When Visibility Backfires: What Not to Measure and Why
- RESTRAT Labs
- 2 days ago
- 12 min read
Updated: 10 hours ago
Measuring the wrong things can hurt your business. Metrics are meant to guide decisions, but poorly chosen ones lead to confusion, bad behavior, and wasted effort. Common mistakes include tracking irrelevant data, overloading dashboards, relying on outdated metrics, and failing to assign ownership. These issues distract teams and create inefficiency.
Here’s what you need to know:
Activity ≠ Results: Measuring effort instead of outcomes can lead to wasted resources, like running machines non-stop to increase utilization but creating unnecessary inventory.
Too Much Data: Overloaded dashboards bury useful insights under noise, making it hard to focus on what matters.
Lagging Indicators: Metrics that reflect past performance come too late to fix problems or guide proactive action.
No Accountability: Metrics without clear ownership become meaningless and often ignored.
To fix this, focus on metrics that directly inform decisions, use early indicators to catch issues sooner, and cut out measures that encourage gaming the system. Visibility should empower teams, not overwhelm them.
Six Common Metrics Mistakes - Julia Wester
Common Visibility Traps
When organizations set up measurement systems, the goal is usually to gain insight, ensure accountability, and track progress. Yet, as Jerry Z. Muller points out:
"The drive to institute metrics often arises from the best of intentions... But after decades of experience with the negative effects of metrics... we should be able to anticipate the recurrent flaws" [2].
These flaws appear across industries, from sprawling corporations to small studios. Recognizing these traps is crucial for creating systems that drive meaningful decisions. Below are four common pitfalls that can derail visibility efforts.
Tracking Activity Instead of Results
One of the most frequent mistakes is focusing on activity metrics that look productive but don’t actually tie to meaningful outcomes. Metrics like counts, hours, or utilization can shift attention away from core goals and toward the activities being measured - a classic example of misplaced priorities [2].
Take a manufacturing plant, for instance. If the focus is on machine utilization, managers might keep equipment running non-stop, unintentionally increasing inventory while slowing overall throughput. Similarly, a creative studio tracking billable hours might see designers inflate timesheets or avoid quick solutions that don’t rack up enough hours. Keith Hoskins summed it up well:
Metrics must have a clear, causal connection to the desired outcomes. Without this link, the system is ripe for manipulation, and the data becomes misleading.
Overloaded Dashboards
Dashboards packed with too many metrics often confuse more than they clarify. When managers face dozens of data points, it becomes hard to separate useful insights from irrelevant noise. This overload can lead to "strategy surrogation", where the dashboard itself feels like the goal rather than a tool to achieve it [3].
Michael Hammer captured this problem perfectly:
"Nobody wants a metric that they don't score 95 on" [1].
This often leads to the inclusion of vanity metrics - numbers designed to make performance look good rather than highlight real issues. For example, a revenue dashboard might focus on gross sales while glossing over shrinking profit margins, or a project tracker might celebrate task completion rates while ignoring bottlenecks that delay delivery. As a result, teams spend more time debating metrics than solving problems, while critical issues like customer churn or resource shortages remain hidden.
Lagging Indicators That Arrive Too Late
Metrics that only reflect past performance often leave teams reacting to problems when it’s already too late to fix them. Quarterly financial reports or annual reviews, for example, provide feedback only after the damage has been done [3]. By the time these numbers surface, opportunities for proactive adjustments are long gone.
Lagging indicators also fail as motivators. Annual bonuses tied to year-end performance are far less effective than frequent, actionable feedback. Without a clear link between daily actions and short-term results, decision-makers are forced to operate blindly, relying on outdated data. This lag can destabilize systems, as teams scramble to respond to signals that no longer reflect current conditions [3]. It also encourages gaming behaviors, where teams manipulate outdated metrics instead of addressing real issues.
For example, a small business might focus on monthly revenue totals while ignoring cash flow or sales pipeline health. By the time the owner notices a revenue dip, the sales pipeline may have been empty for weeks, making recovery slow and painful. Larger companies face similar challenges when project dashboards flag issues only after deadlines are missed and budgets are exceeded.
