Measure developer productivity using the SPACE framework

In this episode, Dr. Margaret-Anne Storey explains how to use the SPACE framework to reason about developer productivity.

We also talk about:
  • The SPACE framework, which focuses on giving a well-rounded understanding of developer productivity
  • How to use and not use productivity metrics for software developer
  • Developer experience as a different mindset to improve developer performance
Dr. Margaret-Anne Storey
About Dr. Maragaret-Anne Storey
Dr. Storey is a Professor of Computer Science at the University of Victoria and a distinguished expert in empirical software engineering. She is also the co-author of the SPACE productivity framework.
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Read the whole episode "Measuring Developer Productivity" (Transcript)

[00:00:00] Dr. Michaela Greiler: ( intro music ) Hello and welcome to the Software Engineering Unlocked podcast. I'm your host, Dr. Michaela. And today I have the pleasure to talk to Dr. Margaret-Anne Storey. But, before I start, let me tell you one of my main goals for 20022. Making the SE Unlocked podcast the best podcast you listen to. I want to eagerly await every single episode. I have a few ideas how to achieve that, but, of course, most valuable input come directly from you. Therefore, I would love if you can spend three minutes to tell me how you like these episodes, and which topic you are most interested in. Just write me on twitter. My handle is se_unlocked. Or, fill in the little survey linked in the show notes(??). It would really mean a lot to me.

[00:00:51] So, now back to Dr. Margaret-Anne Storey. Dr. Storey is a professor of computer science at the University of Victoria and a distinguished expert in the field of empirical software engineering.I had to pleasure to work with Dr. Storey on many occasions. Even this year, she joined me during a research I led on developer experience, looking at what makes developers happy and productive and leads them to stay longer and more engaged in their job. Today, I have her here to tell us more about developer productivity and, especially, I want to know how can we measure it? How can we improve it? And so I'm super happy to have Dr. Story or Margaret-Anne, or actually Peggy, how friends call you. Here on my show. Peggy, Welcome to the show.

[00:01:39] Dr. Margaret-Anne Storey: Thank you very much, Michaela. It's great to be here.

[00:01:40] Dr. Michaela Greiler: In the last episode, I talked about my perspective on developer experience and developer productivity, and well sort of, there was a little bit of a conclusion, bottom line, which is that I think organizations and teams should stay right away from focusing on measuring developer productivity and more think about developer experience. This means like, how do the developers feel about their work? Are they feeling productive or are they happy? Do they feel that they make progress? Are they bothered by some tools and so on? But what is your take on measuring productivity?

[00:02:17] I know you did a lot of studies there, so you have a lot of expertise. What do you think?

[00:02:22] Dr. Margaret-Anne Storey: All of my researches that I've done over the last few years has really pointed toward taking a lot of effort and understanding what you mean by productivity before you try to measure it. So what does productivity mean to you? I know that in your last podcast, you mentioned the space framework, and that is the summary of a lot of years of research that shows that, that there are many different dimensions to productivity.

[00:02:47] To some people it's about pull requests, or lines of code they committed, or features delivered to the customer, or ability to be able to learn something new, or help other people. You can't just say that there's just one way to understand productivity or define it. There's many different ways and, consequently, there's different ways of measuring it as well.

[00:03:08] It's interesting to say that we shouldn't measure productivity, but the fact is a lot of companies will still try to do that. And I think a lot of developers also try to think about how productive am I being? Am I being as productive as I think? I really like this pivot towards thinking about developer experience, which is what we worked on together.

[00:03:31] And you invited me to join that wonderful project that you've worked on. And I loved that because a lot of my earlier research really distinguished developer satisfaction from developer productivity; They're definitely related, so more satisfied, happier developers will be more productive and feel more productive and vice versa.

[00:03:49] But there is this difference. Developer productivity mean to me really is about measuring what they do, right? Or how they do it. The amount of work that they were able to do, or the amount of value that they provide, whereas developer satisfaction or developer experience is more how they feel.

[00:04:02] And those are two quite different things. So I really like that nuanced change that you brought to that through developer framework.

