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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Looking to strengthen your expertise in KPI design and performance measurement? Gain practical knowledge, proven methodologies, and globally recognized certification through The KPI Institute’s Online Certified KPI Professional.
The popularity of sustainability has surged in recent years, causing organizations to grapple with balancing short-term profits with long-term sustainable practices. This has led to concepts like shared value and corporate social responsibility, with companies aiming to create economic and social value while reducing their environmental impact. The movement has sparked active efforts, with social innovators, policymakers, investors, and academics all striving to measure sustainability.
In today’s world, companies must move beyond outdated economic metrics and adopt KPIs that consider the triple bottom line, including social, economic, and environmental aspects of their operations, all while promoting sustainable human well-being.
However, sustainability is a constantly evolving concept that adapts to context and cannot be measured with a single yardstick. The balance between social, economic, and environmental considerations is crucial to achieving sustainability. It is like walking on a tightrope, requiring constant adjustments to maintain equilibrium in a changing world. Each context requires a unique approach, with varying weights and measures for different factors. Customized solutions are needed that address stakeholder needs while maintaining long-term balance, as a one-size-fits-all formula won’t work.
About the Expert
• As a Managing Director, Teodora leads development initiatives to support and enhance the organization’s strategic plan and manages the development and growth of the MENA branch of The KPI Institute.
• An expert researcher, consultant and practitioner with six years of experience in the deployment and implementation of KPI Management Frameworks.
• Pursuing a PhD. in Management on the topic: Rethinking the Performance Management Systems to ensure organizational sustainability, Lucian Blaga University, Romania
• Postgraduate Program in Entrepreneurship and Venture Creation, ISCTE Business School Lisbon, Portugal
• Master’s Degree in Project Management, Romanian-German University, Romania
Key performance indicators (KPIs) have been the north star guiding business strategy for decades. These criteria measure not only sales and revenue but also customer satisfaction as well as employee engagement.However, as the business landscape continues to evolve at an unprecedented pace, the need for deeper insights and more agile measurement arises. This is where the potential of generative artificial intelligence (GenAI) shines, opening doors to a new era of KPI innovation.
GenAI goes beyond automation to produce entirely novel content. It is a creative catalyst, opening up unprecedented possibilities for KPI innovation. Forget rigid, one-dimensional metrics. Powered by GenAI, KPIs become fluent, adaptive, and poetic, capturing not only the whats but also the whys and what-ifs.
Reimagining KPIs for exponential growth
From static to dynamic: GenAI is capable of integrating dynamic KPIs, meaning they can evolve alongside the company that uses them. KPIs also fit seamlessly into a changing market, with trends and strategies naturally shifting along the way.
Unveiling the unseen: Traditional KPIs often fail to hit the nail on the head by overlooking key, intangible factors that could affect performance. GenAI, however, can delve much deeper. With the help of GenAI, it is possible to determine brand sentiment before a particular campaign is launched, anticipate employee engagement within remote teams, or even predict customer turnover before it happens.
Personalized insights, enhanced action: Data mountains no longer need to be intimidating.GenAI transforms data into personalized narratives, crafting stories tailored to individual stakeholders. Sales teams can access actionable insights, marketing managers can monitor real-time customer sentiment, and CEOs can explore what-if scenarios for strategic foresight. This data-driven storytelling fosters informed decision-making and ignites action across the organization.
A practical guide to unlocking GenAI’s potential for KPI innovation
To effectively utilize GenAI tools like Gemini and ChatGPT for KPI innovation, follow these guidelines:
Define goals and challenges: Clearly articulate objectives, whether uncovering customer sentiment or anticipating market shifts.
Frame specific prompts: Use concise prompts such as “generate potential KPIs for measuring brand sentiment on social media.”
Provide relevant context: Enhance responses by furnishing background information about your industry, business model, and existing KPIs.
Experiment and refine: Iterate prompts, rephrase questions, and provide feedback to improve AI understanding.
Collaborate with experts: Involve human expertise in evaluating and implementing AI-generated insights.
While GenAI’s potential for KPI innovation is undeniable, it thrives on synergy, not substitution. The point is this: human guidance is essential. Act now, invest in your future, and become a master of the new KPI era by enrolling in The KPI Institute’sCertified KPI Professional course.
