Why PMs Should Study Statistics: An Interactive Essay Marty Cagan – seasoned product manager and author of a book and blog that makes practically every recommended reading list for new product managers – says that there are two academic courses that “every product manager should take”: finance and computer science. In this interactive essay, I suggest we add another course to this list: statistics. A strong understanding of statistics facilitates three key responsibilities of product managment: understanding analytics, implementing cooprorate change, and making accurate forecasts.

Some thoughts on the moral implications of building habit-forming products I recently finished the book Hooked: How to build habit-forming products I challenged the author’s view on the moral permissibility of creating habit forming products here on medium (It was picked up by product coalition and selected by medium curators 🙌) and again as an interactive essay using idyll.

iPhone Q1 Revenue Forecast This is my first crack at making a forecast as a part of what I’m calling the “Cassandra Project.” The gist of the motivation for the project is that product management and entrepreneurship requires smart bets on the future and that you can’t get good at making smart bets on the future without practice. You can read more here. The forecast I’m making relates to this question: Will the percent change in iPhone revenue growth from Q1 2018 to Q1 2019 be greater than the percent change in revenue growth from Q4 2017 to Q4 2018?

Product managers have to make bets on the future. If you think for a few seconds about the types of risk that product managers are charged with managing, this becomes obvious. Product managers — as Marty Cagan points out — must manage risk around: value risk (whether customers will buy it or users will choose to use it) usability risk (whether users can figure out how to use it) feasibility risk (whether our engineers can build what we need with the time, skills and technology we have) business viability risk (whether this solution also works for the various aspects of our business) All of these require some betting on the future, but managing value risk and business viability risk in particular require forecasting that can be especially difficult to do.

If I had to pick a few words to describe Jessica Powell’s The Big Disruption they’d be the words “hilarious heresy.” “Hilarious” because the book is surprisingly funny. My wife actually kept commenting on how much I was chuckling as I read the book. “Heresy” because it’s a good way of capturing what Powell is doing in the book with all of her criticisms: she’s challenging the silicon valley gospel that tech companies are here to save the world, and given all of the attention and good will towards those companies, “heresy” feels like an appropriate label for this message.

Some problems with the impossibility of achieving OKRs In many ways, OKRs are a neat way of structuring goals for a company. According to Marty Cagan, product managers should be especially interested in OKRs as a goal setting framework since they are a better way of tracking product work than a “product roadmap.” I agree with Cagan. OKRs are often better than typical product road maps. However, there’s an aspect of OKRs that I think is morally and psychologically problematic: the idea that OKRs should be impossible to entirely achieve.

How The Lean Principle Became Profound There are certain books that are required reading for product managers. Eric Reis’ The Lean Startup and Marty Cagan’s Inspired both come to mind. They’re great books with lots of useful techniques and important ideas. Lately, however, the fact that these books are popular and useful has struck me as rather odd. If you take a step back from these books — and the many books, articles, talks, podcasts, etc.

How Startups Can Do Better Cohort Analyses If you’ve ever looked at analytics for software products, you’ve probably run across a graph that looks like this: Graphs like this one depict cohort analyses.1 This particular graph is from Google Analytics. Apple also has one for app analytics. So does Fabric.2 Cohort analyses can be very useful. For example, Eric Reis, in The Lean Startup, recounts how cohort analysis helped his startup realize that their efforts at improving their product weren’t working:

Meditation One Year Later This past November 26th marked my one year anniversary of the day I started meditating. I wanted to jot down some miscellaneous thoughts about the journey that I haven’t already covered in my posts about meditation, startups, and leadership or my post about meditation, addiction, and smart phones. Here I go. Improvement isn’t Perfectly Linear So it turns out that in spite of my goal to meditate every day this past year, I only actually managed to meditate ~ 273 out of 365 days (almost 75%).

“Good programmers are passionate about what they do” is basically a platitude in our industry. 🙄 On the whole, this may be true, but lately I’ve been interested in how our passion for programming might get in the way of us doing well for the companies we work for and may even lead to us being worse at programming specifically. 🤔 Here are some ways I think this passion can make us worse at what we do: