IS WORK OVER?

Automation index

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

A cost dashboard comes earlier. Finding the saving without breaking the network do not.

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

Task comparison

Logistics 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
Costs, OTIF and the dashboard.
Estimate

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

18%52%+9.4
Simulate network, warehouses and the what-if.
Estimate

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

16%40%+6.4
Ops, dirty data and going down to the dock.
Estimate

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

16%22%+3.5
Report, the board and the cut that hurts.
Estimate

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

16%28%+4.5
The haulier, the contract and not breaking the service.
Estimate

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

18%14%+2.5
A real saving, and not dressing OTIF.
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

  • logistics costs
  • OTIF
  • simulate network
  • what-if
  • dirty data
  • haulage contracts
  • dashboards
  • network cuts

Sources for this job· O*NET 13-1081.00· ESCO/ISCO 2421

Statistician

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
Model, clean and visualise.
Estimate

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

20%48%+9.6
Design sample, experiment and biases.
Estimate

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

16%32%+5.1
Client, questions and not overfitting.
Estimate

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

16%22%+3.5
Reproducibility, code and documentation.
Estimate

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

16%18%+2.9
Publication, review and data ethics.
Estimate

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

16%16%+2.6
Not selling a p-value that does not hold.
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

  • Model, clean and visualise
  • Design sample, experiment and biases
  • Client, questions and not overfitting
  • Reproducibility, code and documentation
  • Publication, review and data ethics
  • Not selling a p-value that does not hold
  • estadistico
  • statistician

Sources for this job· O*NET 15-2041.00· ESCO/ISCO 2120

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