IS WORK OVER?

Automation index

How much of a Route planner’s job can AI already do?

An optimiser comes earlier. Fitting the windows without blowing the hours do not.

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

Task comparison

Route planner

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
Optimise, windows and capacity.
Estimate

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

18%52%+9.4
Restrictions, tolls and the right vehicle.
Estimate

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

16%40%+6.4
The salesperson who promises and the plan that will not.
Estimate

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

16%22%+3.5
Recalc, incidents and the next day.
Estimate

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

16%28%+4.5
The warehouse, the cut-off and not leaving the last one.
Estimate

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

18%14%+2.5
That it fits, and not blowing the hours.
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

  • optimise routes
  • delivery windows
  • tolls
  • vehicle capacity
  • recalc
  • traffic restrictions
  • warehouse cut-off
  • driving hours

Sources for this job· O*NET 13-1081.00· ESCO/ISCO 4323

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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