Musings on data

We all love data, and we all make data-driven decisions. – Or at least that’s what we say when someone asks us because “data-driven” is the thing you need to be these days if you want to be cool.

You can spend a LOT of time getting, tracking, analyzing, and reviewing data – but do you actually get value out of that time investment? Maybe, maybe not. In order to get a good ROI on your data investments, you need to be smart and deliberate about what data you look at.

When deciding what metrics you want to track and report on, it’s helpful to think about four key principles:

  1. Data that’s not actionable is just noise – If you measure something, but you cannot act on it, or you have no intention to make an effort to act on it, you’re only wasting your and everyone’s time. It was one of the first lessons I learned at Microsoft: don’t collect and present data unless it helps your case to drive action. Everything else is just noise. Always ask yourself what possible actions might be informed by measuring a specific data set. If you cannot come up with at least a high-level answer, you shouldn’t spend time collecting the data.
  2. Data that doesn’t track against a goal is useless – Assuming you have actionable data, you also need to understand what the ideal state should look like. If you have a metric but no goal to it, you miss the reference point. If that data changes, you have no way of knowing or telling whether that change is good or concerning. Likewise, you will not know whether you are in trouble or you have reached everything you aspired for. You must have a goal or desired end state to contextualize what you’re measuring.
  3. Show what matters, not how much you have – Tell a story when you show data. Don’t show all you have; show what matters and explain why it does. I have seen and learned that at Amazon: some folks took pride in showing pages and pages of data – a sea of numbers – but they failed to convey a message and drive action with the audience. While the story behind the data might be clear to you, it won’t be for your recipients. Analyze the data, understand what’s going on, then tell a story and have everyone focused on the relevant data to that story. Don’t show a sea of numbers, don’t try to show off by how much data you have.
  4. Proxy data is better than no data – Often enough, we care about a certain metric, but we cannot directly or efficiently measure it. Instead of throwing your hand in the air and giving up, think about proxy data. If you cannot measure the specific metric you really care about, what is a proxy metric that correlates with it? What can you measure that gives you a good indication as to whether the metric you really care about might be tracking in the right direction? If you don’t have precise numbers, how can you create approximations that give you at least directional insight? Amazon is big about proxy metrics, as many things they do are too new to have lots of data available. Looking at proxy data is just as good for making business decisions and necessary course corrections.

Do use data and do make data-driven decisions. However, make them based on a sound understanding of what good data means in the given context.


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Lessons from Amazon, a global pandemic, and other crazy times
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