IS WORK OVER?

Automation index

How much of a Category manager’s job can AI already do?

An assortment comes earlier. The category winning without fighting own-label do not.

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

Task comparison

Category 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
Assortment, prices and the shelf.
Estimate

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

18%48%+8.6
Supplier, the negotiation and the one that will not list.
Estimate

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

16%40%+6.4
Promo, the calendar and the one that clashes.
Estimate

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

16%22%+3.5
Data, margin and not killing the category.
Estimate

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

16%28%+4.5
Own-label, the clash and not hiding it.
Estimate

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

18%14%+2.5
That the category wins.
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

  • assortment
  • supplier negotiation
  • category margin
  • promos
  • own-label
  • the shelf
  • calendar
  • listings

Sources for this job· O*NET 11-2022.00· ESCO/ISCO 1221

Radiation oncologist

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
Contouring, fractions and the dose plan.
Estimate

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

16%48%+7.7
Clinic, the tumour and what can be irradiated.
Estimate

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

18%18%+3.2
Simulation, immobilisation and the machine day.
Estimate

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

16%22%+3.5
Side effects, pauses and the patient who cannot take it.
Estimate

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

16%28%+4.5
Board, the surgeon and the medical oncologist.
Estimate

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

18%14%+2.5
Signing the plan and the dose that does not erase.
Estimate

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

16%12%+1.9
Total100%23%

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

Skills and activities

  • contouring
  • plan radiotherapy
  • dosimetry
  • RT simulation
  • fractions
  • tumour board
  • radiation effects
  • immobilise the patient

Sources for this job· O*NET 29-1224.00· ESCO/ISCO 2212

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