IS WORK OVER?

Automation index

How much of a Traffic warden’s job can AI already do?

A camera and a stock ticket come earlier. Running a junction and taking the abuse do not.

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

Task comparison

Traffic warden

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
Tickets, photos and the plate record.
Estimate

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

16%40%+6.4
Junction, closure and the rush-hour jam.
Estimate

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

22%10%+2.2
Tow, parking and the one who stands in the way.
Estimate

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

16%22%+3.5
Events, races and the day’s operation.
Estimate

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

16%28%+4.5
Deal, explain and the insult in the street.
Estimate

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

16%18%+2.9
A fair ticket, and not making a scene.
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

  • issue tickets
  • run junctions
  • tow vehicles
  • control events
  • read plates
  • close roads
  • parking
  • deal with drivers

Sources for this job· O*NET 33-3041.00· ESCO/ISCO 3355

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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