Metrics Without Clear Ownership
Metrics often fail when no one is responsible for acting on them. In these cases, data becomes background noise rather than a tool for decision-making. Managers may cherry-pick metrics to justify pre-existing decisions or ignore data that contradicts their priorities [3]. Without clear accountability, metrics lose their purpose and weaken the entire system.
This issue frequently stems from conflicting goals within an organization. When teams can’t agree on priorities, they tend to track everything, hoping to cover all bases. The result? Dashboards that satisfy no one and fail to guide meaningful action. These "window dressing" metrics stick around not because they’re useful, but because they’ve always been there.
Even worse, such metrics can foster selective use, where leaders highlight numbers that support their narrative and dismiss data that doesn’t. Over time, this erodes trust in the measurement system, making metrics feel like political tools rather than genuine aids for decision-making.
How to Design Visibility That Works
To avoid common pitfalls, design visibility systems where every metric has a purpose: to support clear, actionable decisions. The aim isn’t to measure more or less - it’s to measure with intention. Metrics without a direct link to decisions are just noise, cluttering dashboards without adding value.
Connect Each Metric to a Decision
Metrics only matter if they lead to decisions. Without a clear owner or purpose, they’re just static. Before adding a metric to any dashboard, ask yourself: What decision will this metric inform, and who is responsible for acting on it? If there’s no clear answer, it’s time to rethink its inclusion. As David Manheim explains:
"The choice of easy or convenient metrics should be intentional rather than a default caused by ignorance of the potential issues" [3].
This approach requires understanding the cause-and-effect relationship between what you’re measuring and the outcomes you’re aiming for. Take the example of New York City’s Compstat system in the late 1990s. By tying crime data to tactical decisions, police leaders could allocate resources to high-crime areas, making the data immediately actionable [2].
For an enterprise, this might mean tracking cycle time to identify teams that need capacity adjustments. A contractor might monitor job start delays to decide whether to reassign crews or renegotiate supplier timelines. In both cases, metrics serve as triggers for action - not decorative stats.
Before rolling out a metric, conduct a “pre-mortem”: think about how someone could manipulate it or focus on hitting the number without improving the real outcome [3]. If the metric can be gamed or doesn’t truly align with your goals, it’s better to revise or scrap it altogether.
Use Leading Signals, Not Just Lagging Indicators
Lagging indicators tell you what happened after the fact - useful but too late for immediate action. Leading signals, on the other hand, give you a glimpse of what’s coming, allowing you to intervene early. For instance, a quarterly revenue report is a lagging indicator. In contrast, weekly checks on your sales pipeline can highlight potential revenue issues before they become problems.
Research by Ethan S. Bernstein shows that too much focus on lagging metrics can actually hurt performance. Teams often prioritize looking good on paper over fixing the real issues [6].
For example, a product delivery team might track work-in-progress limits and blocked tasks instead of waiting for a drop in sprint velocity. Similarly, a small studio might monitor material delivery dates and crew availability to prevent missed deadlines. Leading signals allow you to act when the cost of intervention is still manageable.
Put Visibility Where Decisions Happen
Metrics lose their value if they’re locked away in reports that only leadership reviews. Visibility works best when it’s accessible to the people who need it to make decisions. This doesn’t mean eliminating high-level dashboards - it means making sure operational teams have the insights they need to act quickly.
Bernstein’s research on privacy zones highlights that teams perform better when they have room to experiment and adjust without feeling constantly monitored [6]. For enterprises, this might mean giving delivery teams direct access to metrics like capacity utilization, enabling them to adjust workloads without waiting for leadership approval. Contractors could provide crew leads with real-time updates on job sequencing and material availability, allowing them to address issues before they escalate.
By placing visibility where decisions are made, you empower teams to act swiftly, while leadership focuses on strategy rather than firefighting.
