SaaS Metrics: It’s never about the numbers. It’s what we make of them.

“This series is an attempt to unweave, with complete attention, the seemingly complicated and the seemingly obvious of SaaS Metrics, one post at a time.”

Somewhere, on a dashboard, or an excel sheet, a metric is locating a verb.

By statistical means, it has attempted to distill the past (what happened to the revenue?), in order to simplify and measure the mishmash of human behavior (what did they do with it?).

Now, in its quest to be useful, this metric, wants to reach someone.

Someone who can unpack what it means. Someone who knows that the metric is just a piece of information, a tool that’ll set alight candles at the table of questions.

Someone who understands the central precept of working with information, that – as David McCullough shared in a speech – the value of facts, figures, and the like depends on what we make of it.

Thus, the distance between insight and perplexity, owes its existence to how well this ‘someone’ tends to this ‘reach’.

It owes its existence to good judgment.

Good judgement – based on our constantly evolving understanding of biases, customer context, perspectives, mistakes, the sights seen from the shoulders of giants, and experience – is a virtue.

Whatever the metric is telling us (“Your MRR is $27,000”) hasn’t much to offer on its own.

It’s the knowledge with which it’s probed, (“What is the figure hiding? How do we know that this growth is sustainable?”) that leads to better outcomes.

When making decisions, we find ourselves suspended between two worlds – what we’ve always known, and what we know now.

In a letter, the team at MIT’s Endowment Fund, articulated the divide between these worlds with brilliance:

We noticed some years ago that much of the information we consumed was expiring knowledge. Examples of expiring knowledge might include: which cable company got acquired last week? How did manager X perform last year? What is the office vacancy rate in New York City?

While the answers to these questions represent useful context that could help us make decisions today, none have long-term value. In contrast, long-term knowledge might be represented by answers to questions such as: why is the cable industry consolidating? What is the competitive advantage of manager X and is it sustainable? What are the long-term drivers of demand for office space in various cities in the U.S.?

By deliberately tilting our time in favor of long-term knowledge and less towards expiring knowledge, we can slowly create a long-term advantage.

Expiring knowledge is all around (dashboards, daily reports, and notifications) us, finding its way towards the dark quarters of irrelevance.

Long-term knowledge, on the other hand, is rare. And as it arises from connections that occur when deep conversations, old books, and other timeless sources get together, it compounds with time.

The lesson isn’t to ignore the former, but to gauge its relevance for building the latter.

What emerges, then, as one looks at churn, revenues, or cash-flow, is an understanding of where this lone figure, a mere abstraction, fits the rhythms of how the world really works.

It’s never about the numbers (Warren Buffett gets it).

It’s what we make of them.

It’s who we are.

It occurs to one that what we habitually bill as our discoveries are but the projections of what we contain within upon the outside. That the physical reality of the world / nature / you-name-it is but a screen – or, if you like, a wall – with our own structural imperatives and regularities writ large or small upon it.
Joseph Brodsky