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The Jobs-to-Be-Done Framework for Product Builders · Deep Tech Germany – AI, Robotics & Frontier Innovation by Startuprad.io™

• WEBVTT 00:00:04.997 --> 00:00:12.737 Welcome to StartupRed.io, your podcast and YouTube blog covering the German 00:00:12.737 --> 00:00:17.617 startup scene with news, interviews and live events. 00:00:20.317 --> 00:00:24.197 Hello and welcome, everybody. This is Joe from StartupRate.io, 00:00:24.337 --> 00:00:27.397 your startup podcast and YouTube blog from Germany, Austria, 00:00:27.397 --> 00:00:33.837 and Switzerland, bringing you today another episode in our series of entrepreneurship. 00:00:34.497 --> 00:00:38.537 Therefore, I would like to welcome Anthony, who actually goes by the name of 00:00:38.537 --> 00:00:39.797 Tony. Hey, how are you doing? 00:00:40.497 --> 00:00:44.297 Joe, how's it going? I'm doing well. Thank you. I'm also doing good. 00:00:44.437 --> 00:00:47.957 Glad to have you as a guest here. we'll talk 00:00:47.957 --> 00:00:52.637 about innovation today for 00:00:52.637 --> 00:00:55.957 the very simple reason you have quite a 00:00:55.957 --> 00:01:02.657 history in working on innovation and innovation consulting you have published 00:01:02.657 --> 00:01:09.137 in Harvard Business Reviews and you are the creator of outcome driven innovation 00:01:09.137 --> 00:01:15.297 which is pretty cool but before that can you take us a little bit through your Civi, 00:01:15.457 --> 00:01:19.817 what have you done in the past and how you arrived at the knowledge you want 00:01:19.817 --> 00:01:23.137 to share with us today? Sure. I'd be happy to, Joe. Thank you. 00:01:23.797 --> 00:01:30.897 Yeah. My career started back at IBM in the 1980s. I worked there for 10 years from 81 to 91. 00:01:31.197 --> 00:01:34.577 And I have an engineering background, MBA. 00:01:35.697 --> 00:01:40.557 I was working on a product called the PC Junior, if anyone's familiar with that. 00:01:41.057 --> 00:01:46.637 The PC Junior was It was supposed to compete with Apple's home computer. 00:01:46.897 --> 00:01:50.777 It was gonna change and revolutionize the way people view home computing. 00:01:51.597 --> 00:01:57.017 But instead, the day after the product was introduced, the headlines in the 00:01:57.017 --> 00:02:00.097 Wall Street Journal read, the PC Junior is a flop. 00:02:02.630 --> 00:02:07.050 And, Joe, it was. It took us about a year to reconcile and come to grips with 00:02:07.050 --> 00:02:08.510 the fact that it was a failed product. 00:02:08.990 --> 00:02:11.690 And it cost IBM about a billion dollars. 00:02:12.590 --> 00:02:16.910 Now, this was my first product I had worked on, and I didn't realize that that 00:02:16.910 --> 00:02:18.410 kind of thing happened all the time. 00:02:18.570 --> 00:02:22.370 I wondered how a company like IBM, with all its vast resources, 00:02:22.630 --> 00:02:24.810 could make such a poor investment. 00:02:25.670 --> 00:02:30.570 But I realized it wasn't just IBM. It was many companies. And it's oddly enough, 00:02:30.590 --> 00:02:32.550 it's still not back in the 1980s, right? 00:02:32.610 --> 00:02:38.130 It's still happening today where companies often create products that fail in the market. 00:02:39.790 --> 00:02:43.230 And that really got my interest, especially the engineer in me to figure out 00:02:43.230 --> 00:02:48.610 how can we create a process that's more predictable so that we know that the 00:02:48.610 --> 00:02:52.530 products that we're creating will win in the market before we launch them. 00:02:52.810 --> 00:02:56.850 In fact, ideally, before we even start developing them, we want to know that 00:02:56.850 --> 00:03:00.930 they're going to win. So we're not creating products that will fail in the market. 00:03:01.210 --> 00:03:05.650 And that led me down the path to create the outcome-driven innovation process. 00:03:06.570 --> 00:03:07.830 I see, I see. 00:03:09.210 --> 00:03:15.050 You said you are an engineer by training. Are you still running around in your house and fix stuff? 00:03:16.770 --> 00:03:21.810 Yeah, in fact, I am. I see. 00:03:21.810 --> 00:03:28.390 So basically, you were one of the IBM engineers trying to compete with Apple 00:03:28.390 --> 00:03:35.330 home computer and in the very, very early days of the personal computer. 00:03:35.570 --> 00:03:41.070 And you came up with theories, jobs to be done and outcome driven innovation. 00:03:41.070 --> 00:03:46.210 Can you take us a little bit into this project, into this journey, 00:03:46.450 --> 00:03:52.670 how you started developing those frameworks, and where are they different? Sure. 00:03:53.190 --> 00:03:56.350 Well, back in the 1980s, when I started looking around to see, 00:03:56.490 --> 00:04:01.250 well, what is available, that was back in the early days of voice of the customer, 00:04:02.070 --> 00:04:05.470 the house of quality in QFD, conjoint analysis. 00:04:06.050 --> 00:04:11.750 And I realized very quickly that there is no process or there was no process for innovation. 00:04:13.130 --> 00:04:16.170 And I thought, well, let's go create it. 00:04:16.430 --> 00:04:21.490 And what really occurred to me in that PC Junior failure was how the folks at 00:04:21.490 --> 00:04:25.890 the Wall Street Journal knew the very next day that the product was a failure. 00:04:27.390 --> 00:04:31.230 Clearly, they were using some set of metrics to judge the value of the product 00:04:31.230 --> 00:04:33.550 that we did not use to build the product. 00:04:34.190 --> 00:04:38.870 And the thought was, would it be possible to understand the metrics people are 00:04:38.870 --> 00:04:43.190 going to use to judge the value of your product before you start creating it? 00:04:43.690 --> 00:04:49.150 And that way I can say, hey, I know I'm creating a lot more value than my competing products. 00:04:50.416 --> 00:04:54.556 And if I can prove that to myself, then I should feel much more confident that 00:04:54.556 --> 00:04:56.536 the investments I'm making are 00:04:56.536 --> 00:05:00.756 much lower risk and that I will create a product that people will want. 00:05:01.336 --> 00:05:03.996 That was the basic thinking. Is that possible? 00:05:04.976 --> 00:05:10.496 And I thought, well, it had to be possible, but it's been escaping people. 00:05:11.476 --> 00:05:15.396 What really connected the dots for me was the quote from Theodore Leavitt. 00:05:15.736 --> 00:05:18.456 People don't want the quarter-inch drill. They want a quarter-inch hole. 00:05:19.676 --> 00:05:24.916 And I thought, well, this gives us an option, right? We don't have to study 00:05:24.916 --> 00:05:26.496 how to create a better drill. 00:05:26.796 --> 00:05:31.076 Why don't we study the underlying process of creating a quarter-inch hole? 00:05:31.796 --> 00:05:36.356 Now we can go study a process because as an engineer, I love that, right? You can study. 