Grit Is Good. But Quitting Can Be, Too.

(upbeat music) - Welcome to the HBR IdeaCast from Harvard Business Review. I'm Allison Beard. (upbeat music) - It's not about winning, but what it's about is not giving up. - You have to work the hardest. You have to chase what seems impossible. Over, and over, and over again. - It's never give up 'cause you never know what can happen, you never know who you can inspire. - Nobody is gonna hit as hard as life, but it ain't about how hard you hit. It's about how hard you can get hit and keep moving forward. - I will never stop trying because when you find the one, you never give up. - You might wanna give up. - Don't give up. (audience cheering) - Whether it's in sports, movies, politics, or business, we spend a lot of time celebrating people who persevere. We prize stick to itiveness, grit, and persistence. We applaud winners and especially underdogs who beat the odds. But our guest today wants us to rethink those assumptions. If you don't succeed, not just at first, but over and over, is it really best to try, try, try, try again? Long term, do winners never quit and quitters never win? Or should we be thinking less all or nothing terms about our businesses and careers? Annie Duke is an author, consultant, and former professional poker champion. She wrote the book, Quit, the power of knowing when to walk away. Hi Annie. - Hi Allison. - Why is quitting so stigmatized? - Oh my gosh, you know, we have so many cognitive biases that really stop us from stopping things. Our version to quitting is really built pretty deeply into our mind where and then you see this reflected in even the English language. So when you look at the synonyms for grit or grittiness, it's, you know, you have metal or pluck, it's a sign of character, those who stick it out are the heroes of our stories. Whereas when you look up synonyms for quitter, it's like, you know, loser, basically, you know, coward, they're not the heroes of this story, they're the villains. And I think that that is very much a reflection in the way that all language is of the way that our minds think about quitting. - I should step back and ask, is this a version to quitting common across different geographies and cultures or is there something about the American environment that makes it particularly salient here? - Well, to be fair, I haven't looked at every single culture. So I'm not sure that I am perfectly equipped to answer that, but what I can tell you is that biases like the sunk cost fallacy, for example, that cause us to take into account what we've already spent in deciding whether to spend more on an endeavor or continue, loss of version, the endowment effect, the sort of price we put on ownership, how much we overvalue things we own versus identical things that we don't own. Even issues of identity, these really cut across all cultures. These are very well replicated findings over about half a decade of scientific research. - So I think that this is really in large part part of the human condition. - Yeah, and there are so many cognitive biases you just mentioned. A few of them that push us into sticking with things, even when there are signs telling us we probably shouldn't, in your work as a consultant, a human moving about the world. Which one do you see arise most often for individuals thinking about their careers? - I can't really pick one, 'cause I think it's a combination of two things. One would go under the broad category of sunk costs. So in a job setting, you'll see people not shut down projects, not abandon a product they're developing, or even not leave their job, because they'll say, well, that I'll have wasted my time or my money if I quit. Right, so we don't wanna leave a job, 'cause we say I've put so much time into it, I've spent all this years in school and training and learning the culture, and if I quit, I'll have wasted all of that time. I don't wanna shut this project down, because what about all the money that we've already spent on it? If I quit, there's no way that I can get that back. Now, that's a fallacy because it's already spent. What really matters is whether the next minute or the next dollar or the next bit of effort that you put into that project is worthwhile. So I would say that's a very strong force that stops us from quitting. But interestingly, on the other side of things, I would say that loss aversion also really stops us from quitting. Loss aversion has to do with a problem with starting things in the sense that we focus on the potential losses that are associated with the decision that we might make, sort of not thinking about what the expected value is or what the overall return on investment is. You might ask, well, what does that have to do with quitting? Well, when you're quitting something, you're not just quitting, you're gonna start something new. Mm-hmm. And so if we have an aversion to starting things where we imagine the ways in which they might not work out, this will actually stop us from starting new things, which in turn stops us from quitting. So a simple example of that is you'll hear people when they're in a job that they hate. Say things like, well, I don't wanna quit because what if I take a new job and I hate that one and it's not good? The devil you know is better than the devil you don't. Right, and that's really the loss aversion speaking, right? It's like, well, I know I'm gonna be miserable in this job, but if I start something