SPRINT | Jake Knapp & John Zeratsky | Talks at Google

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CAROLINE O'CONNOR: Hi there. I am Caroline O'Connor, and I met Jake and John a couple of years ago when I was a designer in residence at Google Ventures. I was coming over from the Stanford Design School, where I was a faculty member, and I had a chance to see the sprint process that these guys were running with startups up close, and I was really blown away. It was a process that we were teaching at Stanford, but I will say these guys were getting amazing results with what they had honed and refined. And so I'm really, really excited to introduce them today to talk about the book "Sprint" that they've written, which really lays out a blueprint for running these kinds of sprints for your teams and how it's useful and how it can help in the bigger picture. [APPLAUSE] JAKE KNAPP: Thank you, Caroline. Thanks, you guys. So before we have a little discussion, I wanted to talk to you guys about where the sprint process came from and tell you a little story about it. So it all begins back in the year 2003, and it was that year that my first son was born. And that's a picture of him. And I have to tell you that when my son was born, I kind of freaked out a little bit, because I had this realization that he was going to be growing up. He was going to be a baby and then a toddler and then a kid, and this whole sort of life was going to be going on. And when I went back to the office, I realized every day I'm at the office, I'm kind of like missing that. I'm missing out on a piece of his life. And so what I do at the office should really matter. I should be making the most of those hours and days that I spend away. And so I thought, well, I'm going to take a look at what I'm doing. And so I thought about my work week, and I looked at my weekly schedule. And it looks kind of like this. It was meetings. People would schedule me for meetings. I'd say yes. I'd schedule other people for meetings. They'd say yes. And if I ever wanted to get anything important accomplished, I had to kind of wind my way through this like obstacle course of meetings. And I realized I wasn't really doing sort of the best use of my time by winding through those meetings and checking email and just kind of churning a lot of the time, so what I decided to do is get productive. And I read every book I could find on the topic. I read "The Four-Hour Work Week" and "Getting Things Done" and "Brain Rules," and I experimented with different kinds of to-do lists, like five over the course of a couple years. Pretty crazy. And over time, I did get productive. In those little windows when I had a gap between meetings, I would make the most use of it possible. And a few years later, 2007, I was at Microsoft in those days, and I left and came to Google. And when I came to Google, I thought, man, I can't wait to see what the days are going to be like at Google, because Google is this like crazy new place. What's it going to be like? And it turns out, as you guys might know, it's kind of the same. There are a lot of meetings. But I had honed these sort of productive skills for those gaps between meetings, and I knew how to get things done, and I also found that at Google, there was a real spirit of experimentation, and there was a spirit of experimentation in the products but also in the way people worked and the way teams worked. People were willing to experiment with how they conducted their execution on things, and I've started to do a new kind of a quest to make the team process better. And I imagined, what if I could just sort of wipe the week clean, wipe the calendar free of all those meetings, and start from scratch? And so I started doing day-long workshops with teams and then a couple of day-long workshops, and eventually ended up with this week-long process that I call a sprint. And that's what we're going to talk about today. And I took this sprint process in 2012 to Google Ventures, which is now called GV, because since the alphabet thing, we've lost all of our letters. So we're just GV, and at GV we have this interesting challenge, because we're investing in startups, and we want them to be as successful as possible. If you run a startup, you've got all kinds of ideas, but it's hard, because you don't know which ideas you should focus on. It's hard to know. Some of these might be big hits. They might make you a lot of money. They might be really successful. But a lot of them are worth pennies on the dollar, and some of them are downright dangerous. But up front, you don't know. They're just a bunch of question marks. They're just a bunch of ideas. And so this idea in startup land, in Silicon Valley, but really around the world has caught on that you should take an idea, make your best hunch, and just get data about it as fast as you can. The trouble is that getting data requires you to usually build something and launch it. And as most folks who have gone through this cycle know, building almost always takes longer than you think it's going to take. And so that knowledge that the build process will probably take-- if we think it's going to take weeks, it'll probably take months, and if we think it's going to take months, it might take years-- tends to make us more cautious about the ideas that we try. And we argue more about which hunch we should follow. So the sprint gives you a chance in a week to collect data quickly, and we found that that was a really valuable technique for our startups. They could try riskier ideas and try them a lot faster. So that's what I'll tell you guys about today. And the process is broken down day by day into five big steps with a lot of little steps inside. And rather than just tell you about how it works, I'm going to tell you a story. We've done over 100 of these with the different startups in the GV portfolio, and many of them are ones that you might have heard of, but I'm going to tell you a story today about one you may not have heard of. It's a company called Savioke, and Savioke, when it was first-- well, this is their mission statement, but when it was first described to me by my colleague, John, who you'll meet in just a moment, he was like, these guys make robots. And we've totally got to try to find a way to work with these guys. And luckily as it turns out, they had a really pressing question that they wanted answered right away. And so it was a perfect time to do a sprint. So this is the founder of Savioke, this guy named Steve Cousins, and Steve is a robotics expert. He worked at a place called Willow Garage for years and years, and he left Willow Garage with the idea of building robots for the service industry, robots that would be helping us in our sort of everyday lives. He wanted to take robots out of this kind of abstracted world of these really high tech expensive robots and make ones that we'd would have in everyday life. So he built this team of roboticists, engineers, designers, and they decided to build their first robot for hotels, which might seem like