00:05:36.476 --> 00:05:39.836 I was on the manufacturing line studying the manufacturing process, 00:05:40.236 --> 00:05:44.916 right, where you automate things and you eliminate variability and you reduce defects. 00:05:45.396 --> 00:05:51.216 And I thought, if you could study what we eventually call the customer's job 00:05:51.216 --> 00:05:55.236 to be done and break it down into its component parts and figure out how do 00:05:55.236 --> 00:05:57.536 they measure success along each step of the way, 00:05:57.916 --> 00:06:01.196 then we could create solutions that get the job done better. 00:06:01.616 --> 00:06:05.156 And is the solution a quarter-inch drill? Maybe not. Maybe it's something else. 00:06:05.196 --> 00:06:06.936 Let's not assume the solution up front. 00:06:07.356 --> 00:06:11.456 Let's instead focus on what problems customers are trying to solve. 00:06:12.096 --> 00:06:16.636 And again, the key there is viewing the problem as a process the customer is 00:06:16.636 --> 00:06:21.196 trying to execute so that you can start applying Six Sigma thinking, 00:06:22.156 --> 00:06:27.496 lean thinking, statistical process control thinking to solve the problem. 00:06:27.736 --> 00:06:30.636 Okay, so basically your thought was…. 00:06:32.494 --> 00:06:38.974 You want to understand the customer and the process they are using to solve a problem. 00:06:39.134 --> 00:06:46.514 So basically, then your product, the quarter-inch drill, would fit in. Is that about right? 00:06:47.274 --> 00:06:50.314 It might fit in, right? Let's not assume that it will, right? 00:06:51.474 --> 00:06:55.954 Let's study the job of creating a quarter-inch hole and figure out how do people 00:06:55.954 --> 00:06:57.894 measure success when creating a quarter-inch hole? 00:06:58.194 --> 00:07:02.094 Well, I want to start at the right location. You know, I want to make sure I 00:07:02.094 --> 00:07:06.974 don't make the hole too big, too wide, too deep. 00:07:07.174 --> 00:07:12.794 I want to make sure I don't hit it at an angle, right? I have to hit it at 90 degrees. 00:07:13.714 --> 00:07:19.294 I want to minimize the likelihood that burrs occur, little wood spurs, 00:07:19.534 --> 00:07:22.434 when I'm making the hole, right? 00:07:22.594 --> 00:07:26.534 There's a whole bunch of metrics that you think about, and maybe there's a better solution. 00:07:26.694 --> 00:07:30.994 Maybe it's a hole punch. Maybe it's a laser. Maybe it's something we haven't 00:07:30.994 --> 00:07:34.014 even thought of yet from a technology standpoint. 00:07:34.094 --> 00:07:36.334 Dynamite. Right? Maybe it's dynamite. 00:07:37.754 --> 00:07:42.654 And a very controlled experiment. I can see what you did when you were a kid playing in the garage. 00:07:44.734 --> 00:07:48.114 Don't tell anyone. I think I understood the idea. 00:07:48.534 --> 00:07:53.634 Can you give us an example? Can we make up an example? Like really that so that 00:07:53.634 --> 00:07:59.214 our audience starts to understand what is the framework all about and how could 00:07:59.214 --> 00:08:06.634 I apply to an everyday problem to something different than a whole? Yeah, absolutely. 00:08:07.274 --> 00:08:11.014 Well, you know, the key thing to think here is that it goes back to the basic 00:08:11.014 --> 00:08:12.514 reason why people buy products. 00:08:12.794 --> 00:08:15.834 The way we say it now, people buy products to get a job done. 00:08:16.054 --> 00:08:19.094 Right. What we want to know is, well, what is that job? 00:08:19.594 --> 00:08:24.074 And then can we break it down into its component parts using what we call a job map? 00:08:24.234 --> 00:08:29.894 And then go even a step lower and understand needs at this, we call it the outcome level. 00:08:30.294 --> 00:08:36.634 So the example can be preparing a meal at home. We all do this, right? Or cook a meal. 00:08:38.434 --> 00:08:42.374 And there's metrics you use to judge if it's going well or not. 00:08:43.054 --> 00:08:49.274 Like you may all of a sudden say, oh, man, I just burnt part of the meal. 00:08:49.514 --> 00:08:52.234 It got too hot on one side of the pot, right? 00:08:52.614 --> 00:08:58.354 Well, the need is you want to minimize the likelihood of burning the meal, right? 00:08:58.674 --> 00:09:02.374 More specific, I want to minimize the likelihood of overcooking the meal or 00:09:02.374 --> 00:09:05.794 undercooking it. I want to minimize the likelihood that it's not cooked evenly. 00:09:06.294 --> 00:09:10.234 I want to minimize the time it takes to portion out the meal. 00:09:11.346 --> 00:09:14.946 I want to minimize selective over-portioning or under-portioning, right? 00:09:15.066 --> 00:09:20.006 You can start laying all these metrics in place that say, hey, 00:09:20.066 --> 00:09:26.086 if I had the right tool set, I can create a meal perfectly, right? 00:09:26.206 --> 00:09:29.566 Where everything just comes out just fine, right? 00:09:30.206 --> 00:09:35.066 And in most situations, there's 100 different metrics or more, 00:09:35.206 --> 00:09:38.326 especially when you get to some more complicated things. preparing a meal is 00:09:38.326 --> 00:09:43.346 somewhat complicated, oddly enough, but performing a surgical procedure is far more. 00:09:44.246 --> 00:09:49.226 But uncovering what those metrics are is the first step. 00:09:50.126 --> 00:09:56.466 All right, we want the list of 100 metrics. That tells us what the needs are. 00:09:56.666 --> 00:10:01.106 Now, what we don't know yet is which needs are unmet, right? 00:10:01.106 --> 00:10:06.566 So here we rely on quantitative research to go figure out from customers which 00:10:06.566 --> 00:10:10.786 Each of these outcomes are really important and not well satisfied with today's solutions. 00:10:11.626 --> 00:10:16.446 So we ask people, what solution are you using? And what is the importance level 00:10:16.446 --> 00:10:18.726 of each outcome in the current satisfaction level? 00:10:19.186 --> 00:10:21.626 And from there, we can figure out which needs are unmet. 00:10:22.896 --> 00:10:27.256 The goal here at a high level, the goal here is we want to come up with a product 00:10:27.256 --> 00:10:33.296 that's going to get the job done significantly better, meaning 15% to 20% or more. 00:10:33.536 --> 00:10:37.116 That's the threshold we've determined really makes a difference. 00:10:37.476 --> 00:10:40.656 And you can think about this, Joe. Like, would you ever switch from your favorite 00:10:40.656 --> 00:10:45.196 brand if it's going to get the job done 1% better or 2% better? 00:10:45.996 --> 00:10:48.796 Probably not, right? There's got to be some significant movement. 00:10:48.796 --> 00:10:53.476 And we have to be able to prove that the concept that we're about to go develop 00:10:53.476 --> 00:10:59.216 will address the top unmet needs significantly better than current solutions. 00:10:59.736 --> 00:11:02.616 So we have to know what all those needs are, which ones are unmet, 00:11:02.796 --> 00:11:06.976 and then systematically come up with solutions that will address those unmet needs. 