non-Standard hours, and in turn, PPOH will likely follow suit and remain the same, thus no true return reported.