Early signals are, by definition, small. They do not look like problems yet. They look like a slight dip in the score, a participation rate that is a little lower than last cycle, a team that has been sitting slightly below the organisational average for a few weeks. None of these seem urgent. All of them are worth paying attention to.
Early signals in people data rarely announce themselves. They tend to be gradual and easy to rationalise. The score drops a couple of points - probably just a busy period. Participation is down in one team - probably just timing.
The rationalisations are often correct. Most early signals do not develop into problems. But some do - and the ones that do are identifiable in advance, if you are watching closely enough.
Not all movement in a score is significant. The patterns that most often precede problems are:
The practical heuristic is duration. A single cycle of movement is almost always noise. Two consecutive cycles moving in the same direction is worth noting. Three or more is a pattern worth investigating.
When a pattern emerges that is worth paying attention to, the first response should be curiosity rather than intervention. What was happening in this team or period? If the context explains the movement and it resolves, the signal was informative but not urgent. If the movement continues, that is when a more direct response is warranted.
Early signals are only visible if you are measuring frequently enough to see them before they become trends. The habit of watching gradual movement - in score, in participation, in the gap between teams - is what creates the early-action advantage.
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Also worth reading: How to spot patterns across teams before they become problems