Image source: grapestock from Getty Images | Canva
In modern business, focusing on customer experience (CX) is no longer a nice-to-have, but rather a necessity for businesses of all sizes. However, defining a successful customer experience can be difficult because many touch points form the customer journey. By using online surveys, companies can gain quantitative information about the customer experience to actively monitor trends that develop over time. Based on customer feedback, organizations can identify areas for improvement, adjust their strategies accordingly, set better goals for their key performance indicators (KPIs), and strive to deliver the seamless experiences that today’s consumers expect.
Customer experience KPIs
Research shows that CX is now competing with traditional factors such as price and quality in influencing customer loyalty and advocacy. According to Forbes, 77% of consumers consider CX just as important as the main product or service itself. PWC reported that even beloved brands risk losing 32% of their customers after one negative interaction. In addition, poor CX burdens the company with costs. To address this, this article outlines five critical CX KPIs that can be systematically monitored, evaluated, and optimized to help address customer service problems and strengthen a company’s connections with its customer base.
1. % Customer satisfaction score (CSAT)
This KPI measures how customers rate particular interactions with a company, such as getting a response from customer care or processing a return. Users can score their satisfaction with the experience on a scale from “very dissatisfied” to “very satisfied” by responding to an automated questionnaire sent to them. Monitoring the ratings depends on a company’s objectives, but the general rule is that anything above 85% is excellent, and anything below 60% requires rapid attention.
Calculation: CSAT = (Number of Positive Responses / Total Number of Responses) x 100
2. # Net promoter score (NPS)
The NPS, considered the most famous CX KPI, reflects the willingness of consumers to recommend a product to friends and acquaintances. To calculate NPS, a company can conduct a survey of customers from one query: “What is the probability that you will recommend the product to your friends?” The answer is given on a 10-point scale, where 0 is “I will not recommend it in any case” and 10 is “I will definitely recommend.” The respondents can be divided into three groups depending on the scores obtained: promoters, passives, and detractors. The majority of companies consider a score above 80 as excellent, a score between 50 and 80 as very good, and a score below 50 as good.
Calculation: NPS = % Promoters – % Detractors.
3. % Word of Mouth Index (WoMI)
An extension of the NPS index, the creation of the WoMI was motivated by criticism towards the traditional NPS. Researchers believed that the NPS made the incorrect assumption that if a customer does not recommend a product or service, then they are automatically considered detractors. This led researchers to make adjustments to the KPI in order to better reflect reality. It tracks the recommendation, but from the opposite perspective: “What is the probability that you will discourage people from doing business with the company?” This can be rated on a scale of 0 to 10. Those who choose 9-10 on the scale of “dissuading” are categorized as “true detractors.” The threshold varies from one industry to another. It is better to have a lower score, as the target for most companies is less than 10%. To gain a comprehensive understanding of your company’s position among customers, we suggest employing both approaches to obtain a complete picture.
WoMI = (Number of Promoters – Number of Detractors) / Number of Respondents * 100.
4. Consumer Effort Score (CES)
The CES index, which was developed in 2010, is related to the idea that the more effort the product or service requires from customers, the less likely they are to stay with the company. As cited in an article, research by the Corporate Executive Board (CEB) shows that 94% of customers who have an effortless experience are likely to make repeat purchases. The KPI could be measured by the customer’s response to a statement like: “Thanks to the service/product of company X. I was able to easily cope with my problem.” with a rating scale of 1 to 7. Most companies typically receive CES scores ranging from 5 to 5.5. A score exceeding 6 is generally considered above average.
CES = (Sum of response scores) ÷ (Number of responses)
5. Customer churn rate
Simply put, the churn rate is the number of users who stop any interaction with the company. Depending on the industry, this could mean that customers deleted their account, did not re-buy, or simply decided to switch to a competitor. In its simplest form, customer churn can be calculated by comparing the number of customers lost to the total number of customers. By dividing one metric by another, one can get the customer churn rate as a percentage of the total base. The most common acceptable churn rate is 5-7% annually.
Enabling effective CX measurement
KPIs must be monitored and measured in order to improve CX. To do so effectively, a system that accurately collects data from all channels should be considered. This allows requests to be categorized and common issues to be identified. In-depth interviews with both loyal and dissatisfied customers should be conducted to understand the root cause of any problems, as some of which could be related to support services. Consistency in tracking and improving CX KPIs is the key to ensuring decisions and actions in customer service adapt to changing customer sentiment and meeting their needs.
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