A flashlight has a most mundane but curious property: the moment you flip the switch, the room becomes both brighter and darker. Wherever the light beam hits, details are rendered in sharp focus, and objects you hadn’t realized were there become clearly visible. At the same time, the opposite occurs everywhere: the rest of the room not illuminated by the flashlight beam falls into deeper shadow. The darkness is not a flaw of the flashlight; it is a necessary trade-off for the light it produces. The same is true of performance measurement. Each KPI illuminates one dimension of a company’s operations, whether that be revenue growth, customer satisfaction, employee productivity, inventory costs, or operational efficiency. KPIs make it easier for executives to understand, analyze, and (one hopes) improve organizations, converting complexity into data points that facilitate decisions, rather than gut feeling or anecdote alone. For decades, the standard solution has been the same: if one KPI helps uncover something important, perhaps 10 KPIs can provide a better understanding, and 100 can illuminate everything clearly. That’s the rationale behind the modern dashboard: displays of gauges and graphs, crammed with performance indicators, accompanied by meetings to debate the resulting data, all aimed at dispelling ambiguity.
For all intents and purposes, this is a completely reasonable yet equally impossible aspiration. That may sound startling given how much more access we have to data than ever before. We store it on massive servers at minimal cost. We use sophisticated analytics and AI to glean insights from terabytes of information. It seems that if we just gather enough data and track enough metrics, we should eventually be able to eliminate the shadows completely, but we never do. This isn’t because organizations aren’t diligent, or their dashboards are poorly designed, or due to management failing to pick the right KPIs. It is because measurement always has its limitations. The first step in any measurement is deciding what we want to measure, a step often so mundane that it slips below notice.
Someone first decided that customer retention was a worthwhile thing to track.
Someone first determined that employee productivity could be represented and measured in an operational way.
Someone decided to define and track inventory turnover.
While individually unremarkable, these choices coalesce to determine how an organization understands itself, and this is where a conversation about management science turns toward a more ancient philosophical inquiry: is it possible to represent all aspects of reality? As the history of thought suggests, the answer is no. All representations of something omit something from it. Every descriptive attempt leaves something else out. A given perspective must, by its very essence, exclude other perspectives. The limitation of KPIs is not that they don’t capture enough, but that they cannot capture everything simultaneously…and maybe they shouldn’t. Imagine that a cartographer were asked to draw a complete map of a country, including every road, every river, every building, every tree, every shifting cloud, and every stone on its surface. If the map were rendered with perfect accuracy down to the atomic level, it would no longer function as a map – it would be indistinguishable from the country itself. In that case, its utility would depend entirely on what it had omitted.
The Argentine author Jorge Luis Borges nailed this with his short tale “On Exactitude in Science.” The empire there had grown so hung up on perfection that the imperial cartographers had produced a map so detailed and at precisely the same scale that it mirrored the entire empire. This was an incredible (and utterly useless) feat of accuracy.
A map as large as reality provides nothing useful because it has forfeited the very abstraction that made maps useful.
Organizations seem to be striving toward the same ambition when they set out to create dashboards. Each new initiative seems to yield yet another metric. Each new blind spot feels solvable if we can just add one more indicator. Along the way, however, we realize that the dashboard has ceased to represent reality by abstracting from it and has begun to become reality itself by trying to represent every aspect of it.
Rather than helping us understand the world by reducing its complexity to a set of meaningful patterns, the dashboard simply introduces its own brand of complexity. It becomes another source competing for our attention, rather than helping to direct it. The ultimate irony, of course, is that by attempting to eliminate uncertainty, we’ve somehow succeeded in regenerating it.
Therein lies the discomfort. Performance measurement has never been about completeness. It has always been about selection. The pertinent question isn’t whether or not our dashboards contain blind spots. They always will – that is a foregone conclusion. The truly germane question is this:
On which blind spots have we collectively and knowingly chosen to focus, and what price does this quietly cost us?
Every Map Leaves Something Out
Abstraction is the very reason measurement exists.
1933: a philosopher and scientist named Alfred Korzybski made a statement that has endured as one of the most profound observations about the nature of human knowledge: “The map is not the territory.” Maps work precisely because they are incomplete.
A road map omits soil conditions.
A geological map omits speed limits.
A weather map omits property boundaries.
A subway map omits actual geographic distances.
A political map omits mountains and rivers.
None of these maps is wrong per se; they simply emphasize certain features by ignoring others. In other words, every map imposes an opportunity cost.
By helping you see one thing more clearly, it forces you, however temporarily, to stop looking at countless others. The same subtle truth underpins every single KPI we have ever created.
Imagine a manufacturing plant decides to elevate production speed to the top of its list of indicators. Almost immediately, the company begins to view itself through that lens. Conversations about throughput take center stage, and managers trumpet short cycle times. None of that is necessarily bad in itself, but the problem lies elsewhere. As the spotlight shines brighter on the speed-of-production-indicator, other valuable activities start to fall into the shadows. Craftsmanship becomes hard to recognize because it never moves at maximum velocity.
Careful experimentation with new processes is slowed by the urgency to produce.
Mentoring inexperienced workers becomes harder to justify because it doesn’t contribute directly to immediate output.
Knowledge sharing is quietly abandoned because documenting lessons learned doesn’t increase this month’s production figures.
Preventive maintenance suddenly feels like a costly delay rather than a wise investment.
None of those things become any less valuable; they just become less visible, and that is a critical distinction.
Organizations don’t typically abandon what matters because they consciously decide they don’t care about it. More often, they abandon it because attention shifts. Like a river changing its course, attention reinforces whichever pathway it flows through, gradually starving its adjacent tributaries of life. Every KPI generates the current:
Measure costs mercilessly, and resilience is slowly yielding ground to pure efficiency.
Measure speed aggressively, and craftsmanship begins to politely negotiate for a little bit of air to breathe.
Measure customer acquisition relentlessly, and customer loyalty quietly slips into the background.
Measure individual performance exclusively, and collaboration starts competing for recognition.
Measure short-term results obsessively, and long-term capability becomes an investment nobody feels they can afford.
Measure productivity and some amount of creativity has become the opportunity cost.
These aren’t implementation problems but a natural consequence of choosing one map over another. No organization, however sophisticated, escapes this inherent trade-off. The only question is whether it acknowledges it.
To believe otherwise is to believe that light can exist without shadow, or a river can flow down all of its tributaries simultaneously. Neither is possible regardless of how much wishful thinking we may engage in.
Self-reflection: What parts of your organization exist only because they were left off the map? What have your dashboards quietly trained you to stop seeing?
The Things We Know but Cannot Measure
A lot of an organization’s most significant strengths never make their way into a spreadsheet or a performance dashboard. That doesn’t mean they’re worthless. It simply means they’re unquantifiable.
There was once an old tale about a master luthier. Years ago, his apprentice learned how to master every single measurable aspect of the luthier’s art. They learned the ideal wood thickness, neck angle, and sound box dimensions. They learned precise moisture levels for every species of wood. They learned about ratios honed by centuries of master violin makers.
One afternoon, after completing their masterpiece, a violin so technically perfect that it was a work of art, the apprentice presented it to the master. The old craftsman peered at the instrument, ran his hand over its smooth, polished surface, and asked the apprentice one simple question: “Did you listen to the wood?” The apprentice stared at him, confused. He’d measured everything to a T, but he’d never thought to listen. “What does it even mean to listen to wood?”
The story may be apocryphal, but the phenomenon it describes is undeniably real. There’s a form of knowledge that cannot be expressed in mathematical equations or codified in best practices manuals. However, we can recognize it immediately when we see it, though we have difficulty pinpointing its nature.
The experienced doctor whose intuition alerts them to a problem that’s not yet showing up on the medical monitors.
The teacher who somehow senses that a perfectly attentive student with straight A’s is secretly struggling.
The firefighter who somehow knows when a building’s imminent collapse.
The negotiator who intuitively understands when utter silence will be more effective than a persuasive argument.
Ask any of these individuals how they knew, and you’re likely to get equally unsatisfying answers: “It just didn’t feel right.” / “Something was off.” / “You get a feel for it.“
From the perspective of someone seeking concrete data, these explanations can feel maddeningly elusive. Nevertheless, organizations implicitly rely on such judgment calls all day long.
For example, most of Michael Polanyi’s thought process was organized around that observation. He had the famous concept, “We know more than we can tell,” as a challenge to the notion that any valid knowledge eventually would be captured, measured, standardized, and written down. Some knowledge can easily live in a spreadsheet, yet other knowledge lives in people. They accumulate it from experience and mistakes, from gut feeling and intuition, and the kind of pattern recognition and observation which is rarely explicit enough to measure, which Polanyi referred to as tacit knowledge.
Maybe one of the best illustrations comes from something as simple as bicycle riding.
All but the most clumsy can ride a bike, hardly thinking, balancing, managing pressure and momentum, timing the minute variations in the bars, and coordinating muscles all at once. Now try asking someone to describe every single detail needed to balance, and you get a clear sense of just how much their knowledge lies beyond their words.
Knowing how differs from knowing about.Organizations have vast storehouses of this tacit knowledge:
The repair specialist who can listen to a car engine and sense what needs repair down the line.
The customer service rep who detects someone’s incipient dissatisfaction long before the complaint is lodged.
