Modern organizations are obsessed with measurement. Pop into virtually any executive meeting, and you’re likely to find glowing dashboards, reports, infographics, charts, and scorecards packed with performance metrics.
Revenue growth, customer satisfaction, engagement, productivity, utilization, retention, cycle time: if it can be quantified, it’s probably being tracked.
This is the Official Market, or what organizations buy and sell in an attempt to take the inherent complexity of business and turn it into something understandable: reports, scorecards, dashboards, intelligence platforms, and Balanced Scorecards.
Business needs complexity to transform into something manageable. Leadership must see into what happens everywhere in the organization, and metrics give teams a common language to express how they perform. Formal metrics are the right tool for holding employees accountable and for allowing leaders to assess the performance of individuals or teams against others over time.
Yet the potential harms of overreliance on formal measurement systems aren’t merely abstract or as far-fetched as many make them out to be.
Natlia Cuguer-Escofet, a researcher at the University of Pompeu Fabra, and Josep M. Rosanas at Universitat de Barcelona analyzed a set of cases in which performance management systems, when implemented rigidly, led to unintended outcomes, including cases from Spanish banks in the period leading up to the 2008 crisis.
In one such instance, a manager who was resistant to escalating loan-making practices was moved out of a position where loan decisions could be made, despite being given a promotion (in the form of an increased salary and improved office space).
In another instance, a board member who was hesitant about an asset’s value was reluctant to express his reservations because the organization’s incentive systems largely tied everyone’s performance to profit. The performance systems were working as they were designed to, but their output was discouraging decision-makers from making professional decisions when they were most needed.
The takeaway from these scenarios isn’t that measurement is itself flawed; it’s that every organization’s performance system will eventually hit a ceiling where it can’t foresee every contingency. When they become overly committed to using objective indicators, organizations risk inhibiting the human intelligence that might warn them of a problem before it shows up in the results.
The crux of the problem isn’t so much a reliance on measuring performance; it’s the assumption that measurable equals significant.
Organizations are often obsessed with measuring metrics, even though those same metrics sometimes do not truly matter to an organization’s success. These metrics aren’t designed to provide a clear picture of why something is or isn’t working; rather, they simply demonstrate what is going on.
They aren’t about showing how frustrated customers are; instead, they show that the satisfaction level has fallen. They aren’t about the employee turnover going up but about what has led to employee discontentment over time. An organization’s ability to identify the causes of declining numbers is critically important, yet metrics cannot illustrate the complexities driving performance from the bottom up.
This weakness is exacerbated, in many cases, by the fact that metrics are, by their very nature, selective. Each KPI necessarily prioritizes some aspects of performance while overlooking others. Organizations use metrics to measure performance based on what they perceive as critical, yet the business environment and consumer expectations require new perspectives. The KPIs organizations rely on may therefore cease to align with the reality on the ground.
It is simply a matter of fact that metrics are better indicators than drivers. When the system measures certain behaviours and outcomes, employees quickly adapt by doing what the system wants them to do. When employees are measured on customer service call time, for example, they learn to hang up with customers as quickly as possible rather than solve their problem. Metrics lead us to manipulate an organization’s output through what we measure, even if what we measure isn’t indicative of success.
“The problem isn’t a measurement one; it’s a knowledge one. You can know the velocity; you just don’t know where you’re headed, and therefore you just don’t know what to do, which makes managing impossible.” – Jeff Bezos
This system of performance relies upon measurement for decision and action-taking but neglects the human aspect; instead, it relies on information that is already visible or reportable. The challenge is that all of this is usually evident on a dashboard if it is tracked or measured.
With that said, not all aspects of the performance in the workplace are quantifiable:
Trust is hard to measure
Honesty cannot be quantified
Creativity or foresight doesn’t have to be demonstrated on a chart
These are not all reflected in The Official Market, as every metric, KPI, report or business scorecard makes choices about what’s relevant and what isn’t.
Sadly, by focusing solely on what we can readily identify as critical and important, many organizations inadvertently start to devalue or even ignore areas they cannot easily quantify. That, it has been said, means the information in their reporting systems may be missing valuable pieces or even be flat-out misleading.
One example is a business intelligence system that tells people how busy employees were in the office (measured by time spent at the desk, use of specific tools, etc.) but does not measure the outcomes of that work. This system has become completely removed from the actual outcomes that would determine whether employees were actually working effectively or not.
In such instances, organizations become overly dependent on such formally measured criteria and risk suppressing human judgment or observation that would otherwise point them toward a problem early on.
The Black Market
There’s one in every organization.
It might not show up in your year-end results. It might not be mentioned in a quarterly review. It definitely will not be in your executive dashboard, but nearly everyone in the company knows it.
This is the KPI Black Market; this is where you would go when your formal measures do not tell the same story. The name is controversial, but it should not be when people search for additional data to navigate a complex business. If an organization goes to great lengths, many beneficial ideas may fall outside measurement standards.
The Conversations That Never Make the Dashboard
Companies have invested significant resources over the past few years in business intelligence tools that afford a live view of operations. However, much of an organization’s most useful intelligence still travels via conversation.
A sales leader hears multiple account managers mention the same customer pain point.
A product leader notices an increase in “what is that for?” type questions about a new feature.
A team lead finds conversation in their team’s hushed post-all-hands meeting.
A customer success manager starts hearing unusually similar wording in otherwise unrelated client calls, hinting at a shared frustration that hasn’t been logged anywhere yet.
A regional manager notices that high performers are suddenly asking more “confirmation” questions instead of making autonomous decisions.
A project lead observes that status updates remain technically positive, but the tone of delivery shifts: shorter messages, fewer details, less narrative confidence.
An HR partner hears recurring “soft exits” in development conversations – people talking more about uncertainty, optionality, or “keeping an eye on things” rather than commitment.
Those aren’t standard metrics, but they often show trouble before it hits the Profit & Loss (P&L).
That’s partly why leaders place so much importance on informal conversation – it’s where emerging signals like doubt, disappointment, enthusiasm, and apprehension get aired while they’re still in their most formative (and useful) stage.
Once a signal is a metric, it’s already past the critical inflection point. That is due to the fact that dashboards chronicle what happened, while conversations signal what’s about to happen.
We write down and archive at an unforeseen speed, yet much of our knowledge is often contained…elsewhere. That knowledge often moves through the Black Market, with almost blinding celerity.
The Mental Dashboard
Try asking an experienced sales leader what will make the quarter miss your target. They often start with “I have a feeling.” It’s the kind of thing a data scientist will probably break out maniacally in a feverish rash at the sound of it.
How can they predict they might miss when the company invests millions in data and analytics to give you objectivity?!
However, the data science in judgment and forecasting actually supports this kind of intuitive forecasting: experts use intuition often not at random but rather to detect patterns that may not show up explicitly and may even be unable to be easily and systematically articulated, due to experience (e.g., having interacted with customers, products, markets, negotiations, and company stakeholders), which can be more sensitive to some cues than others.
You might experience it as a feeling or a sense:
A salesperson feeling the heat because customer engagement seems “off” but has not yet been captured by metrics.
A regional manager in your organization who believes they sense unusual nervousness in the sales reps during customer interactions.
Customer success may note that the typical post-demo and pilot behaviour among clients has changed slightly, but it is not yet affecting metrics such as engagement and churn. In these kinds of instances, they are not officially being recognized by your data platform.
Yet these sorts of signals often influence forecast judgments, however indirectly. Leaders, in essence, operate with two dashboards: one that they see on their screen and another that resides in their head.
One is evidence of what is happening. The other is the interpretation of what’s happening. Neither works well without the other.
