Metrics

A recent text from a friend:

“Startups should know that their business is failing or succeeding before someone else has to tell them haha”

Good point, but how?

Plenty of ink has been spilled on metrics, KPIs, OKRs, and dozens of other derivations of ways to answer the question: “How are we doing?” or “Are we achieving our goals?” or… in bad cases… “What are our goals?”. Regardless of the types of metrics and goal-setting system that your company, nonprofit, or (if you’re a nerd like me) you personally use, there are several common principles to the best ones.

Input from coworkers. To be fair, I also care about sports.

Principle 1: Performance metrics vs. activity metrics

Simply: Performance metrics tell you whether you achieved your goals; Activity metrics tell you whether you did the things that should lead to achieving your goals.

For a basketball team, the number of points scored is a performance metric (contributing to the overall performance metric of “wins”). Activity metrics will vary depending on a team’s strategy, but might include the number of open three-point shots attempted. More basic activity metrics could include things like how many times particular offensive plays or defensive sets were practiced in a given week.

Lots of metrics!

For a sales team, revenue is a performance metric (THE performance metric). The number of outbound calls is an activity metric. So is the number of meetings held and proposals sent. Or maybe it’s the number of times a blog post is published if the team is pursuing an inbound strategy.

It’s also useful to think of the activity metric as the answer to the first question after reporting that the performance metric was missed or hit: “We didn’t score many points” would likely produce the question “How many open shots did you take?”.

Principle 2: The interrelated metrics stack

The above examples demonstrate how activity metrics build a “stack” that contributes to performance metrics. You should be able to do some math to estimate the performance metric tomorrow if you know the activity metric today. We have a good sense of who will win a game because we know who scores a lot of points.

It gets a little murkier in business and downright muddy in startups. You could be an amazingly hard-working sales team making calls day and night — just crushing your activity metrics — but it might not lead to revenue. Part of this is because you might just be bad at selling, but part of it is out of your control: What if the product isn’t that good?

This is where the interrelated-ness of the metrics stack becomes even more critical. We need metrics to know if the product is good so we know what to fix. For startups, this is especially true because a startup is, essentially, an experiment.

Trust is also important. The sales team needs to trust the product team to make something good, or at least trust that the feedback mechanisms they build will lead the product team to make something good. Metrics force teams to rely on each other.

Principle 3: The causal story

Since startups are an experiment, every startup needs a thesis. The thesis is the team’s belief about what it is that they do uniquely and metrics should be built from this thesis.

For example, where I work, we believe that a network of quality venture partners will contribute to outstanding returns for our fund. We have various theories on how this may happen, but the point is that if (1) our thesis is correct and (2) we achieve the goals contained within the metrics, we will win.

The thesis is, in a way, the part that is unaccounted for in the metrics. It is what we assume to be true.

This is also why some metrics might be more critical for certain teams than others: Certain basketball teams prioritize scoring more points to win and so will be more concerned with the number of open shots they get than the tenacity of their defense.

The upshot of this realization is that every metric should contain a causal story. In other words, you should be able to logically say “If we do x, we will be more likely to achieve our goal.” For example, “If we score more points, we will be more likely to win the game.”

Basically, a shot goes in or it doesn’t go in, it doesn’t change how we played. All it means is that it didn’t go in. — Brad Stevens

Ultimately, the key is to know that if you focus on hitting the metrics, results will take care of themselves. It’s easier to achieve big, difficult goals by hitting smaller ones incrementally.

What did I miss? What would you add?

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