00:11:07.816 --> 00:11:12.716 That was actually the first question that popped into my mind going through 00:11:12.716 --> 00:11:16.336 those steps in jobs to be done, understood. 00:11:16.336 --> 00:11:23.736 It, where would be a place in this very big world here today for entrepreneurs 00:11:23.736 --> 00:11:26.776 listening to this, speaking different languages, 00:11:27.396 --> 00:11:35.016 where would you think there is like a big place where you can find jobs, problems to be solved? 00:11:35.696 --> 00:11:37.356 Would you look on Reddit? 00:11:39.516 --> 00:11:46.476 Well, you're asking a really important question, which is, which problem, 00:11:46.736 --> 00:11:49.036 meaning which market, should I even go after? 00:11:49.336 --> 00:11:55.456 I think that's what you're saying, right? I want to help the audience to guide 00:11:55.456 --> 00:12:01.516 them to places where they find really important jobs, meaning places. 00:12:01.516 --> 00:12:10.296 If they develop any kind of product, they'll very soon be able to make a living 00:12:10.296 --> 00:12:11.836 from that because nobody... 00:12:12.544 --> 00:12:17.084 Too many people care if you have a product that makes an annual revenue of $1,000. 00:12:17.944 --> 00:12:23.884 But if you're talking like $10 million annual revenue, people are getting interested. 00:12:23.924 --> 00:12:26.884 Plus, you can make a living from that. A very good one, by the way. 00:12:27.024 --> 00:12:32.184 And that is something I want to help to guide our audience towards. 00:12:33.244 --> 00:12:38.264 Well, you're on the right point. Because if you pick a market that's not attractive, 00:12:38.704 --> 00:12:43.324 you're going to fail. even if you came up with a decent product, right? 00:12:43.484 --> 00:12:45.904 So you need to pick a good market. 00:12:47.084 --> 00:12:52.684 So how do we define a market? Some people define markets around a technology 00:12:52.684 --> 00:12:58.584 or a product or a vertical or geography, a territory, but we're going to define 00:12:58.584 --> 00:13:00.904 a market around the jobs we've done lens. 00:13:01.064 --> 00:13:06.104 So we say, if people buy products and services to get a job done, 00:13:06.364 --> 00:13:10.844 let's define a market as a group of people and the job they're trying to get done. 00:13:11.004 --> 00:13:15.304 And my understanding would be if you have people with the same problem, 00:13:15.524 --> 00:13:19.544 it doesn't make a lot of difference if you have the right product, 00:13:19.784 --> 00:13:23.604 if they are located in San Francisco, in Shanghai, or in Stuttgart. 00:13:24.144 --> 00:13:27.184 That's exactly right. That's the beauty of jobs to be done, right? 00:13:27.704 --> 00:13:31.104 There's people around the globe who have the same problem, right? 00:13:31.304 --> 00:13:34.004 Like parents, a group of people, right? 00:13:34.504 --> 00:13:36.584 Trying to pass on life lessons to children. 00:13:37.204 --> 00:13:40.064 That's a job to be done. That would be a market. 00:13:40.424 --> 00:13:44.404 So as an entrepreneur, you could say, I can go after parents who are trying 00:13:44.404 --> 00:13:47.784 to pass on life lessons to children, and that's the market I'm going to serve. 00:13:49.084 --> 00:13:53.524 Or you could say, hey, I'm going to go after interventional cardiologists and 00:13:53.524 --> 00:13:57.524 help them restore blood flow in an artery, and I'm going to create a product that does that. 00:13:58.524 --> 00:14:04.784 Or I'm going to work with chefs and create products that will help them prepare a meal. 00:14:05.924 --> 00:14:10.484 You pick, right? You can pick from thousands, tens of thousands of possible 00:14:10.484 --> 00:14:12.904 markets. So which one's most attractive? 00:14:13.244 --> 00:14:17.484 Well, first off, one in which you probably have the capability to go address. 00:14:18.004 --> 00:14:22.004 That's probably key. If you have no skill set in that space, 00:14:22.204 --> 00:14:25.084 you're going to be spending a lot of time, 00:14:26.255 --> 00:14:30.575 experimenting and getting things wrong. So pick something in your bailiwick, right? 00:14:31.155 --> 00:14:34.235 Second, what kind of job would you rather focus on? 00:14:34.335 --> 00:14:40.555 One that's executed by 10,000 people around the globe or one that's executed 00:14:40.555 --> 00:14:44.975 by 300 million people around the globe, right? 00:14:45.175 --> 00:14:49.135 So understanding how many people are getting that job done is critical. 00:14:50.195 --> 00:14:54.935 Understanding are they underserved? Understanding if they're willing to pay 00:14:54.935 --> 00:14:56.315 more to get the job done better. 00:14:57.495 --> 00:15:02.715 This helps you choose from all the possible markets to one that's going to be 00:15:02.715 --> 00:15:06.175 attractive, which would be one that you have the capability to address. 00:15:06.455 --> 00:15:10.115 It's large. A lot of people are trying to get the job done. They're underserved. 00:15:10.475 --> 00:15:13.695 Today's solutions aren't serving the market as well as they could. 00:15:14.295 --> 00:15:18.235 That would be a place to start. Trying to pick your brain here again. 00:15:18.235 --> 00:15:23.835 Where would you personally go right now to find a job to be done? 00:15:24.195 --> 00:15:30.495 For me personally, it would be some place where a lot of people are and writing about the problem. 00:15:30.675 --> 00:15:34.915 That's why I, for example, threw in Reddit as an example. 00:15:36.455 --> 00:15:42.915 We have like a few more places where you could find jobs to be done. 00:15:42.915 --> 00:15:49.615 Maybe not necessarily the emergency room of a big hospital trying to avoid accidents or something. 00:15:50.415 --> 00:15:54.135 Joe, any of those sources are great. Like you can use your imagination to say, 00:15:54.335 --> 00:15:56.115 and I've been using AI for this. 00:15:56.295 --> 00:15:59.775 You can ask AI with the right prompting. 00:16:00.275 --> 00:16:06.535 Like we've created our own GPTs that have ODI thinking built into it. 00:16:06.655 --> 00:16:12.795 And we can ask, you know, give me a list of the top 10 problems that product managers have. 00:16:13.375 --> 00:16:18.655 I've created this list, right? And it comes up with that list of problems. 00:16:18.675 --> 00:16:22.915 And you can help them solve one of them, two of them, or try to solve all of them. 00:16:24.636 --> 00:16:28.876 But the key thing is pick your group of people first. 00:16:30.656 --> 00:16:33.276 Because if you say, hey, I just want to pick a job to be done, 00:16:33.396 --> 00:16:36.516 it could be for anybody. It's so broad. 00:16:37.076 --> 00:16:39.416 What's often easier, especially if you want to go on Reddit, 00:16:39.856 --> 00:16:41.756 you know, pick an audience. 00:16:42.836 --> 00:16:49.276 Where are parents struggling? Where are parents with new children struggling to get the job done? 00:16:49.376 --> 00:16:52.336 Or what jobs are they trying to get done? Now we're down to something. 