Every day, organizations face difficult questions: Which KPIs truly matter? How can strategy move from planning to execution? What practices lead to stronger organizational performance? The articles in this roundup address these and other pressing challenges.
Based on the latest readership data, these are the 10 Performance Magazine articles readers returned to most often so far in 2026.
If you’re looking for practical insights to strengthen strategy, performance measurement, and decision-making, this collection is a good place to start.
1. How Apple Uses the Balanced Scorecard
If your KPIs fail to tell the full story, it may be time to rethink how you measure performance. Learn how Apple uses the Balanced Scorecard to translate strategy into measurable outcomes across the entire organization. Read the article here.
2. 5 Levels of Organizational Maturity in Performance Management
Why does your organization feel busy but still struggle to turn performance data into meaningful results? Discover the 5 levels of organizational maturity—from inconsistent processes and unclear KPIs to an optimized, strategy-aligned system that drives continuous improvement. Check out the article here.
3. KPI of the Day: Utilities: % Electricity supply not restored within 2 hours
Power outages are frustrating—but the real performance issue is how quickly you restore them. This KPI measures the % of electricity interruptions lasting beyond 2 hours, helping utility providers identify restoration bottlenecks, strengthen response strategies, and improve reliability for customers. Find out more about this KPI here.
4. Is Benchmarking Worth a Company’s Investment and Time?
Measure. Compare. Learn. Improve.
Benchmarking transforms isolated performance numbers into meaningful reference points—helping organizations uncover gaps, learn from best-in-class practices, and make smarter improvement decisions. See what our performance management expert says about it here.
5. Southwest Airlines: From Benchmarking to Benchmarked
Your competitors aren’t always your best teachers. Southwest Airlines looked to NASCAR pit crews for lessons in speed, task clarity, and teamwork—then used those insights to transform its turnaround time and become a benchmark itself. Get the details here.
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Whether you’re discovering these articles for the first time or revisiting them for fresh ideas, we hope this collection helps you tackle today’s performance challenges with greater clarity and confidence. If you have any questions or ideas for future articles, don’t hesitate to reach out: [email protected]
In most enterprises, there is at least one, often multiple, dashboards. These glowing arrays of data, updating at lightning speed, are producing weekly reports that land in everyone’s inbox, from the CEO down to the floor supervisor.
The platforms used to gather such metrics are significant investments in configuration, and continued investment is required to extract this information and make it consumable by diverse stakeholders.
The problem is that, in many of these enterprises, the same metrics haven’t influenced a key decision for months. The underlying paradox of measurement within most of our current organizations is that the more we attempt to quantify something, the less effective we seem to become at deriving meaning and insight.
As the volume of available information proliferates, it seems increasingly challenging to discern which actions are necessary, let alone effective. Measuring for progress now seems to have morphed into measuring for mere participation.
Measurement in excess has transformed the metrics themselves into little more than participation indicators that have little to no genuine impact, when, really, you should measure only what can be measured well.
The Measurement Maximalism Trap: How Organizations Got Addicted to Data
The Dashboard That Glows But Doesn’t Guide
The dashboards originally designed for illumination, not for eye-popping designs, have become the organizational equivalent of corporate wallpaper. Visually engaging complexity, not driven to a specific action. This isn’t the flaw in the underlying technology. It’s the flaw in how you’ve defined what is worth measuring.
Today’s analytic toolset makes it easy to record virtually anything. Coupling the ease with an organization whose desire for control equals its belief in the power of more information to be that, led to the phenomenon of what you can call dashboard inflation: metrics accumulate until they crowd out the signal. When a dashboard reports 40 or 50 different metrics, there isn’t the capacity to read them deeply enough to explore anomalies and derive decisive strategic conclusions.
The organization skips and skims through. It glances over, looking for simple, overt, bright, shining red flags. Then it checks the numbers that matter and moves on. What was initially intended to drive action ends up as a task to be filed away as evidence.
The Math That Should Make Any Leader Nervous
Here’s a calculation that is great at cutting conversations short. Imagine an organization with six to ten departments or business units. Give each department an average of 8-10 KPIs to follow, which seems perfectly logical if you think about the unique needs of a single department alone.
Multiply the two, and you’re looking at 48-100 specific measurements the company is technically keeping an eye on.
Next, ask the questions that should follow:
Of all these metrics, how many are really key?
How many truly have an impact on whether or not the company is winning or losing against its highest strategic objectives?