new, what if I'm miserable in that as well? Never mind the fact that you have a much higher probability of being happy in the new endeavor than the one that you're sticking to. And just for people who are thinking, well, don't you have loss aversion for the things that you're already doing, the answer is not as much. It's asymmetric because the status quo, whatever it is that we're sticking to, we don't think about that as starting something new every day, even though in reality it is. So where loss aversion really gets recruited is in the thought about quitting something to start something new. So you can see where these two biases work together in a really maligned way, which is I don't wanna stop something for fear of wasted everything I already put into it. And I don't wanna start something new because I'm worried about maybe that won't work out. - Yeah. And it seems like that would be equally prominent when businesses are thinking about projects and strategies to pursue, are there any particular cognitive biases that you see more often in organizational settings? - One of the biggest things that I see is opportunity cost neglect. We don't tend to take into account the gains that might be associated with another course of action. In comparison to the thing that we're already doing. So if you have resources that are pursuing a particular project, those are resources that can't pursue other projects. And any other project that you might pursue has losses and gains associated with it. We're almost myopic in the sense that we really can't even see the other opportunities that are available to us and that causes us to neglect the gains that might be associated with those other opportunities. One of the places that I see this really strongly separate apart from things like strategic initiatives is in employment decisions. So people will have under performers in a job. And what I see is, again, people really focusing on, well, what if I fire them and I don't hire someone who's good into that new role? And what they neglect is the gains. One of the things that I try to do with them, I said, well, imagine that you did let this person go and there was nobody in the role. Would it be better or worse? And we work through things like, well, they're having a really negative impact on the team. So if they weren't there, I think that the culture of the team would be healthier. Generally, the answer is it would actually be better not to have anybody in the role. And then we really try to focus on what's the probability that somebody new will be better than the person that you currently have. To try to get them to stop focusing on the possibility of loss and start focusing on the gains that might be associated with other options. And this generally helps to get them to those decisions more quickly, whether it's about employment or deciding to stop pursuing a sales lead or shutting down a strategic initiative. - I know that the first step in all of this is understanding that these biases, trying to recognize when they come up. But you make a really good point in the book that there is a difference between recognizing they exist and preventing them from affecting you. - So you're absolutely right, Allison? I think that we have the intuition that once we know about these types of biases that we won't do them. So if I explain really clearly the sunk cost fallacy to you and I say, look, if you buy a stock at 50 and it's trading at 40, you're more likely to hold that stock than in comparison to whether you would buy that stock at 40. So in other words, if you wouldn't buy the stock at 40, you shouldn't hold it just because you happen to buy it at 50. So now I've told you. do that and I'm sure Alison that you have the intuition well okay so now I know that so I won't do it anymore. Right but you tell a really poignant story in the book about a researcher who knew all of it. Yeah so there's a broad umbrella term that kind of all of these forces both cognitive and motivational go under when it comes to sort of failure to quit and it's called escalation of commitment and escalation of commitment is just a broad phenomenon that we have the intuition that once we start something when we discover information that would tell us that things aren't going well we'll actually stop doing what we're doing and what a variety of researchers have shown is very specifically Barry Staw and someone named Jeffrey Rubin who were really kind of the pioneers in this field is that it's kind of perversely opposite in the sense that we'll actually escalate our commitment to the losing cause so we see the negative signals and we just like invest more so Jeffrey Rubin was one of the pioneers as I said and he was very much an expert on these entrapment problems these escalation of commitment problems Jeffrey Rubin was also a very avid mountain climber and he had set a goal for himself to climb the hundred peaks and he was climbing his hundredth peak with a graduate student and like a really heavy fog rolled in and his graduate student said hey you know I I really don't think that we should continue up it's pretty foggy here and he said no it's fine I'm gonna keep going and the graduate student turned around and Jeffrey Rubin's body was found two days later so for anyone who thinks knowing is the same as doing he really understood these problems would be entrapped in losing causes the way that we ignore the signals that we ought to turn