00:16:53.556 --> 00:16:58.696 Yeah you got that right trying to get to sleep at night and stay asleep at night that's a big deal. 00:17:00.856 --> 00:17:06.596 And underserved right if you're a parent with young kids you know that um so it's, 00:17:07.276 --> 00:17:12.016 it's narrowing it down right and that's that's the market selection part of 00:17:12.016 --> 00:17:16.996 the process it's just choosing which problem do i want to help a group of people 00:17:16.996 --> 00:17:23.076 solve and what will be the next step? You have a market, a group of people. 00:17:23.356 --> 00:17:28.716 You have a problem, a job they need to be done. And how would you then approach the next steps? 00:17:28.936 --> 00:17:33.636 We want to really understand that problem at a deep granular level. 00:17:34.216 --> 00:17:36.436 So we wrote an article in the Harvard 00:17:36.436 --> 00:17:40.456 Business Review back in 2008 that introduced what we call the job map. 00:17:41.596 --> 00:17:49.196 The job map is not a process map. It's the opposite, right? A process map lays 00:17:49.196 --> 00:17:51.656 out what people are doing in solution space. 00:17:52.336 --> 00:17:56.976 A job map lays out what people are trying to do in problem space. 00:17:57.476 --> 00:17:59.476 So it's devoid of the solution. 00:18:00.036 --> 00:18:03.876 So a surgeon may be trying to remove an anatomical structure. 00:18:04.136 --> 00:18:11.656 So they have to gain access to the vascular system. They have to find the pathway 00:18:11.656 --> 00:18:12.576 to where they're going to go. 00:18:12.716 --> 00:18:19.096 They have to navigate to get there. They have to close off the blood supply to the structure. 00:18:19.596 --> 00:18:21.296 They have to remove the structure. 00:18:22.716 --> 00:18:27.016 I'm not saying how they're doing any of that, right? But this is the process 00:18:27.016 --> 00:18:30.196 they're going through. This is what they're trying to do to get the job done. 00:18:31.336 --> 00:18:36.216 So this goes a long way because if you just create a job map, 00:18:37.136 --> 00:18:39.756 and this can be done with a handful of interviews with customers, 00:18:39.756 --> 00:18:46.436 If you can create that job map, you know right up front, are there parts of 00:18:46.436 --> 00:18:49.876 the job where people are struggling more to get the job than others? 00:18:50.216 --> 00:18:54.176 We find there's many markets, there's steps in the job that nobody's getting done. 00:18:54.756 --> 00:18:58.236 We find that most products only get parts of jobs done. 00:18:59.960 --> 00:19:05.220 So all this is great news for entrepreneurs who are saying, how am I going to win in the market? 00:19:05.500 --> 00:19:09.300 Well, you're going to get more of the job done better than the competing solutions. 00:19:09.940 --> 00:19:12.900 Those steps that they're ignoring, you're going to tackle. 00:19:13.300 --> 00:19:17.420 Is it, would it be just rephrasing? 00:19:17.760 --> 00:19:20.720 You go through a process, for example, the surgery you described, 00:19:20.840 --> 00:19:30.220 and then interview a few of those surgeons, and they describe different problems, jobs to be done, 00:19:30.480 --> 00:19:36.160 problems to be solved, and you basically make a list, map them on the process. 00:19:36.320 --> 00:19:42.540 And the more people you have, the more you understand this is a big problem 00:19:42.540 --> 00:19:46.600 for many, this is a big problem, this is a minor problem, this is just a problem 00:19:46.600 --> 00:19:49.540 for one person. Would it be something like that? 00:19:50.440 --> 00:19:53.780 Well, I'm going to caution you in the language that you're using there because 00:19:53.780 --> 00:19:58.400 the hierarchy is not all jobs to be done, right? 00:19:58.820 --> 00:20:03.520 There's only one job to be done, right? This is where people get confused, right? 00:20:03.680 --> 00:20:08.140 Removing the anatomical structure, that's the job to be done, right? 00:20:08.220 --> 00:20:11.220 Surgeons may try to, there's other jobs they try to get done, 00:20:11.320 --> 00:20:13.580 but you have to pick the one that you're going to go focus on. 00:20:14.180 --> 00:20:20.440 So removing the anatomical structure would be a great job. So that becomes the job to be done. 00:20:20.940 --> 00:20:22.940 Then you break it down into job steps. 00:20:23.460 --> 00:20:28.260 So we call these job steps, job steps, because they're not the job to be done, right? 00:20:28.700 --> 00:20:33.700 The job is this big thing. The steps are gaining access to the vasculature. 00:20:34.920 --> 00:20:39.060 Finding the pathway, navigating to the pathway, shutting off the blood supply. 00:20:40.074 --> 00:20:44.974 Those are all part of removing an anatomical structure, right? 00:20:45.174 --> 00:20:49.994 So we lay out that job map, and then we go a level lower, and we call these 00:20:49.994 --> 00:20:52.554 the outcomes, the customer's desired outcomes. 00:20:52.974 --> 00:20:56.654 These are the real needs. These are the granular level needs. 00:20:56.654 --> 00:21:04.634 So as I'm trying to gain access to the structure, I want to minimize the likelihood 00:21:04.634 --> 00:21:10.854 that I cause damage to surrounding tissue as I'm navigating through the vasculature. 00:21:11.134 --> 00:21:19.214 I want to minimize the likelihood of bleeding when I'm transecting the vessels 00:21:19.214 --> 00:21:22.174 that go to the structure that I'm trying to remove. 00:21:22.934 --> 00:21:29.714 Again, there's 100 very specific granular outcomes or needs that surgeons are 00:21:29.714 --> 00:21:32.734 trying to address when they're getting the job done. 00:21:33.834 --> 00:21:35.934 We want that entire list. So 00:21:35.934 --> 00:21:39.854 when we go talk to surgeons, we ask them to take us through the journey. 00:21:40.274 --> 00:21:45.314 I like thinking about it like this, Joe. I ask them to go on this very slow, 00:21:45.554 --> 00:21:50.934 slow motion journey with us to tell us what are these steps they go through. 00:21:50.934 --> 00:21:54.734 And then for every step, what are the outcomes they're trying to solve? 00:21:54.874 --> 00:21:57.834 What's the next thing they're trying to do? What are they trying to avoid? 00:21:58.294 --> 00:22:03.654 And we build out this entire hierarchy of customer needs so we can understand the entire market. 00:22:05.091 --> 00:22:10.071 Of removing the anatomical structure that gives us our basis of knowing what 00:22:10.071 --> 00:22:16.031 all the needs are in the market right that's the first step the next step is 00:22:16.031 --> 00:22:17.491 to figure out well which of those are unmet, 00:22:18.271 --> 00:22:23.031 so the first step is putting putting the model together the beauty of this too 00:22:23.031 --> 00:22:29.031 joe is once you put the model together it's valid for years to come right how 00:22:29.031 --> 00:22:32.031 long have surgeons been trying and remove an anatomical structure? 00:22:33.991 --> 00:22:38.171 Decades, centuries, right? Yep. And how are they measuring success? 