Lead Measure and Lag Measure

What it is

The distinction sits at the centre of The 4 Disciplines of Execution by Chris McChesney, Sean Covey and Jim Huling (Free Press, 2012). FranklinCovey's launch release gives the second discipline as acting on the lead measures.

A lag measure describes an outcome after the fact: papers published, revenue booked. By the time it moves, the period that produced it is over. A lead measure describes something done during the period. It has two properties in the framework's account. It is predictive, meaning that doing more of it should move the lag measure, and it is influenceable, meaning that the team can change it this afternoon.

The practical effect is to turn an intention into something countable. A team that wants a better result cannot do anything about the result directly, but it can count calls made, hours spent or visits completed and see the count rise or fall within the week.

In Deep Work (2016), Cal Newport adapted the idea for a single person. His lag measure was research papers accepted. His lead measure was hours of deep work, kept as tally marks on a card placed where he could not avoid seeing it.

In effect

The research that bears on this discipline is research on feedback and monitoring, and it was not designed to test lead measures by name.

Locke and Latham's 2002 review of goal-setting research found that goals combined with feedback on progress performed better than goals alone. A lead measure is a source of that feedback, because it gives a person a number that responds within the same week.

A 2016 meta-analysis in Psychological Bulletin pooled randomised experiments on monitoring progress towards a goal, 138 studies with nearly 20,000 participants. Interventions that prompted people to monitor raised how often they checked their progress and produced a smaller but reliable gain in reaching the goal. Part of the gain ran through the extra monitoring, and the gain was larger when progress was physically recorded. A tally card on a desk is a physical record of this kind. Those experiments tested monitoring interventions, and we are drawing the connection to lead measures ourselves.

A 2022 conference paper on 43 relationship managers at one Indonesian bank reported that each of the four disciplines, lead measures included, was positively associated with meeting credit targets. The data were questionnaires, interviews and company records from a single workplace, so the result describes an association there.

What it does not say

It does not say that any behaviour a team can count is a good lead measure. The framework's claim is that the chosen behaviour drives the result, and that is a hypothesis about each team and each goal. Neither the framework nor the research above establishes it for a particular case. A team can count something easily and find that the count moves while the result does not.

It does not remove the side effects of goal setting. The 2009 paper titled Goals Gone Wild in Academy of Management Perspectives listed more unethical behaviour among the systematic side effects of goals, and a number that people are scored on is a place where that can arise. The paper concerns goal setting in general and does not study lead measures.

It has not been evaluated independently as a discipline. The evidence the framework came with was the vendor's own count of client teams, and the direct study found is a small conference paper from one bank. Not evaluated is not the same as shown not to work.

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