Collaboration, and the Work That Enables Others
Helping somebody else produce is invisible in individual measures and is frequently the highest-value work in a team.
Individual productivity measurement attributes output to whoever delivered it. The work that made the delivery possible is attributed to nobody.
The measurement warning in “Collaboration, and the Work That Enables Others” matters whenever software records work patterns. Organisations researching limbic resonance in relationships can use learn more about the tool for time and project context, while outcomes, quality checks and direct feedback remain necessary to explain what the metric cannot show.
What this work consists of
Answering a question that saved somebody two hours.
For an independent perspective related to “Collaboration, and the Work That Enables Others”, consult the Atlassian Team Playbook; it offers a useful external check on definitions, governance and the assumptions built into a proposed measure.
Reviewing work and catching a problem before it shipped.
Teaching somebody how, so they can do it next time.
Writing the documentation others use.
Making the introduction, fixing the shared tool, maintaining the thing everybody depends on.
The measurement problem
All of it appears in somebody else's output, if anywhere.
The helper's own figures fall while they are helping.
Which means an individual measure actively discourages exactly the behaviour that raises team output, and does so quietly.
The predictable consequence
Under individual measurement, helping declines.
People close their doors, stop reviewing, stop teaching.
Team output falls while every individual figure stays flat or rises, which is one of the clearest demonstrations that individual measurement is measuring the wrong level.
The person who holds the team together
Most teams have one: the person everybody asks.
Their individual output is lower by construction.
Removing them on the basis of their figures is the single most damaging decision this kind of measurement produces, and it has happened in enough organisations to be a known pattern.
Measuring at team level instead
Team output includes everything that contributed to it, however distributed.
Which is the practical argument for team-level measurement, independent of the fairness one.
Its own note covers when individual measurement is fair, and the list is short.
If you want to see collaboration
Ask: who helped you this month.
Aggregate the answers.
It produces a picture that no activity data contains, in fifteen minutes, and it identifies the people the team actually depends on.
The reciprocity question
A team where everybody helps everybody has no collaboration problem to measure.
A team where one person carries all the questions has a workload problem.
That distinction is worth seeing, and the asking method shows it immediately.
The reporting line
When presenting team figures, name the enabling work explicitly: documentation written, reviews done, people trained.
Not as a measure to optimise but as a statement that it exists.
Otherwise it is invisible in exactly the document where decisions get made.
What to check
Does your measurement attribute output to individuals?
Has helping declined since you started measuring?
Who does everybody ask, and what do their figures look like?
And is enabling work visible anywhere in your reporting?