The Spreadsheet Nobody Talks About
Perhaps one of the most unaddressed elements of organizational life is the presence of shadow forecasting mechanisms.
Officially, there’s an organization’s forecast. Unofficially, there often exists a second forecast, which may exist in the form of an individual’s private spreadsheet, in an individual’s notebook, or through individual or team discussion.
It is likely, in some form, that this meeting has been heard in every organization where one exists.
The company forecast is presented.
The numbers look perfectly healthy.
Then inevitably someone pipes up, “OK, but what do we actually think?”
The line dividing the Official and Black markets is drawn with that phrase. The Official forecast might be the organization’s most formal assessment, but the Black Market forecast often represents a compilation of individual experience, customer issues, the news and anything else that doesn’t easily lend itself to tabulation.
It’s curious that shadow forecasts don’t necessarily always compete directly against official outputs. Indeed, they can arise as employees try to circumvent gaps they see in the official mechanisms. The fact of there being a spreadsheet doesn’t necessarily matter, since it is the quest for a depiction of reality that people believe in.
Tribal Knowledge and Unofficial Indicators
Arguably the hottest currency in the KPI Black Market is tribe experience. Most organizations have individuals who seem to be aware of certain things well before the rest of the population becomes aware of them. Those individuals understand which projects are real and which generate polished-looking status charts. They can usually predict the top truly unserved and unhappy customer base even before official complaints surface.
Such employees know which operational hazards warrant attention, even when they do not appear in risk analyses. What’s truly fascinating is that these fellows often don’t even have access to data; however, they have contextual gut feelings. By virtue of experience or informed hunches, they understand and see patterns that systems simply can’t capture.
These people remember what happened last time. They recall the anger, the shouts, the boasts, the merriment, or the frustration. They are living archives, in a sense. As such, organizations often defer significantly to individuals who cannot effectively translate the value of their insights into metrics, yet that value is very much there.
This then creates an interesting paradox.
On the one hand, companies may champion objectivity; on the other hand, in uncertain environments, they often turn to sources of experience who, by their nature, are not subject to objective measurement systems. Similar principles are evidenced in how folks make decisions in the informal universe on a day-to-day basis.
Managers observe how quickly answers are transmitted for questions and inquiries.
Account teams pick up on the customer’s emotional tone rather than on official customer satisfaction reports.
Product team leaders keep their eyes on the number of surprises.
Executive team members will note when the “unhappy camper” stops raising their objections.
These signals often aren’t included on charts but have a tremendous impact on decision-making, at times having a significantly greater impact than the official scores themselves.
Why the Black Market Exists
It may be tempting to see these informal arrangements as proof of the ultimate failure of formal measurement. This is a faulty assumption that relies on a complete misunderstanding of the very premise. The existence of the KPI Black Market signals that organizations are, ultimately, human systems operating in contexts far more complex than can ever be fully captured by numbers.
Dashboards cannot account for every variable. KPIs cannot enumerate every risk. Reports cannot portray trust, morale, judgment, intuition, confidence, or culture. When people and groups try to find order in increasingly chaotic surroundings, it is natural that they create complementary information systems – the KPI Black Market – that support and backstop formal systems. The KPI Black Market is thus not a conspiracy against data, but a very reasonable response to its ultimate shortcomings. It is a natural evolution of a most logical process.
Perhaps the most important irony is that most organizations already rely upon the inputs of this unrecorded channel: they simply do so informally and under the table.
The highest-trusted and most timely signals usually originate elsewhere – between peers, during hallway discussions, through personal observation, or based on embodied tacit knowledge. The KPI Black Market is more prevalent in complex environments where reality is perennially richer than our metrics, and, more generally, in organizations that have simply done too poor a job of creating formal indicators.
What Should Leaders Do About the KPI Black Market?
The existence of the KPI Black Market does not, of course, suggest that companies should discard their dashboards, scorecards, or formal reports. Au contraire!
Formal measurement is crucial if organizational performance is to be consistent and comparable, and if accountability is to be meaningful rather than arbitrary, and so much so that the Official Market is an essential part of organizational life.
The problem isn’t that organizations formally measure performance; it’s that they treat formal measurements as complete representations of reality rather than partial ones.
Great leaders recognize that the best dashboard or scorecard cannot do their thinking for them, but can help them think, and that, in addition to the question “What does this metric say?”, a second question needs to be asked.
“What’s missing from this metric?”
A necessary shift in focus leads to the treatment of signals and the observations of employees as information & value, not noise. The aim here isn’t the wholesale abandonment of measurement, but the supplementation of metrics by insight.
A similar approach can be found in the management literature, and the argument has long been made that formal management controls necessarily contain gaps that must be filled by managerial judgment, a concept of “informal justice”.
In essence, such judgments may allow us to question the validity of a metric because it has not kept pace with changing circumstances. Perhaps the easiest way in which to undertake a measure of diagnosis is for a team of leaders to take the time to ask management to list all of the things that management considers important, and then see what doesn’t appear on the board.
Final Thoughts
It is increasingly common to portray organizations as rational, analytical, almost-organic beings in which decisions are data-driven, and metrics are king.
To a certain extent, this is true. Most of them are, indeed, social entities – powered by the experience, intuition, confidence, and understanding coming from their members. Such a sentiment would be historically true as well, as it was the case well before dashboards existed – managers trusted their intuition and vision. Long before business intelligence platforms were born, people discussed and understood their environment to proceed forward, even when uncertainty loomed like an overcast sky.
Although our reporting tools now offer unprecedented visibility, this doesn’t deny the need for those implicit ways of leading teams to progress. Frankly speaking, they simply shouldn’t impede this.
It would be a naive mistake to assume all critical variables can be measured, as the key predictors of an organization’s success are sometimes elusive to quantification. These signals originate from talks, gut feelings, interactions, observations, and events, which never exactly translate onto a metric dashboard.
However, leading companies leverage both, sometimes in equal measure, and often to great success. A dashboard illustrates the past, while those close to the business can provide current-state insights and often foresight.
This is the key takeaway one should derive from the KPI Black Market. The real value is found where the most trustworthy predictors remain off the official dashboard.
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Picture the following: a customer service team boasting average response times under two minutes. Customers are always getting responses right away. Every target is being met. Yet, customers keep complaining, and complaints are only growing.
How is that possible?
After investigation, you find that while customers are receiving rapid responses, those responses may be doing little to resolve their issues. The team members have been incentivized to close tickets quickly because that is what’s being measured. The original purpose (making customers happy) is now secondary.
This can be a very common issue within companies of any size. KPIs that once represented success are slowly becoming success itself. They stop asking “are we accomplishing what we intended to accomplish?” and start asking “are we meeting the target?” The difference between these questions might seem negligible, but the implications can be significant.
KPIs have a place and are indeed beneficial. Companies need a way to evaluate performance, track progress, and understand where improvement is needed. Without measurements, we operate based on assumptions and intuition alone.
The difficulty is that there are many things that organizations care about that are not easily measured. A single number can’t capture employee loyalty. Employee engagement isn’t the same as a survey score. Collaboration, trust, innovation, and long-term business value just don’t fit on a dashboard. As a result, companies use leading indicators, which we assume represent a desired outcome.
Response time is often seen as a sign of good customer service. Attendance is assumed to show employee commitment. Productivity numbers are assumed to prove effectiveness. This is okay to an extent; in fact, these are often necessary indicators to track. Problems arise when the leading indicator outweighs the outcome it was originally designed to represent.
Economist Charles Goodhart explained this concept best in a statement now known as Goodhart’s Law: “When a measure becomes a target, it ceases to be a good measure.” This may sound academic, but the underlying concept is easy to grasp. The moment people are measured, rewarded, or punished by a metric, they naturally seek to optimize for that metric. This optimization might increase performance, but sometimes it only improves the metric.