How many exist only because someone decided back then that, since the system made them cheap and easy to generate, someone someday might even use them?
For most companies, the number of strategic indicators is considerably smaller than the hundreds one typically sees on a dashboard.
All of the others survive simply as products of inertia, and each of those hundred “key performance indicators” consumes time and brain space that should instead be devoted to the small subset of data that is truly indicative of performance.
If we had 100 “key” indicators, “key” would essentially become a meaningless word.
The “If We Can Measure It, We Should” Fallacy
The measurement maximalism trap is, at its core, a confusion between capability and wisdom. Modern data infrastructure has given organizations the ability to track almost anything in near real-time. However, capability and strategic judgment are not the same thing, and treating them as equivalent is exactly where organizations start losing the plot.
Just because something can be measured doesn’t mean it has strategic value.
Just because a platform supports 200 custom metrics doesn’t mean you need 200 metrics.
Just because data is available doesn’t mean adding it to your dashboard brings you closer to understanding your business.
What it typically brings instead is noise – an ever-growing collection of numbers that require time to maintain, energy to interpret, and attention that could otherwise go toward the things that genuinely drive performance. Gradually, the act of measurement begins to crowd out the act of improvement. Teams work harder at tracking their progress than actually making any. The organization becomes, in a very specific and avoidable way, busy without being productive.
KPI vs. PI: The Critical Distinction Most Organizations Have Forgotten
Not Every Metric Earns the Word “Key”
About 90% of what we call “KPIs” within organizations are not actually KPIs. They are PIs – performance indicators – and the difference is far more material than many admit.
A performance indicator measures something that occurs within an organization: ticket resolution times, report generation volumes, packing efficiency rates, or training completion percentages. These are all valuable numbers, certainly. They offer an operational view to the teams that own the associated processes and help them establish benchmarks for quality. Yet, they are not necessarily key.
A true KPI, used to the full potential of its name, links directly to a strategic objective.
The organization aims to increase its market share > the strategic KPI is market share.
The organization is trying to retain customers > the strategic KPI is customer retention.
It tells leadership at the highest level whether the organization is winning the game it believes it’s playing: revenue growth, net margin, profitability per customer, market share – these are the top-tier measures. Everything else is essentially noise or in service of those top-tier measures.
We have blurred the lines as organizations have grown, technology has become ubiquitous, and we’ve democratized metric-taking across teams.
It’s easy for each department or business unit to grab hold of operational metrics and dub them “KPIs” without asking whether they actually contribute to high-level organizational strategic outcomes.
Dashboards have become cluttered with PIs dressed up as strategic goals. Nobody realized they were promoted; they just sort of got there.
The 40,000-Foot View vs. Getting Lost in the Weeds So, what does a CEO actually need to know about the state of his company at any moment?
He really doesn’t care about the rate at which the warehouse packs goods unless that number affects a critical cost and/or the customer experience of the company as a whole. What he cares about are a couple of well-communicated indicators:
Is the company growing?
Is it making money?
Are customers staying?
Are we executing on the strategy we agreed we would execute upon? At that 40,000-foot level, you typically need at most six to ten really important indicators to accurately describe what’s happening. Everything else, all the departmental and operational process-level metrics, all the ratios that management needs to manage the day-to-day functions, is nobody else’s business in any of these discussions.
The weakness of measurement maximalism is, to some extent, the weakness of the hierarchy: not being able to sort and separate strategic vs operational measurements.
When you start bubbling up all the individual and departmental PIs to an organizational review meeting, the view gets blurred; the managers are going over meeting click-through rates and newsletter open rates rather than the items that are important and telling.
When KPIs Stop Driving Behaviour and Start Decorating Reports
There is a simple test that measures whether a metric warrants the label of KPI:
Does it change the way people behave?
It should detect issues early and clarify what success looks like and what’s left to do: in short, it should help teams focus.
Once a metric accomplishes these 3 things, it may deserve the “KPI” tag. When it doesn’t change behaviour or decision-making, it’s decorative.
If an organization suffers from KPI proliferation, it probably has too many decorative KPIs. Most of their metrics have gradually become decorative out of mere habit or routine report filler. They have ceased to prove anything useful. Those metrics may simply fill the gaps where data collection and reporting are requested, but without providing insights or stimulating any form of change in people’s work or behaviour. When a good KPI changes the organization’s functioning, a bad KPI or one of 50 other KPIs simply doesn’t.
