When I worked at Facebook, the Workplace analytics team had a cool tradition: The team’s weekly meetings always started with a small data quiz.
The winner of the previous week’s competition would prepare a question about the product’s key metrics. For example, “what was last month’s MAU?” or “how many new users joined last week?” or “what proportion of the new companies reach 10 users?” or “what was last month’s revenue?” The question had one requirement: Its answer had to be found on the team’s dashboard.
The participants were to write down the answer without getting help from computers, which meant we could only use our memory to do so. The person whose answer was closest to the correct number got +1 point in the chart, and the person who was the farthest lost 1 point. Every six months, a winner was chosen and the game started again.
I participated in five seasons and won three of them. In one of the final rounds, I was tied with another analyst. The team arranged the final round, where we had to answer five questions in a blitz quiz. I managed to score the winning point and won the mug that you see in the photo below.
I told this story not because I wanted to brag about winning the quiz (well, this too, to be honest). In almost every quiz, the respondents’ guesses on metrics were distributed across a wide range, which I found surprising.
Why? Well, first of all, it was the analysts who played the game. They were the people who worked with data most of their time and should have been good at navigating it. Second, these analysts were working at Facebook, a company that has a very advanced and strong data culture. At Facebook, each team has clear goals, dashboards are available to all the company’s employees, and all meetings start with progress updates on key metrics. How could these people be so wrong in answering questions about the product they were working on?
If you decide to play this game with your company’s employees, you will most likely be as surprised as I was. It will turn out that most people have very vague ideas about the key metrics of your product and business. And some people will have no idea at all.
In this essay, we will discuss why it is important for team members to remember at least approximate values of the key product metrics, why this usually doesn’t happen, and how to get there.
P.S. If you want to learn how data can help you build and grow products, take a look at GoPractice! Simulator.
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