Likes How to Measure Anything.

Transcript context

…I can see why people come to you asking for advice on metrics because you have this framework of, "Here's the type of metrics you want." And then I think, and especially from an engineering team, there's going to be this like, "How do I optimize and make sure I'm doing the right thing and measuring the right things." For someone that wants to do this, and an hour long podcast isn't going to give them all the answers, what do you recommend they go read or go do or look at to help them figure that out? One, I hate to be this person, but I'll point to a few of my papers. I will say I write things down because I get asked them so often, and I want to make sure it is broadly applicable or broadly available, I guess. This SPACE paper, for sure. It's an ACM, and I think the year we published, it was the most read paper at ACMQueue. Yeah. So we tried to make it as readable as possible. So the SPACE paper is nice because it outlines this framework and it gives examples of metrics in every single category. And so hopefully people can look at this and they can [inaudible 00:38:54], "Okay, here's an example to use here, right. Here are some of the things that I could possibly use." And we're seeing that SPACE is being used lots and lots of different places. Another good one could be the paper that I mentioned with Mik Kersten, and it was about... we talked about using data from people and data from systems. We wrote it up in the DevOps context. I want to say this was written in 2016 or 2017 or something. But it helps you think through what types of data are good in which situations because you will never find yourself in a situation when you don't want both types of data. Even teams that I've worked with that are the most advanced. They have absolute instrumentation in every possible scenario. In the most detailed way, they will still survey their developers at least once a year because you can get new insights, right. One book that I love. It's a little dense, but it's really interesting that I love is How to Measure Anything. And it's by Hubbard, and there are parts of it that are real stats heavy, but he has this portion in the front that's in covering intangibles. So it's like, what happens when you don't have data? You have no data. You're starting from nothing. What are good ways to hunch data? And I really love that because he covers some really good ground there. Today's entire episode is brought to you by DX, a platform for measuring and improving developer productivity. DX is designed by the researchers behind frameworks such as DORA, SPACE, and DevX, including Nicole Forsgren, who is my guest for this very episode. If you've tried measuring developer productivity, you know that there are a lot of basic metrics out there and a lot of ways to do this wrong, and getting that full view of productivity is still really hard. DX tackles this problem by combining qualitative and quantitative insights based on the very research Nicole and her team have done, giving you full clarity into how your developers are doing. DX is used by both startups and Fortune 500 companies, including companies like Twilio, Amplitude, eBay, Brex, Toast, Pfizer, and Procter & Gamble. To learn more about DX and get a demo of their product, visit their website at getdx.com/lenny. That's getdx.com/lenny. You also mentioned offline that you might be working on a book that will answer a lot of these questions. Is that something you're up for chatting about?…

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