When Metrics Mislead

Engr. Elaine Macatangay Morales, MPA  |  23 July 2025

“If you can’t measure it, you can’t manage it.” That phrase is often quoted in quality circles, usually to stress the importance of data-driven decisions. But what happens when we can measure something, but measure the wrong thing?

The ISO 9001 standard, particularly Section 9, underscores the importance of monitoring, measurement, analysis, and evaluation to ensure that systems perform as intended. Metrics guide our decisions, signal whether objectives are being met, and highlight areas for improvement. But metrics are only as useful as their relevance, interpretation, and purpose. When poorly chosen or blindly followed, they can distort priorities and incentivize behavior that undermines the very goals they were meant to support.

Why Measure?

We measure for a reason. Metrics are not just numbers; they are answers to questions. Is the process efficient? Is the product effective? Are the goals being achieved?

Efficiency, for instance, is often measured as output over input—how much we accomplish with what we spend. If one manufacturing company reports a 90% energy conservation rate, that sounds impressive—until we ask: compared to what? The previous month? The same period last year? A five-year rolling average? The basis for comparison matters. A high percentage means little if the reference period was an outlier. Without a sound, reasonable baseline, even impressive-looking data can mislead.

Similarly, the rationale for selecting what to measure must be clear. If we’re tracking efficiency, we need to ensure that the inputs and outputs being measured actually reflect value. For example, spending less while achieving the same—or producing more with the same effort—might suggest efficiency. But that also depends on whether we're tracking what really matters, not just what's easiest to count.

When Metrics Are Misused

This principle applies across sectors. In public service, for example, performance is often tracked through the number of trainings conducted, reports completed, or targets “accomplished.” But those numbers can be misleading if they aren't linked to real outcomes. A government agency may claim success for holding a hundred stakeholder meetings, yet fail to show how those engagements shaped better policies, fostered inclusivity, or strengthened public trust.

Likewise, metrics like the “percentage of UPCAT (University of the Philippines College Admission Test) passers” are often used by academic institutions as a proxy for quality education. I once asked a school administrator why this particular metric was chosen. Their response: the UPCAT serves as a consistent benchmark because it is the only national entrance exam taken by nearly all their students, making it useful for comparing performance across cohorts. That may hold true for them, but it may not apply to all schools or systems. More importantly, pass rates alone don’t reveal how students were prepared, what kinds of support systems were in place, or whether teaching strategies aligned with deeper learning goals. Good data opens doors to inquiry. Shallow data closes them.

Metrics Must Be Analyzed

This is where analysis and evaluation matter. ISO 9001 encourages organizations not only to collect data but to analyze what it means. Are the results adequate? Do they show compliance, effectiveness, or risk? Is improvement necessary? If a laboratory uses a 1–5 scale to assess risk, the value means little unless someone interprets the score, acts on the insight, and works to reduce risk. Without that, the process becomes performative, njust another form filed and filed away.

Performative metrics are common in systems under pressure to “look good.” Reports are submitted on time, dashboards glow green, audit findings are “resolved”, yet no one checks if the improvements are real or meaningful. I've seen this firsthand: where deadlines are met but reports lack substance, where checklists are ticked but problems persist. Metrics meant to reflect progress become tools to maintain appearances.

Measure with Purpose

What’s the lesson here? Metrics are powerful, but they are not neutral. They shape how people behave. They reflect what an organization values and influence what gets improved, ignored, or overlooked. That’s why metrics must serve a clear purpose. They should be fit for purpose, based on sound references, and analyzed for insight, not just compliance.

This holds true for self-assessment, too. When we evaluate our own performance, what do we count? Hours worked? Emails read? Tasks completed? Meetings attended? Those may be easy to track, but do they reflect growth, purpose, or alignment with our values?

Metrics should prompt reflection. They should illuminate, not distort. And when used properly, they guide not only better systems, but better decisions—because the goal is not just to measure, but to learn, adjust, and act.

In the end, the question isn’t whether we should measure. It’s what and why. Because if we manage what we measure, then we must take care to measure wisely.