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

Health information technician

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
Code ICD, the discharge set and the episode.
Estimate

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

18%52%+9.4
Filing, scanning and the missing record.
Estimate

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

16%48%+7.7
Loans, copies and the judge who wants the file.
Estimate

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

16%28%+4.5
Documentation emergencies and the discharge that will not close.
Estimate

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

18%18%+3.2
Data quality, audits and billing.
Estimate

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

16%22%+3.5
Confidentiality and not losing the record.
Estimate

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

16%14%+2.2
Total100%31%

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

Skills and activities

  • code ICD-10
  • discharge dataset
  • file records
  • loan records
  • health documentation
  • scan reports
  • clinical data quality
  • confidentiality

Sources for this job· O*NET 29-2072.00· ESCO/ISCO 3252

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