IS WORK OVER?

Automation index

How much of a Volunteer coordinator’s job can AI already do?

A spreadsheet rota comes earlier. Getting them to come, stay, and do no harm, do not.

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

Task comparison

Volunteer coordinator

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
Recruitment, rotas and the volunteer register.
Estimate

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

16%44%+7
Train, support and the one who arrives lost.
Estimate

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

18%16%+2.9
Insurance, agreements and the volunteering act.
Estimate

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

16%32%+5.1
Recognise, keep them and the one who burns out.
Estimate

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

16%28%+4.5
The clash between volunteer and staff.
Estimate

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

18%18%+3.2
That they add, and do not replace paid work.
Estimate

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

16%14%+2.2
Total100%25%

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

Skills and activities

  • recruit volunteers
  • make rotas
  • train volunteers
  • volunteering law
  • retain volunteers
  • volunteer insurance
  • staff conflict
  • volunteer register

Sources for this job· O*NET 11-9151.00· ESCO/ISCO 1344

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

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