IS WORK OVER?

Automation index

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

A script comes earlier. Them not hanging up in ten seconds, and not lying, do not.

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

Task comparison

Telemarketer

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
Script, queue and the shift.
Estimate

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

18%48%+8.6
The call, the no and the one who insults.
Estimate

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

16%40%+6.4
Data, GDPR and not pushing extra.
Estimate

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

16%22%+3.5
Target, the bonus and not dressing contacts.
Estimate

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

16%28%+4.5
The supervisor, quality and not skipping the no.
Estimate

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

18%14%+2.5
That they do not hang up, and not lying.
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

  • scripts
  • call queues
  • GDPR
  • targets
  • call quality
  • shifts
  • contacts
  • the no

Sources for this job· O*NET 41-9041.00· ESCO/ISCO 4222

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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