kind of a funny choice, but if you think about working at a hotel front desk, your day might look something like this. This is a diagram that I just sort of made up, but I think it's probably fairly accurate, because if you imagine the morning times when people are checking out and unpacking, moving around, the evenings with people checking in, there's a lot of activity during those windows at the front desk with people who are there physically, and then also people are calling from the rooms and asking for room service, asking for a toothbrush, a towel, some extra thing. And so it's really hard to staff those bikes. So Savioke thought, If we built a robot that could make some of those deliveries, we could let the folks at the front desk stay there, be focused there, do a really good job there, and then we could also make sure that people in the rooms got stuff they needed. So for the first five months of their existence, Savioke builds these progressively more sophisticated prototypes until they've created this thing, which is called the Relay robot. The Relay is a robot about the size of a trash can. It is self-driving, so it can sort of autonomously navigate the hallways. It's got a little hatch on the top with a locker in it, so at the front desk, you could put in a towel or a toothbrush or whatever, close it up, type in the room number, and then the robot would drive. You can call the elevator, ride the elevator, and make the delivery right at the room door. So all that was great, and they had worked out this pilot program with the Aloft Hotel in Cupertino. And they were going to take their first-- they just had one robot that worked, and they were going to take that one robot and put it into service, and for a fledgling startup, this is like a great opportunity, but also a really big risk. They wanted to make sure they got it right. And it was going to start making deliveries in just a few weeks. But they still had one really big question left unanswered. They weren't sure exactly how the robot should behave. It's a really good question, because if you guys think about, say, Isaac Asimov-- I don't know if anyone here is familiar, if there's any science fiction nerds in the audience, but I'll confess to being a science fiction nerd. There's this really sophisticated idea about how robots should behave, and it's deeply ingrained into the science fiction that has come ever since Asimov wrote these down. But as Steve told us, look, this robot is not that sophisticated. It's not going to be thinking about much. It's just going to be delivering things, and it can't have a conversation with you. He said, we've really been spoiled by Wally and by C-3PO, and we think that robots have sort of thoughts and plans and hopes and dreams, and the reality is that this robot won't be able to have any kind of a dialogue with people, and they were really concerned that people might get frustrated or disappointed if they tried to interact with the robot, ask the robot to do something, tell it something, and got no response. So in order to play it safe with this launch coming up, the safest thing to do is just make sure that the engineering worked well-- they had done that-- and not give it a personality, not do anything that might ruin all that other hard work. But they still kind of wondered, because it seemed like this interesting opportunity, and they had a bunch of ideas, but they didn't have a good way to test them. So we did a sprint together with them. We got to be there in the room while these guys hashed this out over the course of a week, and what happened is on Monday, they brought the robot into our building here in Mountain View, so we could do the sprint there. They rolled it in. Here, it's covered up in a sheet as though a ghost might be less conspicuous on the Google campus than a robot. And brought it in, and as you can see here, it kind of looked like a printer when they first took the blanket off, and we were like, well, OK, you know. But then we saw it driving around, and there's something kind of amazing that happens, because this thing can-- it sees you, and it kind of cautiously moves around you. And they had really engineered that motion exquisitely. It seemed very dog-like almost, and so we fell in love with it. And this is possibly the first robot selfie ever taken. But we just thought like, this robot is-- OK, let's try the personality. We got excited. So on Monday, the first job in the sprint of the team is to share all the information that they've got and make a map. And then on that map, pick the best spot to focus for the sprint. So we decided that the moment of delivery was both the biggest risk and the biggest opportunity for personality, because up to that moment, it's possible that you never saw the robot. You didn't even know that the robot existed. You asked for something to be delivered, and lo and behold, you open your door. You're wearing god knows what, and there's a robot at the door of your hotel room. So what we did then on Tuesday was to come up with a bunch of solutions. How might the personality work? And when we do this, instead of having a big group brainstorm where everyone's shouting out ideas, we instead have everybody sketch on their own. And I mean everybody, so in this instance, it's not a bunch of just designers or product folks working on it. It's everybody on the team, and when I say we're working quietly, it looks like this. It's kind of boring. Everybody is in great detail sketching out their solutions. So then by Wednesday, we've got all these different competing ways for how the robot might behave, and we decide from all of this-- I think we had 10, 15 different approaches-- to focus on three big ideas. So first, we've got giving the robot a face, which obviously carries some risk, because it's going to promise personality. We thought about a lot of different kinds of faces, and we ended up going with this kind of sleepy robot that sort of matched that dog-like impression we got from the way the robot moved, and we thought might suggest that you can't really talk to me. I'm nice, but you can't really talk to me. We wondered if people would like to play games with the robot, and we have this idea of the robot doing sort of a happy dance after the delivery was completed. So on Thursday, we had to build a prototype, and we'd spent the first three days kind of getting all these ideas on the table, making all the choices, and now we had to build a prototype. And we think it's really important that the prototype be realistic so that when we test it with customers on Friday-- that's how the sprint ends-- we'll be able to trust their reactions. So we put together sound effects, sort of a sound effect library, and we divided up the work. So here's somebody from Savioke working on that sound effect library. Here's the face, designing the face, and then just putting it on an iPad Mini on Keynote, and we replaced the panel on the front of the robot with an iPad temporarily, because it would look realistic. And finally, the robot choreography. So