00:22:38.371 --> 00:22:42.531 They're using the same measures today that they used 20, 30 years ago. 00:22:42.911 --> 00:22:46.871 What's different, the technologies that have come along to help them get the 00:22:46.871 --> 00:22:50.271 job done better raises their satisfaction level on these outcomes. 00:22:52.671 --> 00:22:55.251 And what we're trying to figure out at any given point in time is, 00:22:55.551 --> 00:22:58.991 well, which of these outcomes are really important and poorly satisfied? 00:23:01.311 --> 00:23:06.831 And we do that quantitatively. So we would take a survey, put it out to some 00:23:06.831 --> 00:23:11.291 number of customers or potential customers, competitors, customers, 00:23:11.791 --> 00:23:16.531 and ask them to tell us how important each outcome is and the level of satisfaction 00:23:16.531 --> 00:23:19.591 using the solution they have today. 00:23:20.451 --> 00:23:25.031 And from there, we can calculate it out. We use what we call the opportunity 00:23:25.031 --> 00:23:30.191 algorithm. If an outcome is very important and the difference between the importance 00:23:30.191 --> 00:23:33.791 of satisfaction is great, we say the need's unmet. 00:23:34.111 --> 00:23:38.411 So, in other words, if 90% of the population says this is very or extremely 00:23:38.411 --> 00:23:43.231 important and only 20% of the population saying this is very or extremely satisfied, 00:23:43.231 --> 00:23:46.451 we're going to flag that as an unmet need. 00:23:47.791 --> 00:23:50.491 And what we're looking for in the market at any given time is, 00:23:50.611 --> 00:23:56.651 are there 10 or 15 or 20 or 30 unmet needs that we could potentially go better 00:23:56.651 --> 00:23:58.551 address to get the job done better? 00:24:00.271 --> 00:24:05.351 So we identify those needs, and then we work to come up with the solutions that address them. 00:24:05.711 --> 00:24:09.731 And if we can do that successfully, we know we've created a product concept 00:24:09.731 --> 00:24:13.091 that will get the job done significantly better when in the market. 00:24:13.951 --> 00:24:17.451 All this is doable before I spend the first development dollar. 00:24:19.251 --> 00:24:24.071 Because I'm proving on paper that the idea I have is going to move the needle 00:24:24.071 --> 00:24:25.891 along all these important dimensions. 00:24:26.571 --> 00:24:31.491 Just like in the IBM example, what were the metrics that those folks were using 00:24:31.491 --> 00:24:32.791 to judge the value of the product? 00:24:33.571 --> 00:24:38.011 Once I know them, I can just make sure I'm designing the product to address those metrics. 00:24:38.771 --> 00:24:43.571 So that it's like you're stacking the odds in your favor. The way I like thinking about it is this. 00:24:43.811 --> 00:24:47.911 What are the chances of a team randomly coming up with a solution that addresses 00:24:47.911 --> 00:24:54.191 the top 15 unmet needs in the market if they don't know what those unmet needs are? I see. 00:24:55.451 --> 00:25:00.651 About zero, right? But what are the chances of them coming up with a successful 00:25:00.651 --> 00:25:04.191 product if they know and agree on the top 15 unmet needs in the market? 00:25:06.064 --> 00:25:10.324 It goes up dramatically. And that's why the process we use has an 86% success 00:25:10.324 --> 00:25:14.904 rate, because we can prove whether or not we should even enter the market. 00:25:15.424 --> 00:25:20.044 If we don't come up with a concept that's going to get the job done better, then don't build it. 00:25:22.424 --> 00:25:28.284 Yes, exactly. Unless you needed to build a whole package for Coin. 00:25:28.424 --> 00:25:31.884 That would be a possibility, but then you wouldn't be a startup anymore. 00:25:32.744 --> 00:25:36.624 No, that's right. You're growing from the core. at that point. 00:25:37.644 --> 00:25:43.564 I see. And let us know that we understood a little bit jobs should be done. 00:25:43.804 --> 00:25:49.544 That's basically a framework to analyze demands for your clients. 00:25:50.464 --> 00:25:57.764 And how would you then proceed when you have jobs where the market potential is big enough? 00:25:58.224 --> 00:26:02.664 When you say the job potential is big enough, meaning there's a large number 00:26:02.664 --> 00:26:04.204 of people that are underserved. 00:26:04.984 --> 00:26:08.984 Yes, exactly. Right. Well, that's what we just discovered in that quantitative 00:26:08.984 --> 00:26:11.164 research analysis that I just described. 00:26:11.344 --> 00:26:13.364 Right. We do that every one of those outcomes. 00:26:15.164 --> 00:26:20.404 So we're getting data on 100 different outcomes. We know precisely which outcomes 00:26:20.404 --> 00:26:22.704 are really important and not well satisfied. 00:26:24.184 --> 00:26:29.364 So we know for every outcome, if we satisfy this, that will impact 5% of the market. 00:26:29.584 --> 00:26:35.624 If we satisfy that one, that'll satisfy or impact 80% of the market. Let's do that one. 00:26:36.844 --> 00:26:40.484 What we're looking for is what I call the most efficient path to growth. 00:26:40.984 --> 00:26:46.084 You're trying to figure out which needs are underserved across the biggest population. 00:26:47.104 --> 00:26:51.124 So if there's a need that's underserved across 90 or 100% of the population, 00:26:52.024 --> 00:26:53.664 that's where you want to focus, right? 00:26:53.744 --> 00:26:57.844 It's going to impact everybody. And if you can find 10 of those needs that are 00:26:57.844 --> 00:27:00.684 cut across the entire customer population, 00:27:01.725 --> 00:27:06.545 That's the path to growth. So discovering what those needs are that are unmet 00:27:06.545 --> 00:27:10.825 across the largest population is the goal of the research. 00:27:12.445 --> 00:27:15.605 And once you have the answer, you know where to go focus. 00:27:16.145 --> 00:27:21.545 Again, we're flipping this around. Instead of hoping my product addresses the 00:27:21.545 --> 00:27:26.405 top 15 limit needs, we're going to make sure they address the top 15 limit needs 00:27:26.405 --> 00:27:27.325 because we know what they are. 00:27:27.325 --> 00:27:32.425 I think I have a pretty good understanding, as well as our audience now, 00:27:32.865 --> 00:27:35.465 of the jobs to be done theory. 00:27:35.785 --> 00:27:41.285 I would be curious because you've been already talking about AI here. 00:27:41.585 --> 00:27:49.185 We are maybe in the year where AI is really going to grow up to really solve problems. 00:27:49.945 --> 00:27:57.285 How do you, your company, right now use AI for those steps for doing market 00:27:57.285 --> 00:27:58.765 research and so on and so forth? 00:27:59.025 --> 00:28:03.805 Yeah, it's a great question. We've been on this since November a couple of years 00:28:03.805 --> 00:28:05.345 ago, so it's been over two years. 00:28:05.825 --> 00:28:11.745 And I think like most people, our first view was how does AI help us do what 00:28:11.745 --> 00:28:14.265 we currently do better, right? 