Remove Metrics That Cause Bad Behavior
Not all metrics are helpful - some can even harm your system by encouraging counterproductive behavior. Keith Hoskins warns that when a metric becomes a target, it often loses its effectiveness. If a metric encourages gaming, anxiety, or short-term thinking at the expense of overall progress, it’s time to remove it [3][4].
Vanity metrics are a prime example. As Michael Hammer once said:
"Nobody wants a metric that they don't score 95 on" [1].
Organizations often cling to metrics that make them look good but fail to address underlying issues. These metrics create a false sense of security and do little to drive meaningful change.
To identify harmful metrics, ask yourself: Are teams spending more time debating the metric than solving the problem? Are the numbers improving while customer satisfaction or quality declines? Are people gaming the system to hit targets without achieving real progress? If the answer is yes, the metric is likely broken.
Removing a metric isn’t always easy - teams may resist, fearing a loss of control. But as David Manheim points out:
"Naive application of metrics to a system can distort the system and even undermine the original goal" [5].
For enterprises, this might mean discarding metrics like individual utilization rates, which often discourage collaboration. For small businesses, it could mean dropping activity counts that distract from actual outcomes. By cutting out metrics that do more harm than good, you create space for the ones that truly drive progress.
Applying These Principles in Practice
Let’s break down how decision-driven visibility can be applied effectively in different organizational settings. The goal is to move away from overwhelming, metric-heavy reporting and focus on what truly matters: tracking what supports decisions, cutting out unnecessary noise, and making actionable insights readily available.
Enterprise: Improving Governance and Delivery
Large organizations often fall into the trap of "metric fixation", where dashboards overflow with data but fail to provide meaningful insights [2]. To counter this, enterprises need to streamline their metrics without losing sight of critical information.
One way to do this is through periodic metric audits. These reviews help determine whether a metric still offers valuable insight or has become a distraction - or worse, a target for manipulation. During these audits, running a "pre-mortem" exercise can help teams anticipate and address potential issues before they escalate.
Instead of relying on generic metrics, enterprises should use multidimensional indicators that reflect the complexity of their operations. For example, instead of focusing solely on velocity or throughput, metrics like work-in-progress limits, blocked task counts, and cycle time variability can provide a more balanced view. This approach reduces the risk of overemphasizing one metric at the expense of the bigger picture.
It’s also essential to map out a "theory of change" for each metric. For instance, if you’re tracking lines of code, clarify how this connects to software reliability. Without a clear link between the metric and the desired outcome, you risk measuring activity rather than results. This can lead to "strategy surrogation", where teams mistakenly prioritize hitting metric targets over achieving actual objectives.
Lastly, eliminate vanity metrics - those that look good on paper but fail to address deeper issues. While large organizations focus on refining complex dashboards, smaller businesses need a more straightforward approach.
SMB: Simplifying Visibility for Stability
For small and medium-sized businesses (SMBs), the challenge is different. They often lack the resources for advanced dashboards but can still fall into the trap of tracking too much data. The solution? Focus on simplicity that drives decisions without adding unnecessary overhead.
Start by identifying decision-focused metrics. For example, a residential contractor might track job start delays and material delivery schedules because these directly impact project timelines. Similarly, a service business could monitor appointment cancellations and technician availability to adjust operations in real time. These targeted metrics provide just enough insight to guide decisions without overwhelming the team.
Be wary of the "Cobra Effect" - where a metric or incentive unintentionally worsens the problem it’s meant to solve. For instance, tracking the number of jobs completed each week might push crews to rush, sacrificing quality for speed. Before introducing any metric, consider whether it could encourage counterproductive behavior. If so, rethink or scrap the metric altogether.
Another key principle is placing visibility where decisions happen. For example, give team leads access to real-time updates on job sequencing and bottlenecks. This allows them to make adjustments on the fly, reducing delays and improving workflow without waiting for top-down approvals.