normally, the robot is running completely on its own. It's all done with sensors. It's all programmed out, but as you can see here, Tessa's got a remote control like a PlayStation remote. And temporarily, we could do sort of a Wizard of Oz thing with the choreography. It only needed to work for five deliveries for us to be able to get some data on it. So finally, it's Friday. It's time for the test. We're going to find out what happens when you expose this robot personality to people. And what we did, and what we always do is to do these one-on-one interviews. So in this case, our partner, Michael Margolis, came down to do the tests, and here's a photo of him in front of the hotel. And he comes in at 7:00 in the morning and starts sort of rigging the room up for the test. So he's got a suitcase, and inside a suitcase, he's just got all kinds of gear. He's got computers. He's got tripods. He's got duct tape. I don't know how he gets through airport security, but he does consistently. And with the help of the Savioke team, they're making sort of a makeshift research lab out of the hotel room. So they're wiring up these drop cams so that we'll be able to see as the robot kind of moves into position. And then at 9:00 AM, it's time for the first test, the first one-on-one interview. So I want you just for a moment to imagine, put yourself in the shoes of this first customer who shows up, and earlier in the week, you responded to an ad on Craigslist for a usability interview. You've filled out this survey, and you get this email from Michael, and it says, hey, this is going to be in a hotel room, and you're like-- this is like Wednesday to you. You're like, OK, I guess I'll check it out. And then on Friday, like actually, you're like, oh, god, kind of cursing yourself. You're there in the lobby, and Michael shows up, and he's like, OK, so come with me. We're going to go up to my hotel room, and you're in the hotel room, and there's all these cameras, and you're just like-- you're probably a little weirded out. But I mean this just goes to show that even under the most potentially awkward of circumstances, you actually can get good honest reactions from customers, because what Michael does is he puts the customer at ease. So he's wearing his work badge in the hotel, which doesn't totally make sense, but it does show that he is who he says he was. He's got a clipboard. His body language is even very careful, and he's asking questions of the customer. He's saying, tell me about your hotel routines when you check in. Where would you set your suitcase? And if you found that you had forgotten your toothbrush, what would you do? And they say, well, I guess I'd call the front desk and ask where to get one. And he says, OK, I want you to go ahead and call the front desk. Here's the number. So this first person, she calls the front desk, and this is actually the phone number of Allison from Savioke, who says, oh, sure, I'll send a toothbrush right up. So meanwhile we're back watching over video, and we can see on all these, it's kind of like this like FBI setup. He's got all these cameras. And we know that the robot is coming into positions from inside the room she doesn't know. And the robot drives into position. She opens the door, and we can watch the reaction to the personality. We can watch her take the toothbrush and see, does she talk to it? What happens? And so we get to watch this five times throughout the course of Friday. We get to see five totally cold reactions to this robot, and we see what happens. And it turns out that five is enough to give you these big patterns of things working and not working. So it turns out that nobody wanted to play games with the robot, which is good, because that would have been a lot of engineering work. We were able to sort of cut that right off the bat. But the face worked. No one also had any inclination to have a conversation with the robot, to ask the robot to do something verbally. That didn't happen. So the face was a big success. And the dance even worked. They even found the dance, which when described in the abstract, didn't sound that great, honestly, but it was quite delightful in real life. This is a little video of what the robot looks like now out in the wild, and Savioke launched with this sort of robot personality, and they now have more orders than they can fulfill. And as you can see, it has very simple eyes. The dance is really just kind of rotating, but it all gives this kind of delightful feeling to the robot. And it turned out to be something that guests absolutely loved. So the idea with the sprint is, of course, to not make us be so cautious about taking these big bets, to not water down our ideas or play it too safe. It might sound a little bit corny. You can almost be true to your vision, because you know that you're not betting the whole farm on everything. At worst, you'll embarrass yourself in front of five customers, which is nice to know. That's the idea behind the book. There are stories about Savioke and many other companies in there, and it's also kind of a DIY guide. And yeah, let's talk about it. You guys want to come on up? CAROLINE O'CONNOR: So tell us about why does GV have a design team? Like what's the goal of having a design team on a venture capital? JAKE KNAPP: We're trying to slip by as long as possible. Well, the big idea with GV is to invest in companies that we're excited about. We're excited about the businesses they're building. We're excited about the technology that they're building, and we want them to succeed, but we want them to succeed in a way where we make a return on our investment. And so we actually see design as kind of a strategic advantage for us. So if you think about a company that's starting out, and they're starting to get some traction on their business, they've got this really big idea about where they can go with the technology. They've got to, in order to get there, build this kind of bridge between their ideas and the reality of the real world, the reality of what their customers will want to use, be able to use, fit into their lives, and design, as we kind of saw in this story, offers this way to really quickly prototype ideas, understand how they'll actually work in customers' hands. And we find that it's kind of our secret advantage over if those companies were just sort of doing things on their own. CAROLINE O'CONNOR: Yeah. So given you guys have hundreds of companies in the GV portfolio. JAKE KNAPP: Over 300. CAROLINE O'CONNOR: So I imagine there's a ton of things that you could do to try and help them out. How did you come to sprints as kind of the primary way to help the portfolio? JOHN ZERATSKY: Well, we kept investing in companies, and we were like, oh, we can help all these companies. It's not quite like that, although it's not that far from the truth. But I was at GV before Jake joined us, and had a couple people on the design team, and we had worked as designers and writers at other startups in other parts of Google. And so we kind of had this approach where