Consider training for employees. We often measure learning by tracking whether training has been completed. Seems fair on the surface – if an employee completes the training, they are surely learning, right?
Well, not necessarily. When the number of completed trainings becomes a target, the focus shifts.
Employees quickly click through > managers ensure there’s 100% completion before deadlines > dashboards turn green > knowledge retention, skills development, and behavioural change stagnate. The company succeeded in increasing the number but made little to no progress on the desired outcome.
This trend plays out across various industries and sectors. Salespeople push for revenue through deep discounts, thereby impacting long-term profitability. Marketing campaigns aim for engagement numbers even though engagement might be disconnected from real customer value. Project teams celebrate on-time delivery even though the project might not provide tangible benefits. The issue here is not that the metric is necessarily incorrect. The problem is that it only represents a piece of the whole.
A useful analogy for KPIs is to think of them as road signs instead of destinations. Signs tell you if you’re going the right way, but we don’t mistake the sign for the destination itself. Organizations often make this mistake:
Customer satisfaction is not a survey score. ❌
Productivity is not a speed metric. ❌
Attendance does not show employee contribution. ❌
These are signals used to help us understand reality, not reality itself. This difference becomes even more critical when organizations prioritize results while ignoring the actions that lead to those results. A revenue number from last month tells you what has occurred; it doesn’t tell you why. A customer satisfaction number indicates the outcome of a given interaction; it does not show the behaviour displayed during that interaction. By the time a revenue number changes, the behaviours that affected it may have been in place for weeks or months.
That’s why increasingly successful organizations are beginning to differentiate between outcomes and the actions that produce them. Outcomes serve as scorecards, letting you know where you stand. Actions and drivers help you understand how you got there and what you should do next. If leaders focus solely on the scoreboard, they are more likely to react to events after they have occurred. If they understand what causes the score to change, they will be able to influence future outcomes before they become problems.
Through this shift in thinking, we can reach an important conclusion: not all KPIs should be created equal. Some measures help us assess progress towards desired outcomes; others serve as proxies for those outcomes. For leaders, the biggest challenge is recognizing which is which. If the measure becomes the mission, organizations risk optimizing for the numbers rather than for the results they represent.
How Proxy Metrics Quietly Take Over
If most organizations know that KPIs are just indicators, how do so many organizations end up managing the indicator rather than the outcome?
The simplest reason is that proxy measures are convenient.
It’s often hard to measure the actual outcomes we want to influence. For example, real outcomes can take years to show any real results, often can’t be easily isolated from other variables that also affect the outcome, and usually don’t fit well on a dashboard. Proxy measures, on the other hand, are easily and readily available to be captured, reported, analyzed, and benchmarked.
Consequently, organizations tend to get caught in a cycle. Instead of asking “what would indicate we are truly successful?“, they ask, “what data do we already have?“. The available metric slowly evolves into the performance measure.
While this sounds relatively harmless, it quietly creates a shift. Individuals stop focusing on how well they are achieving the actual outcomes and begin talking about achieving the numbers on a dashboard.
Discussions focus on “have we hit the target?” rather than “have we made real progress toward achieving our goal?” The indicator becomes the lens through which we interpret performance, even when it tells only part of the story.
This isn’t to say proxy measures are useless; many of them can provide helpful insights. It’s simply assuming that the proxy and the outcome are one and the same, which is the problem.
For example, completing a training course may indicate that learning has taken place, but it doesn’t confirm any real change in capability. A high customer engagement rate can indicate interest, but does it lead to customer value? An increase in sales calls doesn’t always mean more quality customer conversations were held. These proxy measures may be useful in isolation, but they don’t tell the full story.
Unfortunately, once a metric is valued, people tend to drive it. Usually, this is not due to manipulation or intentional bad practices; it is simply how human beings behave. If a KPI target is linked to rewards, positive feedback, promotions, or performance reviews, people will make sure to meet this metric regardless of whether it aligns with desired outcomes.
The problem then becomes that an increase in a KPI may not necessarily lead to the desired increase in the outcome. There are countless examples throughout history of this behaviour, such as using the enemy’s body count as a measure of success in wars. Such a heinous & vile metric was easier to achieve than actual strategic objectives, and, eventually, simply measuring the metric became the objective itself. The measure dictated the outcome, rather than the outcome shaping the measure.
Now, whether we look at armies or organizations, both can fall victim to the same thinking pitfalls, for they are comprised of people who often err on what is “easier”. Leaders can start managing what’s easy, rather than what’s important.
In a much less combative example, take the instance of a decrease in cost-per-lead: at face value, it doesn’t make much difference if lead quality falls dramatically; an improvement in customer service response times does little if customers still have the same unresolved issues, and a team celebrating meeting all its targets still doesn’t achieve its business goals. Each example shows that the KPI rose or fell as intended, but the desired outcome didn’t.
Perhaps the most intriguing part is that organizations and their people usually know the source of the disconnect:
The sales team knows when target numbers promote busywork
The customer service department knows that quick responses are not the same as solving customer problems
Managers know that an increase in attendees does not necessarily correspond to greater commitment or contribution
However, when people feel a sense of control and certainty that a KPI is moving in the right direction, it becomes difficult to abandon the number, even if we know the real outcomes aren’t shifting as desired.
Numbers, nonetheless, seem more objective and reliable. They are concrete and clear, and they appear to remove uncertainty and complexity from a situation. Clarity, though, is not always accuracy.
A dashboard displaying green lights may suggest great progress, while unseen problems begin to fester beneath the surface of these simple indicators. As an organization becomes adept at performing the actions that achieve the highest success scores on a given metric, it simultaneously develops considerable inertia in achieving its real objectives.
This is why mature performance management systems do not focus on individual metrics, but rather on the overall view. A mature system must incorporate a mix of qualitative data alongside quantitative metrics, so that no individual KPI carries too much weight in determining perceived success.
The real question is not whether there should be proxy metrics at all; it’s whether they are remembered for what they represent. If leaders forget what a proxy metric is supposed to indicate, an organization will spend its energy improving the number rather than the actual desired outcome.
The Five Most Common KPI Traps in Modern Organizations
This quest for proxies seems to manifest itself in infinite ways, yet it follows the same several templates that recur over time, across industries and across hierarchical levels. Although the metrics might vary widely, the error appears eerily similar: the metric eventually succeeds in displacing the thing it was intended to measure.
Response Time Replaces Customer Care
Many customer service teams monitor response time for good reason. Customers typically appreciate quick communication.
The issue is when that speed becomes the primary goal. A team might respond to every single inquiry within minutes, but the response could be generic and fail to resolve the issue. Customers are acknowledged quickly, but still require multiple touchpoints to reach a solution.
This looks good on paper, but in practice, it increases customer frustration. Response time is an important measure, but it isn’t customer service. Customer service is all about understanding problems, solving them, and generating positive experiences. Speed may well be an important factor in achieving these goals, but it alone cannot do so.
Engagement Replaces Value
Engagement has emerged as perhaps the most ubiquitous performance measure in the digital age. Businesses track page views, click-throughs, comments, shares, downloads, logins, and a million other interactive behaviours. Such figures are often collected automatically and can be updated in real-time.
The problem is that this engagement does not necessarily mean any value is being created.
Some content receives millions of page views, while its consumers gain minimal new information. A few software platforms log millions of user logins – their consumers remain stuck performing rudimentary tasks. Several meetings involve many staff members, yet only a handful contribute to improving outcomes.
Engagement does not necessarily mean useful things are happening. It signals that people are attentive. If organizations focus solely on engagement, they create organizations that focus on visibility.
