Tony Ulwick is the founder and CEO of Strategyn, a strategy, and investment consulting firm. As the inventor of the Outcome-Driven Innovation® (ODI) process, he has successfully implemented it at some of the world’s most prominent organizations and across nearly all sectors.
What you will learn
- Why you should start a business that you enjoy doing
- Innovation is not an “aha” moment but a process
- Why you need to discover the unmet needs of your customer to develop a winning product
- How to create a process of predictability for innovating products
- The two $1 billion failures at IBM that provided the insight and motivation for Tony to start his business
- Why Innovative products need to be at least 20% better to win the market and what that looks like
- The importance of processes and systems for long-term business success
- Why startups need a product innovation process to be successful at fundraising
00:00:05 - 00:01:06
Hi everyone and welcome to the Jeff Bullas show. Today I have with me, Tony Ulwick. Now, Tony is the Founder and CEO of Strategyn, a strategy and investment consulting firm. As the inventor of the Outcome-Driven Innovation (ODI) process, he has successfully implemented it at some of the world's most prominent organizations and across nearly all sectors. Tony is a pioneer of Jobs to be Done theory, the inventor of the Outcome-Driven Innovation (ODI) process and Founder of Strategyn, innovation consulting firm strategy. He has applied his ODI process at some of the world's leading companies and across nearly all industries to inform breakthrough innovations, achieving a success rate that is 5 times better than the industry average and I look forward to hearing more about that. And Philip Kotler calls Tony “the Deming of innovation” and credits him with bringing predictability to innovation. Published in Harvard Business Review and MIT Sloan Management Review, Tony is also the author of bestsellers “What Customers Want and Jobs to be Done: Theory to Practice”
Welcome to the show, Tony.
00:01:07 - 00:01:08
Jeff, thanks so much. It's a pleasure.
00:01:09 - 00:01:58
So we had a little chat before you came on, Tony, and we were just getting to dispose the heart of what you do. And in the introduction, I use the term predictability and what we're trying to do today is demystify the science and dark arts of innovation and basically Tony has reduced it to a process which makes it much more predictable. So before we do that, Tony, I am intrigued by stories and I want to know more about what was the call? You did a degree at Rhode Island University, I think it was, and then you went and did an MBA in Florida, is that correct? So what got you into this entrepreneur game?
00:02:00 - 00:04:17
Well it's a good story, you know, I started working with a fairly large company called IBM and I spent 10 years there, nearly my career and I did start as a manufacturing engineer, putting my mechanical engineering degree to good use. And I worked on a product called the PCjr. Now the PCjr, well, so you know where this is going right, because the day after that product was introduced, the headlines in the Wall Street Journal read “the PCjr is a flop” the day after. And I thought well that's bad news, that is bad news. And they were right, it was a flop. It took us about a year to, you know, to reconcile and come to grips with the fact that that was true. It was a billion dollar failure on IBM's part.
And at the same time they were investing in their own operating system that was called the West 27. That was another billion dollar error. It was just phenomenal. And this intrigued me. You know, come on two fronts. I wondered, you know, how could IBM and all those fast resources make such mistakes? And the second thing that really intrigued me was how did those people at the Wall Street Journal know the product was a flop the day we introduced it? Like the thought was that, wouldn't it be nice if we had known that yesterday? Or better yet, how about if we knew a year ago what metrics they were going to use to judge the value of the product to make their evaluation and then we could just, you know, build the product around those metrics and get a better result.
Of course, it's, you know, as you expand on that thinking, you'd say, well, how about if we can go to customers to figure out what metrics they're going to use to judge the value of our products and are those metrics stable over time and can we rely on them to build products around and so on. So that was the thought. That's what got me intrigued and and the idea of innovation, because I always felt like if we knew the metrics, people are going to use to judge the value of our products way in advance, we could just build the products to address those metrics and the headlines would read “the PCjR is the greatest thing since sliced bread.”
00:04:18 - 00:04:23
I want to leap in a little bit there. So you and I come from a certain generation.
00:04:25 - 00:04:28
I think the exact same generation within the plus -6 months. Right?
00:04:28 - 00:04:37
Yeah, Yeah. So we're talking the IBM PC or the world's personal computer revolution back in the ‘80s. Is that correct?
00:04:38 - 00:04:38
That is right.
00:04:39 - 00:05:05
Okay. So I'm going to give a bit of context in my history. I leapt into the middle of that revolution in ‘84 and we were given computers like the Apple and also the IBM PC. And then we had the AT, where did the Jr sit in that framework? And I'm curious. I knew of the Jr, but it's actually had such a brief life. I almost forgot it existed.
00:05:05 - 00:05:19
I've been trying for all these years to forget that that existed, but It was actually released in 1985. So it was post-PC 1AT. So it was, it came after that. Yeah.
00:05:20 - 00:05:27
So what did the IBM PCjr look like? Was it just a floppy disk meant to be a minimal computer product? Is that what it was?
00:05:27 - 00:06:02
Yeah, it was basic, right? It was a very small box, had what became known as the chick lit keyboard. I have one around my house here somewhere. And because it just felt like little chick lit keys. It failed for a number of reasons. But really it failed because it didn't get jobs done that people were trying to get done at home, right? It came with the same software set that people were using for business, right. So, you know, how many people are using VisiCalc, you know, at home, you know, not too many at that point, right.
00:06:02 - 00:06:54
Yeah. It was a very, I think, the modern generation have their smartphones and they're born a lot of them in the ‘90s and the internet is taken as a given. You and I grew up in the area where in a time where you were not connected, it was stand alone and we grew up in an era to where there was personal computers before that was mainframes that were hidden in air conditioned rooms and locked behind locked doors and security and only owned by banks. And I being predicted that the size of the computer market in the world was like three computers I think was their prediction at the time or something around that sort of number. So I think in history and we've had a bit of history, both of us,is you forget how far we've come and I think that's what's rather exciting today.