The project leader who picks up on tensions in a team meeting long before the employees are even conscious of it, or the survey forms do.
The production supervisor who notices a subtle change in a machine’s rhythm before any sensor or maintenance report flags an issue.
The sales manager who recognizes that a long-standing client is preparing to leave, not because of declining revenue, but because of a slight shift in tone during routine conversations.
All those things, those pieces of organizational know-how, don’t fit into a nicely curated dashboard, but that doesn’t make them less true. Unfortunately, just because they don’t fit, that can be an excuse to ignore them, since what can be measured tends to take precedence over what cannot.
It is here that another philosopher enters the picture, not to tell anyone how to run a meeting, but because he wrote so clearly about human thought: Nobel laureate and psychologist Daniel Kahneman, who coined the acronym:
WYSIATI –“What You See Is All There Is.”
His point was simple: human beings naturally construct stories based on the information available to them in the moment. We seldom consider what’s missing. This makes our lives easier in countless day-to-day decisions. Within organizations, it quietly sculpts our culture.
Imagine two leadership meetings.
The first features executives spending an hour analyzing revenue trends, customer acquisition costs, production efficiency, and employee utilization.
All the charts are ready. All the numbers are current.
The second meeting begins with a question that causes a flicker of discomfort: “How much institutional knowledge have we lost this year?”
Now, everyone is hushed, almost deathly silent. This is not because the question is irrelevant, but because no one has a chart tracking decades of experience retiring with long-time employees. No dashboard shows the slow erosion of mentorship. No KPI reports on the silent confidence a junior engineer accumulates watching a senior colleague solve tough problems over half a decade. Thus, the conversation inevitably circles back to the numbers, not necessarily because they are more important, but because they are present.
This is the subtle peril Kahneman described. Visibility masquerades as importance so powerfully that the longer a metric appears on a dashboard, the more likely we are to assume it deserves our attention. Soon enough, the organization behaves as though the measurable world is indistinguishable from the genuinely important world. Hardly. We don’t see trust appear on a dashboard. Nor does curiosity, judgment, wisdom, humility, psychological safety, institutional memory, craftsmanship, talent, or brilliance.
These qualities do not diminish in value because they defy quantification; they simply attract less attention, and attention (arguably more than money or time) is an organization’s most scarce resource. Consider the origin of a great river. Initially, it has countless tributaries – some narrow and tortuous, others wide and majestic. It cannot flow down all of them simultaneously, and once it commits to one path, the others quickly recede. Attention works the same way.
Every meeting agenda, every dashboard, every quarterly objective, every KPI selects one path for the organization’s energy and focus, while the rest begin to fade into the background. This is the opportunity cost of our dashboards, which we seldom discuss. When leaders choose to measure productivity, they aren’t simply choosing to observe productivity; they’re choosing to commit meetings, incentives, conversations, budgets, promotions, and intellectual energy to it.
Something else will inevitably receive less attention: maybe it’s creativity, mentoring, experimentation, or reflection. What is certain is they won’t vanish overnight, but, like an abandoned riverbed, they’ll receive a little less water each season until we eventually wonder what happened to the current. Organizations often assume culture changes because people change. In fact, culture sometimes changes simply because attention changes. The dashboard didn’t tell employees to stop mentoring one another; it simply stopped reminding them to do so. This is the quiet paradox of measurement: not that it tells us what to value, but that it gently nudges us to value what it tells us.
It is perhaps why the most enduring qualities within an organization often remain nearly invisible: the quiet conversations after meetings end, the intuitive grasp that builds over decades, the acts of kindness that, while never appearing on a quarterly report, fundamentally shape the workplace over many years.
No dashboard will ever fully capture them, and maybe it is for the better that none should ever try. After all, the purpose of a map is not to be the territory itself, but to guide our journey through it, without allowing us to forget that the territory is always infinitely richer than the paper upon which it has been sketched. Self-reflection: If your dashboard vanished tomorrow, what knowledge within your organization would still be accessible? What invaluable capabilities might have quietly receded, not for want of value, but for want of attention?
When Measuring Changes Reality
As soon as a metric becomes important, people will start to restructure their lives and their behaviour around it, and, in doing so, the organization has quietly transformed into something new.
Imagine you take a walk through a forest and carry a compass. When you are in wild country, confused as to which way to proceed, it gives you absolute assurance.
It consistently points north regardless of which direction any of the trees are oriented, and no matter how uniform all the trees look. Despite all of this, the compass does not tell you about cliffs. It says absolutely nothing to you about riverbanks or unstable ground, about poison berries or an oncoming storm. It performs perfectly for the set purpose, and it says nothing to you at all about most of the rest of the landscape.
We know that this instrument exists for the sake of asking one particular question, and not for the asking of all these questions. The problem arises when we start treating an instrument as the territory itself. It is on this basis, among others, that KPIs may have gotten themselves into trouble.
When they are first instituted, they do not, at the start, look so obviously bad as things become. What they are expected to do is help people find the way: help us see where things stand, where we are with regard to the world around us. Over time, however, they morph into something rather different.
Instead of helping people make sense of the world, they actually start to shape and create it.
What people ask no longer comes out as: “How can I do something that will help me add value over the longer term?” Instead, people begin to ask: “How can I do something to make the number for this month better?” That is not a good change at all, and neither is its effect.
This is a thought that spills over beyond the confines of business and out to the philosophers again.
German philosopher Martin Heidegger argues that technology does more than simply provide us with tools to perform useful tasks. Technology can also fundamentally change how we see the world. Heidegger’s notion of “enframing” or “Gestell” means, more simply, our tendency to see the world only in relation to how we have divided and framed it for organizing purposes.
The forest can be many things depending on how you see it:
A painter’s inspiration
An adventure park for a child
A natural ecosystem of incredible complexity to a biologist
A resource for a timber company, ripe for extraction
At its core, the forest remains unchanged. The lens through which we view it shifts.
The same phenomenon often occurs in performance management across an organization:
One manager might view an employee just as an 87% score on one dashboard.
A second manager, however, may believe this employee is the lynchpin holding a team together and should be regarded as an experienced mentor.
A third might see them as an untapped potential who will eventually revolutionize company culture.
A fourth could turn to them when a critical problem has no documented solution.
The person hasn’t altered, only their apparent visibility, and this is why the dashboards you install to “measure performance” may end up having a much more profound impact: they do not just capture a representation of an organization – they actively teach that organization what it should consider meaningful.
Take, for example, a call center team for which “Average Handle Time” is the primary KPI. At the outset, this is an appropriate metric. Nobody wants their time on hold, nor for calls to drag on indefinitely, so reduced handling times should, in principle, improve the customer experience. After a period of months and a growing emphasis on meeting the metric, you might see some subtle shifts:
Customers might find their calls cut short, and complex queries are often quickly passed on to someone else.
Calls requiring additional customer support may be concluded sooner than necessary to avoid negatively affecting the metric.
Eventually, employees might be actively encouraged to make calls as brief as possible, even when there is a clear need to spend more time with an individual. No one asked or directed the staff to stop being caring, but they learned that caring did not reflect well in the KPI. This effect isn’t isolated to call centers.
We’ve seen it time and again in organizations:
Hospitals boost patient throughput, but the time available for each patient to connect with their nurse decreases.
Universities champion graduation rates, but in practice, they have reduced the number of required in-person teaching hours to free up resources to process more students.
Software companies are on track to close out their backlog, but accumulate huge amounts of technical debt in the process, which will be handed on to someone else down the line.
Retail chains are promising ever-faster delivery times but work their warehouse employees to the point of burnout during peak periods.
Banks reduce average loan processing times, but the depth of conversations needed to truly understand a customer’s financial situation becomes increasingly rare.
Construction companies meet aggressive project deadlines, but quality inspections become compressed, allowing small defects to accumulate into larger problems later.
The KPI is a success. Reality simply adjusted to accommodate it and, in doing so, became the embodiment of Goodhart’s Law. However, this doesn’t mean people are gaming a metric. We are observing the metric changing the environment, which it was always meant to reflect.
Imagine you put a large rock in a river. ↩️
The river doesn’t stop; instead, it has to reconfigure itself around the obstruction. The water flow is altered, new streams emerge, and debris begins to accumulate in various places. The river becomes something new as a result of a piece of infrastructure that wasn’t built to redefine its flow, but that had that very effect nonetheless.
↪️ KPIs are much the same.
If you introduce a KPI within an organization, it naturally triggers a cascade of reconfigurations. Budgets change, conversation topics shift, job titles are reassessed, and career progression criteria implicitly shift as people respond to whatever behaviour is sanctioned or rewarded. None of this happens as the result of deliberate manipulation; it simply emerges from the fact that people, just like rivers, respond to their environment and incentives in quite natural ways.
Nassim Nicholas Taleb can help us understand why. His career has been dedicated to distinguishing between systems that appear efficient and those that are actually resilient.
Picture a bridge for which a designer aiming to optimize for efficiency might shed every pound of weight considered extraneous. The structure is lighter, streamlined, less costly to build, and mathematically perfect. In theory, it is nothing short of an engineering masterpiece…until an earthquake shakes its foundation or heavy traffic grinds it mercilessly. Suddenly, what was so-called “excess” turns out to be strength. It was resilience, which to an inexperienced eye looked like inefficiency.