we would go from company to company, and we were sort of the experts. Or they thought we were experts, and we thought we were experts, and we kind of felt this pressure and this anxiety of needing to have the answers, to go into a company and say, this is what we think you should do. But it became clear that given the breadth of companies we were investing in and the different challenges that those companies faced, that there was no way we could have all the answers. Nobody could have all the answers, and so we began looking for, instead of the answers, a way to find the answers, and that was really where the sprint process became, we thought, really powerful. So we didn't have to say, well, when I want YouTube, this is what I did. And maybe it'll work for you. We could say, hey, let's work together, and let's figure out the answer to this big question that you're facing. CAROLINE O'CONNOR: Awesome. So you guys have had a chance to apply this process with a lot of different kinds of companies, small startups, big startups, but also you've done a lot of work here at Google, very big organization. What have you guys seen in terms of pitfalls that are maybe common to teams or things that can be blockers for them generally, and how this solves it, or what can block them from doing a sprint well? JAKE KNAPP: I think one of the struggles is having discussions in the abstract. John calls this getting stuck in abstractopia, where you know when you're going to have to build something that it's a big decision. And so we debate. We wave our hands in conference rooms and try to anticipate how people will react in the real world. And that's tough. That's an energy drain, and it often doesn't yield the best decisions. So part of the reason for the sprint was to add a little bit of structure to those conversations and to use some of the things that actually work really well in design. Design is a technique and a set of skills that can enable people to make things real really fast. There's a whole idea of critique and design. And design is usually thought of as this kind of kooky, creative art that people don't-- if they're not designers, they kind of walk quickly past the design room and think like, it's like those guys are playing D and D in there or something. But in the sprint, we've tried to make those things very practical, very accessible to everyone on the team, and then use them to short circuit a lot of those pitfalls. CAROLINE O'CONNOR: Awesome. And how do sprints fit with what everybody thinks of as like regular work? Like the calendar that you showed that we're all too familiar with here at Google-- is it something teams should be doing all the time if they're working well, or when do they bring this process to bear? JOHN ZERATSKY: Yeah, a lot of times we think that that sprints make sense as sort of the kickoff or kind of this initial burst for a new project or a new initiative. So if a company wants to reach a new kind of customer, or they want to introduce a new feature, a new product, sprints are a really good way to sort of kick that off. But they're not meant to be sort of the way that you work all the time. At the same time, there's a lot of ideas that are part of the sprint that we think are really valuable to use sort of in day-to-day work and day-to-day life. One of the examples is sort of about the way that time and activities are so structured in the sprint. For example, I do all of my meetings on Thursdays and Fridays, so a lot of the work that I do, I'm writing, I'm designing, I need uninterrupted work time. So I actually leave Monday through Wednesday open for those things, and then Thursday and Friday are the days for meetings, so being very structured in that Jake and I are very sort of aggressive about-- JAKE KNAPP: It's sort of weird. JOHN ZERATSKY: We're sort of weird about limiting distractions, so Jake introduced me to this idea that he came up with of the distraction-free iPhone. So uninstalling Twitter and removing your email account from your phone, so you can't check your email, and even-- it sounds nuts-- but even like disabling Safari in the restrictions and the settings for the iPhone so that you don't have access to this sort of unlimited pool of potentially very interesting but ultimately distracting information that exists in the world. JAKE KNAPP: You can see the picture that's being painted here. Fundamentally, John and I have very poor self-control, and if left to our own devices in a typical work week, we would be checking Twitter and our email just continually over and over again. And the sprints and then some of these other kinds of methods are ways for us to put rails on it so that it's easy to do the right thing, the best thing with our time. JOHN ZERATSKY: But I think usually what happens with the teams that we work with is that they'll use sprints as sort of the kickoff for some new thing that they're working on. And a lot of times they'll do two or three sprints in a row, so the first sprint is five days the way that Jake described, and the second sprint is usually shorter. Usually the prototype that you built and tested, there may be some problems with it, some things you want to fix, and then there's some other things that went really well, that worked out really well, and so the team will then do a shorter sprint where they tweak that prototype and test it again, and then maybe the next week, they do another sprint, where instead of tweaking that existing prototype, they create a different kind of prototype, something that they can test with live traffic or do a different sort of more quantitative kind of test. CAROLINE O'CONNOR: Awesome. Can you talk a little bit about user testing as a forcing function for teams? You guys have that set on Friday, but talk a little bit about how that can help with the distractions. JOHN ZERATSKY: Well, the sprint is actually just an elaborate scheme to get more companies to do user research. JAKE KNAPP: Well, it's also-- I mean it does get back to that idea of me being a procrastinator. And I did have this realization that when I had a deadline, like many, many procrastinators, I suddenly got really productive right before the deadline. So if you decide you're going to run a sprint, and then on Monday you say, these are the customers we're bringing in. You start recruiting them. You know that five strangers are coming in on Friday, on Thursday, you'll be like, you don't want to embarrass yourself. So you will get really productive. And there's all these good reasons for bringing in customers. It makes you focus on those customers in a very concrete way throughout the week, so you're not just waving your hands, but you know these are the people who are coming in. And it also gives you data right away. It's the very fastest way that you can get some data on a complex idea like the ones that we put into a prototype. But that forcing function is a very real, very powerful part of having people show up. JOHN ZERATSKY: Part of our motivation for sort of building the sprint around customer interviews