Finally, set up regular checkpoints to ensure metrics remain relevant and aligned with your business goals. This helps prevent drift and keeps the focus on what truly matters. Whether for large enterprises or SMBs, aligning metrics with actionable decisions is the foundation for maintaining operational clarity and efficiency.
Conclusion
What Leaders Should Remember
Visibility isn't just a feature; it's a deliberate design choice that shapes how teams behave and make decisions. The difference between systems that empower and those that frustrate often boils down to whether metrics are designed to answer specific questions or merely populate dashboards.
W. Edwards Deming once said, "A system must be managed" [7]. When organizations react to every fluctuation as if it's a crisis, they create unnecessary stress and foster reactive management. The key is learning to separate the noise - routine variations that don't require action - from genuine signals that demand attention.
Effective visibility reduces stress by clarifying what truly matters. It ensures that decision-critical signals are available at the right time and place. Poor visibility, on the other hand, amplifies irrelevant noise, encourages gaming the system, and shifts focus away from meaningful work. As Jerry Z. Muller observed, "after decades of experience with the negative effects of metrics... we should be able to anticipate the recurrent flaws" [2]. These flaws include goal displacement, oversimplifying complex performance into misleading numbers, and substituting metrics for strategy.
The best systems treat metrics as tools to enhance - not replace - professional judgment [2]. For visibility to work, metrics must avoid punitive associations, involve teams in their design, and undergo regular checks to ensure they remain relevant.
The future of measurement will depend on leaders who embrace these principles and prioritize disciplined visibility design.
The Future of Measurement
As businesses become more data-driven and the ability to collect information improves, the challenge will shift from gathering data to designing systems that make that data meaningful. Organizations that succeed will focus on purpose-driven measurement rather than falling into the trap of "metric fixation" - the belief that measuring everything guarantees success [2]. Transparency alone doesn't equal performance, and in some cases, excessive visibility can even create more issues than it resolves.
Looking forward, the focus must shift from building elaborate dashboards or tracking endless data points to asking a simple question: Does this metric actually improve decision-making and execution, or does it just give the illusion of control? David Manheim cautions that "naive application of metrics to a system can distort the system and even undermine the original goal" [5].
The organizations that excel in this new era of measurement will be those that use visibility to anticipate and prevent problems, rather than just documenting failures after the fact. They'll design systems where metrics guide decisions without becoming the end goal, where signals arrive early enough to prompt action, and where the costs of measurement never outweigh the benefits. This level of discipline will be the hallmark of operational excellence.
FAQs
How do I tell if a metric is being gamed?
Metrics can be "gamed" when they push people to prioritize hitting specific targets over achieving the actual goals those metrics are meant to represent. For instance, you might notice this when there's an obsessive focus on meeting numbers instead of addressing real problems. Other signs include activity-based metrics that don't translate into meaningful outcomes or short-term gains that come at the expense of long-term success. Additionally, metrics that are unclear in guiding decisions or compete with one another for attention can easily be manipulated, making them less effective at driving smart, impactful choices.
What are good leading indicators for a small business?
Good leading indicators for a small business are like an early warning system - they provide signals that help you make timely decisions and address potential issues before they snowball. For example, keeping an eye on job counts, utilization rates, or new customer inquiries can reveal trends in workload and demand. Operational metrics like task completion times or the number of proposals sent can point out inefficiencies or bottlenecks in your processes.
The key is to focus on indicators that directly influence decisions. Avoid getting sidetracked by lagging metrics or activity stats that don’t lead to actionable insights. Instead, choose signals that help you stay proactive and keep your business running smoothly.
Who should own each metric on a dashboard?
Each metric on a dashboard should have a clear owner - whether that's an individual or a team - who is directly responsible for the decisions tied to that metric. When ownership is established, metrics become more relevant, actionable, and closely linked to decision-making processes. For instance, the sales team might oversee revenue-related metrics, while the operations team takes charge of job completion metrics. Defining ownership not only minimizes confusion but also helps prevent manipulation of data, ensures alignment between metrics and actions, and promotes accountability, leading to smoother workflows.
