IS WORK OVER?

Automation index

How much of a Shelf replenisher’s job can AI already do?

A wave comes earlier. Filling the shelf without blocking the aisle do not.

This percentage does not predict how many people will lose their jobs.

Task comparison

Shelf replenisher

Where the time goes

Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.

The time saving for each task is estimated separately.

TaskShareAIPoints
Wave, location and the cage.
Estimate

No public source provides a precise figure. This is our estimate.

16%36%+5.8
Shelf, date and the one at the back.
Estimate

No public source provides a precise figure. This is our estimate.

22%10%+2.2
Aisle, the customer and not blocking.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Out of stock, calling it and the gap.
Estimate

No public source provides a precise figure. This is our estimate.

16%28%+4.5
The peak, overtime and not mixing batches.
Estimate

No public source provides a precise figure. This is our estimate.

16%18%+2.9
Shelf full, and aisle clear.
Estimate

No public source provides a precise figure. This is our estimate.

14%12%+1.7
Total100%21%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • waves
  • the shelf
  • dates
  • aisles
  • stock-outs
  • cages
  • batches
  • gaps

Sources for this job· O*NET 43-5081.00· ESCO/ISCO 9334

Last-mile manager

Where the time goes

Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.

The time saving for each task is estimated separately.

TaskShareAIPoints
Zones, capacity and route cuts.
Estimate

No public source provides a precise figure. This is our estimate.

16%44%+7
KPIs, first attempt and incidents.
Estimate

No public source provides a precise figure. This is our estimate.

16%36%+5.8
The courier, the lobby and the one who will not open.
Estimate

No public source provides a precise figure. This is our estimate.

18%16%+2.9
Peaks, rain and hiring too many or too few.
Estimate

No public source provides a precise figure. This is our estimate.

16%28%+4.5
The angry customer and not dressing delivered.
Estimate

No public source provides a precise figure. This is our estimate.

18%18%+3.2
Cover the peak, and not leaving the neighbourhood orphaned.
Estimate

No public source provides a precise figure. This is our estimate.

16%14%+2.2
Total100%26%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • delivery zones
  • first attempt
  • delivery KPIs
  • last-mile peaks
  • lobbies
  • delivery incidents
  • courier capacity
  • cut routes

Sources for this job· O*NET 11-3071.00· ESCO/ISCO 1324

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