Any company unable to differentiate between them faces a measurement challenge that is beyond the reach of mere dashboard adjustments.
The Real Cost of KPI Overload: Cognitive Fatigue, Decision Paralysis, and Teams That Stop Thinking
When More Data Produces Fewer Decisions
The hypothesis on which measurement maximalism operates is that more data equates to better decisions. It seems sound and scientific. It’s also quite wrong.
When executives see the dashboard, they usually don’t feel their decisions are being enhanced; the opposite generally occurs. Productivity may have increased, but consumer satisfaction has fallen. Moreover, 40 separate indicators are currently being updated simultaneously. As a result, decision makers delay while scheduling another round of meetings and trying to determine the scale of the real threat.
This is what experts call decision-making paralysis, a symptom of excessive reliance on indicators. Whenever individuals’ capacity to process additional input is overwhelmed, they automatically delay making decisions until a broader range of statistics is available. As more information is considered and more individuals are involved, the perceived uncertainty also grows, and, meanwhile, whatever issue the metrics were intended to uncover deteriorates.
The tragic reality is that these measurement frameworks, which have been used to accelerate decision-making, only lead to a stagnation of decision-making.
Hitting the Metric While Missing the Mission
Here’s a situation that illustrates the danger of mismatched KPIs more effectively than almost any theoretical statement we could make.
A company sees that its Net Promoter Score, its gauge of customer loyalty and enthusiasm, is falling. They identify a solution. Compensation and enticements are provided when feedback is being collected.
NPS rises. The number looks healthy in the next quarter’s report. The actual causes for the customers’ discontent – the friction or the failure of the product – were not, however, altered in the slightest. Many organizations develop this practice, often unwittingly, as they learn to prioritize the score rather than the outcome for which the score was originally developed.
Organizational staff who primarily gain recognition for meeting KPIs develop mechanisms to meet them.
It’s not pessimism – but rather human conduct in reaction to incentive design. Colleagues can tell which things are tested, observed, noticed, and rewarded. Individuals shift accordingly. They obtain experience in offering the appearance of efficiency, but not necessarily the efficiency itself. This is called “conquering the score while neglecting the objective” – one of the most costly forms of failing a company may encounter, since it is quite hard to spot in retrospect.
The dashboard seems all right, and values develop from the correct orientation. However, real life is slowly being corroded.
The Quiet Epidemic of Reporting Fatigue
There’s another cost of KPI saturation that doesn’t show up on any dashboard but that everyone inside organizations swimming in it can feel: the sheer time it takes to feed the beast that is the measurement system.
Getting a hundred different KPIs to tick and tock requires somebody or somebodies to collect, validate, refresh, format, and disseminate that data, frequently, sometimes weekly or monthly.
To a mid-size company, for example, those hours pile up in a hurry. Its analysts produce reports, managers pour over numbers they sort of get, and department heads struggle to fill out the same old forms with numbers only slightly different from last quarter.
That’s time spent feeding the system rather than fixing what’s broken, creating what’s needed, improving customers’ lives, helping their team develop, or making whatever executive decision they truly need to make. It’s the modern corporate bureaucracy, disguised as diligent management work. Over time, a unique, unspoken kind of demoralization seeps into these companies. The people who signed up to build things or help people come in and feel as though they’re spending an outsized fraction of their time on activities that yield little beyond raw data.
The link between their efforts and actual business outcomes begins to blur. Engagement lags persistently, subtly, maybe not to a critical degree, maybe, and not all at once, but to devastating effect down the line. The chosen metrics were designed to empower them to do more. They’re instead burning the fuel that could help them do so.
Signal-to-Noise Collapse: When Reporting Becomes the Work
Vanity Metrics and the Illusion of Progress
There’s an all-too-common disease lurking in metrics-driven workplaces: the proliferation of what could be described as “vanity metrics,” a collection of figures that make a report or a presentation look good but have little or no connection to real business performance: total hits to our website, our number of Facebook followers, the number of features we shipped this week, the amount of customer support tickets we logged, and so on.
These are all relatively easy to produce and easy to feel positive about, and, in most cases, have nothing at all to do with the really important questions like “Are we growing the right way?” or “Are customers truly getting value from what we produce?“
Vanity metrics are seductive because the directionality is right when you simply add more effort.
Your number of social followers will increase as you post more social updates. Your output quantity will increase as you produce more output. Your customer activity will rise when you do more of it. However, the link to a positive result is nonexistent.