Organizations do the same thing every single day.
A business that meticulously limits its inventory appears brilliantly efficient-until supply chain networks fail.
A company paring down its staff to achieve peak productivity appears financially responsible until demand surges, and there’s no one around to respond.
A factory delaying routine maintenance to keep machinery humming may look great on utilization metrics-until an easily avoidable mechanical failure brings everything to a standstill.
An organization minimizing cybersecurity spending appears fiscally disciplined until a single breach costs more than years of preventive investment.
Every optimization quietly borrows against resilience, and every optimization comes with a price tag paid in foregone opportunities. The problem is that resilience is silent until it is needed. It’s like the unseen roots of a wise old tree, readily ignored as long as the wind doesn’t howl, yet absolutely essential once it does.
Perhaps this is why we so often hail visible efficiency while neglecting invisible capability.
Resilience is expensive, slack is wasteful, redundancy feels inefficient, curiosity feels unproductive, reflection is just a delay, until uncertainty strikes and the very things we criticized for slowing down progress become the reason progress remains possible.
This isn’t a case against optimization; it is rather an argument against ignoring its cost. Every optimization narrows the river, forsaking countless tributaries. Every intensification of a beam of light plunges another part of the field into shadow. The practice of leadership is therefore not merely about pursuing improved performance against metrics. It is about the disciplined recall of all that this pursuit inadvertently leaves in the shadows.
Self-reflection: If the uncertainty we know is lurking should arrive tomorrow, what might your dashboard wish it had kept safe? What unseen resilience has it already surrendered in favour of something far more tangible?
The Blind Spots We Choose
Leadership is not about the search for perfection or visibility. It is the wisdom to choose which shadows you can live with.
If there is one temptation that has been with us in every civilization, in every scientific breakthrough, it is the notion that the next tool will at last allow us to see it all: a better telescope, a more detailed microscope, a faster computer, a larger database, a smarter algorithm, a more inclusive dashboard. With each passing generation comes this same silent belief: this time, maybe this time, the blind spots will be gone. Inevitably, history shows a different pattern. Every innovation expands our view only to make evident what we had not yet seen.
The telescope opened the sky only to reveal a far larger universe than we had ever imagined.
The microscope unveiled worlds unseen, only to reveal how much more complex life was than we had ever known.
The process of discovery is the same again and again. The more we illuminate, the more we realize what remains to be illuminated, and businesses are no different when it comes to this topic.
Every metric answers a question but raises ten more. Every dashboard reduces uncertainty in one area while allowing for endless uncertainty to persist elsewhere. The goal, then, was never to create a dashboard that had no blind spots (Borges’ perfect map). The goal, instead, was something far humbler & more valuable: to understand what blind spots we have accepted.
Herbert Simon offers another key insight here. He famously noted: “A wealth of information creates a poverty of attention.”
Businesses today, almost without exception, do not lack information. Quite the contrary, they have way too much of it. Every department, every software system, every meeting, every team, every person – everyonepours information ceaselessly, splitting attention like atoms.
Yet, attention is a very limited resource; like sunlight, it brightens the spots where it lands but does little elsewhere.
Every meeting on one topic takes time that might otherwise have been devoted to another.
Every incentive reinforces one behaviour and subtly undermines another.
Every promotion tells employees (intentionally or unintentionally) what is valued.
Every promotion carries an opportunity cost, just as surely as a cash purchase.
It may also explain how an organization seems to lose characteristics it never deliberately gave up:
Curiosity gives way to Conviction ➔ Thought becomes Action ➔ Action becomes the new Thought ➔ Reflection cedes to Urgency ➔ Long-term Thinking collapses under the weight of Quarterly Performance Reviews.
No one sets out to make a career of being certain or impatient. The river simply shifts its course: a bit more attention to one side, a bit less to the other, and so it continues, day by day, until the landscape has changed beyond recognition. That may be the paradox of measurement.
When we measure, people move in the direction we point the lens. They engage with what is presented in meetings and what leaders routinely ask about. Everything else slowly slips out of view, not for lack of value, but because it has fallen out of organizational focus.
Thus, we arrive at the point that measurement always requires humility. Humility reminds us that no dashboard, however powerful, is the absolute truth of the world. Every measure is a perspective, and every perspective is incomplete. The question is not to eliminate our blind spots, but to come back to them again and again and ask:
What have we stopped noticing?
What assumptions have become so deeply embedded that they no longer warrant questioning?
What capabilities have we quietly allowed to atrophy because they didn’t make their way into a report?
These questions are important because organizations are dynamic systems in constant flux.
There’s a famous observation attributed to the ancient philosopher Heraclitus: “No one steps into the same river twice.”
The person has not changed, but the river has moved on. An organization is similar in this regard: it itself might not have changed, but the markets it operates in, the customers it serves, the technology it uses, and the culture it promotes have changed.
Even if a KPI reads the same numerically, the underlying reality it represents may have morphed beneath the surface. An 85% customer satisfaction rating now may not reflect the same customer expectations as five years ago. A current employee engagement survey, using the same wording as previous surveys, may be interpreting an evolving sense of what meaningful work means today.
The numbers endure, but their meaning shifts, which is why our dashboards can never be sacred. The minute we cease to scrutinize our metrics, we cease to scrutinize the reality they represent. It may be that the best leaders aren’t the ones with the most sophisticated dashboards or who track the most metrics. Maybe the best leaders are those who:
Never mistake the map for the territory
Remember that each illuminated beam also casts a shadow
Know that every river in the organization might have flowed somewhere else
Have the insight to put down the dashboard now and again, and wonder what it cannot show us
Final Thoughts
Learning to Respect the Shadows
Every photographer chooses a frame. Every sculptor removes stone to reveal a statue. Every author leaves unwritten pages behind. Every traveler follows one road while countless others disappear beyond the horizon. Every act of creation is also an act of exclusion. Every KPI is a decision about what deserves to be seen. Every dashboard is a statement about what an organization believes is worth discussing. Every target shapes behaviour long before it records it. Every number carries an opportunity cost that cannot be eliminated, only accepted. The problem has never been the existence of these tools, but more so forgetting that they are tools in the first place. A map is invaluable precisely because it is not the territory. A flashlight is useful precisely because we understand it cannot illuminate the entire room. Likewise, a KPI is powerful precisely because it simplifies reality enough for us to act, yet that simplification comes at a great cost:
It purchases clarity with incompleteness
It exchanges breadth for focus
It gains certainty by accepting blindness elsewhere
This is the opportunity cost of knowledge itself.
Therefore, we can infer that the purpose of performance management is neither to eliminate uncertainty nor to measure everything that matters, but to consciously and deliberately choose where we wish to shine the light, and to remember that, somewhere just beyond its edge, the rest of reality patiently waits in the shadows.
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Modern organizations are obsessed with measurement. Pop into virtually any executive meeting, and you’re likely to find glowing dashboards, reports, infographics, charts, and scorecards packed with performance metrics.
Revenue growth, customer satisfaction, engagement, productivity, utilization, retention, cycle time: if it can be quantified, it’s probably being tracked.
This is the Official Market, or what organizations buy and sell in an attempt to take the inherent complexity of business and turn it into something understandable: reports, scorecards, dashboards, intelligence platforms, and Balanced Scorecards.
Business needs complexity to transform into something manageable. Leadership must see into what happens everywhere in the organization, and metrics give teams a common language to express how they perform. Formal metrics are the right tool for holding employees accountable and for allowing leaders to assess the performance of individuals or teams against others over time.
Yet the potential harms of overreliance on formal measurement systems aren’t merely abstract or as far-fetched as many make them out to be.
Natlia Cuguer-Escofet, a researcher at the University of Pompeu Fabra, and Josep M. Rosanas at Universitat de Barcelona analyzed a set of cases in which performance management systems, when implemented rigidly, led to unintended outcomes, including cases from Spanish banks in the period leading up to the 2008 crisis.
In one such instance, a manager who was resistant to escalating loan-making practices was moved out of a position where loan decisions could be made, despite being given a promotion (in the form of an increased salary and improved office space).
In another instance, a board member who was hesitant about an asset’s value was reluctant to express his reservations because the organization’s incentive systems largely tied everyone’s performance to profit. The performance systems were working as they were designed to, but their output was discouraging decision-makers from making professional decisions when they were most needed.
The takeaway from these scenarios isn’t that measurement is itself flawed; it’s that every organization’s performance system will eventually hit a ceiling where it can’t foresee every contingency. When they become overly committed to using objective indicators, organizations risk inhibiting the human intelligence that might warn them of a problem before it shows up in the results.
The crux of the problem isn’t so much a reliance on measuring performance; it’s the assumption that measurable equals significant.
Organizations are often obsessed with measuring metrics, even though those same metrics sometimes do not truly matter to an organization’s success. These metrics aren’t designed to provide a clear picture of why something is or isn’t working; rather, they simply demonstrate what is going on.
They aren’t about showing how frustrated customers are; instead, they show that the satisfaction level has fallen. They aren’t about the employee turnover going up but about what has led to employee discontentment over time. An organization’s ability to identify the causes of declining numbers is critically important, yet metrics cannot illustrate the complexities driving performance from the bottom up.