around and yet he kept going and he perished one of the solutions that you recommend is to calculate the expected value of a particular course of action you know that could be staying where you are it could be doing something different you know as a poker player you're used to sort of thinking about probabilities but for the rest of us you know how do you make effective estimates in that way you know especially when they're internal factors you know your own feelings but also external ones like the market and luck well first of all I just want to make something really clear that when you make a decision whether you're doing an explicitly or not you are making these types of forecasts you are making these types of estimates if I choose to marry person A instead of person B what's implied in that is that I've determined that the chances that I'm happier with person A is greater than the chances that I'm happier with person B I think where we get tripped up is that when we say them out loud and explicitly we sort of think about it like a test like all of a sudden you could be right or wrong but it's not about being right or wrong it's about thinking explicitly about what path is going to be more likely to help you achieve your goals given what you know at the moment understand and that it is a forecast and it's probabilistic and you're having to do these things you know knowing very little in comparison to all there is to be known but if you're implicitly doing it anyway it's always going to be better to do it explicitly first of all you can ask other people about it and they can help give their perspective you can look things up from taking you know one career over another I can look at on average what's the opportunity for promotion how long does it take someone from the position that I'm taking to get to the next level or to get into leadership or maybe even to get to the C-suite and the other thing is when you do this you can actually write those things down and then as the world unfolds as it does it makes it a little bit easier to close the feedback loops that would help you then learn because you can see what was I thinking at the time why did I choose the path that I chose and now it's much easier to learn from that you know we think of expected value is like well I have to calculate exactly what my return on investment is going to be but we can think more broadly just about what are the chances I'm happy doing a or B happy being a proxy for all the things that we value and I've actually done this with people I did it with a woman named Sarah Olston Martinez who was in ER doc who was really really unhappy in her job and she asked me just for help with a decision about whether she should quit she had another job offer from an insurance company where she was going to be evaluating cases so I said to her well if you're really deeply unhappy and have been for years in the job that you're in why don't you want to go and take this new job and you know loss of version she said well what if the new job doesn't work out so I shifted the conversation to one of expected value but one which is palatable to somebody who might not be so mathematical I said imagine it's a year from now what are the chances that you're happy in your current position and she said well that's 0% I said okay so imagine you take this new job and I understand you're worried it won't work out but what do you think the chances are that you're happy in that new position she said well like I'm not sure but I guess maybe it would be like 50 50 and I said well it's 50% greater than 0 and she said yes and she quit the next day and by the way she's much happier for it so that does seem more straightforward for you know either or decisions you had one great line from the book success does not lie in sticking to things it lies in picking the right thing to stick to and quitting the rest but that suggests you know from among multiple options picking the best one that's gonna give you the greatest chances of achieving the very most you can and so what do advise people to do when they're confronting multiple paths first of all ask yourself can I do any of these things in parallel as an example I was a professional poker player and I was a speaker focused on decision-making and I did some consulting obviously it made it a lot easier when I thought about quitting poker that I had something else to turn to and companies you know quite obviously have to do that they're pursuing multiple projects at once so what's a good way to figure out what's the strongest option versus the things that you should stop doing so one is just generally when you're choosing to start something you're gonna be taking your best guess at it so you want to collect as much information as you can hopefully you can get some base rates in other words sort of what happens in situations similar to the one you're considering get different perspectives of the members of your team think about the resources you have and then make your best forecast or educated guess about what the most fruitful paths to follow are gonna be and reject the rest but what comes with that because of these issues that we get stuck in stuff is that we have to think in advance about what would make us stop the thing that we're starting we could choose a path that's gonna work out 80% of the time and by definition that means it's not gonna work out 20% of the time and we don't have any control over