What leaders usually conclude
The instinctive read is a strategic misalignment problem — the product team needs a clearer brief about what the business actually needs. This is not wrong, but it typically leads to another round of strategic communication, which often does not change the outcome, because the underlying issue may not be a lack of clarity about the strategy but a mismatch between what the strategy asks for and what the product team’s actual metrics reward.
What the evidence suggests
Steven Kerr’s research on reward systems, drawn from a manufacturing company, an insurance firm, and settings spanning politics, medicine and academia, describes precisely this structure: organisations frequently reward one set of behaviours while hoping, without actually incentivising, a different outcome. As Kerr put it, “most organisms seek information concerning what activities are rewarded, and then seek to do… those things, often to the virtual exclusion of activities not rewarded.” A product team measured on shipped features and engagement metrics will optimise for shipped features and engagement metrics — entirely rationally — even where the business’s actual need, that quarter, might be something engagement metrics do not capture well, such as expanding into a new customer segment or addressing a source of churn that engagement dashboards do not surface clearly.
This connects to a further, related mechanism: V. F. Ridgway’s research on performance measurement found that quantitative measures, however useful, can produce consequences the organisation did not intend when relied on without full awareness of their limits. A product team’s engagement metrics are a genuinely useful signal for some questions and a poor one for others, and the gap between what the metric measures and what the business actually needs at a given moment tends to widen exactly as the company scales and diversifies, because a single set of product metrics was rarely designed to capture every dimension a growing, increasingly complex business now depends on.
Jay Galbraith’s research on organisation design supplies a structural explanation for why this drift is so difficult to catch in real time. As a company scales, the information the product team needs — a genuinely current read on the business’s shifting priorities — has to travel from wherever it originates (often sales, finance, or leadership conversations about competitive positioning) to the product team, and that channel is rarely as fast or as reliable as the product team’s own internal metrics dashboard. The result is a structural information lag: the product team’s own numbers update daily, while its understanding of what the business actually needs updates only whenever someone deliberately closes that gap, which in a fast-growing, increasingly complex organisation happens less often than the business itself is actually changing.
Competing explanations
A firm might instead attribute the drift to weak product leadership — a team simply making poor prioritisation calls despite good information. Leadership quality is a real variable, but this explanation does not account for why strong, capable product teams in different companies show the same pattern: teams hitting their stated metrics while the business drifts. The recurrence across different teams and different leaders points toward the incentive structure itself, rather than the judgement of any particular team.
It is also worth distinguishing this from a simple metrics-design flaw. Even a well-designed metric, chosen carefully at one point in a company’s life, can become misaligned with the business’s needs purely because the business itself has changed — expanded into new segments, encountered new competitive pressure — while the metric, and the team’s incentive to hit it, has not been revisited to reflect that change.
Goal-setting cadence tends to reinforce the drift once it starts. Many technology companies set quarterly targets for product teams that, once agreed, remain fixed for the quarter regardless of what the wider business subsequently learns about its own priorities. A team locked into a quarter-old target has every reason to keep optimising for it even after the business’s actual need has shifted, since changing course mid-quarter typically means missing the original goal without necessarily being credited for whatever more relevant work replaced it.
Where this shows up
People working in technology companies will probably recognise this pattern first. The wider Professional and Knowledge-Based grouping and the other sectors page show how it presents elsewhere.
Questions worth considering
- Does what this product team is measured on actually track what the business currently needs most, or has the two quietly diverged?
- If the product team’s current metrics stayed exactly the same but the business’s priorities changed, would anyone notice the mismatch before it showed up in results?
- How would this organisation know if its product metrics were measuring something real but no longer the most important thing?
- When did anyone last deliberately compare what the product team optimises for against what the business’s current commercial priorities actually are?
Your team is facing similar challenges?
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