This weakness is exacerbated, in many cases, by the fact that metrics are, by their very nature, selective. Each KPI necessarily prioritizes some aspects of performance while overlooking others. Organizations use metrics to measure performance based on what they perceive as critical, yet the business environment and consumer expectations require new perspectives. The KPIs organizations rely on may therefore cease to align with the reality on the ground.
It is simply a matter of fact that metrics are better indicators than drivers. When the system measures certain behaviours and outcomes, employees quickly adapt by doing what the system wants them to do. When employees are measured on customer service call time, for example, they learn to hang up with customers as quickly as possible rather than solve their problem. Metrics lead us to manipulate an organization’s output through what we measure, even if what we measure isn’t indicative of success.
“The problem isn’t a measurement one; it’s a knowledge one. You can know the velocity; you just don’t know where you’re headed, and therefore you just don’t know what to do, which makes managing impossible.” – Jeff Bezos
This system of performance relies upon measurement for decision and action-taking but neglects the human aspect; instead, it relies on information that is already visible or reportable. The challenge is that all of this is usually evident on a dashboard if it is tracked or measured.
With that said, not all aspects of the performance in the workplace are quantifiable:
Trust is hard to measure
Honesty cannot be quantified
Creativity or foresight doesn’t have to be demonstrated on a chart
These are not all reflected in The Official Market, as every metric, KPI, report or business scorecard makes choices about what’s relevant and what isn’t.
Sadly, by focusing solely on what we can readily identify as critical and important, many organizations inadvertently start to devalue or even ignore areas they cannot easily quantify. That, it has been said, means the information in their reporting systems may be missing valuable pieces or even be flat-out misleading.
One example is a business intelligence system that tells people how busy employees were in the office (measured by time spent at the desk, use of specific tools, etc.) but does not measure the outcomes of that work. This system has become completely removed from the actual outcomes that would determine whether employees were actually working effectively or not.
In such instances, organizations become overly dependent on such formally measured criteria and risk suppressing human judgment or observation that would otherwise point them toward a problem early on.
The Black Market
There’s one in every organization.
It might not show up in your year-end results. It might not be mentioned in a quarterly review. It definitely will not be in your executive dashboard, but nearly everyone in the company knows it.
This is the KPI Black Market; this is where you would go when your formal measures do not tell the same story. The name is controversial, but it should not be when people search for additional data to navigate a complex business. If an organization goes to great lengths, many beneficial ideas may fall outside measurement standards.
The Conversations That Never Make the Dashboard
Companies have invested significant resources over the past few years in business intelligence tools that afford a live view of operations. However, much of an organization’s most useful intelligence still travels via conversation.
A sales leader hears multiple account managers mention the same customer pain point.
A product leader notices an increase in “what is that for?” type questions about a new feature.
A team lead finds conversation in their team’s hushed post-all-hands meeting.
A customer success manager starts hearing unusually similar wording in otherwise unrelated client calls, hinting at a shared frustration that hasn’t been logged anywhere yet.
A regional manager notices that high performers are suddenly asking more “confirmation” questions instead of making autonomous decisions.
A project lead observes that status updates remain technically positive, but the tone of delivery shifts: shorter messages, fewer details, less narrative confidence.
An HR partner hears recurring “soft exits” in development conversations – people talking more about uncertainty, optionality, or “keeping an eye on things” rather than commitment.
Those aren’t standard metrics, but they often show trouble before it hits the Profit & Loss (P&L).
That’s partly why leaders place so much importance on informal conversation – it’s where emerging signals like doubt, disappointment, enthusiasm, and apprehension get aired while they’re still in their most formative (and useful) stage.
Once a signal is a metric, it’s already past the critical inflection point. That is due to the fact that dashboards chronicle what happened, while conversations signal what’s about to happen.
We write down and archive at an unforeseen speed, yet much of our knowledge is often contained…elsewhere. That knowledge often moves through the Black Market, with almost blinding celerity.
The Mental Dashboard
Try asking an experienced sales leader what will make the quarter miss your target. They often start with “I have a feeling.” It’s the kind of thing a data scientist will probably break out maniacally in a feverish rash at the sound of it.
How can they predict they might miss when the company invests millions in data and analytics to give you objectivity?!
However, the data science in judgment and forecasting actually supports this kind of intuitive forecasting: experts use intuition often not at random but rather to detect patterns that may not show up explicitly and may even be unable to be easily and systematically articulated, due to experience (e.g., having interacted with customers, products, markets, negotiations, and company stakeholders), which can be more sensitive to some cues than others.
You might experience it as a feeling or a sense:
A salesperson feeling the heat because customer engagement seems “off” but has not yet been captured by metrics.
A regional manager in your organization who believes they sense unusual nervousness in the sales reps during customer interactions.
Customer success may note that the typical post-demo and pilot behaviour among clients has changed slightly, but it is not yet affecting metrics such as engagement and churn. In these kinds of instances, they are not officially being recognized by your data platform.
Yet these sorts of signals often influence forecast judgments, however indirectly. Leaders, in essence, operate with two dashboards: one that they see on their screen and another that resides in their head.
One is evidence of what is happening. The other is the interpretation of what’s happening. Neither works well without the other.
The Spreadsheet Nobody Talks About
Perhaps one of the most unaddressed elements of organizational life is the presence of shadow forecasting mechanisms.
Officially, there’s an organization’s forecast. Unofficially, there often exists a second forecast, which may exist in the form of an individual’s private spreadsheet, in an individual’s notebook, or through individual or team discussion.
It is likely, in some form, that this meeting has been heard in every organization where one exists.
The company forecast is presented.
The numbers look perfectly healthy.
Then inevitably someone pipes up, “OK, but what do we actually think?”
The line dividing the Official and Black markets is drawn with that phrase. The Official forecast might be the organization’s most formal assessment, but the Black Market forecast often represents a compilation of individual experience, customer issues, the news and anything else that doesn’t easily lend itself to tabulation.
It’s curious that shadow forecasts don’t necessarily always compete directly against official outputs. Indeed, they can arise as employees try to circumvent gaps they see in the official mechanisms. The fact of there being a spreadsheet doesn’t necessarily matter, since it is the quest for a depiction of reality that people believe in.
Tribal Knowledge and Unofficial Indicators
Arguably the hottest currency in the KPI Black Market is tribe experience. Most organizations have individuals who seem to be aware of certain things well before the rest of the population becomes aware of them. Those individuals understand which projects are real and which generate polished-looking status charts. They can usually predict the top truly unserved and unhappy customer base even before official complaints surface.
Such employees know which operational hazards warrant attention, even when they do not appear in risk analyses. What’s truly fascinating is that these fellows often don’t even have access to data; however, they have contextual gut feelings. By virtue of experience or informed hunches, they understand and see patterns that systems simply can’t capture.
These people remember what happened last time. They recall the anger, the shouts, the boasts, the merriment, or the frustration. They are living archives, in a sense. As such, organizations often defer significantly to individuals who cannot effectively translate the value of their insights into metrics, yet that value is very much there.
This then creates an interesting paradox.
On the one hand, companies may champion objectivity; on the other hand, in uncertain environments, they often turn to sources of experience who, by their nature, are not subject to objective measurement systems. Similar principles are evidenced in how folks make decisions in the informal universe on a day-to-day basis.
Managers observe how quickly answers are transmitted for questions and inquiries.
Account teams pick up on the customer’s emotional tone rather than on official customer satisfaction reports.
Product team leaders keep their eyes on the number of surprises.
Executive team members will note when the “unhappy camper” stops raising their objections.
These signals often aren’t included on charts but have a tremendous impact on decision-making, at times having a significantly greater impact than the official scores themselves.
Why the Black Market Exists
It may be tempting to see these informal arrangements as proof of the ultimate failure of formal measurement. This is a faulty assumption that relies on a complete misunderstanding of the very premise. The existence of the KPI Black Market signals that organizations are, ultimately, human systems operating in contexts far more complex than can ever be fully captured by numbers.
Dashboards cannot account for every variable. KPIs cannot enumerate every risk. Reports cannot portray trust, morale, judgment, intuition, confidence, or culture. When people and groups try to find order in increasingly chaotic surroundings, it is natural that they create complementary information systems – the KPI Black Market – that support and backstop formal systems. The KPI Black Market is thus not a conspiracy against data, but a very reasonable response to its ultimate shortcomings. It is a natural evolution of a most logical process.
Perhaps the most important irony is that most organizations already rely upon the inputs of this unrecorded channel: they simply do so informally and under the table.
The highest-trusted and most timely signals usually originate elsewhere – between peers, during hallway discussions, through personal observation, or based on embodied tacit knowledge. The KPI Black Market is more prevalent in complex environments where reality is perennially richer than our metrics, and, more generally, in organizations that have simply done too poor a job of creating formal indicators.
What Should Leaders Do About the KPI Black Market?
The existence of the KPI Black Market does not, of course, suggest that companies should discard their dashboards, scorecards, or formal reports. Au contraire!
Formal measurement is crucial if organizational performance is to be consistent and comparable, and if accountability is to be meaningful rather than arbitrary, and so much so that the Official Market is an essential part of organizational life.
The problem isn’t that organizations formally measure performance; it’s that they treat formal measurements as complete representations of reality rather than partial ones.
Great leaders recognize that the best dashboard or scorecard cannot do their thinking for them, but can help them think, and that, in addition to the question “What does this metric say?”, a second question needs to be asked.
