Examples
Examples
Try the starting example
- Aggregates: role, supplied comparison group X/Y, total pay $, matched hours
- A,X,900,10 A,Y,1000,10 B,X,1000,10 B,Y,600,5
- Overall pay/hour for X and Y (USD)
- X: 95; Y: 106.666666667
- Unadjusted relative gap, (Y−X)/Y (%)
- 10.9375
- Common pooled-hours role weights (%)
- A: 57.1428571429; B: 42.8571428571
- Common-role-mix pay/hour for X and Y (USD)
- X: 94.2857142857; Y: 108.571428571
- Common-mix relative gap, (Y−X)/Y (%)
- 13.157895
- Within-role relative gap, (Y−X)/Y (%)
- A: 10; B: 16.6666666667
Try another scenario
- Aggregates: role, supplied comparison group X/Y, total pay $, matched hours
- A,X,900,10 A,Y,1000,10 B,X,1000,10 B,Y,500,5
- Overall pay/hour for X and Y (USD)
- X: 95; Y: 100
- Unadjusted relative gap, (Y−X)/Y (%)
- 5
- Common pooled-hours role weights (%)
- A: 57.1428571429; B: 42.8571428571
- Common-role-mix pay/hour for X and Y (USD)
- X: 94.2857142857; Y: 100
- Common-mix relative gap, (Y−X)/Y (%)
- 5.714286
- Within-role relative gap, (Y−X)/Y (%)
- A: 10; B: 0
Calculation method
Calculation method
Overall pay/hour for X and Y (USD)
For each supplied group divide total pay by total matched hours.
Unadjusted relative gap, (Y−X)/Y (%)
Compare the overall rates using Y as the reference denominator.
Common pooled-hours role weights (%)
For each role use its X+Y hours divided by all pooled hours.
Common-role-mix pay/hour for X and Y (USD)
Apply identical pooled role weights to each group’s within-role pay/hour.
Common-mix relative gap, (Y−X)/Y (%)
Compare the standardized rates with Y as reference.
Within-role relative gap, (Y−X)/Y (%)
Within each role compare pay/hour with Y as reference; no covariate regression is implied.
Symbols and units
- a
- Aggregates: role, supplied comparison group X/Y, total pay $, matched hours
Use the units shown. A list keeps the order in which you enter its values. The symbol ^ means “raised to the power of”.
Assumptions & limits
Assumptions & limits
- A descriptive two-group common-role-mix worksheet using supplied aggregates. X/Y labels are not inferred demographics. Differences do not establish causes, equal-pay compliance or a defensible employment decision; no individual ranking is produced.
Are these inputs private?
These calculations run in your browser. A shared link contains the values you choose to share. Only questions submitted to the separate AI finder are sent to OpenAI.
Further reading
ILO: supplied workforce records and full-time-equivalent measurement background ↗
Background reading; this does not imply endorsement or independent review of SumFizz.