Worse, vanity metrics muddy the waters. Genuine metrics like customer retention and the quality of outcomes you help users achieve are harder to work with than tracking output, and they rely much more on human interpretation than the former does.
It’s therefore all too easy to focus on those and neglect to measure those that might not look as good in a report but do provide far more actionable information.
The Bureaucratization of Measurement
There comes a scale at which KPI culture transforms from managing performance to compliance. It’s where measurement has become bureaucracy, full stop. You know when you’re getting there through certain signs.
Measures with no clear strategic explanation, but which were introduced into the monthly report so recently that it feels too dangerous to try to take them out again.
KPI meetings in which nothing much gets followed up afterward.
Reports that are seen, signed, stamped, and stored away.
People who know the targets they have to meet, but don’t know how they relate to anything else that the company does or wants to achieve.
As soon as measurement has begun to develop a life of its own, it loses any reason for it to have had one in the first place: to promote action that enhances performance.
Its purpose becomes simply to ensure the self-preservation of a framework for producing reports that prove reports are being produced in a seemingly organized way.
As the system appears to be very active, the system is also largely uncontested – the dashboard is refreshing, and the monthly reports are being circulated; therefore, it is clear that something is being controlled.
How Good Metrics Quietly Become Bad Incentives
The most insidious part about KPI saturation, perhaps, is what it does to our behaviour in the long run, even when the metrics were a well-intentioned effort to start with. Every single metric, the second that it’s tied to an evaluation, begins to drive behaviour. That is, after all, its job, but that’s different from improving the system the metric was designed to measure.
People get good at gaming the system to produce the number. We optimize around a specific KPI. We cut corners to hit the number. Risk-aversion increases because a miss, however minor, kills the score, and suddenly we have a workplace perfectly optimized for the appearance of performance while the real work goes unimproved.
The issue isn’t individual greed or lazy employees. It’s the predictable consequence of over-measuring and under-trusting. It seems like, by now, we’d have learned that when we tie evaluation to everything, the only smart move is to play the game, not do the work. Metrics were intended to indicate how we could improve things. In systems of over-measurement, we have replaced honest indicators with carefully managed signs of activity: noise dressed up as useful data.
From Measurement Maximalism to Measurement Intelligence: How to Build a Leaner, Smarter System
Start With the Question, Not the Dashboard
The antidote to measurement maximalism, to this idea of just measuring more and more, doesn’t actually mean “measure less for the sake of measuring less.” It means “measure with intent,” and to do that, we need to start with the most important thing, and most organizations get this part wrong more often than they get it right.
What typically happens, if you look at most organizations’ KPI frameworks and dashboards, is that they approach the creation of those frameworks based on the answer to “What’s out there for me to measure?”
Therefore, we assess what data we have, what the analytics tool can tell us, and what can fit on the dashboard, and we build the dashboard from what’s available. That feels pragmatic, and the dashboard ends up looking great, and, by and large, we’ve approached the problem backward.
The real right thing to do is actually to come back to another question: “What decision am I trying to use this metric to inform?”
If the question of what decision I’m trying to make doesn’t have a really, truly clear answer, then maybe that metric shouldn’t be on the dashboard. Maybe that KPI, that part that I’m measuring, just doesn’t belong on the dashboard unless there’s a decision tied to it, a meaningful way for me as a decision-maker to consume it.
If it’s not driving a decision for someone, it won’t serve as a helpful management tool; it will become a floating, isolated data point, and that is the real distinction between measurement intelligence and measurement maximalism. It’s not “how much do we measure” but “how focused do we measure,” which ultimately comes down to a company having more than just an objective in mind.
It should have a specific decision for every metric or set of metrics, a specific type of decision it’s going to serve, and a specific accountable owner who is expected to act as a consequence of observing the metric. If any of those three requirements are not met, perhaps that metric should be dropped.
The KPI Audit: A Framework for Cutting Without Going Blind
The practical dilemma for most people is not a lack of clarity regarding having too many KPIs; rather, it’s determining how to reduce them while maintaining visibility on the really important items. The best tool for identifying which KPIs to prune and which to keep is a system, and it does not have to be overly complicated.
For every measurement indicator on every dashboard, ask:
Does this measurement relate directly to a company’s strategic goal (the ones that really are on there)?
Does it drive a decision and prompt a quick response as the score fluctuates?
Can an informed employee explain what the measurement is tracking and why it’s important?