[00:04:12] Dr. Michaela Greiler: You brought up two things, which I think are also in my opinion, two extreme different things, which is the things that they do and the value that those things bring. I thought about this, especially in my entrepreneurial journey, it even impacts me much more, so that everything that I do should also lead to impact and have impact and have value.

[00:04:42] Sometimes I see in literature that it's productivity versus performance, where performance is a little bit more output oriented. But even there, I think it's really hard to grasp. So, what is productivity? In my last podcast, I was comparing it to the industrial age where we really have off producing something which comes back to lines of code, and impact has nothing to do with lines of code.

[00:05:01] You can have one line of code. It can have a huge impact. It can be a drastic bug, or it can be a line of code that really is such a satisfying thing for the customer. I think there are really a lot of nuances, and I wonder, people very often, I see them measuring productivity because it's the easier metric. I actually really liked the SPACE framework. I'm super inspired by it, but I'm also a little bit skeptical on the metrics side of it. I think it's so great to have it as a mental model to think about productivity in all those different variations. But then on the end, we have like these metrics that are very isolated, and then we try to stick them together.

[00:05:40] As I understand it, Right? You're the expert here. So I'm happy to hear much more about that, but so we should have different dimensions and take at least three or something. But then in the end, we were taking very different metrics, and how are we going to combine them? What will the combination tell us?

[00:06:07] Can we even interpret it? So these are all questions that are racing up in my head. What do you think about that?

[00:06:13] Dr. Margaret-Anne Storey: I'm not a fan of developing a lot of metrics, honestly. Let me just maybe step back a little bit and just remind our listeners what the SPACE framework is about in case they didn't get to listen to your last podcast, which, by the way, was great. I loved your discussion. SPACE framework is very much an overarching framework to think about different dimensions of developer productivity. The goal behind it wasn't so much defining metrics, but just thinking about when we talk about productivity, what are the dimensions about productivity that we may mean, or other people may mean. So SPACE is an acronym, and the first letter is S, and that stands for developer satisfaction and wellbeing. If we think about understanding developer productivity or improving developer productivity, if we make some change, say to improve developers productivity, we need to think about the impact of that change on developer satisfaction and developer wellbeing. The second one is P, which is performance. So performance are the outcomes or the quality of the work that you're doing. And again, what performance means really varies from developer to developer, engineer to engineer, or managers. They all have different views about those performance outcomes that they care about.

[00:07:31] And the last three dimensions, the A is for activity, which is what a lot of people think about when they think about development productivity. They think about lines of code. They think about pull requests. They think about features that are delivered to the customer. So that's kind of the typical one that developers tend to think about when you ask them about developer productivity. C is communication and collaboration. In the research that I did with now, thousands of different engineers, when you ask them, what does being productive mean to them?

[00:08:03] For many, they say it's about collaborating with others. How well I helped others and how well I collaborated with others. And that's not surprising because software development is such a collaborative activity. You don't write code by yourself anymore. And then finally, E, which you also touched on, is how efficient I can be. My ability to be able to get my work done without a lot of interruptions and my ability to get in that very pleasant flow state, so that I really feel immersed in the work that I'm doing. The work that I'm doing isn't so challenging that I feel overwhelmed, but it's at that sweet spot of being challenging enough that I feel that it's very rewarding.

[00:08:38] Arty Starr also talks about flow in her book called Flow about software development and talks about the joy of development, which relates again to that experience and developer satisfaction. The SPACE framework, honestly, is very high level because it impacts all of those things, right? It impacts how developers feel, their satisfaction, and their wellbeing, the performance, the quality, the outcomes of the project that you're working on, or the tasks that you're doing. And then it also looks at the activities that you do and then how you collaborate with others. And then that efficiency and flow part, which again, relates into satisfaction and has an impact on performance.

[00:09:16] So these dimensions, they're not stand alone dimensions. Maybe you make a change that makes developers feel more satisfied, and their wellbeing goes up. So, for example, you make a change that allows developers to spend one day a week learning something new.