00:28:15.745 --> 00:28:20.005 And so we've been on that path. What we do is we encourage everybody in our 00:28:20.005 --> 00:28:25.525 company to use AI for that purpose and experiment with it and try it out. 00:28:26.025 --> 00:28:30.905 We've given them access to learning about AI. 00:28:31.165 --> 00:28:37.785 In our monthly all-hands meetings, we call on people to give us examples of how they're using AI. 00:28:38.025 --> 00:28:43.105 So we're really encouraging this from a cultural standpoint and getting people indoctrinated in it. 00:28:43.665 --> 00:28:46.905 But in a more sophisticated way, we're trying to figure out, 00:28:46.965 --> 00:28:55.985 well, can we collect a set of needs through AI, right? Can we program this in such a way? 00:28:56.165 --> 00:29:00.445 Now, the interesting thing about our approach is that it's very rules-based. 00:29:00.885 --> 00:29:05.145 Like our outcome statements have 28 different rules that they follow. 00:29:05.685 --> 00:29:09.385 They've got to be stable over time. They can't contain adjectives. 00:29:10.185 --> 00:29:17.265 There's a bunch of reasons behind every rule. But once we've programmed AI with 00:29:17.265 --> 00:29:19.905 all the rules, we have our own GPT, like I said. 00:29:21.265 --> 00:29:25.705 One for market definition, one for job mapping, one for outcome gathering. 00:29:26.845 --> 00:29:31.805 And we query it. We see, can I come up with a set of need statements? 00:29:33.065 --> 00:29:34.605 And it's pretty good. 00:29:36.245 --> 00:29:41.225 But you wouldn't know it's pretty good unless you're an expert at collecting 00:29:41.225 --> 00:29:45.505 these kinds of statements and know what to look for, right? So... 00:29:46.854 --> 00:29:50.094 I think it'll clearly get better and better over time. 00:29:50.374 --> 00:29:57.474 But where we're at with it right now is I feel the AI helps practitioners that 00:29:57.474 --> 00:30:01.294 know how to do ODI, helps them get it done faster, more effectively. 00:30:02.714 --> 00:30:07.474 But it doesn't replace it yet. So I think we're in pretty good shape from that 00:30:07.474 --> 00:30:09.014 standpoint for a little bit. 00:30:10.034 --> 00:30:15.334 But ultimately, what people want to do is to get answers to all the questions that ODI helps answer. 00:30:16.314 --> 00:30:21.694 Like, how do I differentiate myself from my top competitor? Am I satisfying 00:30:21.694 --> 00:30:23.934 the needs to a great enough degree to make a difference? 00:30:24.894 --> 00:30:29.854 Is there a segment of people that nobody's targeting that I could go after? 00:30:30.194 --> 00:30:34.494 Like, we found in the all-terrain vehicle manufacturing space, 00:30:34.574 --> 00:30:40.354 for example, we found a segment that was about a quarter of the market that nobody was attacking. 00:30:40.634 --> 00:30:46.294 They didn't know it existed from a needs perspective. This is why we do outcome-based 00:30:46.294 --> 00:30:47.754 segmentation, you know, other 00:30:47.754 --> 00:30:50.174 groups of people that struggle in different ways to get the job done. 00:30:50.954 --> 00:30:55.634 We don't segment around demographics or psychographics or attitudes or behaviors 00:30:55.634 --> 00:31:01.954 because those are all really just proxies for segmenting around unmet needs, right? 00:31:02.094 --> 00:31:04.974 So instead, we just segment around the unmet needs because we know what they are. 00:31:05.534 --> 00:31:11.834 And it gives us a whole insight into different opportunities that we could potentially go address. 00:31:12.794 --> 00:31:16.354 So, you know, I think, you know, AI is going to be, it's going to take a while 00:31:16.354 --> 00:31:19.894 before AI can do all that qualitative and quantitative work effectively. 00:31:20.714 --> 00:31:28.354 So for now, it's a keen eye watching all this stuff, but we're making our tool 00:31:28.354 --> 00:31:31.574 set and everything available to people so that they can start practicing and 00:31:31.574 --> 00:31:32.994 coming up the learning curve. 00:31:33.174 --> 00:31:37.294 And I think, you know, some of the entrepreneurs in the audience would like that. 00:31:37.454 --> 00:31:41.214 We've built a certification site, training site that makes some of this stuff 00:31:41.214 --> 00:31:43.114 possible. as a starting point. 00:31:44.963 --> 00:31:49.143 Jobs-to-be-done approach. I think we now heard about it. 00:31:49.303 --> 00:31:54.303 How would it help entrepreneurs to mitigate risk? 00:31:54.503 --> 00:32:04.563 And do you believe also investors would appreciate a proven methodology to their approach? Yeah. 00:32:05.103 --> 00:32:08.403 Well, we know on the latter question there, definitely, yes. 00:32:08.403 --> 00:32:15.023 We know a number of companies who've taken the data and presented it to their 00:32:15.023 --> 00:32:18.583 investors to help secure funding. 00:32:19.703 --> 00:32:24.803 And they find it very impressive because they go in with the story of saying, 00:32:24.903 --> 00:32:27.083 hey, we're going to beat this competitor along these dimensions. 00:32:27.083 --> 00:32:28.663 Here's the top unmet needs. 00:32:29.363 --> 00:32:35.423 Here's the data from the market that says we're going to get the job done 15%, 20% better or more. 00:32:36.363 --> 00:32:42.383 So they can make that argument. So they're not investing in hope, right? 00:32:42.523 --> 00:32:46.423 They're investing in something that they know is possible because they've mitigated the risk. 00:32:46.743 --> 00:32:53.303 Do you make the AI tools you've been talking about, do you make them available 00:32:53.303 --> 00:32:56.503 for people to use? We're going to. 00:32:58.103 --> 00:33:06.363 We're still testing them. We're trying to put the right design in place to make it usable. 00:33:06.363 --> 00:33:13.203 So we're getting there but what we do have already is we have all the rule sets 00:33:13.203 --> 00:33:19.943 and everything that we use to create the the prompts and things like that that's all. 00:33:22.341 --> 00:33:26.041 That's all part of our certification program. I see. 00:33:26.601 --> 00:33:33.481 My next question would be, because everybody, especially if your startup scale 00:33:33.481 --> 00:33:37.581 up, if you're not yet an established company, you always feel the competition. 00:33:37.821 --> 00:33:42.421 How do you think startups can leverage the jobs we've done and outcome-driven 00:33:42.421 --> 00:33:45.981 innovation for themselves to compete in the market? 00:33:49.201 --> 00:33:52.761 Well, the very first thing they should do is make sure they define their market 00:33:52.761 --> 00:33:56.861 as a group of people and a job to be done, and then co-create the job map. 00:33:57.301 --> 00:34:01.961 Sit with customers. They can do this in a couple of days and lay out what job 00:34:01.961 --> 00:34:03.861 they're trying to get done and what those steps are. 00:34:04.621 --> 00:34:06.261 And even before you get to the 00:34:06.261 --> 00:34:11.201 outcome level, you can see, are my products getting the entire job done? 00:34:11.581 --> 00:34:16.541 Are there competing products getting the entire job done? Are people cobbling together solutions? 