IS WORK OVER?

Automation index

How much of a Last-mile manager’s job can AI already do?

A zone map comes earlier. Hitting the peak without leaving the neighbourhood without a courier do not.

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

Task comparison

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

Tram driver

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
Checks, log and the cab.
Estimate

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

16%32%+5.1
Drive, stops and the pedestrian who steps out.
Estimate

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

24%8%+1.9
Badly parked car, calls and Control.
Estimate

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

16%22%+3.5
Timetable, reliefs and rush hour.
Estimate

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

16%28%+4.5
The tourist, the bike and not over-hooting.
Estimate

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

14%18%+2.5
Hit nobody, and make the terminus.
Estimate

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

14%12%+1.7
Total100%19%

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

Skills and activities

  • drive trams
  • urban stops
  • pedestrians
  • badly parked cars
  • Control
  • rush hour
  • cab checks
  • terminus

Sources for this job· O*NET 53-4041.00· ESCO/ISCO 8311

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