Labour productivity - reporting [in progress]

Owned by Jan Dabrowski
Last updated: Apr 07, 2022
3 min read

Production-like report

With ability to:

  • Filter by any worker(s)

  • Resolution by week, day, hour, shift, activity

  • Group by line, activity

  • Aggregate manhours or number of people

This will answer questions like:

  • How much time this person spent on each line, on different shifts today?

  • Which order required most time for this person each hour today?

  • Which order was the most labour-intensive last week?

  • What is the total manpower needed to run each line today? this week?

Labour impact on OEE

Additional human resources might (or might not) have an impact on line OEE.

By looking at each day/week for OEE and total man hours used in that period we can calculate:

  • m/h - average number of humans in each hour - ‘density’ of people. 2 m/h means that in each hour on average there are 2 people working on the line

  • achieved OEE for the hour

This will gives us the following report for all lines, specific line or SKU.

I’d expect that smaller number of workers is achieving worse OEE, because e.g. changeovers and failure solving take longer amount of time, but at some point the OEE stop increasing (or even decrease after some threshold, because the line is too crowded)

We might even go a step further and calculate this ratio (OEE / manhours). This essentially tells us how much additional OEE value each worker produces. And is very simple to analyse - the top spot reveals the most optimal line occupancy:

Not that in the chart above we divide OEE (which is effective time / total time) by average man-hours which is (total man-hours / total time). Therefore it’s the same as effective time / total man-hours.
This second equation might be even easier to understand:
”additional line effective time added by each additional man-hour”

Activity actual vs planned duration with different human involvement

By comparing the duration of the activity with the expected duration, we get a % saying how much time the activity took compared to the plan. 200% means that the activity took 2x as long as expected.

Then, we can average that over all activities of certain type, and group by the average number of people involved:

This report can answer question “How many people are needed, to complete this activity in time”

This report can be additionally extended to show:

  • Durations for different SKUs - maybe completing an order in time for one SKU require only 1 person, and for another SKU even 3 people?

  • Durations for different changeover types