Improve Paid Labor Utilization
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Improve Paid Labor Utilization

What?

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 every hour of paid labor, a certain level of productivity from the machines is expected. Defining this metric with Amper data can reveal inefficiencies caused by labor management issues. Improving this metric will not only enhance overall labor utilization, but also machine utilization. Armed with this information, you can justify hiring more staff or changing your SOPs to ensure that the team is performing value-added work, such as operating machines.

Time Commitment: Low

Features Required: Downtime labeling if you want to count setup time towards time earned, Tally Sheets if you want to see Paid Labor Utilization by Operator

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Case Studies:

How?

Set up a tracking system

We recommend tracking this metric weekly for 1 month before kicking off projects to improve it.

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Use the template below to track this data over the course of 4 weeks 👇
Paid Labor Hours Utilization.xlsx11.9KB

There are 2 ways to measure your Paid Labor Utilization: with and without downtime labeling data.

Using downtime labeling allows your operators to earn hours that would otherwise be considered “downtime”. A good example of this is “Setup”. When an operator is not running a machine, but performing a setup, you may want to consider this as earned labor.

1. Without using downtime labeling

  1. First, you'll need to determine your machine to operator ratio.
    • Example: 1 operator should be running 3 machines at any given time.
  2. 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.
  3. Calculate Paid Labor Utilization
    • 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.
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Example:

  • Machine uptime = 1,500 hours
  • 2 machines per operator
  • Paid labor hours = 1,000
  • Efficiency Goal = 75%
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2. Using downtime labeling to earn extra hours

  1. First, you'll need to determine your machine to operator ratio.
    • Example: 1 operator should be running 3 machines at any given time.
  2. Then, you'll determine an acceptable goal of efficiency. Typically we see 75% to account for breaks, lunches, or any other acceptable downtime not captured by downtime labeling. 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.
  3. Calculate Paid Labor Utilization
    • 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.
    • Setup time - comes from Amper collected downtime labeled as “setup”
    • Efficiency goal - determined in step 2.
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Example:

  • Machine uptime = 1,500 hours
  • 3 machines per operator
  • Setup hours = 500 hours
  • Paid labor hours = 2,000
  • Efficiency Goal = 75%
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Analyze results and take action

If a machine’s 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 fewer 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.