The number went up.
Before celebrating, I would like to know which number.
More messages answered? More hours worked? More people reached?
Each can describe something useful. Each can also leave the important part unexplained.
Imagine a team asked to answer enquiries faster. The response time improves. Excellent.
But if the first reply simply tells everyone that somebody else will contact them, the clock looks better while the customer is still waiting for help.
The measure has recorded a real event. It has not necessarily recorded the result we wanted.
I think this becomes particularly interesting when a number is easy to see and the purpose behind it is harder to examine.
A full calendar looks productive. It does not tell us what the appointments accomplished.
A widely viewed article has reached people. That alone cannot tell us whether the right people read it, found it useful or explored anything else.
There is nothing wrong with tracking the number. The difficulty begins when we ask it to answer a question it was never designed to answer.
What are we trying to understand?
I would start by finishing this sentence:
“We are measuring this because we want to understand…”
If the answer is “whether our communication is useful,” response speed may need company: what happened to the enquiry afterwards? Did the person receive what they needed?
If the answer is “whether people are discovering our work,” reach matters. If we want to understand whether that discovery leads to enquiries, we need to look further along the path.
The objective determines what else deserves attention.
It also helps us notice the work that a simple count can miss. One conversation might resolve a problem that twenty earlier messages left untouched. An appointment might end with a decision that removes the need for three more meetings.
Counting the activity remains useful.
Understanding its contribution takes another question.
And when the number falls?
This changes how we discuss a disappointing result, too.
A lower number may deserve investigation. It does not automatically mean that the underlying work has become worse.
Look at the timeframe. Look at what was counted. Look at the behaviour around it.
Perhaps fewer people arrived, but more of them found something relevant. Perhaps the decline points to a problem that needs attention. We need evidence to distinguish those possibilities.
I want measurement to improve our understanding of the work.
For that to happen, we have to keep asking a question that the dashboard cannot answer for us:
What would a useful result look like outside the dashboard?
That question also belongs in any discussion about what someone is trying to achieve.
Silvia
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