Metrics didn’t grant self-knowledge, they quietly rewired it into numbers that never feel enough

There are plenty of useful things a metric can reveal. There are even more it can obscure or corrupt. And after well over a decade of tracking their own life in ever greater detail, the author lands on a blunt conclusion: the more they measured, the less they learned, and the worse they felt.

The story is not about a flashy tech breakthrough. It starts with a small, plastic, clip-on Fitbit that began counting steps in 2011. One number, simple enough to feel harmless. Then the “soft numerical nudge” worked, briefly, by turning a sedentary lifestyle into daily movement. But the goal slid fast. “6,000 daily steps” quickly turned into “10,000,” then “15,000,” and eventually settled at “20,000 for years.” That is the first revealed problem with metrics: they do not merely track your life, they change what you care about.

This is where the author’s own setup becomes a mirror for how organizations behave. They didn’t just stop at steps. They traded pedometers for heart-rate monitors, then smartwatches, sleep-tracking rings, and “an embarrassing number” of macronutrient-tabulating apps. Outside health and fitness, their journalism career coincided with the rise of social media and web analytics tools like Chartbeat, which promised to quantify harder-to-measure ideas such as “job success” and “impact” using page views, followers, retweets, likes, and other attentional metrics.

In theory, those numbers should add clarity. In practice, the author says that over the 10-plus years of tracking steps, active calories, sleep, story engagement time, stress levels, and more, they gained “virtually nothing” in terms of greater self-knowledge. The only “new learning,” they write, is that they liked to make numbers go up and down. And the second-order consequence was darker: the swirl of data did not lend meaning or insight to how they relate to themselves, their work, or the important people in their life. Instead, “the more personal” the tracking became, the worse they felt about pretty much everything.

The author then articulates two lessons that translate directly into how boards, investors, and exec teams build incentive systems. First: whatever the amount of data you are collecting right now, it will never feel sufficient. There is always a new metric around the corner, a better way to remix readings, or a more “accurate” measure of what is important. They list examples from personal tracking, including heart-rate variability, daily stress, exercise “readiness,” and cardiovascular or “fitness” ages. Measurement begets more measurement, and the pipeline of “better metrics” keeps running.

Second: when your original goals are nuanced, metrics push you toward simplified proxies and ranks. The author gives the pattern: if you want to become a better journalist, page views and leaderboards offer a convenient proxy for success; if you want to improve at cooking, foodie metrics steer you toward recipes with longer ingredient lists. The trap is powerful because it feels objective, but it usually replaces the messy reality of value with whatever is easiest to score. This phenomenon has a name in the book discussed in the piece: C. Thi Nguyen’s The Score: How to Stop Playing Somebody Else’s Game (Penguin Press, 2026). Nguyen calls it “value capture,” where you adopt external sources of measurement and then let them rule you without adapting them to suit your life.

The author quotes Nguyen directly: “In value capture, you’re essentially outsourcing your values.” And that outsourcing shows up as outsourcing the process of figuring out your own sense of meaning. The author’s personal example is simple but revealing: their walks shifted from feeling meditative to prioritizing miles. When the metric becomes the mission, the original goal can quietly disappear while the scoreboard keeps looking “productive.”

Importantly, the piece argues that value capture is not just personal. The author writes that individuals, institutions, and even entire societies can fall prey to the same dynamic, and that it appears everywhere, including journalism, education, business, food, hobbies, and health tracking. Nguyen’s restaurant example illustrates the mechanism: a restaurant stops caring about making good food and starts caring about maximizing its Yelp ratings. The same logic is applied to education through GPA. Scientists can start caring about getting the biggest grants rather than finding truth. Even religion gets pulled in, through an internal leaderboard.

The author adds a concrete anecdote: a pastor told them their church became obsessed with baptism rates. Leaders set up an internal leaderboard where pastors competed on monthly baptism rates, and it started dominating attention. This is exactly what metric escalation does when it meets institutional power. A metric meant to reflect impact becomes the competition platform, and the organization starts optimizing for the measurement itself.

For decision-makers, the strategic stakes are the part that should land hardest. If metrics are constantly revised, if “sufficient” data is always out of reach, and if proxies slowly replace nuanced goals, then every dashboard update can become a governance shift. Boards and leaders should assume that incentives will shape behavior, not just report it. The author’s decade of self-tracking is personal, but the lesson is structural: when you let external rankings set what is important for you, you also outsource your meaning. That is the recurring failure mode, and it is why metric-driven strategies often look rigorous while they quietly degrade what they claim to improve.