specifically is that the startups that we work with and imagine a lot of the teams that you guys are on here, your center of gravity or your sweet spot is writing code and shipping software. That's what we all know how to do. And so there's a tendency for that to be the thing you do when you're trying to figure out something. And you see this in sort of like the lean startup and different approaches like that like I'll create an MVP, create some basic version of the product that you can get out there and you can get data as quickly as possible, but we think there's this amazing shortcut, which is creating this realistic prototype. And then instead of having to launch it and having to analyze the data, just watching people react to it. We think it's not a replacement for sort of quantitative testing and launching something in the wild, but it gets you a different kind of data. It gets you this really rich qualitative understanding of which things are working and which aren't. And the best thing is you can do it in a few days instead of weeks or months. JAKE KNAPP: You can try a sprint once, do that experiment with your team, try working in a different way, and it all comes with the sprint. And then you can see how it works. CAROLINE O'CONNOR: So for partners at a venture capital firm, you guys have pretty unusual backgrounds. No top hats or monocles that I've ever seen. JAKE KNAPP: We left it at the door. CAROLINE O'CONNOR: Can you tell us a little bit about how you came to be partners at GV? JAKE KNAPP: Well, that's a very long story, Carol, but I'll begin at the beginning. I won't begin all the way at the beginning, but I studied art and painting in college, which was, generally speaking, not helpful for any of the work I did after that. But I've always been interested in computers and making things, and when I was a kid, I would make games on the computers and test them on my unwilling friends not knowing that that was basically what I'd end up doing sort of forever, only not with games. But for me, the process that led me to GV was, ironically, not about having a ton of startup expertise. I've learned a lot about startups and built that by being at GV, but actually just having this sort of interest in figuring out how teams can use design and how teams can make better use of their time. So it was the opportunity at Google to really test that out and experiment over and over again and make the process better that gave me the experience that I needed to be able to start doing that here. But you have another very different road to GV. JOHN ZERATSKY: Yeah. I got my start in journalism. I was actually introduced to design by working at a newspaper, and so I sort of accidentally found my way into this really interesting kind of design work. So every day I would come in. It was a daily newspaper. I would come in, and the editors would say, OK, here are the stories that we have for today's paper, for tomorrow's paper, I guess. Here are the photos that we have, and here's sort of the priority. These are the most important stories. These are the least important. And so I'd kind of do this puzzle of putting the paper together and figuring out how everything fit. And then it was a paper that was distributed on a college campus, the University of Wisconsin. So the paper would be printed, and then I would go to class the next day, and I would actually watch people read the paper. So I was like doing usability testing without really knowing it, and in a lot of ways, that experience kind of crystallized my approach to work-- trying to get in a lot of reps, trying to create environments or seek out environments where I could get in a lot of these little loops of trying something and then seeing how it worked with customers, and then fixing it and making it better the next time around. So after that, I worked at a startup called Feedburner as a designer. We were acquired by Google. Worked at Google in Chicago, worked at YouTube doing sort of product design, UX design work all along, and I was attracted to GV for a lot of the same reasons as Jake. I wanted this opportunity to work with so many companies working on so many different things. I saw it as being sort of like being at the newspaper again. I knew that I was going to have these loops. I was going to have this opportunity to try things, make them better, and try them again. CAROLINE O'CONNOR: Awesome. So the question is, how do you make sure that the small sample of users that you're getting relates to the larger sample that you're going to be working with? JAKE KNAPP: Well, one of the great things that happens in the course of setting up the customer interviews is early in the week, you talk about all of the different customer types that you have. And you figure out, OK, we're going to focus on this group, and what happens when you make that decision is you start to get very real about what defines that group, because if we want people to come in who look like that, who use that kind of software, have that kind of job, whatever it is, then you realize, well, in order to get them, we're going to need to post an ad here or contact our network of folks here, and we're going to need to screen people out. We're going to need to recruit a lot of people and put together a survey, where we ask them questions, and we want the results of those questions to tell us, is this our customer or not? And it's that survey, that sort of screener that we use that helps us make sure we're getting the right people. But that exercise, having to do that is something that we find many teams at all kinds of companies small and large defer. They talk in sort of broad brush strokes about their customers, but the sprint makes you get very specific, because you want to make sure you get the right people in. JOHN ZERATSKY: Yeah, and that exercise on Monday of creating the map is also really helpful, because you avoid the temptation to think in terms of personas and what kind of person it is, and you think more about what situation is the person in, and what are they doing? What's the task they're trying to complete? And that's sort of that-- Jake showed that big map and then zooming in on that one point, so in that case, it's a traveler who is checking into a hotel and realizes that they forgot their toothbrush. So you can look for people who would likely be in that very specific situation. JAKE KNAPP: To give you a concrete example, when I worked with Slack, who's a sort of messaging software, they were interested in finding better ways to explain how Slack works to companies who aren't tech companies. Slack's grown tremendously with tech companies, and they're figuring out how to explain it to other kinds of teams. And so they knew that they wanted to expand to other kinds of teams. In the sprint, they had to get really specific about which kinds of teams, which are the best example of representative teams? Is it a team who's in media? Is it a team who's in health care? What should we look for? What questions should we put in the survey to find those people? CAROLINE