IS WORK OVER?

Automation index

How much of a Tactical analyst’s job can AI already do?

A clip comes earlier. The manager using it, and it not being noise, do not.

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

Task comparison

Tactical 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
Video, tags and the report.
Estimate

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

18%48%+8.6
Opponent, patterns and the one who hides.
Estimate

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

16%40%+6.4
Preview, the dressing room and not drowning them.
Estimate

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

16%22%+3.5
Live, the tablet and the change.
Estimate

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

16%28%+4.5
The manager, the ego and not contradicting in public.
Estimate

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

18%14%+2.5
That it is used, and not being noise.
Estimate

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

16%12%+1.9
Total100%27%

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

Skills and activities

  • tag video
  • opponent patterns
  • preview
  • bench tablet
  • tactical reports
  • dressing room
  • changes
  • data noise

Sources for this job· O*NET 27-2022.00· ESCO/ISCO 3422

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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