Productivity Replaces Effectiveness
One of the oldest and most frequently measured indicators of performance is productivity.
The number of tasks performed, phone calls made, e-mails sent, reports generated, and tickets closed can tell you something about how busy things are and about operational efficiency. However, you should never confuse activity with effectiveness.
One salesperson can be two or three times as active (in terms of calls made) as another, while identifying far fewer useful sales opportunities. One project team may tick off all the task items on their schedule without having solved the problem the project was designed to fix.
Productivity asks, “How much work got done?“
Effectiveness asks, “Does it matter?“
Organizations that focus on productivity often become incredibly busy without ever becoming more effective.
Attendance Replaces Contribution
One of the easiest measures to monitor is attendance.
People either turn up or they do not. The measurement of contribution, however, is far more involved: someone can attend every meeting and add nothing, whereas another may contribute only two or three times, yet those points may be instrumental in forming key decisions.
It may also be the case that an organization equates attendance with contribution when, in reality, contribution levels depend on involvement, knowledge, collaboration, and the ability to solve problems. Attendance is a good operational measure. That said, it is NOT an indicator of success.
Output Replaces Outcomes
The most frequent KPI pitfall is the confusion between outputs and outcomes.
Outputs are the products an organization puts out.
Outcomes are the effects of these outputs.
Although obvious when articulated, it is often lost when trying to measure things.
Think of a facility team whose job it is to clean an office building. What the facility team measures might include the number of floors cleaned, the time spent cleaning, or the amount of cleaning supplies used. These are all outputs because they show activity. The number of floors is an output; the number of floors scrubbed (to the point they were clean and didn’t feel sticky) would be an outcome.
What if the employees continue to complain that the floors are sticky? The output numbers suggest the team is successful, but the outcome proves otherwise.
The same logic applies to training programs, change management initiatives, marketing campaigns, and transformation projects that are measured by training completion, logins, impressions, and milestones. The output metrics tell us that we did things, but the outcomes measure whether we actually made anything happen. Both are needed.
When we are so focused on outputs, however, we run the risk that they become the sole measure of success, so the team can meet every goal, complete every task, and satisfy every reporting requirement but do absolutely nothing. That’s why there is such risk associated with proxies – they allow us to progress on paper while standing still.
What High-Performing Organizations Measure Differently
At this point, it may sound like the answer is just to get rid of KPIs entirely. Far from it. The matter of fact could not be farther from the truth.
While organizations need measurement, leaders need visibility into performance, and teams need feedback to understand whether their actions are moving the organization in the direction the leadership intends.
The problem is not measurement itself; the problem is making sure the measurement is connected to the thing it’s supposed to be measuring. High-performing organizations understand that KPIs are learning and decision-support tools, not outcomes in themselves. They use metrics to understand performance, and they avoid the urge to turn a metric into an outcome.
I) One of the most critical adjustments they make is to separate outcomes from the behaviours that lead to them.
Many organizations focus almost entirely on outcomes: revenue, customer satisfaction, retention, profitability, market share, and similar figures that often top executive dashboards. These numbers are important, but they are also trailing indicators – they tell you what already happened. When customer satisfaction scores start to slip, the underlying reasons may have existed for months. When revenue declines, the factors that led to the drop may have been building for quite a while.
Whilst high-performing organizations do keep a close eye on outcomes, they also identify the behaviours and performance drivers that contribute to these outcomes:
A sales team might be concerned with revenue as an ultimate outcome, but it also looks at the quality of prospects it’s working on, the level of activity its team has-how many calls and meetings-and its closing rate. All of these will affect revenue and allow leaders to spot problems before they significantly impact sales figures.
A customer service team will continue to track customer satisfaction scores, but it will also look at how many times a customer contacts it for a single issue, how quickly agents respond, the quality of communication, and customer effort.
The objective is not necessarily to replace outcome measures with behaviour measures, but to tie them together.
Outcomes tell you where you are, behaviours give you an idea of how you got there, and where you are likely to go in the future. This changes how you use KPIs from simple reporting tools into proactive management tools.
II) Another difference in mature performance systems: these organizations rarely use a single metric for an important organizational objective.
Let’s use customer experience again: organizations often turn to NPS or customer satisfaction scores. These have value, but no single metric adequately describes the concept. It may make more sense to use customer satisfaction metrics alongside retention rates, complaint counts, resolution speed, customer effort, and actual customer feedback.
Each one captures a different piece of the puzzle, which is why they should be looked at together. The same logic applies to nearly every other aspect of the business.
Revenue should be examined along with profitability.
Productivity along with quality.
Employee engagement along with retention and performance.
Efficiency along with effectiveness.
When measures are viewed as interconnected pieces of information, the temptation to optimize one measure at the expense of another diminishes significantly.
III) Lastly, and probably most important of all, high-performing organizations retain an element of wonder about what they might be missing with their KPIs.
They understand that metrics are a form of simplification and allow us a glimpse into the world of perceptions. No dashboard can fully capture customer trust, employee loyalty, innovation, culture, teamwork, or the ability to adapt; yet all of these can be profoundly important drivers of organizational success.
Instead of assuming that every important thing can and must be expressed as a number, leaders at mature organizations accept the inherent limitations of measurement and complement their data with conversations, observations, customer inputs, employee knowledge, and professional judgment.
In other words, they use data, but not as a replacement for decision-making, since the purpose of performance management is not perfect reports but reports that provide a deeper understanding of performance. Such work takes more than merely watching numbers on a screen.
A Simple Test for Every KPI You Use
The risk of proxy metrics is that it is uncommon for a bad metric to be bad to begin with.
They usually begin as rational indicators of important goals and slowly take on a life of their own as companies get increasingly obsessed with bettering the indicator itself. This necessitates periodic reevaluation.
Each of your KPIs should, on occasion, be examined with a basic but critical question: Is this metric still telling us something about our performance, or has it become the performance?
The answer may not be crystal clear, but a few practical questions can reveal a KPI that might be losing sight of the original goals.
What outcome is this KPI supposed to represent?
Each metric should relate clearly to an organizational goal.
If the goal is unclear or hard to articulate, the KPI might be measuring activity rather than progress. One helpful test is the question “Why should we even care about this number?” The answer often highlights whether the metric is still relevant to the desired outcome.
If the KPI improves, does the outcome necessarily improve?
If you can improve the metric without improving the outcome, there is a risk that the KPI serves as a surrogate for something weaker.
Training completion can increase without any skills being gained.
Website traffic can go up without any value being added.
Response times can increase without the customer’s problems being solved.
You should be very wary whenever it’s possible to optimize a KPI independently of an outcome.
What behaviours does this metric encourage?
Performance metrics influence all actions. Some actions will be productive, some less so.
A sales performance metric can prompt positive customer outreach. It may also prompt undue discounting.
An activity performance metric can prompt work, but it may also prompt busywork.
So, the question is not simply whether a KPI triggers activity, but whether it triggers beneficial activity.
Can people hit the target while missing the point?
This issue seems to be at the very core of Goodhart’s Law: if it is possible to obtain the metric without producing the desired result, then the KPI may become the goal.
A lot of the examples mentioned within the article fall into this category – where the team “hit the number” and still made little real progress toward the overall aim. In these cases, other indicators may be necessary.
What important outcome are we not measuring?
Each KPI measures just one dimension of the business. As attention to any specific KPI increases, another aspect of performance will likely fall into a “blind spot.”
Customer acquisition may be analyzed, while customer retention is neglected.
Productivity may be measured, while quality is left out of the discussion
Operational efficiency may be increased at the expense of innovation
The ongoing question of what is not on the dashboard will ensure that important business outcomes do not fall completely out of the organization’s mindshare.
