IS WORK OVER?

Automation index

How much of a Table official’s job can AI already do?

A scoresheet comes earlier. Clock, fouls and not wrecking the result do not.

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

Task comparison

Table official

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
Sheet, clock and the protocol.
Estimate

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

16%40%+6.4
Fouls, the warning and the one who argues.
Estimate

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

18%14%+2.5
Timeout, the scoreboard and not jumping it.
Estimate

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

16%28%+4.5
The referee, the table and not contradicting.
Estimate

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

16%22%+3.5
The crowd, the shove and keeping calm.
Estimate

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

18%18%+3.2
A clean result, and the sheet signed.
Estimate

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

16%12%+1.9
Total100%22%

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

Skills and activities

  • scoresheets
  • clock
  • fouls
  • timeouts
  • scoreboard
  • the table
  • protocol
  • warnings

Sources for this job· O*NET 27-2023.00· 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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