As a product manager, my work involves using metrics to quantify assumptions. As product managers, we live in extremes. Optimistic when we envision and pessimistic when we plan. So grounding myself in data is but a second nature.

However if you think that this is only at work, you would be wrong. My family and friends can vouch that I take my madness well beyond work. Questions ranging from life choices to next Netflix recommendations are ripe for quantisation. They have suffered my queries, but in my opinion benefitted from getting the best answer from me.

The work that brings me joy usually involves numbers, measurement and data. In my defence, I grew up on a Math-Science fact based diet. Both my degrees were quantitative inclined too. So, when I chose to bring the concept of measurement into a discussion, it is not me bringing guns into a knife fight. It is rather levelling up the discussion field based on facts we could all agree ( or disagree on)

Here are the reasons why I think metrics are matter for all manners of conversations

1. Metrics enable shared understanding

You can arrive at consensus through many paths but having clarity on metrics is by far the quickest. Metrics enable you to have a viewpoint outside of your opinions. We hold on to our opinions with dear life, but we do not hold on our data with the same gusto. That is good, that is a learning mindset.

The formula for arriving at a decision is quite simple.

  • Unearth a shared context
  • Develop an common understanding
  • Reach consensus

When we discuss an issue it is important that we agree how to measure it, if we don’t now we are in the realm of politics. Most questions don’t have absolute answers. The right answer to most questions is “Well, It Depends”

2. Metrics enable focus

The right metrics help us focus to define and solve problems better. When you discuss the underlying data for an issue you don the hat of an observer and scientist. It gives you more manoeuvring room in discussions. Metric adds that critical dimension in defining your problem space.

A couple of months ago a friend asked for advice on a good camera to buy. The 5 Whys would have led me down an obvious path. Instead of talking megapixels, lens quality etc we took a different tack. We spoke about what excites him about photography. We spoke about time spent in differentiations stages of a photographers work flow. We did a little Marie Kondo exercise on which parts of the process bring him joy. I helped him frame the problem in Cycle time . Cycle time is the average time taken to complete a process. In this case the time between clicking a picture and sharing. It resonated with him.

This level of abstraction helps reduce analysis paralysis. Solutions are problems you encounter. The art is picking the one that solves the need at hand with minimal effort.

P.S: My friend now owns an iPhone and I no longer have to answer queries on cameras

3. Metrics enables nuanced thinking

Let us take an example of writing. You could measure your effectiveness as a writer in many different ways. Number of words written per day is one . It is a vain metric that has no nuance. It does not obsess about the end goal of why you write. You seldom write for volume but then why measure. Chasing such vain metrics can only bring you grief. At some point I will do a series of blog posts on how vanity metrics have ruined companies.

Instead we could focus on the whole system for writing . Inputs and outcome. Outcomes could be quality of feedback, how did the idea translate, leads generated. Inputs could be how writing consistency, ideas in pipeline, audience research. Hell, if you are still keen you could even add vain metrics like words per day but this time they have a lot more colour.

So adding the right metrics gives you a better nuanced appreciation of the problem. It enables you to develop a better sense of what you can and cannot control. It enables different viewpoints and opens you to lateral solutions. This gives more surface area for attacking the problem.

What is more critical is that data and metrics enable you to use different toolkits. You cannot solve a problem with the same thinking that caused it. Quantifying a problem opens up several avenues. You could use mental models, iteration and the exciting world of experimentation.

Conclusion

Data is not a crutch to rely on but rather an exoskeleton for your decision making framework. Thinking in metrics is a school of philosophy. It is the subtle art of asking the right questions. The answers are incidental and usually point to more questions. At the heart of data lies stories, stories that aren’t always obvious, stories that bring great joy to the observer. And I haven’t even begun talking about Algorithms.