O'CONNOR: So the question is we have so much data. Do you want to be looking at the data that you've got and digging into that before you do a sprint, or do you do the sprint earlier? How do you think about that? JAKE KNAPP: Yeah. So there's maybe three things I'll remind myself, there's three things I want to mention. The first one actually is that you should be really careful of three-day sprints or anything short of five, because usually the first thing people cut when they make the sprint shorter is that realistic prototype and the test. So I do know there are some folks who will compress all the steps into three days, and then you have to look out for like dehydration of like passing out, because it's pretty intense. But if you actually are doing it at the normal pace, you just want to be really sure you build that realistic prototype and test it. Otherwise, you might not know if you have the right idea. JOHN ZERATSKY: Yeah, you can cut out days, but you can't cut out steps. Or you shouldn't cut out steps. JAKE KNAPP: Yeah. That's a nice concise way of putting it. But in terms of when you have a lot of data, knowing what to do with it, I think John and I both came from working at Google where there was tons of data. John worked on YouTube. I worked on Gmail, and obviously, those are products where you launch something, and you get a lot of data about what's going on. But even when you have a ton of data, it can be very hard to know why something is working or not working. And so we certainly have the experience of working for a long time on a new feature, launching it, and seeing that people were using it or not using it, but not knowing why still. And that's part of the thing that you'll get with the kind of qualitative research that you do in a sprint when you're doing interviews is that you'll know why. You'll be able to see people actually doing it, and you don't have to just guess what the numbers mean. In terms of when to do the sprint, I think what we really look for is a big question. And so Savioke is honestly among all of our sprints, it's more unusual for us to work with a startup when they're so close to launch. It's not crazy or unheard of, but it's more common to do it at the beginning when you have that big question. You're starting off on a totally new product or a big new feature, or maybe it's the start of a new quarter, and you know that you're going to be putting a lot of effort in. You just want to check where things are. But it's that feeling of, gosh, we're making big decisions, but we don't know for sure. We're arguing or we're scratching our heads. You can satisfy that with a sprint. JOHN ZERATSKY: Yeah, I would say that to your question about sort of bringing data into the sprint and how to incorporate that, having a lot of data to work with when the sprint starts is actually a luxury. It's actually a great thing. And the sprints that I can think back to that were the most successful started with a lot of data. Either we did a round of customer interviews, or we had a lot of quantitative data about how people were using the product or how effective the marketing was. It does take some work to distill that and analyze it and present it in a way that makes sense, but that's always a challenge. So what we'll typically do is we'll invite sort of someone from a data team or a product manager or, in our case, a lot of times, it might even be the CEO or something, because we're working with these really small companies. And they'll give us on that first day of the sprint a half an hour or an hour sort of run-through of who's overseeing. Here is maybe the conversion funnel, or here are the usage patterns in the product, and this is what we know so far, and this is what we're trying to figure out. CAROLINE O'CONNOR: So is five days really the number for a sprint? Could you do it in one day? And how do you think about sort of cutting it down or playing with time? JOHN ZERATSKY: Well, we've experimented a lot, so that's kind of the first thing is we're pretty confident that it's the right number of days. But I like your question about-- you asked, what is the essence? Like if you were going to sort of slim down the sprint, what would be like the absolute essentials to not get rid of? And I want to hear Jake's answer. JAKE KNAPP: Well, you definitely don't want to get rid of that realistic prototype and the test, because what happens at the end of the sprint is you run that test, and then you're seeing how customers react, and then that's surprising. Ideas that seem so brilliant on Wednesday turned out to be duds, and then something that maybe you just took a risk on, and one thing we didn't talk about so much is that we'll sometimes make two or three competing prototypes and see how they do head to head. And maybe it's that riskier idea that turns out to work, but you don't know that until you've shown it to customers. And the other things you get when you have a realistic prototype is for the team, it's this concrete-- it's like you fast forward it into the future. What if we were done already with the product, and it looked like this? And that's really helpful. It's helpful for the team to decide if the product seems to fail with customers, do we have belief that this artifact is something we can make better? And we're just going to try to make it better in another sprint, or are we off track? This wasn't as great as we imagined. JOHN ZERATSKY: Yeah, I think a lot of the short sprints that we've seen or that we've heard about, for whatever reason, they tend to be oriented or sort of weighted toward the early parts of the sprint. So they tend to be more about coming up with ideas, and I actually think that coming up with ideas is usually not the challenge. People are constantly thinking of ideas, and in fact, we found that the ideas that people come up with in the sprint are often not as good as the ideas that people have had kind of rattling around their brains for the last months or years. And I think it's because the ideas in the sprint are sort of abstract, they're unrefined, and they're new, whereas the existing ideas have been through the wringer, so to speak, of kind of thinking about them, working on them, considering them. JAKE KNAPP: Just to be clear, we make sure people put those old ideas into [INAUDIBLE]. JOHN ZERATSKY: Exactly. Yeah. JAKE KNAPP: They're on the table. But I think then you can take-- the essence of it also is to-- we're sort of geeky about human interactions. John and I are a little-- I don't know. We're sort of pod people. But we think that if you can put some structure around the things that we often do at work with no structure, that it helps a lot, and so there are a bunch of little pieces in a sprint that can be helpful at any time. It can be really helpful when you're having and you're starting to talk and have evolved into a brainstorm in a meeting to say, wait, hold on a second. Let's all quietly write down our ideas. All of a sudden, you give the introvert or the person who's not so good at pitching their