that part of the equation so what I recommend for people to do is say imagine it's a year from now and things didn't work out they were kind of a disaster looking back you realize there were early signals that things weren't going well what were they and you write those things down so if it's a project it could have to do with blown timelines blown budgets product failures early signs that you don't have product market fit for example but you write those things down now you have created a list of what I would call kill criteria and when you observe those things in the world you stop and you now switch to something else which could be an option that you rejected in the past it could be a new option that you're newly considering and what that's gonna do is it it's gonna basically make it so that you're reducing the cost of choosing a path that ended up not working out well because what we have to remember again is that when we start things we're doing it under uncertainty the good news is that we can quit when we find out new information the bad news is the science tells us we don't do that so that's what we're trying to solve for yeah we do you know hear from Silicon Valley in particular or this whole idea fail fast which in essence is sort of quit fast right figure out a project isn't working and leave it behind so you can focus your energies elsewhere so what are some ways that you see organizations doing that yeah so first of all I just want to say I hate the term fail fast because it makes it seem like stopping something is a failure and I think that stopping something that isn't worthwhile is a success I want people to start saying succeed fast or quit fast I think this obsession with failure I'm not sure that it's helpful because it keeps tying quitting to failure and quitting is not a failure but there's another way that you can approach sort of the prioritization of projects which is to make sure that the path you're on is the right path to pursue because you've actually solved the hard part of the problem so let me try to explain using a mental model and this mental model comes from Astor Teller who is the CEO otherwise known as captain of moonshots over at X which is Google's innovation hub so obviously they're doing things that are highly uncertain when they choose to start a project mostly things are going to not work out, but if it does work out, it's going to create this amazing change for the world. And the way that Astor Teller approaches everything is that he wants to get to that answer really quickly, of whether the thing that they're pursuing is worth continuing with. And so he offers up this mental model, which I think is wonderful, called monkeys and pedestals. And here's how it goes. So, Allison, imagine that you've decided that you're going to create an act, and the act is that you're going to train a monkey to juggle flaming torches while standing on a pedestal. Now, obviously, people are going to give you tons of money for that. Yay. So, if you're going to approach that project, there's kind of two pieces to the project. One is training the monkey to juggle the flaming torches, and the other is building the pedestal. So, my question for you is what should you attack first? Well, I've read the book, so I would train the monkey. Right. Now, what's interesting, though, is that in normal project planning, people would build the pedestal first. And the reason for that is that the pedestal is also known as low hanging fruit. I'm sure that you've been in project meetings where people are like, well, what should we do? Well, what's the low hanging fruit? Let's do that first. Well, the problem with building pedestals first is that you already know you can do it. If you build the pedestal first, it's the illusion of progress. You're not actually making any progress because you already know you can do it. The bottleneck, the hard part of the problem, is if you can train that monkey to juggle the flaming torches, that's the thing that you don't know. So, what Astro Teller's mental model tells us is that we need to attack the hard part of the problem first. In other words, when we're thinking about pursuing something, we need to say, what are the unknowns? What are the bottlenecks to success? And let's not do anything until we figure out if we can solve for that. So, actually, here's a really good example of the power of monkeys and pedestals in terms of prioritization. So, at some point in X's history, they were pitch the hyperloop, essentially a vacuum tube that will take a train from coast to coast in the United States in like two hours. So, in this particular case, the technology itself wasn't a monkey because that had already been proven you could move things through these tubes just fine, but they did identify two monkeys that they didn't know if they could solve for. The first had to do with regulatory problems, which was that you're going to have to move this system through many, many different townships. These of them are going to have different regulations. And that seemed like a very tough problem to solve. And separate, and apart from that, really, to know whether this thing is going to work, you have to know, given the speeds that this is going to run at, that you can stop the train safely without killing people on board. So, that's a pretty big monkey, right? And so, as they discussed it, they realized that in order to get the train all the way up to speed, that