[00:09:29] That could have an impact on their ability to collaborate with others. If they don't all work on that same day, they won't hear back from others, and it might have an impact on their activity, at least in the short term. So you have to think about these together. In the SPACE framework paper that we wrote about, we spent a lot of time talking about these different dimensions and the fact that there are these different metrics. None of us, I think, really believes that, okay, take SPACE, choose three dimensions, and then choose three metrics, and you're done. That's not really the best way to use it. However, doing that would be better than choosing one metric.

[00:10:11] The benefit from SPACE comes is thinking about these different dimensions and thinking about what is it we understand about these different dimensions. What do you and I understand about activity, and what that means to have more outputs. When I say software quality, what does that mean to you? What does it mean to my peers on my team? What does it mean to my manager? What does it mean to my manager's manager? And when I say that I'm spending a lot of time collaborating, what does that mean to you? And what does that mean to other people? And so on. So really, thinking about those different dimensions, realizing that any change in one is going to have an impact on the other dimensions and coming back continuously to reflect on those and to reflect on how do we each think about these and how do we each think these will be affected, if we do make a change to try to improve overall.

[00:11:01] Dr. Michaela Greiler: One thing that came up also in the developer experience work that we did is this idea of between short-term and long-term. And I think, especially in measurements, are falling short in that regard, right? With your example where you have wellbeing coming or going up because they're spending one day learning, and then two other dimensions going down because now they have less overlap for the collaboration, and they are writing less pull requests or lines of code. There's also another dimension, which would be maybe learning right? And learning then in terms of what's actually the performance of the engineers? Do they create better things? maybe they are inspired and all this becomes really intangible. How do we measure it? Is it happening right now? Maybe it's happening. We see this. If you measure the things, wellbeing, let's say we have a survey and we ask people and we see well-being goes up, then we see from Git, well, the commits go down. We see maybe collaboration overlaps go down. We can measure that as well, but what's really hard to measure here is that, maybe somebody has an innovative idea. Or maybe somebody had this idea and learned something, and this saved us from a bug or created the more maintainable software system because of the things that they learned here.

[00:12:17] This is a little bit my critique point here, and I really like your stand on it. It's just a mental model to help get all these different dimensions a little bit more organized, because there are so many things floating around. So this helps us looking at the SPACE framework.

[00:12:35] We can at least go through some of the dimension, and we're not measuring it, but we make a thought experiment like I did right now and say we have a very strong feeling that, in the long run, our engineers will be more innovative. We'll be up to date. They will learn. They will maybe stay longer with us. I know that for every job that I was stuck, where I felt like I'm not learning, I was very unhappy. And I think a lot of engineers are like this, they want to learn. So, I think maybe it's a nice mental model to think around those things.

[00:13:10] Dr. Margaret-Anne Storey: That's a really good summary. I'm going to just mention some of the more recent works that I did with Brian Hopkin and Tom Zimmerman, where we looked at alignment between different developers and their managers, in terms of how they define productivity.

[00:13:24] And we also ask them how they define software quality, and what we found is that there are many, many different views of what productivity and software quality mean. If you're saying to somebody, should we use this new tool? Should we allow engineers to spend time learning?

[00:13:40] You have to unpack what are all of your assumptions about what the impact of that change will be on developer experience or the quality of the product, whether it's in the short or long-term, and literally expose all of those assumptions, but also expose what it is that you don't know.

[00:14:0] If we make this change or introduce this new tool, what are the things that we need more information about? And often enough, I've sat in on a lot of meetings, and people are using terms like productivity and quality, and it's clear that they don't even mean the same thing. And yet, they're in these meetings trying to make decisions, and these decisions are very strategic, and the decisions are often made without really unpacking.

[00:14:26] We have comfort when we have signals of what's going on, but software development is a very complex sociotechnical activity, and you can't reduce it to these very simple metrics.

[00:14:39] This came out in the work that we did too, Michaela, but not everybody's the same, right? Some engineers might be happy not knowing what the impact is, and they may be happy helping the people around them. And that's what they really care about: I helped four people today.

[00:14:55] I've worked with people like that. They're not egocentric at all, and they're less focused on understanding the vision. They're happy to help the people around them. There's no single way to measure this, even if we use surveys as well.