“What’s missing from this metric?”
A necessary shift in focus leads to the treatment of signals and the observations of employees as information & value, not noise. The aim here isn’t the wholesale abandonment of measurement, but the supplementation of metrics by insight.
A similar approach can be found in the management literature, and the argument has long been made that formal management controls necessarily contain gaps that must be filled by managerial judgment, a concept of “informal justice”.
In essence, such judgments may allow us to question the validity of a metric because it has not kept pace with changing circumstances. Perhaps the easiest way in which to undertake a measure of diagnosis is for a team of leaders to take the time to ask management to list all of the things that management considers important, and then see what doesn’t appear on the board.
Final Thoughts
It is increasingly common to portray organizations as rational, analytical, almost-organic beings in which decisions are data-driven, and metrics are king.
To a certain extent, this is true. Most of them are, indeed, social entities – powered by the experience, intuition, confidence, and understanding coming from their members. Such a sentiment would be historically true as well, as it was the case well before dashboards existed – managers trusted their intuition and vision. Long before business intelligence platforms were born, people discussed and understood their environment to proceed forward, even when uncertainty loomed like an overcast sky.
Although our reporting tools now offer unprecedented visibility, this doesn’t deny the need for those implicit ways of leading teams to progress. Frankly speaking, they simply shouldn’t impede this.
It would be a naive mistake to assume all critical variables can be measured, as the key predictors of an organization’s success are sometimes elusive to quantification. These signals originate from talks, gut feelings, interactions, observations, and events, which never exactly translate onto a metric dashboard.
However, leading companies leverage both, sometimes in equal measure, and often to great success. A dashboard illustrates the past, while those close to the business can provide current-state insights and often foresight.
This is the key takeaway one should derive from the KPI Black Market. The real value is found where the most trustworthy predictors remain off the official dashboard.
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Picture the following: a customer service team boasting average response times under two minutes. Customers are always getting responses right away. Every target is being met. Yet, customers keep complaining, and complaints are only growing.
How is that possible?
After investigation, you find that while customers are receiving rapid responses, those responses may be doing little to resolve their issues. The team members have been incentivized to close tickets quickly because that is what’s being measured. The original purpose (making customers happy) is now secondary.
This can be a very common issue within companies of any size. KPIs that once represented success are slowly becoming success itself. They stop asking “are we accomplishing what we intended to accomplish?” and start asking “are we meeting the target?” The difference between these questions might seem negligible, but the implications can be significant.
KPIs have a place and are indeed beneficial. Companies need a way to evaluate performance, track progress, and understand where improvement is needed. Without measurements, we operate based on assumptions and intuition alone.
The difficulty is that there are many things that organizations care about that are not easily measured. A single number can’t capture employee loyalty. Employee engagement isn’t the same as a survey score. Collaboration, trust, innovation, and long-term business value just don’t fit on a dashboard. As a result, companies use leading indicators, which we assume represent a desired outcome.
Response time is often seen as a sign of good customer service. Attendance is assumed to show employee commitment. Productivity numbers are assumed to prove effectiveness. This is okay to an extent; in fact, these are often necessary indicators to track. Problems arise when the leading indicator outweighs the outcome it was originally designed to represent.
Economist Charles Goodhart explained this concept best in a statement now known as Goodhart’s Law: “When a measure becomes a target, it ceases to be a good measure.” This may sound academic, but the underlying concept is easy to grasp. The moment people are measured, rewarded, or punished by a metric, they naturally seek to optimize for that metric. This optimization might increase performance, but sometimes it only improves the metric.
Consider training for employees. We often measure learning by tracking whether training has been completed. Seems fair on the surface – if an employee completes the training, they are surely learning, right?
Well, not necessarily. When the number of completed trainings becomes a target, the focus shifts.
Employees quickly click through > managers ensure there’s 100% completion before deadlines > dashboards turn green > knowledge retention, skills development, and behavioural change stagnate. The company succeeded in increasing the number but made little to no progress on the desired outcome.
This trend plays out across various industries and sectors. Salespeople push for revenue through deep discounts, thereby impacting long-term profitability. Marketing campaigns aim for engagement numbers even though engagement might be disconnected from real customer value. Project teams celebrate on-time delivery even though the project might not provide tangible benefits. The issue here is not that the metric is necessarily incorrect. The problem is that it only represents a piece of the whole.
A useful analogy for KPIs is to think of them as road signs instead of destinations. Signs tell you if you’re going the right way, but we don’t mistake the sign for the destination itself. Organizations often make this mistake:
Customer satisfaction is not a survey score. ❌
Productivity is not a speed metric. ❌
Attendance does not show employee contribution. ❌
These are signals used to help us understand reality, not reality itself. This difference becomes even more critical when organizations prioritize results while ignoring the actions that lead to those results. A revenue number from last month tells you what has occurred; it doesn’t tell you why. A customer satisfaction number indicates the outcome of a given interaction; it does not show the behaviour displayed during that interaction. By the time a revenue number changes, the behaviours that affected it may have been in place for weeks or months.
That’s why increasingly successful organizations are beginning to differentiate between outcomes and the actions that produce them. Outcomes serve as scorecards, letting you know where you stand. Actions and drivers help you understand how you got there and what you should do next. If leaders focus solely on the scoreboard, they are more likely to react to events after they have occurred. If they understand what causes the score to change, they will be able to influence future outcomes before they become problems.
Through this shift in thinking, we can reach an important conclusion: not all KPIs should be created equal. Some measures help us assess progress towards desired outcomes; others serve as proxies for those outcomes. For leaders, the biggest challenge is recognizing which is which. If the measure becomes the mission, organizations risk optimizing for the numbers rather than for the results they represent.
How Proxy Metrics Quietly Take Over
If most organizations know that KPIs are just indicators, how do so many organizations end up managing the indicator rather than the outcome?
The simplest reason is that proxy measures are convenient.
It’s often hard to measure the actual outcomes we want to influence. For example, real outcomes can take years to show any real results, often can’t be easily isolated from other variables that also affect the outcome, and usually don’t fit well on a dashboard. Proxy measures, on the other hand, are easily and readily available to be captured, reported, analyzed, and benchmarked.
Consequently, organizations tend to get caught in a cycle. Instead of asking “what would indicate we are truly successful?“, they ask, “what data do we already have?“. The available metric slowly evolves into the performance measure.
While this sounds relatively harmless, it quietly creates a shift. Individuals stop focusing on how well they are achieving the actual outcomes and begin talking about achieving the numbers on a dashboard.
Discussions focus on “have we hit the target?” rather than “have we made real progress toward achieving our goal?” The indicator becomes the lens through which we interpret performance, even when it tells only part of the story.
This isn’t to say proxy measures are useless; many of them can provide helpful insights. It’s simply assuming that the proxy and the outcome are one and the same, which is the problem.
For example, completing a training course may indicate that learning has taken place, but it doesn’t confirm any real change in capability. A high customer engagement rate can indicate interest, but does it lead to customer value? An increase in sales calls doesn’t always mean more quality customer conversations were held. These proxy measures may be useful in isolation, but they don’t tell the full story.
Unfortunately, once a metric is valued, people tend to drive it. Usually, this is not due to manipulation or intentional bad practices; it is simply how human beings behave. If a KPI target is linked to rewards, positive feedback, promotions, or performance reviews, people will make sure to meet this metric regardless of whether it aligns with desired outcomes.
The problem then becomes that an increase in a KPI may not necessarily lead to the desired increase in the outcome. There are countless examples throughout history of this behaviour, such as using the enemy’s body count as a measure of success in wars. Such a heinous & vile metric was easier to achieve than actual strategic objectives, and, eventually, simply measuring the metric became the objective itself. The measure dictated the outcome, rather than the outcome shaping the measure.
Now, whether we look at armies or organizations, both can fall victim to the same thinking pitfalls, for they are comprised of people who often err on what is “easier”. Leaders can start managing what’s easy, rather than what’s important.
In a much less combative example, take the instance of a decrease in cost-per-lead: at face value, it doesn’t make much difference if lead quality falls dramatically; an improvement in customer service response times does little if customers still have the same unresolved issues, and a team celebrating meeting all its targets still doesn’t achieve its business goals. Each example shows that the KPI rose or fell as intended, but the desired outcome didn’t.
Perhaps the most intriguing part is that organizations and their people usually know the source of the disconnect:
The sales team knows when target numbers promote busywork
The customer service department knows that quick responses are not the same as solving customer problems
Managers know that an increase in attendees does not necessarily correspond to greater commitment or contribution
However, when people feel a sense of control and certainty that a KPI is moving in the right direction, it becomes difficult to abandon the number, even if we know the real outcomes aren’t shifting as desired.
Numbers, nonetheless, seem more objective and reliable. They are concrete and clear, and they appear to remove uncertainty and complexity from a situation. Clarity, though, is not always accuracy.
A dashboard displaying green lights may suggest great progress, while unseen problems begin to fester beneath the surface of these simple indicators. As an organization becomes adept at performing the actions that achieve the highest success scores on a given metric, it simultaneously develops considerable inertia in achieving its real objectives.
This is why mature performance management systems do not focus on individual metrics, but rather on the overall view. A mature system must incorporate a mix of qualitative data alongside quantitative metrics, so that no individual KPI carries too much weight in determining perceived success.