you basically have to build almost the whole thing. Before you could figure out if you could stop it safely, which is tons and tons and tons of money, before we can figure out whether we can actually stop the thing safely. So, they've rejected the idea. How long did it take them to reject it using monkeys and pedestals? It took them 15 minutes. Now, let's compare that to Virgin, who did decide to pursue the Hyperloop. They've raised hundreds of millions of dollars for this. And there was just an article in the New York Times, maybe a month or so ago, where they said, "Oh, the Hyperloop is in trouble." We can't figure out if we're going to be able to build this all the way across country, given the fact that every single township has different roles. But then the other thing was that they had only ever built enough of the system to get the train up to one sixth of the speed that it would eventually reach. They had never been able to accomplish a real safety test. At which point, they did not abandon ship. Instead, they're pivoting, let's say, to instead of wanting to bring people across country, they want to bring cargo across country, which is a problem that we don't really have. Let me give you a counter example, though. So we've all heard the story of the James Webb telescope that was years and hundreds of millions of dollars in development, many, many challenges, setbacks, they finally created a design, and they did deploy it. And it's now sending us pictures from the deepest reaches of space. So it does sometimes work, right, to grit, not quit. I'm not at all saying that you shouldn't stick to things. It's that you should stick to things that are worthwhile. So I imagine with the James Webb telescope while there were setbacks, they did actually have the monkey solved. In other words, they did understand that they could build the lens. They knew that they could launch it into space. I mean, we already had the Hubble telescope up there, right? Like the hard part of the problem, I'm sure that they were very confident that they could solve. Yeah, and if you've decided that you can solve the hard part of the problem and the payoff is great enough, then you have to grade out the setbacks also. I have no issue with that whatsoever, including in your own life. Yeah, and I was going to ask you about sort of famous founders and CEOs and politicians and musicians and actors and athletes who do face sons of adversity and they don't give up on their dreams and they end up really successful, but I imagine it's the same thing. It's like they've made that calculated risk that they have the talent or they have the connections or they have the drive, frankly, to get to where they want to go to get to that goal. Yeah, I mean, look, first of all, I want to be really careful of survivorship bias here, right? So I want to be really careful about the founder who got down to their last 50,000 couldn't raise another round kept at it and somehow managed to turn it around and have us take the lesson from that that you should get down to your last 50,000 and you know, keep going, right? Yeah, we all know most founders fail. Right, so, but again, I think it's a calibration issue. Great is great. Like sometimes you see something that other people don't see, but sometimes when the world is yelling at you to stop and you ignore them. That's no longer a virtue, then it's folly. So that leads me to ask you just about one other saying that you hear all the time quit while you're ahead. Do you believe that that's the right thing to do? Well, your head is like terrible advice, but then again, all advice about quitting is terrible advice. So you have like, you know, winners never quit, quitters never win so and so forth. So we know that that's really bad advice because winners quit a lot. They quit all the things that aren't worthwhile so that they can stick to the things that are quit while your head is also really bad advice because the areas we make about quitting are mostly quitting too late, but occasionally it has to do with quitting too early and specifically when we quit too soon is when we're ahead. So just a really simple example when you look at retail traders, well, retail traders will also put in take gain orders. It's like you buy it at 50 at 60. You're going to automatically sell it and take the gain and what happens there is that they also cancel those orders, but in order to sell it at 55. In other words, they'll sell much earlier than the take gain that they've set in place. Why? Because when we're ahead, we love to quit and turn those gains on paper into realize gains because we don't want to keep the risk on. And so we don't need advice quit while you're ahead because we already do it in fact too soon. Terrific. Well, thank you so much for teaching us about the value of sometimes quitting and not gritting. It's been a pleasure. Well, thank you very much. That's Annie Duke, author of Quit, the power of knowing when to walk away. If you like today's episode, we have more podcasts to help you manage yourself, your team, and your organization. Find them at hbr.org/podcasts or search hbr in Apple podcasts, Spotify or wherever you listen. This episode was produced by Mary Dew. We get technical help from Rob Eckhart, Hannah Bates is our audio production assistant, and Ian Fox is our audio product manager. Thanks for listening to the hbr.idea cast. We'll be back with a new episode on Tuesday. I'm Alison Beard.