00:34:16.941 --> 00:34:18.521 Is there a platform play? 00:34:19.801 --> 00:34:26.781 Are we leading people to execute the process in an iterative order where they're 00:34:26.781 --> 00:34:31.101 going to go back and iterate and waste time because we don't have the steps in the right order? 00:34:31.841 --> 00:34:36.221 And oddly enough, we see that quite a bit, Joe, where products force people 00:34:36.221 --> 00:34:39.761 to do things inefficiently, which we want to eliminate. 00:34:40.241 --> 00:34:44.961 Job Maps help point that out as well. So just getting started with that is key. 00:34:45.801 --> 00:34:50.601 But as an entrepreneur, and I'm an entrepreneur, I started Stratagion back in 00:34:50.601 --> 00:34:53.481 91, and we've had different product sets since then. 00:34:54.041 --> 00:34:59.501 The first thing I do is I go get the data set so we know where the unmet needs 00:34:59.501 --> 00:35:04.321 are, and we can focus on the right segments, the right unmet needs. 00:35:05.885 --> 00:35:08.845 So we know we're going to win in the market. And that's why we've been around 00:35:08.845 --> 00:35:12.805 33, 34 years doing this type of work. 00:35:13.965 --> 00:35:20.325 Every time I'm talking about tools, processes, what I always have in mind is 00:35:20.325 --> 00:35:23.105 how can people make mistakes? 00:35:23.265 --> 00:35:27.845 What are the most common mistakes here? Because I have seen pitch deck over 00:35:27.845 --> 00:35:29.365 pitch deck over pitch deck. 00:35:29.485 --> 00:35:35.885 And the people are addressing people, well-educated, higher income, 25 to 45. That's it. 00:35:38.405 --> 00:35:43.445 And that's usually when I start scratching my head. Well, guys, 00:35:43.625 --> 00:35:45.045 you got to do better than that. 00:35:45.405 --> 00:35:53.185 What are the common mistakes you have seen people making with the jobs to be done theory so far? 00:35:53.705 --> 00:35:57.585 Yeah, as they start applying it, they stumble at every step. 00:35:57.705 --> 00:35:58.905 I'll just start by saying that. 00:35:59.085 --> 00:36:02.645 And the very first step is to identify what's my market. 00:36:04.005 --> 00:36:07.725 And again we define a market as a group of people and the job to be done, 00:36:09.425 --> 00:36:14.625 this sounds like it should be easy it's not easy so for example you could be a kettle maker, 00:36:15.505 --> 00:36:19.625 and you could say well i'm in the kettle market right and so you go to your 00:36:19.625 --> 00:36:24.605 customers and say why do you use my kettle well i use it so i can heat water 00:36:24.605 --> 00:36:30.125 great all right so then what happens Is it part of a bigger job? 00:36:30.625 --> 00:36:33.945 Yeah, it is, actually. You know, I use that water and I combine it with some 00:36:33.945 --> 00:36:38.865 coffee and put it in this cup and add some sugar and some cream. 00:36:39.025 --> 00:36:41.765 And now I've created a hot beverage for consumption. 00:36:42.948 --> 00:36:49.388 So as the kettle maker, now you have to decide, do I want to just make kettles 00:36:49.388 --> 00:36:55.008 and get part of this bigger job done, or do I want to try to get the bigger job done? 00:36:55.128 --> 00:36:58.128 Where do I want to define my level of abstraction? 00:37:00.408 --> 00:37:04.368 Nespresso and Keurig, they get the entire job done, so you can create a hot 00:37:04.368 --> 00:37:05.328 beverage for consumption. 00:37:06.068 --> 00:37:13.248 But people still buy pots or kettles just to heat water very quickly because 00:37:13.248 --> 00:37:17.328 maybe they're going to make soup or tea or something different. 00:37:18.468 --> 00:37:24.428 So they have to decide amongst that level of abstraction where they want to play. 00:37:24.748 --> 00:37:32.208 Now, what we always recommend to people is we say, it's okay to go beyond your core. 00:37:32.888 --> 00:37:38.228 So if you're the kettle maker, it's okay to go beyond heating the water to the right temperature. 00:37:39.188 --> 00:37:44.468 As long as you still include heating the water to the right temperature as part of that bigger job. 00:37:45.308 --> 00:37:49.788 So if I eventually said, if I went all the way too far and said, 00:37:49.928 --> 00:37:56.648 my job is to prepare dinner, then I'm not going to get the granular level of 00:37:56.648 --> 00:37:59.108 detail on heating water to the right temperature. 00:37:59.428 --> 00:38:03.028 I've gone too far. But if I stay with, you know, I want to create a hot beverage 00:38:03.028 --> 00:38:05.088 for consumption, you're probably going to be safe. 00:38:05.868 --> 00:38:09.388 And you could say, I don't want to go beyond the kettle market. 00:38:09.428 --> 00:38:13.728 I just want to help people create, you know, get to the right temperature as 00:38:13.728 --> 00:38:17.388 quickly as possible and stay there and cool down when they need it. 00:38:17.488 --> 00:38:24.048 You know, and they could just get all the outcomes just on that very narrow focused job. Right. 00:38:25.546 --> 00:38:29.146 And that's a choice. It's a strategic choice. Where do you want to go? 00:38:29.326 --> 00:38:31.446 Do you have the capability to get the entire job done? 00:38:31.966 --> 00:38:35.706 We know that solutions evolve to get the entire job done. Are you going to be 00:38:35.706 --> 00:38:39.606 the platform play? Or are you going to be a feature on someone's platform? 00:38:40.826 --> 00:38:45.446 So, tough questions. When you've been talking about that, I was wondering, 00:38:45.926 --> 00:38:53.486 a lot of startups out there work in some form or derivative of agile development. 00:38:53.826 --> 00:39:02.046 How could they integrate jobs to be done, outcome-driven innovation in this process? 00:39:02.846 --> 00:39:08.366 Well, the way I think about it is jobs to be done in ODI make agile more agile. 00:39:09.506 --> 00:39:14.846 Because to me, Agile more or less begins when you start developing the product, right? 00:39:14.886 --> 00:39:20.646 You want to develop it in the most efficient way, but you have to be developing the right product. 00:39:21.626 --> 00:39:25.166 Everything before Agile and everything before development is what I call the 00:39:25.166 --> 00:39:26.246 innovation process, right? 00:39:26.266 --> 00:39:30.086 The output of the innovation process is the concept that you know is going to 00:39:30.086 --> 00:39:34.246 win in the market before you start developing it, right? That should be the output. 00:39:34.986 --> 00:39:38.386 Then you take the concept, you put it in development. That's when you apply Agile. 00:39:38.626 --> 00:39:42.806 And the beauty here is you're not iterating on what the product does anymore 00:39:42.806 --> 00:39:44.306 because you already defined that up front. 00:39:44.786 --> 00:39:48.086 So the only thing you're iterating on is the design, right? 