Modern business tools have unlocked a superpower that’s caused unexpected problems: the ability to “measure” just about everything. If it passes through a piece of software, people track it, graph it, color-code it, and stick it on an executive dashboard labeled with an obscure three-letter acronym.
Analysts build sprawling, multi-tabbed monuments to almighty data. Leaders look at them during business reviews, nod sagely, but go right back to running the business on gut instinct. The dashboards aren't broken because the data is wrong. They’re broken because we confuse capability with utility.
To fix it, every single data point needs to pass a simple, three-part test of three questions: Can we? Should we? Do we?
Deconstructing the Three Questions
“Can We?” is about Technical Capability. Do the tools, instrumentation, and data pipeline exist to capture this number accurately without requiring humans to type it into a spreadsheet? More importantly, is what’s captured objectively measurable, or is it really a subjective feeling?
“Should We?” is the domain of Strategic Relevance. Does this metric actually correlate to revenue growth, business health, or a desired strategic outcome?
“Do We?” maps to Operational Reality. Is this metric captured, reported on, and actively used by humans to drive day-to-day behavior?
Ideally, every metric satisfies all three with a resounding "Yes." But usually, companies stop at two of three, at best.
Three Dangerous “No’s”
When only two of the three criteria are met, data-driven decisions degrade into dysfunction.
1. Can + Do, but Shouldn't — The Vanity Metric
This is an alluring activity, yet it lacks strategic relevance. It happens when something is measured because it is easy to capture and to show activity.
Commercial Examples: Website clicks, raw emails sent, and volume of software features released.
The Reality: Marketing celebrates a 40% spike in web traffic. Sales management demands every SDR make 50 “touches” per day. Product releases new features twice quarterly. But a click is not a buyer, spam is not a conversation, and no one is demanding more “stuff” in the catalog.
The Dysfunction: Although the organization reviews these metrics constantly, no one dares question them. Marketing spends budget on clickbait traffic to inflate the charts. Sales reps automate mindless spam to hit their activity quotas. Engineers celebrate a growing repo. Meanwhile, actual revenue misses the goal entirely.
2. Can + Should, but Don't — The Blind Spot
This is when legitimate potential is defeated by human inertia. The technology is built, and the strategy requires it, but cross-functional friction keeps insights locked away in departmental silos.
A Commercial Example: Sales velocity broken down by Marketing lead source.
The Reality: Marketing and Sales constantly argue over lead quality, yet turf wars, system barriers, and dissimilar syntax make stitching the data together across platforms too difficult to muster.
The Dysfunction: Sales managers run their pipeline meetings out of old habits, focusing strictly on total deal value rather than likelihood of winning. Marketing stays siloed, optimizing for raw lead volume, not pipeline speed. The data is available, but it sits in the dark alone, detached from downstream impacts.
3. Should + Do, but Can't — The Illusion
This is the most dangerous combination of all. Leadership demands “data,” and the team delivers. But the underlying measurement is fundamentally broken, subjective, or downright wrong.
A Commercial Example: CRM Pipeline Forecasts and Customer "Health Scores".
The Reality: Executives look at pipeline dashboards every Monday to forecast future revenue, but the data inside the system is mostly a reflection of arm-twisting during the last funnel review.
The Dysfunction: Sales reps adjust deal stages to appease leaders before the weekend deadline, and Customer Health Scores are based entirely on subjective gut-feel check-ins rather than objective system usage metrics. The numbers are specific on an executive slide, but they are a total illusion. The quarter misses the mark again.
Data Utopia
To declutter commercial dashboards and get teams focused on what matters, take a hard look at the current reporting metrics and run them through the three questions:
If you can track it and do track it, but shouldn't—delete it. It's a Vanity Metric causing noise.
If you can and should, but don't—establish the process. Drag that Blind Spot into the light.
If you should track it and do track it, but can't do it accurately—stop the Illusion. Acknowledge it’s a fantasy, and let it go.
If you’re ready to transition your metrics from corporate noise into a clear dashboard, let's talk.