Individual Measurement and When It Is Fair
The conditions under which measuring one person's output is reasonable, and why they rarely all hold.
Most of this collection argues for team-level measurement. There are cases where individual measurement is fair, and they share specific properties.
The human context in “Individual Measurement and When It Is Fair” should be set before a workforce platform is configured. A team evaluating step-rate compensation guide for step rate compensation can keep the rollout credible by stating the purpose, selecting only necessary settings and documenting how employees can review or correct records.
The conditions
The person controls the outcome: their output does not depend substantially on others, on queues, or on what work arrives.
For an independent perspective related to “Individual Measurement and When It Is Fair”, consult the ICO employment-practices guidance; it offers a useful external check on definitions, governance and the assumptions built into a proposed measure.
The work is comparable: their items are similar in size and difficulty to each other and to colleagues'.
The measure is complete: it captures most of what they contribute, including help given to others.
And the conditions are equal: same tools, same support, same work mix.
All four, not three.
Where they hold
Piece work with uniform items.
Commission-based sales of comparable products, with territory accounted for.
Some processing roles with randomly allocated work.
These are real and they are a smaller share of modern work than measurement systems assume.
Where they do not
Anything involving handoffs or dependencies, which the systems section covers.
Anything where work is chosen rather than allocated.
Professional and knowledge work, per the unit problem.
And any role where enabling others is part of the job, which the collaboration note argues is most of them.
The allocation question
If people choose their next item, individual comparison measures choices as much as performance.
If work is allocated, the allocator determines the figures.
Either way somebody other than the person affects their number, which is the condition that fails most often.
The fair version where it applies
Measure it, pair it with quality, review the allocation for fairness, and discuss it with the person rather than ranking them.
The ranking adds nothing that the conversation does not, and it adds every problem the people section describes.
Using it for development
Individual data can be useful to the person: where their time goes, what they get stuck on.
Given to them, for their own use, with nobody else seeing it.
That is a different arrangement from assessment and it is the one most likely to be welcomed.
The honest default
Team level, unless all four conditions hold.
And where somebody asks for individual figures, test against the four rather than against whether the data exists.
Availability is not justification, which is the point this whole section rests on.
What to check
Do all four conditions hold for any role you measure individually?
Who determines which work each person gets?
Is enabling work captured anywhere?
And is individual data ever given to the person for their own use?