Final Thoughts
KPIs remain one of the most powerful tools for leaders to align efforts, monitor performance, and allocate resources.
With that said, they are but a tool. They break down when an organization forgets the difference between the metric and the outcome the metric is supposed to capture.
A fast response isn’t great service.
High engagement isn’t value creation.
Productivity isn’t effectiveness.
Attendance isn’t a contribution.
Output isn’t impact.
The best organizations remember and manage accordingly; they use numbers to inform judgment rather than replace it. They focus on outcomes while being acutely aware of the behaviours that produce them. They remain attuned to the fact that a helpful metric today can become a damaging target tomorrow.
At the end of the day, a KPI’s value isn’t in proving that we can win at numbers. Its value lies in helping us improve our numbers. That’s when KPIs truly fulfill their potential as indicators of success rather than proof of it.
It is generally accepted within most organizations that strategy is filtered through structure: a group of executives defines priorities, these executives delegate to leaders, department heads manage their reports, and then people at lower levels of the hierarchy do the work.
That, at least, is the story told by the organizational chart. However, work does not flow smoothly through a company in the same way it does along an organizational chart in the boardroom.
Strategy flows through invisible networks. It moves through trust, it relies on reputation, friendship, alliances, credibility, influence, and memory. Employees are actually dependent on those specific individuals who offer reliability in the midst of political and chaotic organizational circumstances.
These hidden networks are what is called the informal organization.
For many organizations, the informal structure plays a more significant role than the formal one.
A leader may be officially responsible for a particular transformation project, but the individual whom everyone in the company recognizes as the real leader responsible for it might actually be another person. A strategic task may be implemented not because formal procedures were followed for approval but because a key trusted contact used informal connections to move it forward behind the scenes, and another project with impeccable governance procedures might completely collapse because the informal network never really backed it.
This is the hidden dimension that many strategy models seem to ignore.
While the organizational chart clarifies accountability, the informal organization illustrates behaviour. Where & when the two are at odds, the strategic execution of the task succeeds or fails.
According to researchers Alberto F. De Toni and Fabio Nonino, the informal organization is “the real central nervous system” of companies, and operational coordination is managed primarily through informal connections rather than organizational structures.
These assumptions revolutionize the perspective from which execution needs to be addressed.
If strategy execution is achieved through human interaction, it is crucial to focus on whom each individual actually looks to for guidance and help, rather than to whom they officially report.
Why Organizational Charts Rarely Reflect Reality
Organizational charts rarely represent reality because two companies are present in reality simultaneously: the formal and the informal organizations.
A) The formal organization is structured hierarchically through a complex web of reporting lines, departments, roles, and decision-making procedures.
B) The informal organization is a social web of non-work-related connections that develop over time.
As a result, in many organizations, people look to specific individuals within the company regardless of the organization chart; this may be because of a specific skill, expertise, empathy, or political acumen these individuals possess. Such individuals act as unofficial decision-makers, the people one goes to before making a formal decision, the people who possess the expertise or social power to navigate through difficult organizational dynamics and push forward projects.
There is usually a significant gap between what is expected within the formal organization and what people actually do, and these unseen decision-makers in every company are the informal leaders.
Whether they may or may not occupy high-level executive positions is irrelevant, for employees approach them for guidance before making decisions; they understand how the real system operates and have the political agility to remove obstacles and make stalled projects run smoothly. They also understand the organization’s politics and history, enabling them to negotiate effectively without alienating others.
Although they may sometimes appear to lead initiatives, their authority is not granted but is derived from the credibility, expertise, emotional intelligence, and positive social influence they command from others within the company. Essentially, they earn the right to lead by demonstrating competence and building trust with others over time.
De Toni and Nonino identified several recurrent informal roles within organizations, including opinion leaders, central connectors, bottlenecks, consultants, experts, and “helpful people”. The influence these roles have varies.
For example, opinion leaders impact how people react to change and are closely watched by the workforce. Central connectors are critical to effective internal communications. These people serve as an infrastructure within the organization, facilitating informal communication and connections across functions and departments.
Such networks become strategically important because, generally, strategy execution relies less on the command-and-control structure than on the socially constructed legitimacy of what one is trying to accomplish. People might comply with an authority, but commit themselves to it through trust.
How Informal Networks Empower or Sabotage Strategy Execution
One important fact that many people get wrong about organizational dynamics is that there is no direct, mechanistic implementation of strategy; rather, strategy is interpreted and executed socially. It is through the informal organization that an initiative might be perceived positively or negatively by employees, depending on their interpretation.
They don’t make their assessment of a transformation process solely on formal data but look to people in other departments to see how they react. The internal strategy debate takes place in private meetings, casual hallway chats, e-mail groups, and lunches. If people in influential positions secretly mistrust a transformation project, then the initiative itself might be in danger.
It may seem mysterious from the outside, but people within the organization often know what is happening. This means the informal leaders will have agreed, and the organization’s internal decision-makers will align informally.
Conversely, a strategy might fail not because its objectives are faulty, but because the people responsible for its execution did not feel any personal connection or investment in the idea. They might not even fully trust the people in charge of leading the change. If this happens, the formal objectives must take a back seat, and social legitimization becomes the priority.
When the Trusted Operators Become Bottlenecks in an Organization
Having said all that, it is important to note that informal influence also has a sinister downside. The very same people who make organizations work can quietly become execution bottlenecks.
One of the case studies examined in de Toni and Nonino’s study was that of an executive named Andrea, who had become overwhelmingly important to the flow of information within his business unit. The organization became so reliant on him that removing him from the communication network would result in a dramatic drop in information flow, leaving numerous individuals isolated.
This is extremely common, and every organization has the “go-to person”: the reliable fixer/operator who always knows the answer. These people initially expedite execution since people trust them.
Over time, organizations implicitly build themselves around them, waiting for their response. Projects are put on hold, waiting for the individuals’ input. Teams refrain from making any moves without consulting them. Information gets funneled to and from these individuals rather than being disseminated. It is almost ironic that the most trusted people within organizations can be hidden scalability bottlenecks, not due to poor execution but because they become integral to too much of the organization’s functionality.
Formally, the organization may seem healthy. Reporting lines exist; governance structures remain intact, and processes are in place. Operationally, the company may be held together by only a handful of informal influencers.
When these individuals burn out, leave, are let go, or face internal political isolation, they can significantly weaken the organization’s execution systems. This is one of the underlying reasons why so many organizations can’t scale despite complex formal structures.
The Hidden Politics of Organizational Influence
A major misconception within organizations is that they operate on logic alone. In reality and proven practice, interpretation, emotions, identity, trust, and influence drive organizations. This is where workplace politics come in.
Politics can sometimes have a negative connotation, but in its simplest sense, politics is simply the circulation of influence within systems that have an uneven distribution of authority, resources, and priorities, and every organization has an unequal distribution of influence. The interesting aspect is that influence does not always travel downwards. Influence can travel horizontally, upward, or, at times, completely outside the organizational hierarchy.
According to researchers of informal organizations, there are three ways in which influence is gained:
by positional authority
by expertise
by relational credibility
The former formal structures in organizations can take advantage of hierarchy and authority, whereas the latter systems favor expertise and trust.
This is extremely significant because, despite employees verbally following formal leaders, they may actually look to others for validation, instruction, guidance, and explanation. The outcome is shadow leadership in many organizations. These people officially have no leadership titles, yet they informally coordinate teams, affect and mold company culture, mentor junior staff, influence hiring, and direct operational behaviour. They are the emotional glue of the organization, and organizations usually realize their impact only once they depart; communication breaks down, teamwork falters, trust erodes, confidence corrodes, and morale plummets.