The real question is not whether there should be proxy metrics at all; it’s whether they are remembered for what they represent. If leaders forget what a proxy metric is supposed to indicate, an organization will spend its energy improving the number rather than the actual desired outcome.
The Five Most Common KPI Traps in Modern Organizations
This quest for proxies seems to manifest itself in infinite ways, yet it follows the same several templates that recur over time, across industries and across hierarchical levels. Although the metrics might vary widely, the error appears eerily similar: the metric eventually succeeds in displacing the thing it was intended to measure.
Response Time Replaces Customer Care
Many customer service teams monitor response time for good reason. Customers typically appreciate quick communication.
The issue is when that speed becomes the primary goal. A team might respond to every single inquiry within minutes, but the response could be generic and fail to resolve the issue. Customers are acknowledged quickly, but still require multiple touchpoints to reach a solution.
This looks good on paper, but in practice, it increases customer frustration. Response time is an important measure, but it isn’t customer service. Customer service is all about understanding problems, solving them, and generating positive experiences. Speed may well be an important factor in achieving these goals, but it alone cannot do so.
Engagement Replaces Value
Engagement has emerged as perhaps the most ubiquitous performance measure in the digital age. Businesses track page views, click-throughs, comments, shares, downloads, logins, and a million other interactive behaviours. Such figures are often collected automatically and can be updated in real-time.
The problem is that this engagement does not necessarily mean any value is being created.
Some content receives millions of page views, while its consumers gain minimal new information. A few software platforms log millions of user logins – their consumers remain stuck performing rudimentary tasks. Several meetings involve many staff members, yet only a handful contribute to improving outcomes.
Engagement does not necessarily mean useful things are happening. It signals that people are attentive. If organizations focus solely on engagement, they create organizations that focus on visibility.
Productivity Replaces Effectiveness
One of the oldest and most frequently measured indicators of performance is productivity.
The number of tasks performed, phone calls made, e-mails sent, reports generated, and tickets closed can tell you something about how busy things are and about operational efficiency. However, you should never confuse activity with effectiveness.
One salesperson can be two or three times as active (in terms of calls made) as another, while identifying far fewer useful sales opportunities. One project team may tick off all the task items on their schedule without having solved the problem the project was designed to fix.
Productivity asks, “How much work got done?“
Effectiveness asks, “Does it matter?“
Organizations that focus on productivity often become incredibly busy without ever becoming more effective.
Attendance Replaces Contribution
One of the easiest measures to monitor is attendance.
People either turn up or they do not. The measurement of contribution, however, is far more involved: someone can attend every meeting and add nothing, whereas another may contribute only two or three times, yet those points may be instrumental in forming key decisions.
It may also be the case that an organization equates attendance with contribution when, in reality, contribution levels depend on involvement, knowledge, collaboration, and the ability to solve problems. Attendance is a good operational measure. That said, it is NOT an indicator of success.
Output Replaces Outcomes
The most frequent KPI pitfall is the confusion between outputs and outcomes.
Outputs are the products an organization puts out.
Outcomes are the effects of these outputs.
Although obvious when articulated, it is often lost when trying to measure things.
Think of a facility team whose job it is to clean an office building. What the facility team measures might include the number of floors cleaned, the time spent cleaning, or the amount of cleaning supplies used. These are all outputs because they show activity. The number of floors is an output; the number of floors scrubbed (to the point they were clean and didn’t feel sticky) would be an outcome.
What if the employees continue to complain that the floors are sticky? The output numbers suggest the team is successful, but the outcome proves otherwise.
The same logic applies to training programs, change management initiatives, marketing campaigns, and transformation projects that are measured by training completion, logins, impressions, and milestones. The output metrics tell us that we did things, but the outcomes measure whether we actually made anything happen. Both are needed.
When we are so focused on outputs, however, we run the risk that they become the sole measure of success, so the team can meet every goal, complete every task, and satisfy every reporting requirement but do absolutely nothing. That’s why there is such risk associated with proxies – they allow us to progress on paper while standing still.
What High-Performing Organizations Measure Differently
At this point, it may sound like the answer is just to get rid of KPIs entirely. Far from it. The matter of fact could not be farther from the truth.
While organizations need measurement, leaders need visibility into performance, and teams need feedback to understand whether their actions are moving the organization in the direction the leadership intends.
The problem is not measurement itself; the problem is making sure the measurement is connected to the thing it’s supposed to be measuring. High-performing organizations understand that KPIs are learning and decision-support tools, not outcomes in themselves. They use metrics to understand performance, and they avoid the urge to turn a metric into an outcome.
I) One of the most critical adjustments they make is to separate outcomes from the behaviours that lead to them.
Many organizations focus almost entirely on outcomes: revenue, customer satisfaction, retention, profitability, market share, and similar figures that often top executive dashboards. These numbers are important, but they are also trailing indicators – they tell you what already happened. When customer satisfaction scores start to slip, the underlying reasons may have existed for months. When revenue declines, the factors that led to the drop may have been building for quite a while.
Whilst high-performing organizations do keep a close eye on outcomes, they also identify the behaviours and performance drivers that contribute to these outcomes:
A sales team might be concerned with revenue as an ultimate outcome, but it also looks at the quality of prospects it’s working on, the level of activity its team has-how many calls and meetings-and its closing rate. All of these will affect revenue and allow leaders to spot problems before they significantly impact sales figures.
A customer service team will continue to track customer satisfaction scores, but it will also look at how many times a customer contacts it for a single issue, how quickly agents respond, the quality of communication, and customer effort.
The objective is not necessarily to replace outcome measures with behaviour measures, but to tie them together.
Outcomes tell you where you are, behaviours give you an idea of how you got there, and where you are likely to go in the future. This changes how you use KPIs from simple reporting tools into proactive management tools.
II) Another difference in mature performance systems: these organizations rarely use a single metric for an important organizational objective.
Let’s use customer experience again: organizations often turn to NPS or customer satisfaction scores. These have value, but no single metric adequately describes the concept. It may make more sense to use customer satisfaction metrics alongside retention rates, complaint counts, resolution speed, customer effort, and actual customer feedback.
Each one captures a different piece of the puzzle, which is why they should be looked at together. The same logic applies to nearly every other aspect of the business.
Revenue should be examined along with profitability.
Productivity along with quality.
Employee engagement along with retention and performance.
Efficiency along with effectiveness.
When measures are viewed as interconnected pieces of information, the temptation to optimize one measure at the expense of another diminishes significantly.
III) Lastly, and probably most important of all, high-performing organizations retain an element of wonder about what they might be missing with their KPIs.
They understand that metrics are a form of simplification and allow us a glimpse into the world of perceptions. No dashboard can fully capture customer trust, employee loyalty, innovation, culture, teamwork, or the ability to adapt; yet all of these can be profoundly important drivers of organizational success.
Instead of assuming that every important thing can and must be expressed as a number, leaders at mature organizations accept the inherent limitations of measurement and complement their data with conversations, observations, customer inputs, employee knowledge, and professional judgment.
In other words, they use data, but not as a replacement for decision-making, since the purpose of performance management is not perfect reports but reports that provide a deeper understanding of performance. Such work takes more than merely watching numbers on a screen.
A Simple Test for Every KPI You Use
The risk of proxy metrics is that it is uncommon for a bad metric to be bad to begin with.
They usually begin as rational indicators of important goals and slowly take on a life of their own as companies get increasingly obsessed with bettering the indicator itself. This necessitates periodic reevaluation.
Each of your KPIs should, on occasion, be examined with a basic but critical question: Is this metric still telling us something about our performance, or has it become the performance?
The answer may not be crystal clear, but a few practical questions can reveal a KPI that might be losing sight of the original goals.
What outcome is this KPI supposed to represent?
Each metric should relate clearly to an organizational goal.
If the goal is unclear or hard to articulate, the KPI might be measuring activity rather than progress. One helpful test is the question “Why should we even care about this number?” The answer often highlights whether the metric is still relevant to the desired outcome.
If the KPI improves, does the outcome necessarily improve?
If you can improve the metric without improving the outcome, there is a risk that the KPI serves as a surrogate for something weaker.
Training completion can increase without any skills being gained.
Website traffic can go up without any value being added.
Response times can increase without the customer’s problems being solved.
You should be very wary whenever it’s possible to optimize a KPI independently of an outcome.
What behaviours does this metric encourage?
Performance metrics influence all actions. Some actions will be productive, some less so.
A sales performance metric can prompt positive customer outreach. It may also prompt undue discounting.
An activity performance metric can prompt work, but it may also prompt busywork.
So, the question is not simply whether a KPI triggers activity, but whether it triggers beneficial activity.
Can people hit the target while missing the point?
This issue seems to be at the very core of Goodhart’s Law: if it is possible to obtain the metric without producing the desired result, then the KPI may become the goal.
A lot of the examples mentioned within the article fall into this category – where the team “hit the number” and still made little real progress toward the overall aim. In these cases, other indicators may be necessary.
What important outcome are we not measuring?
Each KPI measures just one dimension of the business. As attention to any specific KPI increases, another aspect of performance will likely fall into a “blind spot.”
Customer acquisition may be analyzed, while customer retention is neglected.
