IS WORK OVER?

Automation index

How much of a Demand planner’s job can AI already do?

A forecast comes earlier. Neither an empty shelf nor a drowned warehouse do not.

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

Task comparison

Demand planner

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
Forecast, promotions and bias.
Estimate

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

18%52%+9.4
Safety stock, lead time and the order.
Estimate

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

16%40%+6.4
Sales, the spike and the promo nobody flagged.
Estimate

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

16%22%+3.5
S&OP, consensus and the fight over numbers.
Estimate

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

16%28%+4.5
The supplier who fails and not covering with air.
Estimate

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

18%14%+2.5
Neither empty nor drowned, and not inflating the forecast.
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

  • demand forecast
  • safety stock
  • lead time
  • S&OP
  • promotions
  • forecast bias
  • supplier orders
  • empty shelf

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

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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