Often, leadership takes the path of believing the issue is operational and cannot pinpoint why it is failing, even though the true culprit is the loss of a central node of relationships.
Shadow Leadership, Institutional Memory, and Cultural Gatekeepers
Informal influence is even stronger when backed by institutional memory. People who possess institutional memory remember failed transformations, lost systems, failed restructuring processes, and broken promises of leaders. They are the cultural gatekeepers.
While these individuals sometimes save organizations from repeated mistakes, other times they preserve antiquated thinking, which impedes necessary change. Their influence, however, is not captured in formal strategies. Regardless of the direction of influence, this individual heavily dictates organizational behaviour. Though a newly-hired executive may have formal authority, a lack of access to their deep trust networks could hinder execution; conversely, long-tenured individuals without executive titles may wield much more influence because of their greater understanding of the organization’s emotional and political history.
This is why external consultants who offer excellent frameworks often fail: they have analyzed the visible organization and ignored the invisible part. The formal structure indicates authority, while the informal structure indicates credibility; the two may not always be the same.
Why Organizational Change Fails Invisibly First
One of the critical takeaways from studying informal organizations is that while technical systems fail visibly, social systems fail invisibly, first through hesitation, withdrawal, silence, and avoidance. This is characterized as passivity disguised as caution.
1) The first signal of change is relational.
Collaboration becomes strictly transactional, people stop sharing information freely, and departments isolate themselves politically rather than coordinating toward a common goal.
2) Then, the second signal of change is control.
The immediate, and often incorrect, reaction of organizations at this point is to add layers of control. More committees, more reporting structures, and more oversight mechanisms are put in place.
3) These first two signals inevitably lead to the third signal of change, which is dilution.
All of these initiatives negatively impact organizations by watering down the trust that is essential for rapid adaptation and change.
Truly successful companies learn to leverage their informal structures rather than ignore them. Instead of asking who holds authority, they learn who influences behaviour. Their strategies focus on communication flows, trust networks, and relational systems rather than solely on reporting lines.
Social Network Analysis and the Rise of Informal Leaders
Today, many organizations utilize social network analysis to uncover the invisible relational dynamics at play within the company.
In the case of the Euris Group, network analysis identified communication networks, expertise, problem-solving collaborations, and hidden organizational relationships within the company. It turned out that the most influential individuals in the organization were not necessarily the highest-ranking personnel, but instead were those who possessed three traits: expertise, problem-solving ability, and accessibility.
The researchers referred to them as “primus pilus” (named after the Roman soldier who directly supported and guided soldiers into battle). It seems an apt modern analogy because often in today’s organizations, the people who lead and truly drive execution are not those who deliver the strategic presentations but rather those who come to the fore when situations become tough: the operators who turn abstract concepts into practical actions, those who can bridge the gap of expertise and relatability, those that act as liaison between information and understanding, and those who reduce system friction.
These individuals are often the de facto stabilizers between high-level vision and practical operations, and failing to acknowledge them has created enormous strategic blind spots for some organizations.
Final Thoughts
The informal organization, as a subset of the main organization, provides a critical insight into the nature of strategy: execution is not only based on structure but is deeply human.
Companies move not simply through reporting lines but through relationships, trust, credibility, memory, identity, and influence. While the organizational chart outlines who has authority, the informal network explains how things actually get done and with what degree of haste.
There are several lessons to keep in mind, but perhaps the most important concerns strategy: namely, that the most powerful systems in organizations are not necessarily those intentionally designed by anyone, but those that develop organically.
High performance rarely happens by chance. Someone has to build the systems, ask the difficult questions, and keep improving them long after the first results appear.
That has been a constant throughout Faisal Ba-Aqeel’s career. As the co-founder of Chartten, an AI-powered business support platform launched in 2025, he is applying more than 21 years of experience across procurement, operations, facilities management, and business transformation to solve a challenge he has repeatedly encountered throughout his career. The platform was born from his belief that while organizations already have access to powerful digital tools, routine operational work continues to consume valuable time because skills, technology adoption, and digital awareness vary across teams. By reducing administrative burdens and simplifying day-to-day business processes, Chartten is designed to help organizations focus on decisions that create real value.
Before co-founding Chartten, Faisal built and scaled procurement, operations, and facility management functions across industries including logistics, food, retail, and technology. Working with organizations such as FedEx, Supreme Foods, Al Romansiah, Delivery Hero, and Careem, he led complex projects in fast-growing environments where disciplined execution, data-driven decision-making, and continuous improvement were essential to delivering results.
What can leaders learn from someone who has built systems across industries, transformed business operations, and now channels those lessons into building an AI platform for modern organizations?
In this interview with Performance Magazine, Faisal reflects on the principles that have guided his career, the thinking behind Chartten, and the mindset required to build organizations that continue to perform as they grow.
Building something from nothing is rarely a straight line. How would you describe the mindset you bring into a role where the structure, the process, even the team, doesn’t exist yet?
A strong foundation comes from understanding the scope of work, knowing the purpose, estimating the required resources (tools, manpower, funds, technology, etc.), involving the right people, aligning stakeholders, consulting and benchmarking the market, and studying the obstacles and risks before execution begins. From there, execution is followed by continuous observation, regular updates to the involved team, and the application of continuous improvement.
You have developed procurement and facility functions from the ground up at more than one company. When you start a function with no existing structure, what do you set up first, and why does that piece come before everything else?
Gathering data (from there, I can see everything that is going on), then analyzing it, helps me make decisions in accordance with company policies and goals. As the widely recognized principle says, “You can’t manage what you can’t measure,” and, as W. Edwards Deming famously said, “In God we trust; all others must bring data.”
At Delivery Hero, you supported the expansion of dark stores, coffee shops, and cloud kitchens at the same time. How did you track performance across formats that differ so much from one another, and what numbers told you a location was on track?
Setting up SLAs (internal and external) based on internal clients’ (colleagues’) project deadlines. Once these boundaries are understood, I compare them with the tools I have, then hire the required manpower (qualified team members) who will lead the work and meet those deadlines on time. Then, I divide the tasks into SMART goals and start measuring them through all possible tools (MS Project, dashboards, and Power BI) to ensure we are on track.
Procurement and facility work often pulls in different directions, one chasing savings, the other chasing speed and reliability. How do you decide which one wins when a decision can’t satisfy both?
Completely agree, as one focuses on saving while the other focuses on spending to ensure business stability. My role is to understand the components and specifications in facilities, including the latest technologies to optimize the work, then secure and align such innovations in-house with a well-drafted contract. After that, I keep evaluating and monitoring performance and results while continuously improving wherever needed.
Your work has touched fresh chicken supply, dark store rollouts, and cloud kitchens, sectors with very different risk profiles. What changes in your approach to performance tracking when the product on the line is perishable versus when it isn’t?
Knowing the nature of the product and its challenges allows us to set up the right and well-agreed terms across all tiers (upstream and downstream). Then, putting in place a proper process (clear communication, real-time data sharing, buffer stock, strong relationships, technology, etc.) allows us to become more resilient from a business perspective. The nature of the product is certainly a challenge, but applying the above makes everything observable and keeps risks to the lowest possible level.
You moved from sales at FedEx into procurement and operations later in your career, a shift many professionals don’t make. What carried over from that early sales experience into how you manage supplier relationships and targets today?
The titles, techniques, and angles seem different, but believe me, sales and procurement are two sides of the same coin: value exchange. Sales taught me commitment, negotiation, contracts, relationships, numbers, and results, all to achieve business value through a win-win approach. Knowing sales absolutely helped me understand how procurement works and how both functions share the same value, allowing me to play my role properly while contributing to business success.
