Pick two: (1) Delivery speed, (2) number of features, or (3) feature quality.

The realities of software development constrain optimization. We can never accomplish all three:

  1. Delivery speed: the velocity of shipping new features (which is different from the sprint velocity).
  2. Number of features: the product’s capabilities or components.
  3. Feature quality: features actually work as advertised, due to their design and their technical construction (which is different from whether the users will derive value from those features).

Here’s why you can’t get all three. At small companies, there’s never enough time or people to attain all three. …


TL;DR — copy this Google spreadsheet to report your range of error in 5 seconds.

If you consider a measurement of user behaviour to be just a “sample” of the true, or natural, user behaviour, then you can use some simple equations to produce a range of error for your measurements in each sample.

To interpret sample results with varying sample sizes, you need to report a margin of error to know if there is actually a difference between the sample results.

In product management analytics, we typically want to measure ranges of error on a proportions (i.e. percentages, rates)…


This is a co-authored blog post with my friend and fellow product manager Nikta Kanuka, who has published it on her blog.

The product manager role varies from one organization to the next. At some companies, in addition to identifying user and business problems, PM’s are expected to come up with solutions to those problems (or they take this task upon themselves). In other companies, this function lies squarely within the UX team’s ownership.

So — should PMs solely define problems? Or also solve those problems? …


This article is intended for people trying to develop the intuition behind the k-factor, and learning how to spot the bullshit.

When I started reading up on k-factor, I noticed most blog posts explicitly skipped the “technical” aspects of calculating viral growth.

In undergrad (physics and math), I became a huge believer that understanding actual math in derivations of equations is necessary to understand the concepts the equations describe. This is also part of my strongly held belief that only trained scientists should be setting government scientific policy, but anyway…

In other words, the “technical” parts matter.

So I’m going…

David Pardy

Toronto product person (Properly, Helpful, Intra Vires). ♥️ triathlon and huskies.

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