Productivity may be measured, while quality is left out of the discussion
Operational efficiency may be increased at the expense of innovation
The ongoing question of what is not on the dashboard will ensure that important business outcomes do not fall completely out of the organization’s mindshare.
Final Thoughts
KPIs remain one of the most powerful tools for leaders to align efforts, monitor performance, and allocate resources.
With that said, they are but a tool. They break down when an organization forgets the difference between the metric and the outcome the metric is supposed to capture.
A fast response isn’t great service.
High engagement isn’t value creation.
Productivity isn’t effectiveness.
Attendance isn’t a contribution.
Output isn’t impact.
The best organizations remember and manage accordingly; they use numbers to inform judgment rather than replace it. They focus on outcomes while being acutely aware of the behaviours that produce them. They remain attuned to the fact that a helpful metric today can become a damaging target tomorrow.
At the end of the day, a KPI’s value isn’t in proving that we can win at numbers. Its value lies in helping us improve our numbers. That’s when KPIs truly fulfill their potential as indicators of success rather than proof of it.
It is generally accepted within most organizations that strategy is filtered through structure: a group of executives defines priorities, these executives delegate to leaders, department heads manage their reports, and then people at lower levels of the hierarchy do the work.
That, at least, is the story told by the organizational chart. However, work does not flow smoothly through a company in the same way it does along an organizational chart in the boardroom.
Strategy flows through invisible networks. It moves through trust, it relies on reputation, friendship, alliances, credibility, influence, and memory. Employees are actually dependent on those specific individuals who offer reliability in the midst of political and chaotic organizational circumstances.
These hidden networks are what is called the informal organization.
For many organizations, the informal structure plays a more significant role than the formal one.
A leader may be officially responsible for a particular transformation project, but the individual whom everyone in the company recognizes as the real leader responsible for it might actually be another person. A strategic task may be implemented not because formal procedures were followed for approval but because a key trusted contact used informal connections to move it forward behind the scenes, and another project with impeccable governance procedures might completely collapse because the informal network never really backed it.
This is the hidden dimension that many strategy models seem to ignore.
While the organizational chart clarifies accountability, the informal organization illustrates behaviour. Where & when the two are at odds, the strategic execution of the task succeeds or fails.
According to researchers Alberto F. De Toni and Fabio Nonino, the informal organization is “the real central nervous system” of companies, and operational coordination is managed primarily through informal connections rather than organizational structures.
These assumptions revolutionize the perspective from which execution needs to be addressed.
If strategy execution is achieved through human interaction, it is crucial to focus on whom each individual actually looks to for guidance and help, rather than to whom they officially report.
Why Organizational Charts Rarely Reflect Reality
Organizational charts rarely represent reality because two companies are present in reality simultaneously: the formal and the informal organizations.
A) The formal organization is structured hierarchically through a complex web of reporting lines, departments, roles, and decision-making procedures.
B) The informal organization is a social web of non-work-related connections that develop over time.
As a result, in many organizations, people look to specific individuals within the company regardless of the organization chart; this may be because of a specific skill, expertise, empathy, or political acumen these individuals possess. Such individuals act as unofficial decision-makers, the people one goes to before making a formal decision, the people who possess the expertise or social power to navigate through difficult organizational dynamics and push forward projects.
There is usually a significant gap between what is expected within the formal organization and what people actually do, and these unseen decision-makers in every company are the informal leaders.
Whether they may or may not occupy high-level executive positions is irrelevant, for employees approach them for guidance before making decisions; they understand how the real system operates and have the political agility to remove obstacles and make stalled projects run smoothly. They also understand the organization’s politics and history, enabling them to negotiate effectively without alienating others.
Although they may sometimes appear to lead initiatives, their authority is not granted but is derived from the credibility, expertise, emotional intelligence, and positive social influence they command from others within the company. Essentially, they earn the right to lead by demonstrating competence and building trust with others over time.
De Toni and Nonino identified several recurrent informal roles within organizations, including opinion leaders, central connectors, bottlenecks, consultants, experts, and “helpful people”. The influence these roles have varies.
For example, opinion leaders impact how people react to change and are closely watched by the workforce. Central connectors are critical to effective internal communications. These people serve as an infrastructure within the organization, facilitating informal communication and connections across functions and departments.
Such networks become strategically important because, generally, strategy execution relies less on the command-and-control structure than on the socially constructed legitimacy of what one is trying to accomplish. People might comply with an authority, but commit themselves to it through trust.
How Informal Networks Empower or Sabotage Strategy Execution
One important fact that many people get wrong about organizational dynamics is that there is no direct, mechanistic implementation of strategy; rather, strategy is interpreted and executed socially. It is through the informal organization that an initiative might be perceived positively or negatively by employees, depending on their interpretation.
They don’t make their assessment of a transformation process solely on formal data but look to people in other departments to see how they react. The internal strategy debate takes place in private meetings, casual hallway chats, e-mail groups, and lunches. If people in influential positions secretly mistrust a transformation project, then the initiative itself might be in danger.
It may seem mysterious from the outside, but people within the organization often know what is happening. This means the informal leaders will have agreed, and the organization’s internal decision-makers will align informally.
Conversely, a strategy might fail not because its objectives are faulty, but because the people responsible for its execution did not feel any personal connection or investment in the idea. They might not even fully trust the people in charge of leading the change. If this happens, the formal objectives must take a back seat, and social legitimization becomes the priority.
When the Trusted Operators Become Bottlenecks in an Organization
Having said all that, it is important to note that informal influence also has a sinister downside. The very same people who make organizations work can quietly become execution bottlenecks.
One of the case studies examined in de Toni and Nonino’s study was that of an executive named Andrea, who had become overwhelmingly important to the flow of information within his business unit. The organization became so reliant on him that removing him from the communication network would result in a dramatic drop in information flow, leaving numerous individuals isolated.
This is extremely common, and every organization has the “go-to person”: the reliable fixer/operator who always knows the answer. These people initially expedite execution since people trust them.
Over time, organizations implicitly build themselves around them, waiting for their response. Projects are put on hold, waiting for the individuals’ input. Teams refrain from making any moves without consulting them. Information gets funneled to and from these individuals rather than being disseminated. It is almost ironic that the most trusted people within organizations can be hidden scalability bottlenecks, not due to poor execution but because they become integral to too much of the organization’s functionality.
Formally, the organization may seem healthy. Reporting lines exist; governance structures remain intact, and processes are in place. Operationally, the company may be held together by only a handful of informal influencers.
When these individuals burn out, leave, are let go, or face internal political isolation, they can significantly weaken the organization’s execution systems. This is one of the underlying reasons why so many organizations can’t scale despite complex formal structures.
The Hidden Politics of Organizational Influence
A major misconception within organizations is that they operate on logic alone. In reality and proven practice, interpretation, emotions, identity, trust, and influence drive organizations. This is where workplace politics come in.
Politics can sometimes have a negative connotation, but in its simplest sense, politics is simply the circulation of influence within systems that have an uneven distribution of authority, resources, and priorities, and every organization has an unequal distribution of influence. The interesting aspect is that influence does not always travel downwards. Influence can travel horizontally, upward, or, at times, completely outside the organizational hierarchy.
According to researchers of informal organizations, there are three ways in which influence is gained:
by positional authority
by expertise
by relational credibility
The former formal structures in organizations can take advantage of hierarchy and authority, whereas the latter systems favor expertise and trust.
This is extremely significant because, despite employees verbally following formal leaders, they may actually look to others for validation, instruction, guidance, and explanation. The outcome is shadow leadership in many organizations. These people officially have no leadership titles, yet they informally coordinate teams, affect and mold company culture, mentor junior staff, influence hiring, and direct operational behaviour. They are the emotional glue of the organization, and organizations usually realize their impact only once they depart; communication breaks down, teamwork falters, trust erodes, confidence corrodes, and morale plummets.
Often, leadership takes the path of believing the issue is operational and cannot pinpoint why it is failing, even though the true culprit is the loss of a central node of relationships.
Shadow Leadership, Institutional Memory, and Cultural Gatekeepers
Informal influence is even stronger when backed by institutional memory. People who possess institutional memory remember failed transformations, lost systems, failed restructuring processes, and broken promises of leaders. They are the cultural gatekeepers.
While these individuals sometimes save organizations from repeated mistakes, other times they preserve antiquated thinking, which impedes necessary change. Their influence, however, is not captured in formal strategies. Regardless of the direction of influence, this individual heavily dictates organizational behaviour. Though a newly-hired executive may have formal authority, a lack of access to their deep trust networks could hinder execution; conversely, long-tenured individuals without executive titles may wield much more influence because of their greater understanding of the organization’s emotional and political history.
This is why external consultants who offer excellent frameworks often fail: they have analyzed the visible organization and ignored the invisible part. The formal structure indicates authority, while the informal structure indicates credibility; the two may not always be the same.
Why Organizational Change Fails Invisibly First
One of the critical takeaways from studying informal organizations is that while technical systems fail visibly, social systems fail invisibly, first through hesitation, withdrawal, silence, and avoidance. This is characterized as passivity disguised as caution.
1) The first signal of change is relational.
Collaboration becomes strictly transactional, people stop sharing information freely, and departments isolate themselves politically rather than coordinating toward a common goal.
2) Then, the second signal of change is control.
