Duck Tales: The performance review process at DuckDuckGo (Ep.47)

In this episode, Jeffrey (Operations) and Anne (People Ops) discuss how performance reviews work in a distributed leadership model, and how the process has scaled as we’ve grown.

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Jeffrey: Hello everyone, and welcome to Duck Tales, where we go behind the scenes at DuckDuckGo. We discuss the stories, technology, and the people that help build privacy tools for everyone. In each of these episodes you’ll hear from the employees about our vision, product updates, engineering, or things like approaches to AI.

Anne: There’s a lot of

Jeffrey: My name is Jeffrey and I’m on the internal efficiency team at DuckDuckGo.

Anne: Yeah,

Jeffrey: And today I’m joined with my colleague Anne. Anne, do you want to introduce yourself?

Anne: Hi, I’m Anne. I’m on the People Ops team at DuckDuckGo. It’s been about five years now, which I can’t believe, but lots of exciting stuff over that time.

Jeffrey: Great. Today we’re gonna be talking about our internal performance reviews and how we run them. And how would you describe our performance review process to someone who’s never heard of DuckDuckGo?

Anne: Well, I think the important thing to start with is sort of describing DuckDuckGo’s distributed leadership model, because with distributed leadership, that’s going to feed into performance reviews. And so the short answer I would give with that is that there’s no one decider of performance. There’s multiple different ways, multiple different people that give input, as well as a really strict requirement that it be evidence-based. And we’ll get into this a bit later, I’m sure. But we’ve done a lot of work on the evidence-based piece and being an asynchronous organization really helps with that because mostly everything is written down. So that’s that’s the high level that I would give.

Jeffrey: Who do we how do we decide what collaborators get involved with each person’s reviews?

Anne: Yeah, this has been a really interesting question over the years. And I would I would just love to brag a bit about how we used to do it when it was, you know, we were a smaller organization and then talk about how we’ve evolved that because well, I think way long ago it was the organization was small enough to just kind of know. You knew who should be giving input for who. And then the organization grew to the point where we needed help figuring out, right? You can’t one person couldn’t hold it all in their head.

And so you very generously helped us create an algorithm that put out a spreadsheet that basically it ingested information about people’s leadership relationships to one another, their work overlap with one another, and their experience giving feedback, among other things, calculated all of those relationships, also taking into account load.

Because you know, maybe one person should review 50 people, but that’s just too many, right? So balancing those trade-offs and then making a suggestion, which was really cool. And then those suggestions obviously had to be reviewed by humans and still, you know, load adjusted and everything. And there were several rounds of human review. So that was great. And then that also came to the point where we outgrew that because even those suggestions were gonna start fraying at a point, and the human review was cumbersome.

And so we’ve moved, I think quite naturally toward leaning on functional calibrators who are closer to the functional work and then pulling in the objective side of the house, which is sort of like where work is getting executed and having those be the default inputs for people. But yeah, that’s kind of how that’s changed over time. And it’s really, it’s been a really exciting problem, fun problem to be a part of.

Jeffrey: For the most part it’s scaled with as the company has grown and we’ve just had to make small changes here and there.

Anne: Yeah, I it’s as a people person, I also say, you know, people say how do we keep our culture as we grow? And this is similar to that where you say we don’t keep something, right? We s how do we scale something in accordance with our values as we grow? And then this I think would be a really good example of that in a really unique one too.

Jeffrey: Cool. What makes evaluating performance here different from a typical company?

Anne: Well, similar to what I said before, right? Distributed leadership means you have to figure out who it’s not like a managerial chain where the manager writes a performance review with peer feedback and then that gets approved by their manager and that gets approved. You know, it’s not a chain of approvals, it’s a collaborative process, which is also why that was one of the main reasons. There were several, but one of the bigger but bigger blockers for us purchasing performance review software from a company was that none of them had the functionality to have the level of collaboration that we have, like back and forth collaboration. And so there’s that. And then the real just like I said earlier, reliance on data. We are an asynchronous organization that really leverages processes in our project management tool, Asana, to fill the gaps of what a lot of live meetings would be. And I would imagine other Duck Tales have talked about no meeting Wednesdays, which is like for real. At other companies, it’s kind of in air quotes, but I would say here, not all of their companies to be clear, but oftentimes that can slip. But here it’s pretty, pretty legit. And so yeah, we’re generally meeting light, and so everything is in Asana, and you can pull that in to work summaries. And that’s also something you’ve been involved with, is really having a set of validated summary of work over the period of the year with links, right? So you can actually go and dig into the work over the course of the year as needed. And yeah, that’s the other thing I would really be I would say is is unique that the reliance on evidence and links and things you can actually see and look at and review is pretty high.

Jeffrey: Right. You touched on this a little bit, but can you go into how the process has scaled as we’ve grown? Or evolved.

Anne: Yeah, so yeah, that was one of the things is obviously sw figuring out how to fill those collaborative evaluator roles. Another is automation. We’ve really, you know, built our own system that integrates with where work gets done for us, which is Asana. And as a people operator, I feel blessed that I’m just given IT resources to be like, hey, you need this system to work. Here’s some really awesome skilled IT folks to help you make it a reality. And we have some really cool people on the team working to build our own performance review system that integrates exactly with where work happens for us. And so I’d say that is one that we’ve built that system and it’s evolved over time alongside other systems, right? So we have things like our daily asynchronous personal stand-up.