Would a person use this measurement to make better decisions than they otherwise would without the measure?
If the answer to any of the questions is a simple no, it means the measurement warrants significant evaluation. If you answer simply no to two or more of these questions, you could also answer simply no, since it means your measurement is unlikely to be as productive as you had initially hoped.
In addition to asking these three questions, there is a logical framework for determining how many KPIs the organization requires at different levels, which may serve as initial talking points among interested parties.
Disclaimer:The following numbers are not set in stone and are not end-all be-all guidelines; they should serve only as a starting point for a theoretical discussion on cutting down KPIs in an environment that sprouted so many of them that you don’t even know what each one tracks. They do not represent a cookie-cutter suggestion or a golden standard – they are merely the beginning of a conversation. Each company and industry is different and requires distinct efforts to maximize the use of KPIs.
For practical guidelines or a detailed plan, tailored to a specific organizational situation, get in touch with us here: https://kpiinstitute.org/contact-us
With that out of the way:
A) At the individual employee level, there is some empirical support for certain limits. Often, that revolves around the idea that one person should own no more than three KPIs at any level. If that exceeds 3, few owners can dedicate time to it, and possession skews towards fiction rather than fact.
B) At the team level, you may set up team dashboards of about ten to fifteen KPIs, as long as every measure in the dashboard is genuinely owned, assigned to a goal, and the KPIs are regularly and critically examined and are not simply noted and filed away.
C) At the organizational level, usually around no more than six to ten genuinely strategic KPIs are to be shown to executives, not out of some arbitrary constraint but out of an awareness of the cognitive limits of human beings when focusing on complex and interrelated decisions. Numbers greater than 6 – 10 make it more of a data repository than a viable system. People start focusing on quantity rather than quality.
Treat Metrics as Signals, Not Verdicts
The cultural shift that distinguishes high-performing organizations from those drowning in the metric-maximalist world is this: high-maturity organizations do not use metrics to replace judgment; they use them to inform judgment. In a KPI filled organization, metrics are always verdicts. If a metric is green, things are okay. If it’s red, someone is failing.
Teams spend their time explaining away numbers rather than understanding the system that generated them. Leaders look at averages and move forward regardless of what the averages mean; anomalies are not explored because there are too many data points to examine. In a measurement-intelligent organization, those same numbers initiate dialogue rather than conclude one. An unusual move in a metric isn’t a verdict; it’s a prompt to go deeper and inquire further, to understand what caused the movement.
Why has a number moved?
What is it signaling about the underlying system?
Is it still the thing being measured?
What action is really indicated?
Qualitative insight is as important as quantitative data, not less. The number may signal a shift, but it usually doesn’t say what to do about it. The judgments of people closest to the work, who understand the context far better than any dashboard could, are considered insights, not distractions.
Moreover, accountability in a measurement intelligence organization remains human. Decisions don’t get handed off to dashboards. They are held by humans, with dashboards as backup.
If It Doesn’t Drive a Decision, It Doesn’t Belong
The simplest reframing any organization can adopt for serious measurement culture improvements is this: a KPI that doesn’t inform a decision is not a KPI – it’s noise.
Much like writers kill their darlings when they remove words, sentences, paragraphs, or entire chapters, businesses should do the same with KPIs. Not every metric residing in your data system today will survive or should survive.
Some will be metrics that only made sense three years ago when an entirely different priority was at play. Others will be internal departmental KPIs quietly slipped into the executive dashboards. Many are vanity metrics that are too vain to keep. Pruning these will enable you to stop operating blind and start to see clearly for the first time in what feels like a long time.
Final Thoughts
Measurement is not evil.
Measuring things up is a response that makes complete sense – that impulse to understand if whatever you are up to is actually happening, to detect what might soon become an acute problem, to gauge what may be a slept-on trend, and to want to hold people to account for results.
Yet, when measurement takes on a life of its own, it seems more crucial to do measurement for its own sake. Dashboards become more of a concern than just tools that support decision-making. Teams devote so much effort to feeding some form of measurement tool to demonstrate progress toward the desired end that the effort shifts away from running the business to the business of measuring the business.
Metrics are powerful tools. Used with intention, they drive the kind of accountability that genuinely changes things. However, they are terrible masters, and the organizations that remember the difference (that keep humans in charge of judgment while using data to sharpen it) are the ones that turn performance measurement into a real competitive advantage.
Measure less to understand more to decide better.
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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.
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.
