Identify and act on lead measures

Focus daily behavior on lead measures — the predictive actions you control — not lag measures you can only observe.

Why it works

Lag measures (revenue, weight, test scores) report results after the window for action has closed. Lead measures are predictive and influenceable in real time. Shifting attention to lead measures addresses the control problem: you cannot directly control whether you hit a goal, but you can directly control whether you perform the weekly behaviors that predict it. This creates actionable feedback rather than post-hoc evaluation.

How to do it

1. For your WIG, list 5–10 behaviors that you believe are predictive of achieving it.
2. Select 1–2 as your lead measures: they must be predictive, influenceable by you, and measurable weekly.
3. Track lead measure performance week over week — this is your primary performance dashboard.
4. Adjust the lead measure if it turns out not to be predictive after 4–6 weeks of data.

Evidence

The lead/lag distinction maps onto predictive vs. outcome measurement in management science. Feedback specificity and control are well-supported moderators of goal pursuit; acting on controllable precursors is a sound application of control theory and self-regulation research. (mechanistic)

Identifying true lead measures is harder than it looks: correlation with the lag measure does not imply causation, and teams sometimes game lead measures without improving lag outcomes (Goodhart’s Law).

Common mistake

Choosing lead measures that are easy to track rather than genuinely predictive — for example, "number of prospecting emails sent" when the actual predictor of sales is call quality, not volume.