Involving the People Measured
The people doing the work know where the measure will be wrong. Asking them before deployment is cheaper than finding out after.
Measurement designed without the people measured is designed without the information needed to design it. This is practical rather than consultative.
The human context in “Involving the People Measured” should be set before a workforce platform is configured. A team evaluating employee monitoring under GDPR for gdpr employee monitoring can keep the rollout credible by stating the purpose, selecting only necessary settings and documenting how employees can review or correct records.
What they know that you do not
Which items are large and which are trivial, which is the comparability problem.
For an independent perspective related to “Involving the People Measured”, consult the U.S. Equal Employment Opportunity Commission; it offers a useful external check on definitions, governance and the assumptions built into a proposed measure.
What varies month to month for reasons outside their control.
Where the recording is ambiguous.
What they would stop doing if the measure mattered.
And which of the work is invisible to any system, which is usually more than expected.
The three questions
What would you say shows a good month for this team?
What would make this number wrong?
What would you have to stop doing to make it go up?
An hour with a team produces better measure design than any amount of external analysis.
Why the third question is the most valuable
It names the gaming in advance.
People answer it honestly when nothing is attached, and they are describing a weakness in the measure rather than confessing an intention.
The answers tell you exactly which counterweight you need.
What to do with the answers
Adjust the definition.
Add exclusions for work that should not count.
Add the counterweight they identified.
And publish the known limitations, which the previous note covers.
The ownership effect
A measure a team helped design is one they explain rather than resent.
They correct errors in it.
And they raise problems with it openly rather than working around it, which is the behaviour that keeps the data usable.
Where involvement is not appropriate
Where a measure must be independent for assurance reasons: audit, safety, regulatory.
Here the people measured can be consulted on definitions but should not control them.
Saying which situation you are in avoids the suspicion that consultation is theatre.
Ongoing rather than once
Review with them periodically.
Work changes, and a measure designed around last year's work describes last year.
The team notices first, and a standing route for them to say so is the cheapest maintenance available.
The signal when involvement is refused
If a measure cannot be explained to the people it measures, or they object strongly and specifically, that is information about the measure.
Not always decisive — sometimes the objection is to being measured at all.
But a specific objection usually identifies a real defect, and it is worth separating the two.
What to check
Were your measures designed with the teams?
Has anybody asked the third question?
Are the limitations they identified written down?
And is there a route for them to raise problems with a measure?