IS WORK OVER?

Automation index

How much of a Parts clerk’s job can AI already do?

An OEM code comes earlier. Giving the part that fits, not the lookalike, do not.

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

Task comparison

Parts clerk

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
Catalogue, equivalents and the code.
Estimate

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

18%52%+9.4
Counter, the waiting shop and the doubt.
Estimate

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

16%22%+3.5
Stock, urgent orders and the one that is late.
Estimate

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

16%36%+5.8
Returns, warranties and the wrong part.
Estimate

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

16%28%+4.5
The mechanic, the blurry photo and not selling blind.
Estimate

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

18%14%+2.5
The one that fits, not the lookalike.
Estimate

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

16%12%+1.9
Total100%28%

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

Skills and activities

  • parts catalogue
  • OEM equivalents
  • shop counter
  • urgent orders
  • returns
  • part warranties
  • parts stock
  • part codes

Sources for this job· O*NET 41-2022.00· ESCO/ISCO 4321

Logistics analyst

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
Costs, OTIF and the dashboard.
Estimate

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

18%52%+9.4
Simulate network, warehouses and the what-if.
Estimate

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

16%40%+6.4
Ops, dirty data and going down to the dock.
Estimate

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

16%22%+3.5
Report, the board and the cut that hurts.
Estimate

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

16%28%+4.5
The haulier, the contract and not breaking the service.
Estimate

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

18%14%+2.5
A real saving, and not dressing OTIF.
Estimate

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

16%12%+1.9
Total100%28%

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

Skills and activities

  • logistics costs
  • OTIF
  • simulate network
  • what-if
  • dirty data
  • haulage contracts
  • dashboards
  • network cuts

Sources for this job· O*NET 13-1081.00· ESCO/ISCO 2421

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