Decision-Objective drift: why good decisions lead to the wrong outcomes

There is a pattern I keep seeing repeat itself in organisations that execute well, and which I think is important to name because it is exactly the kind of problem that does not show up in any dashboard.

The numbers are moving in the right direction, the team works with coherence, decisions make sense within the existing system, and yet the results that actually matter never quite materialise. And when the organisation looks for the cause, the answer almost always points to the same place: better metrics are needed, better processes, or better tools. So adjustments are made, more is measured, what was already being optimised gets optimised further, but the problem returns.

What is rarely asked, because the system does not generate the question naturally, is whether the decision-making criteria driving the organisation is actually aligned with the outcome it needs to build towards.

And this is not a problem specific to any industry or size. I see it in organisations that are scaling, in operations teams managing complex systems under pressure, and in leadership teams making long-term strategic decisions. The context changes, but the pattern is always the same: there is an active objective guiding day-to-day decisions, that objective produces real and measurable results, and at some point those results stop reflecting what the organisation actually needs to demonstrate. Not because execution has failed, but because the objective guiding the decisions stopped being the right one, and no one updated it in time.

What makes this pattern particularly difficult to detect is that it produces no friction whilst it operates. The system keeps functioning, meetings keep making sense, and no one has visible reasons to question the direction because nothing signals that something is failing. The problem only becomes visible when there is no longer any margin to correct it, which tends to be exactly the worst possible moment to discover it.

Why your business strategy may be misaligned without anyone noticing

And yet, when the problem finally surfaces, the search for causes almost always points in the wrong direction, because the reason this happens is not a lack of discipline or information, but something more structural and more difficult to see from the inside.

Every organisation, at some point in its trajectory, develops an implicit success logic: a definition of what progress looks like, which number needs to move, which decision is the right one. That logic forms early, gets repeatedly validated by real results, and over time becomes the default criterion against which everything that follows is evaluated. And that is where the trap lies: the problem is not that this logic exists, it is necessary and efficient as long as the objective does not change. The problem is what happens when the objective changes but the logic does not, and the system keeps optimising for something that is no longer what the organisation needs to build towards, without anyone having consciously decided that.

And that moment of change rarely announces itself. There is no meeting where someone declares that the existing success criterion has stopped being valid. What happens instead is that a new objective enters the picture whilst the system keeps optimising for the previous one. And because the system keeps producing positive signals, no one has visible reasons to question it.

What accumulates during that period, decision by decision, without anyone deliberately designing it, is a gap between what the organisation is building and what it needs to demonstrate for the objective that actually matters. A gap that does not appear in any internal report, that generates no operational friction, and that only becomes visible when someone external sits down to assess what was built.

Case analysis: why high revenue does not guarantee the value you expect

To make this concrete, I want to share a real case that illustrates this pattern with clarity.

An organisation with an active exit strategy spent years making decisions that were perfectly coherent with its objective of growing: it acquired large clients, increased its revenue significantly, and built a solid growth narrative. Every decision made sense within the existing system, and the system confirmed it with positive signals at every step.

What no one was questioning is that in parallel to growing, the organisation had started to consider selling the business. And those two objectives, growing and selling, are not measured in the same way. Growing pushes towards maximising revenue, closing the largest accounts available, and demonstrating momentum. Selling, on the other hand, pushes towards demonstrating an attractive risk profile to a buyer, which includes client diversification, sustainable income, and controlled concentration. In concrete, day-to-day decisions, what serves one objective actively undermines the other, but because only one of the two objectives was guiding the day-to-day decisions, the contradiction never became visible until it was too late.

When the moment came to sit across from a real buyer, revenue was high but the risk profile had deteriorated. Income depended on a small number of large clients, which in valuation terms is not read as strength but as concentration risk, a factor that buyers discount directly from the price. The decision-maker themselves noted that they had bet on large clients to drive growth, but that same decision ended up undermining their position at the moment that mattered most.

What failed was not execution. What failed is harder to name, and harder to fix, than any metric.

How to identify this pattern in your own organisation

This case is about an exit strategy, but the pattern it describes is not. The same problem can occur when an organisation scales into a new market without updating the criterion with which it evaluates its decisions. When an operations team optimises for efficiency whilst the organisation needs to be building capacity. When delivery speed is measured whilst what actually matters is sustainable quality. Or when an organisation adopts AI because competitive pressure demands it, without first defining what should change as a consequence of that adoption, and how it would know that change is actually happening. The context changes, but the pattern is always the same: a decision-making system built around one objective produces behaviours coherent with that objective, and does not adjust itself when the objective changes.

What all these situations have in common is that no one made the right question explicit before the decisions that mattered had already been taken.

A question to take with you: is the criterion with which your organisation makes decisions today building towards something concrete, or simply towards more of the same?

If you recognise this pattern in your organisation, I have developed the full analysis of this case, including how to detect this pattern before it becomes costly, what signals indicate it is already active, and the five real options that exist once you know where you stand.