Digital transformation and Power BI tracking came up more than once in your background. Walk us through how a tracker actually gets used day to day. Who looks at it, how often, and what happens when the numbers slip?
Learning to use data and visualization has helped me lead the business, and I built Operations Trackers, Procurement Trackers, and others. I then shared those trackers with the involved parties (internal and external) to align and review them daily, weekly, or monthly (depending on data privacy and relevance), understand business performance, and stay on track to achieve targeted business levels. They also drive real-time decisions, accountability, and corrective actions before small gaps become major problems.
You’ve worked across SAP, Oracle, Microsoft Dynamics 365, and several analytics platforms. When a company already has legacy systems in place, how do you decide what to keep, what to replace, and how fast to move?
I start with a fit-gap analysis by mapping business processes against current ERP capabilities. I keep what supports the core business value and replace or remove what does not align with business needs (while considering costs, of course). The priority is to address the highest-impact areas first, followed by the lower-impact ones. I believe there is no perfect system that fits every business, but systems can be customized according to business needs.
KAIZEN workshops, process organization, automation projects: your background includes a fair share of internal restructuring. What signs tell you a department needs this kind of intervention before the problems become visible at the top?
When small issues interrupt time that should be spent on real priorities, it’s time to use tools such as Muda, Kanban, or Gemba to identify bottlenecks and unnecessary motion, find the root cause, and resolve it before it becomes a bigger issue. The goal is to stay on track with SLAs, policies, and KPIs while applying a continuous improvement methodology.
You’ve delivered projects in three months that other companies might plan for a year. What gets cut from the usual planning process to make that timeline possible, and what risks do you accept in exchange?
I focus on the strategic view, liquidity, and timelines, then accelerate the approval cycle and budget process. This includes combining and eliminating unnecessary steps, such as placing bulk orders for small, repetitive items or supplying new items before common ones, while predicting potential risks by understanding business needs. This approach makes us more resilient and able to closely monitor progress. The accepted risks include extra workload, additional audits, and rework for exceptions outside standard operating procedures (SOPs).
Across FedEx, Supreme Foods, Al Romansiah, Delivery Hero, and Careem, the industries shift but the pattern of building and fixing systems repeats. Looking back at that pattern, what do you think it says about how performance management should work in fast-moving companies versus established ones?
In fast-moving companies like Delivery Hero, performance management is daily: live dashboards, fast feedback, and leaders act as expeditors who fix systems on the go. In established firms like FedEx, Supreme Foods, or Al Romansiah, it is more structured, with quarterly reviews, SOP-driven KPIs, and stability as the priority. The pattern shows that both continuously improve systems, but fast-moving companies prioritize speed over policy, while established companies follow policy to ensure stable outcomes.
Looking at everything you’ve built across these industries, what do you hope the next chapter of your career adds to that story, and what kind of mark do you want to leave on the strategy and performance management space going forward?
To lead in a strategic role, eliminate the operational mistakes I have seen in previous companies as a priority, scale business potential across my network and the companies I have worked for, and drive integration that adds real value to society. The mark I want to leave is creating alignment, empowering people at all levels, sharing knowledge and experience, and driving innovation that integrates with society and creates lasting value.
Many companies end up in a failure state because people believe it is due to poorly formulated strategies, when in fact many already possess decent-to-good strategies, yet fail to move the needle beyond the predispositions, processes, and priorities that served their past incarnation.
For example, a company may shift its strategic focus, but its KPIs reward old behaviour; its leaders declare transformation, but its middle managers still receive rewards based on old targets; it adopts new technologies while utilizing processes established for non-existent markets.
These contradictions slowly and imperceptibly build up over time, forming a phenomenon known as strategy debt.
In many ways, it is the equivalent of technical debt in software: the price organizations pay for the impact of previous, now-obsolete strategic decisions, inherited assumptions, legacy priorities, and previously resolved choices that continue to exert influence on their present state.
However, unlike the clearly identifiable problems in operations, strategy debt can lie hidden for many years. It may even happen that a business might encounter strange misgivings when implementing its new strategy because the old one simply never left the room.
As markets evolve and accelerate, strategy debt has emerged as one of the most significant and unrecognized hurdles to progress and execution. While businesses are unlikely to fall at a single catastrophic misstep, many suffer over time as their ability to adapt declines, even while they continue to optimize for the realities of the past.
Think of it like a car that slowly accrues one too many fittings & components that grind against each other. Just one won’t cause a crash; one hundred, however, start to become a significant livelihood problem. This is eerily similar for businesses, too!
This reality can be unsettlingly mundane: the staff are so accustomed to the competing priorities, overlapping processes, interminable alignment meetings, and initiatives no one seems to question anymore that it feels completely normal within the business.
The business still moves; it just moves slowly, weighed down by sluggish decision-making and languid initiatives, to the point where its very livelihood is endangered.
This introduces decision debt.
Every strategic decision is associated with assumptions made when it was initiated. As markets speed up, this timeframe shortens and assumptions quickly become obsolete, continuing to impact new realities in unintended ways unless reconsidered.
This results not in immediate collapse but incremental strategic dragging, and by the time the organization recognizes the issue, the debt has already compounded tenfold.
How Organizations Build Strategy Debt Over Time
Organizations do not normally set out to build strategy debt; quite the opposite, in many cases. Companies often attempt to foster stability and predictability by adhering to established procedures and objectives.
Traditional business strategy was once based on stable conditions. 5-year plans, annual forecasts, hierarchical structures, and fixed performance systems seemed logical in periods when market shifts were predictable and gradual.
Now, the business environment is drastically different.
Consumer behaviour changes rapidly, technologies can reshape entire industries overnight, competitive advantages erode at unprecedented speed, pivots can introduce completely new competitors where there were few before, yet many businesses still operate under strategies built for a more gradual, incremental landscape.
This marks the first noticeable layer of strategy debt: outdated assumptions and conditions become permanently embedded in an organization’s structure.
A KPI implemented three years prior, for instance, might still dictate behaviour today, despite significant shifts in the company’s business model. Similarly, a customer profile crafted earlier in development may continue to inform research, product iteration, sales, and marketing efforts, even though it no longer reflects the ideal target audience.
These inherited strategic choices gradually become ingrained in an organization’s DNA, amplifying decision debt.
Decision debt is the accumulation of past choices whose context is no longer relevant. The decisions themselves may have been sound at the time, but the organizational process for evaluating or challenging them has not evolved, leaving them in place beyond their useful lifecycle.
This can explain why some organizations appear highly dynamic and engaged yet produce minimal tangible progress. They are not failing to execute the strategy; however, the strategy they are executing may be obsolete.
The irony is that, more often than not, a company’s success makes it particularly susceptible to strategy debt. When a strategy is proven to be effective, companies naturally build systems around it: processes are optimized and standardized, key metrics are deeply ingrained, silos are segmented as expected, and entire departments are built to replicate success.
The more successful a company has been historically, the harder it is to challenge its underlying assumptions, particularly when it tries to transform. The barrier is not just implementing a new strategy; it is dismantling the influence of the old one, which is a far more difficult challenge.
The Silent Costs of Strategy Debt
One of the biggest misconceptions about strategy debt is that it’s limited to long-term, strategic discussions.
In reality, it can quickly become an operational problem: employees feel overwhelmed by competing priorities; managers can’t translate strategic intent into concrete actions; departments are unknowingly at cross-purposes while pursuing the same goals.
The organization is busy, but progress is slow, and strategy debt creates friction across the business.
1) One common symptom is initiative overload.
Companies accumulate more and more projects, frameworks, priorities, and transformation programs without retiring old ones. In other words, new strategic directions are piled on top of existing ones instead of replacing them. Employees are forced to build tomorrow’s company while also keeping yesterday’s business alive.