ideas, you give them a chance to have their idea be on a level playing field with everyone else's. Sometimes it's helpful to just put the ideas on the wall and vote, the kind of thing that we do in a sprint all the time. It helps you shortcut sometimes a discussion that isn't necessary. And the idea of talking to customers-- putting what you have in front of customers is something you can do. Even if you're not running a sprint, you can test your product and put it in front of people and start to answer those why questions. CAROLINE O'CONNOR: So the question is, how do you go from 17 ideas on paper to the few that you're going to test, and how teams navigate that well? JOHN ZERATSKY: That's probably the most like robotic, scripted part of the whole sprint. And for good reason, because it is very challenging. I guess we sort of talked through the specifics, but I'll lay out the high level, which is that we have a very particular set of voting exercises that we do starting with what we call a heat map, which is where everybody just sort of looks at the ideas and has these small colored sticky dots. They get effectively an unlimited number of them, so if they spend them all, they can get more, and just put a dot on anything that seems interesting. Then we do what we call a straw poll sort of round of voting, where people get larger dots, and they get a limited number. But it's non-binding, so you're sort of going around the room looking at the ideas and voting on the ones that seem most promising. And then we do a really fast critique, so the group together talks about which ideas they thought were the best and which ones maybe are problematic or not as interesting. And then one of the more sort of unusual steps is that we then rely on the decision-maker in the sprint to actually make the final call. So the leader, the executive, the CEO, whoever it is-- that person gets to sort of absorb all the work and all the ideas and all the opinions that have been shared in the room, and make the final call about which prototype or which prototypes to build and test. JAKE KNAPP: One of the ways that we think about this is if you think about your phone. Like every morning, if you charged your phone overnight, you wake up, the battery's full, and then throughout the day, you do stuff, and the battery wears down, unless you have a cooler phone than I do. But that's what happens to me. Our ability to make decisions is kind of like that, so we wake up in the morning. We've got like a full battery of decision-making ability, and then as the day goes on, if you have a lot of intense conversations, if they're 17 ideas, and you're trying to narrow them down to three by like arguing the whole day or like pitching one versus the other, like your battery is just going to go [SHRINKING NOISE]. And it's not going to work. And so in the structure that John described, what we're trying to do is make those decisions as effective as possible so that every time you burn a little battery, you're making progress. And to do that, we cut out sales pitches. We make a lot of the evaluation silent. We make the sketches anonymous, so you're not evaluating who made it. And then ultimately, when it starts to be the hardest part of the decision, we turn it over to that one person who we know will make an opinionated call. So we don't have to worry about group think. We don't have to worry about watering down and getting to a consensus. We're just saying like, OK, look, decider, you make the call, and then we'll find out. Right away we'll get data, so you can take a chance. CAROLINE O'CONNOR: So the question is, how do you modify this for situations where humans are not that end consumer? JOHN ZERATSKY: Well, I think that is a really interesting question, and I don't think we've done a sprint like that. JAKE KNAPP: I'll give you an answer that-- I'll start with a bad answer to that question, which is that for most things-- and you may be talking about an exception to this-- for most things, there is some point at which the product does touch a human. And it might be downstream. It might be that you're building a back end service that, in turn, supplies something to another service, and in turn, the place where it touches the human is somewhere downstream. But fundamentally, humans are the problem. Whenever anything, you make something, and it doesn't work well, or there's a problem, or people don't like it, it's that surface area where the human touches it that's usually the unknown. And so we often think, well, where is that human touch point? What is it? It might not be like a software interface. It might be a sales conversation. You might be building back end that's going to supply functionality with the expectation that we'll be able to sell this to a third party or that it'll enable us to do some new kind of query that people will want, searches that they'll want to run or something. I'm just making this up, but that idea often helps us get to the root of the question, which is about what will people do? People are the ones who are hard to predict. Now if that doesn't work, the answer that's slightly better, but I'm waving my hands a lot more, is that you try to prototype what you would be supplying if all of the coding was done. And you say, during our day when we're prototyping on Thursday, we're going to be faking that part. And then we're going to be somehow manually supplying that to whatever's on the other side and seeing what comes out. I'm not a back end developer, so you're probably just laughing at me, but I think that might be the idea. OK JOHN ZERATSKY: I was going to suggest that she change the test to try to come up with-- the test that we do, our customer interviews, but there might be some other kind of test that you could think up. I'm also waving my hands, but there might be a different way of sort of validating whether an idea or an approach is any good or not. JAKE KNAPP: A big part of the magic is that constraint of five days, and we know that the steps in the sprint will provide us rails to evaluate ideas, make decisions, and then very quickly, try something, and it might not be right, but for me, there's so much frustration when you spend weeks or months doing that sort of discussion and trying to decide. And so yeah, it might be just a different kind of test, and you commit to doing the sprint to have something at the end, so you can see what it might be like. CAROLINE O'CONNOR: I have one more I wanted to throw at you guys. You talk a lot about the value of having the whole team watch the user testing and really see it for themselves and be connected to it. I found that to be really challenging at Google given the calendar situation. And so then you end up with challenges to a data set of [INAUDIBLE] of five, that that can't possibly be valid, and especially for folks who haven't sort of seen the user test. Do you guys run into that? And if you do, how do you deal with that? JAKE KNAPP: Well, that idea of having everyone watch is really important, and one of the reasons why it's important is