By now, it should be obvious that a tool like Amper can tell you how efficient your machines are, but did you know it can also show you how effective your labor is? The idea is that for each hour of labor paid, you should see a certain amount of productivity from your machines.
Defining this metric with Amper data will help uncover inefficiencies caused by labor management issues. Improving this metric will not only improve your overall labor utilization, but your machine utilization too.
With this information, you can justify more hires or change your SOPs to ensure the team is doing value-added work—like running machines.
There are 2 ways to measure your Paid Labor Utilization: with and without downtime labeling data. In this example, we will walk you through how to use your machine utilization data only.
- First, you'll need to determine your machine to operator ratio.
- Then, you'll determine an acceptable goal of efficiency. Typically we see 50-60% to account for breaks, lunches, setups, or any other acceptable downtime. This can be different for each factory. By adding this to the equation, your goal for the Paid Labor Utilization metric will be scaled to 100% or more.
- Calculate Paid Labor Utilization
-Example: 1 operator should be running 3 machines at any given time.
-Machine uptime - comes from Amper collected production time.
-Number of machines per operator - determined in step 1.
-Paid labor hours - comes from your labor management payroll system. OR some customers log operators in/out of machines each day and use these collected hours with Amper.
-Efficiency goal - determined in step 2.
4. Set up a tracking system
-We recommend tracking this metric weekly for 1 month before kicking off projects to improve it.
-Use the template below to track this data over the course of 4 weeks 👇
5. Analyze results and take action
To analyze the results, you must assume that operators should either be running machines or doing setups with their time. So if machine utilization is 30% and the paid labor utilization is 100% or more (operators are always doing setups or running machines), you know that you either need to:
- Do less setups
- Do setups in less time
- Get more operators to run machines while others are doing setups
Conversely, if the operators aren't being utilized with setups or running machines, you can kick off an analysis to see what they are doing instead, and restructure some workflows to increase labor efficiency.