Automation index
How much of a Shelf replenisher’s job can AI already do?
A wave comes earlier. Filling the shelf without blocking the aisle do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Shelf replenisher
21%
AI can already do 21% of this job.
#435 / 633
View rankingShelf replenisher
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.
| Task | Share | AI | Points |
|---|---|---|---|
Wave, location and the cage.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 36% | +5.8 |
Shelf, date and the one at the back.EstimateNo public source provides a precise figure. This is our estimate. | 22% | 10% | +2.2 |
Aisle, the customer and not blocking.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Out of stock, calling it and the gap.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The peak, overtime and not mixing batches.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Shelf full, and aisle clear.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 12% | +1.7 |
| Total | 100% | 21% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- waves
- the shelf
- dates
- aisles
- stock-outs
- cages
- batches
- gaps
Sources for this job· O*NET 43-5081.00· ESCO/ISCO 9334
IS WORK OVER?
Data architect
28%
#83 / 633
View rankingData architect
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.
| Task | Share | AI | Points |
|---|---|---|---|
Models, lineage and the catalogue.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Pipelines, quality and the data contract.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
The analyst who finds nothing and the mess.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Privacy, retention and the field you cannot keep.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The business, shadow IT and not building another lake.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
That it gets used, and not letting raw data rot.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 28% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- model data
- lineage
- data catalogue
- data contracts
- pipeline quality
- retention
- data lakes
- privacy
Sources for this job· O*NET 15-1243.00· ESCO/ISCO 2511