I’ve been reflecting on the idea of measurement—what we measure, why we measure it, and what it ultimately tells us. A patient I saw recently reminded me of this conundrum. She was fixated on a particular number, her AMH level, as if it were the sole indicator of her fertility potential. While AMH is a useful marker, it doesn’t tell the whole story. It’s a piece of a larger puzzle, much like how a single metric in a startup’s early data can be misleading.
In the world of angel investing, much like in the clinic, numbers can both illuminate and obscure the truth. I recall a founder I backed who was thrilled about hitting a certain user growth metric. Yet, when we dug deeper, it turned out that the impressive spike was due to a short-lived promotional campaign. The metric, while accurate, was not meaningful. It didn’t reflect sustainable growth or user engagement, just as an AMH level alone doesn’t determine a woman’s ability to conceive.
The urge to quantify is understandable. Numbers provide a sense of control, a semblance of certainty in a world that often feels unpredictable. But we must ask ourselves: what do these numbers truly represent? Are we measuring what matters, or are we clinging to convenient figures that offer false assurance?
Take, for example, the process of evaluating a new product in a startup. It’s tempting to rely on dashboards that spit out a slew of KPIs. But a small pilot needs more than just numbers; it requires clarity and context. We need to define what success looks like, who the product is reaching, and over what period we’re measuring its impact. Without these definitions, even the most accurate numbers can lead us astray.
Consider the case of Asha, a hypothetical startup focused on streamlining supply chain processes. For Asha, an activation event might mean a customer processing their first order batch. Yet, an account created is not equivalent to activation. Each metric answers a different question and helps us build a nuanced picture of the startup’s health.
Let’s put this into perspective with a hypothetical scenario: ten qualified business owners receive Asha’s offer; four decide to pay and use the service; three complete the setup, and of those, two go on to renew their subscription. If we were to simplistically state, “two-thirds of customers renewed,” we’d be misleading ourselves. It ignores the journey and the nuances of each step, much like how focusing solely on AMH levels oversimplifies the complexities of fertility.
When looking at renewal rates, we must consider timing. Did all customers reach the renewal date? Were there delays in starting? Labeling them as failures when their outcomes aren’t fully known is akin to writing off a patient before they’ve had the chance to complete their treatment journey.
In both medicine and investing, small numbers can skew perceptions dramatically. Reporting counts alongside rates provides a clearer picture. Presenting a small pilot as a reliable forecast for thousands of potential customers is a classic trap. These numbers should inform our next steps, not lock us into a false sense of security.
Additionally, we should track the quality of delivery. How many batches required corrections? Were there missed commitments? This type of data can reveal more about a product’s viability than a single growth metric. In the clinic, a similar principle applies: the quality of care and patient outcomes hold more weight than any single lab result.
In my experience, repeat use tells a compelling story. If a customer returns, it signifies trust and satisfaction. But we need to match our observation window to their natural cycle. A seasonal service should not be judged by daily activity, much like how fertility treatments require patience and an understanding of biological rhythms.
Comparisons are crucial. Groups that started simultaneously and received similar offers provide valuable insights. If a later group performs better, it’s vital to investigate what changed. Was it the customer mix, the level of support, or perhaps an improvement in the product itself? Improvement is encouraging, but we must be cautious in attributing causation.
In all of this, our metrics should fit on a single page—one that includes the funnel, customer outcomes, delivery effort, cash collected, and the next decision. If a metric doesn’t influence our actions, we must question its value.
In my practice, I’ve learned that measuring what truly matters requires us to go beyond convenient figures. It’s about understanding the story behind the numbers, much like how I strive to understand each patient’s unique journey. In the startup world, as in healthcare, the numbers are just the beginning. They prompt us to ask the right questions, to dig deeper, and to ultimately make informed decisions. It’s a lesson I’ve learned through years of experience, and one I continue to apply in every facet of my work.
Measurement should not be about validation but about exploration. It’s the compass, not the destination. Whether in the clinic or the boardroom, I’ve found that the most meaningful insights come from listening—to patients, to founders, and to the subtle cues that numbers might hide. This approach allows us to truly measure what matters and to navigate the complexities of both life and business with a clearer vision.
Part of the Building Frugal Startups: Lessons from the Trenches series — read the full guide.