Averages are everywhere in people data.
Average engagement scores.
Average wellbeing.
Average satisfaction.
They look helpful. They feel objective. But when it comes to understanding how people actually feel at work, averages often hide the very problems leaders need to see.
An average is designed to simplify. It takes lots of different experiences and turns them into one number. The problem is, people don’t experience work “on average”.
When sentiment shifts in one part of the organisation, an average often absorbs it rather than highlights it. A small but serious issue can disappear inside a stable-looking number.
Leadership teams often look at an average score and think:
“Things look broadly fine.”
“Nothing urgent is happening.”
“Let’s keep an eye on it.”
Meanwhile:
One team is struggling
A manager is under pressure
Frustration is building quietly
The average doesn’t lie, but it doesn’t tell the whole story either. This is why organisations are sometimes surprised by problems that, in hindsight, were visible for months.
In people data, the most important signals often sit at the edges:
Teams under sustained pressure
Groups whose sentiment is dropping quickly
Pockets of disengagement that don’t show up overall
Averages pull attention toward the middle and away from these edges. As a result, leadership conversations focus on stability instead of movement. This dynamic is explored further in The Danger of Averages in People Data.
Averages are comfortable. They reduce complexity and avoid uncomfortable questions. But they also:
Delay difficult conversations
Encourage “wait and see”
Make responsibility less clear
When the average looks acceptable, it’s harder to justify early action, even when something doesn’t feel right.
Leaders don’t need more numbers. They need visibility into:
Where sentiment is changing
How fast it’s moving
Which areas need attention first
That requires looking beyond averages and paying attention to variation and movement, not just the headline score.
Averages aren’t wrong. They’re just blunt. When organisations rely on them too heavily, early warning signs get smoothed away, and problems surface only once they’ve grown harder and more expensive to deal with.