Right. So everybody does a stand-up for themselves every day and that gets recorded. And so then that can filter back into this whole performance review process because you have a record of what you were focused on every day. You have a record of the project you were focused on every week. You we have a whole summary of the relationships of your project advisory, career advisory, everything. You know, we’ve basically been automating more of these things to be centralized in a way that’s digestible for users. And those two things have really evolved together in in a way that’s pretty cool.

Jeffrey: I’m really proud of the our daily stand up we call our daily one must, but it’s been with us for a while now and it’s all asynchronous where people can fill it in in the morning and then everybody who needs to know can see what their stand up is. Cool.

Anne: Yeah, that’s the transparency part too, right? You can kinda go see what anyone’s working on at any time, which is pretty cool.

Jeffrey: How is this process suited for our remote asynchronous first culture?

Anne: Yeah, I mean I think similar to the things I’ve said before too, it’s it’s it fits the culture because for one, we have all of this substrate to work with, right? We have all of the the asynchronous culture is really reliant upon things being written down. And when things are written down, you can really shortcut a lot of the you know, forgetting what happened or whatever, or even just misremembering. And so you know, we have like bias checks that can happen on the data because the data are actually there, obviously all reviewed by people. But yeah, so it’s fit for us for that reason because of what you’re actually working with. And then the collaboration, too, is I think this is just part of asynchronous work in general. If you’re in a live meeting discussing something, it really just kind of depends on your processing speed in the moment for what you’re thinking and deciding on.

And we don’t make decisions as a general rule live. We can have discussions about them. Or maybe if it’s a really gnarly one, but generally decisions are happening in a really thought out way. And that’s the same thing with performance conversations, right? So it’s not just having a live debate about something in a calibration, right? You’re actually looking at, you’re having time to consider things and look at the actual evidence as opposed to just having a live conversation with all of its associated biases. So that’s that’s one thing I would I would say.

Jeffrey: Default to having things written down helps with the evidence. Yeah. What are the challenges with the process?

Anne: Yeah, I guess the flip side of having the everything written down is it’s not actually everything written down, right? Obviously, we still there’s a lot of that happens with like context and in a chat or in a live call. And we don’t want to over rotate on, well, if it wasn’t written down, then it didn’t happen. And that just relies on people’s judgment. And so that does rely on people actually taking the time to look at things and make those judgments. I think we have really smart capable people doing that. So it’s a challenge that just is something that they need to keep in mind. It’s not really something we’ve had to solve for necessarily. And then as we’ve grown, the question, you know, a lot of this is very time-intensive, right? There’s a lot of conversation around each of these pieces and a lot of consideration that goes into it. And then, you know, just the question organizationally is: how can we make this easier for everyone?

As much as you know, we all really value performance reviews and also it can be if you’re someone who has a lot to do, it’s a lot of work. We very much appreciate everyone who puts the work in because everyone cares about doing it well, and doing it well takes a lot of time. So that’s been a challenge for us is how can we keep the quality bar while, you know, making it easier and easier to do every time.

Jeffrey: Mm-hmm. It kinda leads into the last question of what our future plans are. Do you want to go into any of that?

Anne: Yeah, so high level. We’ve done a lot of work over the years to streamline, like I was talking about all of the data, and then it feeds into, you know, we have up to five different like categories of ratings. We call them professional dimensions. And we’ve done a lot of work to sort of categorize those things and how so to streamline the amount of work you have to do as someone who’s evaluating. And all of that work really we’re trying to take it to the next level of having that happen in a real focus time period rather than in combination with other work. And also, we used to give so well, I’ll finish that thought first, which is we’re going to move to a shorter cycle, which is going to be about three weeks. That’s the goal. Where everyone, we talked about our daily standup earlier, where ever if you have a task to do that day for the performance review, your daily stand-up will be write my self-reflection.

Everyone at the company writes it that day, and then they can move on to other things. So that it’s not this kind of organizational cost that’s dispersed across some time. And it also gives people the freedom to really focus on it that day because it is their one must. So you can really put all your attention there. And that follows through the rest of the process. The other piece is, you know, we are we used to do these annual, you know, shout-outs and focus areas, right? Which was the sort of written part of the review.

Sometimes they could be quite long, and that takes a lot of time to review, also. And as we thought about it scaling, and we’re just thinking also about scaling our career advisor function and coaching and you know, leveling up career advisors as we scale, which I think is a very normal company scaling thing, is our annual shout-outs and focus areas right for everyone? Like really, we shouldn’t just be doing this once a year. And of course, we should all be getting coaching conversations in an ongoing way. And so we’re actually building the process around ongoing coaching that happens in folks one-to-ones regularly as opposed to sort of having this heavy text written piece in the performance review. So that’s something we’re experimenting with. And I say experimenting with because everything at DuckDuckGo is an experiment and changes in response to evidence and how it’s going and the needs of the organization, but that’s what we’re looking at next.

Jeffrey: I’m really excited about the shorter time period for it and the focused week that it’ll be great.

Anne: Someone who was one of the highest loaded folks at the organization, I yeah, that you’d be very excited.

Jeffrey: Yeah. All right. I think that covers all of our topic today. Thanks for joining me, Anne. See y’all later.

Anne: Great to see you, Jeffrey. Bye.

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