[00:15:08] Dr. Michaela Greiler: There's so many good things that you just said that I want to touch upon. Why are organizations striving for measurements? The higher up, the more we want some tools. We want to understand the world. And I think it's this idea of models of abstractions, because it's just too hard to grasp. So if you are the team lead, and you have five engineers, you probably have a really good idea of how things are going.

[00:15:30] Are we productive? Are we performing? And so on. If you then the manager of managers, and you have a team of 50, I think it's really hard to understand everywhere. Are we doing good? If you have an organization of 500 engineers, it's like, I'm flying blind, right? I'm still really, really skeptical about building a model, which is so abstract that every model is wrong that it doesn't reflect the reality.

[00:15:55] And it doesn't really help us. And I like what you said about, there are things that we know, but there are unknown unknowns? We don't even know what we don't know. And I think a lot of our activities in engineering or some of the else is about the unknown unknowns.

[00:16:10] We have to make decisions with the information that we have right now, to the best of our ability, and I'm really wondering if those metrics. If they're helpful? Or is it just that we feel that it's helpful? Maybe it's, I think it's maybe helpful for somebody that has some agenda, right?

[00:16:26] So they want to come up and now to make the metrics look great. And it's, again, this short-term vision of, oh, I want to Excel here, I want to be the VP of engineering here, so I make this because it's easy, right? And even if you have five or six or seven metrics, we can tune them.

[00:16:47] We know that, we can make people respond to it. We can't show that this is really the outcome that we strive for long-term, but it enables us, maybe, for some hidden agenda that's more personal than what we are actually going for this main goals. What's your perspective on that?

[00:17:05] Dr. Margaret-Anne Storey: I think that a lot of organizations use metrics because it helps have a handle on complexity. If I can somehow measure what's going on, then I can have confidence that the decisions that I made last week or last month or a year ago were the right decisions. Or I might get data back that indicates that those decisions were not right and that we need to make a change. Good managers know that there isn't just one metric. They'll know that there's a host of metrics. And I think really good managers and really good leaders will also listen and ask the right questions to find out more nuances, more deeper understanding about what those metrics mean.

[00:17:45] I'm not saying don't use metrics. Use metrics and also have rich insights and be continually reflecting and revisiting your assumptions and thinking about what are are your goals.

[00:17:57] Are our goals to sell more of our products? Well, yes. Right? Because we need the money to be able to make sure that our developers are well paid, but once we've done that, what else are our goals? Is it to improve the culture so that when people come to work, they feel secure? And they feel safe and happy and they have psychological safety?

[00:18:16] Is our goal to retain our really best talent over the long-term? And how will we do that? Understanding those goals and then understanding which of these metrics from a whole different set of possible metrics, I think is one thing to do, but really looking at what do our metrics tell us.

[00:18:35] But what do they also allied, right? What do they hide? What are they wrong about? What is our data gathering? What is our data not gathering? Every time we define a metric, what risk are we introducing by using it? And what else do we need to gather? Maybe some stories or insights to give us that full picture.

[00:18:56] That's why I think the SPACE framework is quite powerful, because it helps us kind of identify a whole set of things that we need to ask questions about and that we need to listen to those answers, to be able to make better decisions in the future and make change.

[00:19:12] Whether it's change to address a problem or change to make some kind of improvement. There's a lot of different things to consider, and it's an attempt to get people to slow down and not to rush, to define metrics and then create a dashboard and then look at it once a week and say, look, our numbers have gone up...Wait a minute, what's happening behind the scenes here?

[00:19:31] Dr. Michaela Greiler: So what comes to my mind when you talk about that is the goal question metrics framework.(??) And it's a little bit of a different approach. I always say, do not measure productivity. You know what I mean by that is in this very simplified way. I think the data is so, so powerful, and I think those things are two very separate areas. The critique that I have for how people use it is that they are creating metrics, but they're not data driven. I always felt this connection because you had the same thought about data-driven investigations and researches, which is we combine qualitative with quantitative. I personally really think that the only in combination, they become powerful.

[00:20:19] I think that only qualitative isn't as powerful, only quantitative can be extremely misleading. This is the metrics area that I'm talking about in the critiquing so strongly. But I think that if we combine them, this can be extremely powerful.