The result is a chronic strategic gridlock that functions in an unbalanced state.
2) A second symptom is decision paralysis.
When assumptions are no longer retired, organizations find themselves constantly complicating decision-making.
Employees spend a great deal of time seeking consensus on strategy because each department operates on a different strategic foundation. Sales might focus on revenue growth, product teams on retention, operations on efficiency, and leadership on innovation. Nothing here is wrong per se, at face value.
However, we now run into the problem that the organization has never explicitly identified which goals are most important in today’s environment and which are not.
As a result, we sit in a state of simulated agreement.
Middle managers feel this pressure the most. They are caught between dynamic leadership expectations and immobile operational systems tied to outdated strategies, and it’s often their job to deliver organizational change while maintaining expectations built on old strategies. The cumulative result is employee burnout.
Now, to be clear, this doesn’t happen because employees don’t want to change, but because they’re trying to balance many competing strategic identities.
3) A third symptom is quite an insidious problem: reinvention work.
We find ourselves rebuilding old processes, decisions, initiatives, methodologies, techniques, and systems because the original intent isn’t well-documented. Employees leave, institutional memory fades, procedures become bogged down in a muck of paperwork, and the organization is forced to play archeologist to recall why this system exists in the first place.
A surprisingly significant part of operational inefficiency comes from this.
Meetings take longer; action plans now sprawl over several months instead of weeks; decision-making requires more scrutiny; teams avoid risky actions because the underlying strategy is unclear.
Now the organization loses another critical factor: decision velocity, and in today’s markets, slow adaptation is more dangerous than an imperfect decision. A flawed decision can be recovered with agility; an organization slowed by accumulated strategy debt can’t.
Warning Signs Of An Organization Optimized For Yesterday’s Market
Strategy debt usually doesn’t reveal itself through dramatic pronouncements; instead, it’s a subtle process that becomes normal over time.
A) A clear indicator is repeated strategic discussions that don’t result in definitive decisions.
Leadership meetings are consistently stuck with the same questions and topics each quarter. Discussions don’t lead to clarity; they just keep going because the organization is stuck between its past assumptions and current realities.
B) “Zombie projects” are another warning sign.
These are projects that aren’t truly abandoned, nor are they properly completed; what’s more, they seldom truly become formally canceled. They linger in organizational consciousness and continue to drain time and resources because no one wants to be the one to finally pull the plug finally.
Companies with heavy strategy debt almost invariably suffer from an abundance of such projects.
C) Strategic language bloat becomes commonplace.
As strategy becomes less concrete, words like “digital transformation“, “customer-centricity,” and “innovation acceleration” become ubiquitous while being progressively less aligned with real work.
The more vague the actual strategy becomes, the more words people use to fake alignment. Employees are usually aware of this long before management.
D) A heavy reliance on historical best practices is yet another indicator.
The organization insists on evaluating new business opportunities against the conditions that applied in the past. Leaders still measure new opportunities against the same customer profiles and old assumptions that were effective in the past.
Rather than adapting its strategy to the market, the organization unconsciously tries to fit the market into its strategy. This is often where growth grinds to a halt.
E) Cultural implications also apply to strategy debt.
Risk-averse cultures often persist despite the organization’s claims to foster innovation. Employees become hesitant to challenge old processes because they are directly linked to historical success. “It’s always been done this way” becomes more than a bad habit. It becomes an instinct for self-preservation.
This can happen within companies that still claim to be agile and adaptive. The organization outwardly embodies the concept of change but structurally resembles stagnation.
F) A truly dangerous portent is when the strategy planning process itself becomes a performance.
Employees attend workshops without any real expectation of meaningful change. Strategy is observed as a ritual rather than enacted as a plan.
At that stage, strategy debt is no longer just a drain on execution. It is an erosion of trust, and once employees no longer believe that strategic change is possible, the organization’s ability to adapt will collapse from within.
How Organizations Can Cut Down Strategy Debt Before It Strangles Growth
This doesn’t mean organizations should stop thinking about the long term.
The company still needs direction, priorities, planning, and strategic intent. However, modern strategy demands an approach different from the rigid strategic planning models most organizations have inherited from a bygone era. The best-run organizations treat strategy as an iterative concept rather than a perpetual one.
Instead of presuming the original strategy will hold true in the long term, they establish mechanisms to continually reassess assumptions and update priorities as the business environment evolves. In other words, they actively manage down strategy debt.
One method is to conduct regular “strategy debt audits“.
I) The purpose is to examine all the major strategic decisions taken in the previous twelve to twenty-four months and pose one seemingly obvious question: “If I were taking this decision today, would I still do so?“
Few organizations take time to re-examine old decisions, unless an immediate crisis necessitates their review. This is a mistake that many managers simply glide over.
II) Another essential aspect is the segregation of actual strategy and inherited inertia.
Companies must identify which activities, reports, KPIs, and operational models continue to support current objectives, rather than those that persist because no one ever bothered to examine them. This, however, demands knowledgeable & charismatic leadership.
Letting go of past objectives can be difficult because organizations tend to imbue past strategies with emotional significance (especially if they were once effective). It makes sense – organizations are made of people, and people are emotional beings first and foremost who look to latch onto security reasons before speculative efforts.
However, failing to replace outdated systems generally incurs higher future costs.
III) Organizations should also normalize “kill lists” for strategies.
Just as businesses create roadmaps for launching new ventures, they should create specific lists of priorities that they will actively stop pursuing. Strategic subtraction can be as important as strategic addition.
IV) Preserving context is another crucial improvement.
Most organizations simply don’t document decisions sufficiently. They record outputs, not insights. Their successors end up inheriting conclusions without understanding how they were reached.
Understanding why a decision was made can often be more important than understanding what the decision was. After all, circumstances will eventually change, and organizations must retain the ability to challenge past logic rather than mindlessly follow past decisions.
V) Finally, organizations must embrace adaptive strategy execution.
The most resilient businesses today are not those that perfectly predicted the distant future. They are those who can adjust rapidly without causing organizational confusion. This means creating operational and mental flexibility.
Modern strategy is less about rigidly defined plans and more about building organizations that learn constantly. After all, the biggest strategic risk in today’s environment is not making the wrong decision; it is optimizing for decisions that have long since become ineffective.
Final Thoughts
The biggest danger of strategy debt is that it is usually not created by error.
The majority of strategy debt originates from perfectly logical, even effective and successful, decisions made in the past. That is what makes them dangerous. Companies tend to become emotionally attached to the strategies that made them succeed.
However, business markets change far more quickly than organizational inertia. In time, past strengths will inevitably turn into present weaknesses.
The most adaptive companies will not be those that were the most foresightful; they will be the companies most willing to challenge outdated assumptions and priorities, and to re-evaluate decisions when they no longer serve the purpose.
This requires a shift in the company culture. It involves a transition away from a fixed, immutable conception of strategy towards a more fluid, iterative learning process. It requires acknowledging that every strategy decision has a life span. Some expire rapidly; others last much longer. None should be permanently exempted from reassessment. After all, strategy debt compounds silently.
Initially, this appears as minor operational disruptions, shifting priorities, or a decline in velocity. Ultimately, it can evolve into a more pervasive issue, one in which the company can no longer adapt as quickly as its environment demands.
In today’s environment, the ability to adapt is not just a strategy; it is strategy itself.
Bridging the gap between strategy and execution requires more than intent—it requires the right frameworks and capabilities. Enroll in the Certified Strategy and Business Planning Professional and Practitioner program by The KPI Institute to learn how to align strategy, planning, and performance for meaningful organizational results.