00:39:48.206 --> 00:39:53.346 So how do I make sure it's easy to install and set up and interface with and 00:39:53.346 --> 00:39:58.666 clean and maintain and upgrade, right? So you're focused on what we call the 00:39:58.666 --> 00:40:00.846 consumption chain jobs, right? 00:40:01.646 --> 00:40:05.966 And so instead of iterating on what the product does while you're developing 00:40:05.966 --> 00:40:10.886 it, you've quit that step. And that's huge, right? 00:40:11.846 --> 00:40:16.506 Yeah, it is. Right? And I know like in Lean Startup, for example, 00:40:17.026 --> 00:40:22.166 they often say, go ahead and hypothesize the market, the product, 00:40:22.186 --> 00:40:23.466 and the needs all at once. 00:40:25.026 --> 00:40:28.426 It's like trying to solve a very complex simultaneous equation, 00:40:28.646 --> 00:40:30.346 extremely difficult to solve. 00:40:31.726 --> 00:40:36.066 Unless you use some mathematical principles to say, let's just solve one piece at a time. 00:40:36.346 --> 00:40:41.846 Let's make the market a, not a variable, but let's make it a constant. Let's pick the market. 00:40:42.406 --> 00:40:45.246 It's parents trying to pass on life lessons to children. All right, 00:40:45.326 --> 00:40:46.426 so now that's a constant. 00:40:47.546 --> 00:40:51.366 So now let's come up with the needs, right? 00:40:51.386 --> 00:40:54.766 So we can study all the needs associated with passing on life lessons. 00:40:54.906 --> 00:40:56.006 Now that becomes a constant. 00:40:56.806 --> 00:41:00.506 Now let's come up with the solution. We know the needs, we know which are unmet. 00:41:00.846 --> 00:41:05.266 And now we can solve the equation. Now we can achieve product market fit, right? 00:41:05.626 --> 00:41:11.826 Now the thing that we're creating we know is going to address the unmet needs in the market, right? 00:41:12.546 --> 00:41:17.446 That's the beauty of the approach. And it just brings a little science to the 00:41:17.446 --> 00:41:18.906 process and helps mitigate risk. 00:41:20.830 --> 00:41:26.950 I have only two more questions for you, but one of them, I would need a job 00:41:26.950 --> 00:41:32.330 to be done because the startups have then, if they decide to use the framework, 00:41:32.650 --> 00:41:38.650 a job to measure the success of the implementation of jobs to be done, 00:41:38.910 --> 00:41:40.130 outcome-driven innovation. 00:41:40.690 --> 00:41:42.490 How would they do it? 00:41:43.190 --> 00:41:46.490 Yeah. Well, you can measure the success along a number of different ways. 00:41:47.250 --> 00:41:52.250 You can measure success early on, saying, you know, is the market I've chosen 00:41:52.250 --> 00:41:55.270 an attractive market? That would be a measure. 00:41:57.070 --> 00:42:01.210 Do I understand the entire job the customer is trying to get done? 00:42:02.010 --> 00:42:07.270 That could be a metric. Do I have all the needs associated with the market? 00:42:07.570 --> 00:42:09.990 Do I know which ones are unmet? 00:42:10.830 --> 00:42:14.230 Do I know if there's segments of people with different unmet needs? 00:42:15.930 --> 00:42:20.110 And are my solutions designed specifically to address those needs? 00:42:20.270 --> 00:42:23.790 And the final measure is, am I going to move the level of satisfaction so I'm 00:42:23.790 --> 00:42:26.010 going to get the job done significantly better? 00:42:27.150 --> 00:42:31.110 Just like I said right up front, the goal of the innovation process is to come 00:42:31.110 --> 00:42:34.710 up with a solution that you know with a high degree of certainty is going to 00:42:34.710 --> 00:42:41.650 win the market before you start developing it, not after it's launched like the PC Junior. Right. 00:42:42.610 --> 00:42:47.290 So that's that's the ultimate measure right there. Does my product concept move 00:42:47.290 --> 00:42:48.650 the needle? Can I prove it? 00:42:50.270 --> 00:42:56.110 I see. So the last question would be only what resources or training would you 00:42:56.110 --> 00:43:01.450 recommend for entrepreneurs interested in mastering jobs to be done outcome 00:43:01.450 --> 00:43:03.190 driven innovation methodologies? 00:43:04.770 --> 00:43:09.610 Yeah, Jeff, that's a great question. You know, we spent the last five years, 00:43:09.770 --> 00:43:16.870 and I spent a couple years, me personally, just writing more material to help train practitioners. 00:43:16.930 --> 00:43:20.270 It's all located on our website. 00:43:20.930 --> 00:43:22.310 It's called ODI Pro. 00:43:23.250 --> 00:43:28.310 You can Google it and quickly find it. But it includes the certification courses 00:43:28.310 --> 00:43:31.610 that help you become a good practitioner. but probably more important, 00:43:31.890 --> 00:43:36.650 it has a whole bunch of webinars and presentations, 00:43:37.403 --> 00:43:41.623 And instructions in there on how to make it happen. You know, 00:43:41.643 --> 00:43:42.583 how do you do an interview? 00:43:44.683 --> 00:43:48.443 And this is where entrepreneurs often struggle because they don't have the skill 00:43:48.443 --> 00:43:50.923 sets to go sit and talk to customers. 00:43:51.063 --> 00:43:52.343 They're not necessarily qualitative 00:43:52.343 --> 00:43:56.863 and quantitative research and data analysts and that sort of thing. 00:43:57.063 --> 00:44:01.423 But those are the type of skill sets that are required to make this stuff happen. 00:44:01.423 --> 00:44:08.383 And you should have them on your team as any organization who's trying to win in the market. 00:44:09.903 --> 00:44:13.143 Well, I would say pretty good closing words. 00:44:13.403 --> 00:44:17.903 Thank you very much for being here, my guest. We had a little interruption, 00:44:17.903 --> 00:44:22.983 and I do have two two-year-old boys and two five-year-old boys here playing in the background. 00:44:23.423 --> 00:44:26.583 Just a room next to me. I hope the noise wasn't too bad. 00:44:26.943 --> 00:44:30.163 Tony, thank you very much. It was a pleasure having you as a guest. 00:44:30.163 --> 00:44:34.463 We link down here in the show notes for everybody who'd like to learn more, 00:44:34.863 --> 00:44:37.963 something like your Wikipedia article, your LinkedIn profile, 00:44:38.203 --> 00:44:43.543 the website of your company, the Jobs to be Done framework, and two of your 00:44:43.543 --> 00:44:45.703 Harvard Business Review articles. 00:44:46.263 --> 00:44:49.743 Excellent. And there is a free book at Jobstobedonebook.com, 00:44:49.883 --> 00:44:53.743 a free e-book or free audio book. So that's also a possibility. 00:44:54.543 --> 00:44:59.423 Great. Awesome. so only thing left for me to say is thank you very much it was 00:44:59.423 --> 00:45:04.383 a pleasure talking to you thank you Joe I appreciate it have a good day bye bye. 00:45:09.443 --> 00:45:18.703 That's all folks find more news streams events and interviews at www.startuprad.io 00:45:18.703 --> 00:45:21.883 remember sharing is caring sharing. 00:45:22.000 --> 00:45:34.784 Music.