[00:20:34] In industry, it hasn't really landed. It's also quite complex to combine that to have mixed research approaches. And behind the research approach, there is also a hypothesis, questions that have to be tackled, and so on.

[00:20:48] I'm consulting organizations, where we look at their data, because I think it's so powerful, and it can help us guide and make decisions in this very complex world. But I'm always missing this qualitative aspect that we actually go and say, what does this mean? And so coming back to code reviews, it's turnaround time, is on one hand super interesting metrics. On the other hand, it's completely meaningless. If I take it as face value, if I built a dashboard and I'm printing out turnaround time there, it's maybe meaningful for the first week. It only becomes meaningful, if I do the qualitative work, which means that now I'm digging deep, and I'm trying to understand what's happening here. Why I'm seeing this number? Is this even a number that I should take at face value?

[00:21:36] Dr. Michaela Greiler: Probably not. Most of the time not. And I wonder how can we bring that to industry? How can it be applicable and manageable for industry? what's your take on that?

[00:21:50] Dr. Margaret-Anne Storey: Oh, that's such a great point. I think that there are a lot of cases of industry that do use mixed methods and do use qualitative data and quantitative data. I've seen some examples of this, and I've seen some examples be used really, really well. I don't want to mention any company or any person in particular, but I saw it with large companies.

[00:22:08] And I saw one colleague in particular. He went, and he sat, and he watched developers to see what their pain points were, and that was incredibly valuable to identify some really easy to solve pain points.

[00:22:21] Dr. Margaret-Anne Storey: Another example, this was more research that I did with Microsoft, and we published this in our Tripoli software. One of my student, Laura McCloud, she was looking, we were looking at the data and tools. And she was going around and following, sort of jumping from office to office and seeing what happened behind the scenes.

[00:22:42] The code review tools collect all of the telemetry of what happens that the tool records, but it doesn't record the engineer jumping over to somebody's office and saying, ah, by the way, I just tagged you in some code that needs reviewing. Do you think you could do this quickly for me?

[00:22:58] Or, oh, I see that you submitted this code, and it's got this really big problem with it. Do you want to fix it before you really send it to me to review it? Because they don't want to embarrass somebody by finding a big bug. So understanding what kind of happens behind the tools and behind the data is really, really critical.

[00:23:18] Showing examples of this with companies and showing them why that's powerful to have these rich quotes, these rich stories, about what's going on to augment the data, to go hand in hand with the data, I think does shift how people approach it.

[00:23:31] Data only tells us what's happening. It doesn't tell us the why. It doesn't tell us what we should fix. It doesn't always tell us what is actionable in here that we can change. So we may see over time that engineering productivity, according to the activity metrics goes down, but that doesn't tell us why it's going down, necessarily. We have to observe, talk to developers to find out what's going on here. Why are you not committing as much code as you used to? And then by talking to them, you can then get insights that help you make changes, and then you can use your metric to see, okay, is there a change? Do we see this change?

[00:24:13] Dr. Michaela Greiler: And I think especially with that one, it could be just a change of how people use the tool. Maybe they squash commits, and we are...

[00:24:19] Dr. Margaret-Anne Storey: Yes.

[00:24:20] Dr. Michaela Greiler: Counting commits, right?

[00:24:21] Dr. Margaret-Anne Storey: Yeah.

[00:24:22] Dr. Michaela Greiler: I think the biggest problem here also is that okay, if you have one team, it's normally quite simple, but if you have several teams, and they have very different work styles, then these numbers really become meaningless.

[00:24:34] I would love to find more ways for organizations to bring that insight. This ability to actually have metrics. But not only have metrics, really have measurements. I distinguish between measurements, investigations, instead of metrics. I define it once, and then, half a year later, they are outdated. They're not reflecting reality, but I'm measuring, I'm having data, I'm looking at data, I'm doing investigations. This investigation mindset. I think that would be so strong for organizations. And the ones that I'm working with, I see so many really good results. It's almost like enlightenment where metric is a light somewhere making a little bit, in the dark, something visible.