that if everybody can't watch together, then it often falls on one person's shoulders to conduct the interviews and then communicate what he or she saw in those interviews to everyone else. JOHN ZERATSKY: And that person has to be really convincing. JAKE KNAPP: Yeah. Yeah, incredible, and it's a lot of work, and there's a time delay to put that information together. So if you get everybody in the room together on a Friday watching it, this magical thing happens where there is no argument about what people saw, and there's also-- we've never had a sprint where after watching five interviews, people, no matter how much hard core data nerds they were, didn't say like, oh, yeah. It's clear what the big findings were, what the big patterns were, because by that fifth person, you're just starting to see the same things, things that you saw earlier happen again. There's nothing new. And I don't know if you want to talk about Y5. JOHN ZERATSKY: Well, I was just going to add something and talk about one of the mechanisms that we use to sort of make sure that people stick around for the research and actually watch the research is by making sure that the people in the sprint all participate in the creation and the selection of those ideas so that everybody is sketching, everybody's involved in the decision-making process, everybody's involved in the prototyping, and the reason that's important is that then those people really want to see what's going to happen in the test. It's like people are then into it. They're in suspense. They want to find out if their ideas are going to work out or not. So by making sure that the entire team is going to participate, even if that means a smaller team, a smaller core team who's going to be really focused, it creates an incentive for those people to stick around for the end. JAKE KNAPP: There's a study done by Jacob Nielsen in the '90s where he evaluated hundreds of these kinds of interviews to see at what point the sort of learnings trailed off, and it turns out that whether you interview five people or 30, by the time you've talked to five, you'll see 85% of what you'll ever see. And so you're better off-- that's the point of diminishing returns-- you're better off then turning your efforts to doing a new prototype and fixing it or changing it. And so we've also seen that anecdotally in our own experience that, again, by that fifth interview, it starts to be repeated information. JOHN ZERATSKY: We both heard a great metaphor the other day for this. Imagine if there was a piece of carpeting here that was kind of flipped up, and people were coming up to ask us questions or something, and 20 people were going to come up and ask a question. And the first two people tripped on the piece of carpeting. Would we need to watch the other 18 people all trip on the carpeting? We wouldn't need to. So there are some things like that that just become so obvious that need to be fixed or things that are working well after even a couple of customers that five really is a magic number for customer research. JAKE KNAPP: In the sense of being a complement to large scale data. Either later on or before, you have that large scale data that can tell you something different about it, but five works well. And because it's so important to have the team there, to have everyone see that research, we really think that you're better off, if you don't have time to do that realistic prototype that fifth day when you test, you're better off not doing a sprint at all, because it might be a sign that what you're working on is not important enough to the team. And so in that case, you might want to wait until it is the important thing, and you're willing to do it right, because you'll get so much better results by going all the way through. CAROLINE O'CONNOR: How important is it to test three ideas and evaluate them against each other as opposed to maybe just testing one idea? JAKE KNAPP: We don't always test three, but we often do, and the reason why it's valuable is because-- actually, there's a couple reasons. One is that if you know you have two or three, you can take bigger risks. So you're less likely to try to make this really tough call between two promising directions or to try to sort of water them down or merge them into one idea. The other thing is that frankly, we've done this enough times that we know how often we're wrong. We know how often founders, anybody who's a decision-maker is wrong. It just turns out that humans are unpredictable, and when you show them this new thing, it's really hard to tell how they're going to respond. And so you have just increased your hit rate. If you've got two or three different things, it turns out that the chances that one of those is the right one is much, much higher. JOHN ZERATSKY: In the Savioke story, there were three different ideas, but they were all packaged into one prototype. So a lot of times, that's what we'll do. We thought it would be weird if there were like multiple robots making deliveries in your hotel room. But if it's something-- JAKE KNAPP: Here's your toothbrush. JOHN ZERATSKY: If it's a more conventional type of product, if we're talking about like when we worked with Blue Bottle Coffee, so we were helping them figure out how to expand their business online, how to bring the experience that they created for their customers in their stores to the web. We had a lot of different ideas for how we might do that, and what we did in that case was we took those different ideas, and we created three separate prototypes, and what it looked like to the customers we tested with were three different websites where you could buy coffee. JAKE KNAPP: Three totally different coffee companies. JOHN ZERATSKY: They even had different brands. We made up fake logos. They had different color schemes. And so that's a really powerful way to test when you have ideas that are completely in conflict. With Savioke, the face and the games and the dance were not in conflict, so we could put them together. But if you have ideas that are in conflict, these multiple competing prototypes with fake brands, they create that illusion for the customer that they're looking at real stuff, and they're just sort of reacting and thinking out loud and telling you, I really like this one, because it seems I don't know if I can trust it or whatever. You're sort of watching them shop between these different options. CAROLINE O'CONNOR: Thank you, guys, so much. This was really, really interesting. JOHN ZERATSKY: Thanks, everyone, for coming. Thank you. [APPLAUSE]
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Channel: Talks at Google
Views: 50,033
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Keywords: talks at google, ted talks, inspirational talks, educational talks, SPRINT, Jake Knapp, John Zeratsky, jake knapp golf, jake knapp design sprint, design sprint, golf
Id: peK4xFdji8I
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Length: 52min 53sec (3173 seconds)
Published: Mon Mar 28 2016
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