The immediate, and often incorrect, reaction of organizations at this point is to add layers of control. More committees, more reporting structures, and more oversight mechanisms are put in place.
3) These first two signals inevitably lead to the third signal of change, which is dilution.
All of these initiatives negatively impact organizations by watering down the trust that is essential for rapid adaptation and change.
Truly successful companies learn to leverage their informal structures rather than ignore them. Instead of asking who holds authority, they learn who influences behaviour. Their strategies focus on communication flows, trust networks, and relational systems rather than solely on reporting lines.
Social Network Analysis and the Rise of Informal Leaders
Today, many organizations utilize social network analysis to uncover the invisible relational dynamics at play within the company.
In the case of the Euris Group, network analysis identified communication networks, expertise, problem-solving collaborations, and hidden organizational relationships within the company. It turned out that the most influential individuals in the organization were not necessarily the highest-ranking personnel, but instead were those who possessed three traits: expertise, problem-solving ability, and accessibility.
The researchers referred to them as “primus pilus” (named after the Roman soldier who directly supported and guided soldiers into battle). It seems an apt modern analogy because often in today’s organizations, the people who lead and truly drive execution are not those who deliver the strategic presentations but rather those who come to the fore when situations become tough: the operators who turn abstract concepts into practical actions, those who can bridge the gap of expertise and relatability, those that act as liaison between information and understanding, and those who reduce system friction.
These individuals are often the de facto stabilizers between high-level vision and practical operations, and failing to acknowledge them has created enormous strategic blind spots for some organizations.
Final Thoughts
The informal organization, as a subset of the main organization, provides a critical insight into the nature of strategy: execution is not only based on structure but is deeply human.
Companies move not simply through reporting lines but through relationships, trust, credibility, memory, identity, and influence. While the organizational chart outlines who has authority, the informal network explains how things actually get done and with what degree of haste.
There are several lessons to keep in mind, but perhaps the most important concerns strategy: namely, that the most powerful systems in organizations are not necessarily those intentionally designed by anyone, but those that develop organically.
High performance rarely happens by chance. Someone has to build the systems, ask the difficult questions, and keep improving them long after the first results appear.
That has been a constant throughout Faisal Ba-Aqeel’s career. As the co-founder of Chartten, an AI-powered business support platform launched in 2025, he is applying more than 21 years of experience across procurement, operations, facilities management, and business transformation to solve a challenge he has repeatedly encountered throughout his career. The platform was born from his belief that while organizations already have access to powerful digital tools, routine operational work continues to consume valuable time because skills, technology adoption, and digital awareness vary across teams. By reducing administrative burdens and simplifying day-to-day business processes, Chartten is designed to help organizations focus on decisions that create real value.
Before co-founding Chartten, Faisal built and scaled procurement, operations, and facility management functions across industries including logistics, food, retail, and technology. Working with organizations such as FedEx, Supreme Foods, Al Romansiah, Delivery Hero, and Careem, he led complex projects in fast-growing environments where disciplined execution, data-driven decision-making, and continuous improvement were essential to delivering results.
What can leaders learn from someone who has built systems across industries, transformed business operations, and now channels those lessons into building an AI platform for modern organizations?
In this interview with Performance Magazine, Faisal reflects on the principles that have guided his career, the thinking behind Chartten, and the mindset required to build organizations that continue to perform as they grow.
Building something from nothing is rarely a straight line. How would you describe the mindset you bring into a role where the structure, the process, even the team, doesn’t exist yet?
A strong foundation comes from understanding the scope of work, knowing the purpose, estimating the required resources (tools, manpower, funds, technology, etc.), involving the right people, aligning stakeholders, consulting and benchmarking the market, and studying the obstacles and risks before execution begins. From there, execution is followed by continuous observation, regular updates to the involved team, and the application of continuous improvement.
You have developed procurement and facility functions from the ground up at more than one company. When you start a function with no existing structure, what do you set up first, and why does that piece come before everything else?
Gathering data (from there, I can see everything that is going on), then analyzing it, helps me make decisions in accordance with company policies and goals. As the widely recognized principle says, “You can’t manage what you can’t measure,” and, as W. Edwards Deming famously said, “In God we trust; all others must bring data.”
At Delivery Hero, you supported the expansion of dark stores, coffee shops, and cloud kitchens at the same time. How did you track performance across formats that differ so much from one another, and what numbers told you a location was on track?
Setting up SLAs (internal and external) based on internal clients’ (colleagues’) project deadlines. Once these boundaries are understood, I compare them with the tools I have, then hire the required manpower (qualified team members) who will lead the work and meet those deadlines on time. Then, I divide the tasks into SMART goals and start measuring them through all possible tools (MS Project, dashboards, and Power BI) to ensure we are on track.
Procurement and facility work often pulls in different directions, one chasing savings, the other chasing speed and reliability. How do you decide which one wins when a decision can’t satisfy both?
Completely agree, as one focuses on saving while the other focuses on spending to ensure business stability. My role is to understand the components and specifications in facilities, including the latest technologies to optimize the work, then secure and align such innovations in-house with a well-drafted contract. After that, I keep evaluating and monitoring performance and results while continuously improving wherever needed.
Your work has touched fresh chicken supply, dark store rollouts, and cloud kitchens, sectors with very different risk profiles. What changes in your approach to performance tracking when the product on the line is perishable versus when it isn’t?
Knowing the nature of the product and its challenges allows us to set up the right and well-agreed terms across all tiers (upstream and downstream). Then, putting in place a proper process (clear communication, real-time data sharing, buffer stock, strong relationships, technology, etc.) allows us to become more resilient from a business perspective. The nature of the product is certainly a challenge, but applying the above makes everything observable and keeps risks to the lowest possible level.
You moved from sales at FedEx into procurement and operations later in your career, a shift many professionals don’t make. What carried over from that early sales experience into how you manage supplier relationships and targets today?
The titles, techniques, and angles seem different, but believe me, sales and procurement are two sides of the same coin: value exchange. Sales taught me commitment, negotiation, contracts, relationships, numbers, and results, all to achieve business value through a win-win approach. Knowing sales absolutely helped me understand how procurement works and how both functions share the same value, allowing me to play my role properly while contributing to business success.
Digital transformation and Power BI tracking came up more than once in your background. Walk us through how a tracker actually gets used day to day. Who looks at it, how often, and what happens when the numbers slip?
Learning to use data and visualization has helped me lead the business, and I built Operations Trackers, Procurement Trackers, and others. I then shared those trackers with the involved parties (internal and external) to align and review them daily, weekly, or monthly (depending on data privacy and relevance), understand business performance, and stay on track to achieve targeted business levels. They also drive real-time decisions, accountability, and corrective actions before small gaps become major problems.
You’ve worked across SAP, Oracle, Microsoft Dynamics 365, and several analytics platforms. When a company already has legacy systems in place, how do you decide what to keep, what to replace, and how fast to move?
I start with a fit-gap analysis by mapping business processes against current ERP capabilities. I keep what supports the core business value and replace or remove what does not align with business needs (while considering costs, of course). The priority is to address the highest-impact areas first, followed by the lower-impact ones. I believe there is no perfect system that fits every business, but systems can be customized according to business needs.
KAIZEN workshops, process organization, automation projects: your background includes a fair share of internal restructuring. What signs tell you a department needs this kind of intervention before the problems become visible at the top?
When small issues interrupt time that should be spent on real priorities, it’s time to use tools such as Muda, Kanban, or Gemba to identify bottlenecks and unnecessary motion, find the root cause, and resolve it before it becomes a bigger issue. The goal is to stay on track with SLAs, policies, and KPIs while applying a continuous improvement methodology.
You’ve delivered projects in three months that other companies might plan for a year. What gets cut from the usual planning process to make that timeline possible, and what risks do you accept in exchange?
I focus on the strategic view, liquidity, and timelines, then accelerate the approval cycle and budget process. This includes combining and eliminating unnecessary steps, such as placing bulk orders for small, repetitive items or supplying new items before common ones, while predicting potential risks by understanding business needs. This approach makes us more resilient and able to closely monitor progress. The accepted risks include extra workload, additional audits, and rework for exceptions outside standard operating procedures (SOPs).
Across FedEx, Supreme Foods, Al Romansiah, Delivery Hero, and Careem, the industries shift but the pattern of building and fixing systems repeats. Looking back at that pattern, what do you think it says about how performance management should work in fast-moving companies versus established ones?
In fast-moving companies like Delivery Hero, performance management is daily: live dashboards, fast feedback, and leaders act as expeditors who fix systems on the go. In established firms like FedEx, Supreme Foods, or Al Romansiah, it is more structured, with quarterly reviews, SOP-driven KPIs, and stability as the priority. The pattern shows that both continuously improve systems, but fast-moving companies prioritize speed over policy, while established companies follow policy to ensure stable outcomes.
Looking at everything you’ve built across these industries, what do you hope the next chapter of your career adds to that story, and what kind of mark do you want to leave on the strategy and performance management space going forward?
To lead in a strategic role, eliminate the operational mistakes I have seen in previous companies as a priority, scale business potential across my network and the companies I have worked for, and drive integration that adds real value to society. The mark I want to leave is creating alignment, empowering people at all levels, sharing knowledge and experience, and driving innovation that integrates with society and creates lasting value.
