There is a particular kind of quarterly review that has become common in mid-sized businesses. The dashboard opens. Leads are up. Engagement is up. Website traffic has grown. Social following has climbed. Every chart in the deck points in the right direction. And somewhere in the room, usually unspoken, is the quiet unease that none of this feels like the business is actually doing better. Revenue is flat, or growing slower than the metrics would suggest it should. Margins haven't moved. The problems that were being discussed a year ago are still being discussed. And yet the numbers on the screen say progress is being made. This is not a contradiction that resolves itself with more patience. It is usually a sign that the business has started measuring something other than what it meant to measure, and has stopped noticing the difference.

When the Measure Becomes the Target

In 1975, the economist Charles Goodhart, then working on UK monetary policy, made an observation that has since become one of the more quietly important ideas in management thinking. Any measure that becomes a target for behaviour will, over time, stop being a good measure of the thing it was designed to track.¹ People and organisations adapt to what is being measured, not to the outcome the measurement was meant to represent. Once that adaptation happens, the number can keep rising while the underlying reality it once reflected stalls or even declines. The social scientist Donald Campbell reached a related conclusion a few years earlier, studying how performance indicators behave inside public institutions. Campbell's Law, as it came to be known, held that the more a quantitative indicator is used for decision making, the more it will be subject to corruption pressures, and the more it will distort the very process it was meant to monitor.² A test score used to evaluate teachers eventually gets taught to, rather than used as a byproduct of genuine learning. A sales metric used to evaluate a team eventually gets optimised directly, sometimes at the expense of the outcome the sale was supposed to represent. Mid-sized businesses fall into this pattern constantly, usually without recognising it as the same pattern. Website traffic becomes a target, and it rises through channels that bring visitors who never convert. Lead volume becomes a target, and the definition of a lead quietly loosens until the number climbs while lead quality falls. Content output becomes a target, and more gets published while less of it says anything a reader would remember. None of this is dishonest. It happens gradually, through hundreds of small optimisations, each one locally reasonable, until the metric and the outcome it was supposed to stand in for have quietly come apart. This is visible across almost every industry, once you know where to look. A hospitality brand tracking occupancy will fill rooms through rate cuts that erode margin faster than occupancy improves revenue. A telecom operator tracking subscriber additions will onboard customers who churn within the first billing cycle, because the metric rewarded the acquisition, not the relationship. A manufacturing unit tracking units produced will hit its number while quality complaints rise in the same quarter, because nobody adjusted the target when the definition of a good outcome should have widened. In every case, the number was real. It simply stopped being connected to what the business needed it to represent.

Surrogation

The Harvard Business School researchers Michael Harris and Bill Tayler gave this phenomenon a precise name in a 2019 study: surrogation.³ It describes the moment when a team stops treating a metric as a proxy for a strategic goal and starts treating the metric as the goal itself. The measure was only ever supposed to stand in for something harder to observe directly, customer trust, market position, the health of a pipeline. Surrogation happens when the stand-in quietly replaces the thing it was standing in for. Harris and Tayler's research found that this substitution is not a failure of intelligence or diligence. It happens most often in teams that are highly engaged and genuinely trying to perform well against the goals they have been given. The problem is upstream of effort. It sits in the choice of what got measured in the first place, and in how quickly everyone in the organisation forgot that the metric was a translation, not the original text. This is where the discomfort of the illusion of progress actually lives. It is not that teams are gaming the numbers cynically. It is that the numbers became the mission somewhere along the way, and nobody made that decision explicitly.

Why the Balanced Scorecard Didn't Fix This

In 1992, Robert Kaplan and David Norton introduced the Balanced Scorecard, a framework designed specifically to correct an earlier version of this same problem, the tendency of businesses to manage exclusively against financial metrics that reflected past performance rather than future capability.⁴ The scorecard asked leadership to track customer, process, and learning measures alongside the financial ones, on the theory that a fuller picture across categories would prevent any one number from becoming a false proxy for overall health. The framework was widely adopted. It did not fully solve the problem it was built for. What frequently happened instead, as later research by the organisational scholar Marshall Meyer documented, is that businesses adopted the structure of the scorecard while still allowing one or two metrics within it to dominate decision making in practice.⁵ The scorecard multiplied the number of things being measured. It did not, by itself, change the underlying tendency to let the easiest or most visible metric quietly become the real target. This detail matters because it suggests the illusion of progress is not solved by measuring more things. A business can have a sophisticated, multi-dimensional dashboard and still be captured by surrogation, if leadership has not maintained an active, ongoing relationship with what each number is actually meant to represent.

The Cost of Measuring What Is Easy

Some things are simple to measure and say little. Some things say a great deal and are difficult to measure. The gap between these two categories is where most mid-sized businesses quietly default. Website visits are easy to count and loosely related to revenue. Customer trust is hard to quantify and closely related to it. Content volume is trivial to track. Whether a reader remembers what they read six months later is not. Sales calls made is a number available at the end of every day. Whether those calls are changing how prospects think about the business is a question that requires judgment, time, and a willingness to sit with ambiguity. The historian Jerry Muller, whose 2018 book on this subject examined how the obsession with measurable performance has spread across medicine, education, and business alike, described this as a kind of institutional convenience.⁶ Measuring the easy thing feels like accountability. It produces a number that can be reported upward, defended in a meeting, and compared across time. Measuring the hard thing produces a judgment that can be argued with. Organisations, under time pressure, gravitate toward the version that cannot be argued with, even when it is measuring less of what actually matters. This is not a comfortable observation for any business that prides itself on being data-driven. The data was never the problem. The problem is that being driven by data requires knowing, continuously, whether the data in front of you is still connected to the thing you originally cared about, and most businesses stop checking once the dashboard is built.

What This Actually Requires

There is no metric immune to this pattern. Any number, however well chosen at the outset, will eventually be optimised toward by people who are rewarded for it, and will eventually drift from the outcome it once represented. This is not a design flaw to be fixed once. It is a condition to be managed continuously. That management is less about better dashboards and more about a standing willingness to ask, of every metric currently driving decisions, what it was originally meant to stand in for, and whether it still does. It requires someone in the business being willing to say, in a room where the numbers look good, that the numbers looking good is not the same as the business being better. That is a harder thing to say than it sounds, particularly to a team that worked hard to move those numbers.

A Question Worth Sitting With

The next time a review shows metrics trending in the right direction, it is worth asking a different question than usual. Not whether the number went up. Whether anyone in the room could explain, in plain language, what the number was originally supposed to be evidence of, and whether it is still evidence of that, or has simply become the thing being chased. Most businesses have at least one metric they would struggle to answer that question about. Finding out which one is uncomfortable. It is also usually where the real diagnosis begins.

Falgun has worked with founder-led businesses across telecom, hospitality, and premium consumer brands for 28 years. He writes from experience, not observation.

References

References
Goodhart, Charles. Problems of Monetary Management: The UK Experience. Papers in Monetary Economics, Reserve Bank of Australia, 1975.
Campbell, Donald T. Assessing the Impact of Planned Social Change. Evaluation and Program Planning, 1979.
Harris, Michael, and Tayler, Bill. Don't Let Metrics Undermine Your Business. Harvard Business Review, September-October 2019.
Kaplan, Robert S., and Norton, David P. The Balanced Scorecard: Measures That Drive Performance. Harvard Business Review, January-February 1992.
Meyer, Marshall W. Rethinking Performance Measurement: Beyond the Balanced Scorecard. Cambridge University Press, 2002.
Muller, Jerry Z. The Tyranny of Metrics. Princeton University Press, 2018.

The Illusion of Progress: When Metrics Improve but the Business Doesn't