[00:25:16] Dr. Margaret-Anne Storey: The other thing that I've come across is that a lot of folks in industry think that interviewing or observing developers is very time-consuming, and it doesn't have to be. You can learn a lot from sitting with your team at lunch and asking them, what are your barriers? What are the challenges that you face? How is your experience? And gathering those insights just even once a month can lead to a lot of insights that you can then use to make change, right?

[00:25:45] Dr. Michaela Greiler: I think one perspective that I also want to add here is that this qualitative aspect that I'm talking about doesn't always have to be talking to people or observing people. It could be that there's a person that has this task, and they're going in, they're investigating, let's say, 50 pull requests. And they are writing down what's happening here. Or the last three bugs, why did that actually happen? Some quality metrics. Or if you're thinking about metrics again, metrics for me would be oh, line coverage. But then a person really doing the investigation going and saying, why is this project so different in line coverage than that project?

[00:26:22] Or why are people having those large pull requests over here and not there? And very often, if we then do the work, and I call this also qualitative, because you're not collecting data. It's not quantitative. You have to look at it, you have to investigate, and you have to see, oh, actually this is very coupled.

[00:26:40] This is the reason maybe there's a framework.

[00:26:42] And metrics, don't tell you this story. And I think that this is really what's so important for engineers to improve the experience and to improve their productivity, their performance. To reduce their pain points.

[00:26:53] Dr. Margaret-Anne Storey: Actually, you reminded me of one good example when you talked about coverage. We did this study that I mentioned that looked at the quality. How developers define quality, and how managers defined quality. And we have this framework called TRUCE, which is the timely delivery of robust features that delight users, support future collaboration and future evolution of the product. This definition of quality came from the developer and managers' words that they gave us in the survey we did. Again, there are five dimensions. Quality you can think of according to these different dimensions, and test coverage is quite interesting because that would fall under robustness.

[00:27:34] That you have really good tests for the code that you're delivering so that it will potentially catch some of the bugs that you have in the code that you push out today. But you might also have tests that don't necessarily cover the code as it is today, but are there to support change in the future. So they allow you to make changes in the future. Obviously, they cover the code still, but they're more focused on not finding bugs today, but allowing somebody else on my team to make changes in the future. So how do you tease that apart? Understanding what it is that you're looking at is really, really critical.

[00:28:15] Metrics, if you use them or measurements, any measurements, if you use them in a blind way, you're going to be missing that nuance, and they're gonna get stale. And people will misuse them. And they'll be abused, and they'll be gamified. So really bringing that nuance in is critical, and addressing the misconception, I guess, that it takes a lot of time to bring that extra information, and it doesn't. We need to think about it and build a culture that it's important to ask these questions along all of these different dimensions.

[00:28:46] Dr. Michaela Greiler: I think there also have to be role models, but I totally agree with everything that you said. I actually think we are at the end. I'm so happy that you were here, and I definitely will invite you again. So thank you so much, Peggy. Is there something that you think makes this conversation a little bit more rounded that is still missing from this productivity idea?

[00:29:08] Dr. Margaret-Anne Storey: I guess, just to sum up, if you're thinking about developer productivity, also think about developer experience, and also think in terms of quality, like product quality, and to really kind of think about those three independently, and to think about if you make some changes or you're making decisions, what are the dimensions of each of those three things? What are those dimensions that you need to think about? And if you're working with other people, find out what their assumptions are. If you're talking in a team, and somebody is talking about developer experience, or developer productivity, or software quality, just say: hang on a second, what does that mean to you? Even if you do that, I think it'll shift the conversation in the room quite a bit.

[00:29:54] Dr. Michaela Greiler: Unpacking their assumptions, this is so powerful. So thank you, Peggy. Thank you so much for joining my show.

[00:30:01] Dr. Margaret-Anne Storey: Thank you so much. It's been great.

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[00:30:04] Dr. Michaela Greiler: I hope you enjoyed another episode of this Software Engineering Unlocked podcast. Don't forget to subscribe, and please let me know how you liked this episode by writing me on twitter seunlocked, or filling in my little survey in the show notes(??). And with this, I'll talk to you in two week. ( _outro music* ) Bye! ( _static noise ) ( clicking noise )

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