IS WORK OVER?

Automation index

How much of a Packaging engineer’s job can AI already do?

A 3D prototype comes earlier. Surviving transport and opening on the shelf do not.

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

Task comparison

Packaging engineer

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
Spec, 3D and the drop test.
Estimate

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

18%48%+8.6
The packing line and the one that will not fit.
Estimate

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

16%22%+3.5
Material, recyclability and unit cost.
Estimate

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

16%36%+5.8
Supplier, die and pack colour.
Estimate

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

16%28%+4.5
Marketing, legal and not lying on the pack.
Estimate

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

18%14%+2.5
That it survives the trip, and not oversizing the plastic.
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

  • design packs
  • drop test
  • packing line
  • recyclability
  • die-cut
  • unit cost
  • pack spec
  • 3D prototype

Sources for this job· O*NET 17-2112.00· ESCO/ISCO 2141

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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