00:06:55 - 00:07:14
I agree. Yeah, we've come a long way from a technology standpoint. We need to catch up from a understanding of innovation standpoint though, because there's still so many myths out there and like you mentioned trying to demystify innovations, spent my goal for the 30 plus years and we're still at it.
00:07:14 - 00:07:39
Okay, so you observed a problem and a product failure early on in your career. So that, obviously you were curious of why IBM had spent two lots of $1 billion dollars on two product failures, in other words, the operating system on the computer. So what happened over the next few years after that sort of ah-ha moment early on in your career at IBM?
00:07:39 - 00:09:50
I spent the last five years of my IBM career working in product planning and it's kind of a term that was popular back then but you don't see that term use so much anymore, it's generally the role of the product manager to figure out what's the next iteration of the product and lay out the product roadmap. But in the product planning role, we try to figure out, you know, conceptualized products that we knew would win in the marketplace. That was the goal. And I started searching for, first off within IBM, you know, what's the process they used to do that? Clearly it wasn't very good, has written this by some of the other failures, right? So I started looking around the industries to see, does anyone have a good innovation process?
And we looked at all different kinds of tools, you know, we looked at things that were new back then like conjoint analysis. Hey, I went to see Dr. Paul Green at Wharton business School to go talk with him about this new idea of conjoint and how that would help create more predictability. We were introduced to the voice of the customer that was new at that time and the house of quality, QFD, there's a whole series of things that were happening. It was great times. But one thing I recognized very quickly is that there really was no unifying theory of innovation or no end to end innovation process that people could rely on.
So that's when I went back to thinking through, as I mentioned already, you know, what are those metrics people are using to judge the value of our products? Can we know them well in advance? And it was around, I guess it was 1990 time frame, I was doing some work for IBM Australia and had spent about a month and a half out there. Maybe it was the excessive amount of caffeine I had during that time frame but it occurred to me, that's when I was first introduced to espresso and I was like well I couldn't have enough.
00:09:50 - 00:09:55
Did you spend time in a building that looks straight down the Harbor Bridge?
00:09:55 - 00:09:59
I did. In fact. Yeah essentially. Beautiful.
00:10:01 - 00:10:21
I remember that building. In fact I did an interview there and they didn't let me into our BM. I applied for a job there and I think maybe you whispered in there and said Jeff is not the right sort of fit for you guys. But by the way, that IBM building now is a block, is an apartment tower.
00:10:21 - 00:13:50
Yeah, it was just, I love being there. And I was just so focused on work and it finally occurred to me, you know, some manufacturing engineer, the goal of manufacturing of course is to produce a predictable output, right? And what you do in that space, is you try to figure out what do we have to measure and control to produce a predictable output? And manufacturing is a process, right? Clearly, it's a process. So, if we can figure out what do we have to measure patrol along each step of the way to ensure we get a predictable result. Now let's take that same concept and shift it over to customers and say, well, you know what, you heard this quote: “People don't want the quarter inch drill, they want the quarter inch hole”, right? So, if they want the quarter inch hole, that's a process. And this is what occurred to me, it's like, you know, people are trying to execute a process, They're trying to create a quarter inch hole. So, how about we apply the same thinking, we do manufacturing over to creating products, because we can say that, well, customers are executing our process. They're trying to create a quarter control. What if we study the job of whatever they're trying to do, getting a hole done and break it down step-by-step and figure out what are their measurable outcomes. How do they measure success as they're going about getting that job done? And that was the breakthrough because it turns out people do buy products to get a job done and you can break down those jobs into steps and you can figure out what are the measurable outcomes. They used to measure success for getting the job done. And the beauty of this is the jobs that people trying to get done are very stable over time. So these metrics they use to measure success are stable over time, like people listening to music, people have been listening to music forever, right? So, but there's a set of metrics. People used to judge success and those metrics don't change over time. What's changing over time is our technology and solutions that help them get those jobs done better. So, I started thinking of this as more or less as an equation, right, where you're trying to come up with solutions that address these metrics and once you do all the metrics associated with a particular job and you had them in some order and we'll get to that in a second. You can start testing different ideas against the set of metrics to see which ones get the job done best.
And then the other thing that occurred to me is we can start prioritizing these metrics and how would you want to prioritize them? Well, the thought was, let's figure out which of these are most in need of improvement. In other words, which ones are unmet or underserved. So this led me down the path of integrating a quantitative research methods into the equation where we could figure out of these 50 or 70 outcomes or metrics people are using which ones are really important and not well satisfied. So we could do that quantitatively and lo and behold we could figure out what are the top unmet needs of customers in a given market. So if we could expose all that up front, we can start brainstorming ideas to develop solutions to get those top on that needs effectively satisfied.
00:13:51 - 00:14:14
Yeah. So what is, okay, let's just pause there a little bit. So how do you discover those unmet needs? Because today we have ways of testing, it may be cheaply with even Facebook Ads, what are pain points and needs that need to be met? So what were some of the methods used to unearth those needs? If you see that as being important.
00:14:14 - 00:17:22
Yeah, well, sure. So, you know, if people are trying to get a job done and they have all these needs associated with getting the job done, the thought was well let's capture all of them, right. So how do you capture all the customers' needs? And then we can figure out which met, but let's just capture them first. So the methods we use are just talking with customers. What we do is I asked them to take us on like a slow motion journey of getting their job done. So for example, you know, we work with surgeons who are performing a surgical procedure and we just go from beginning to end, tell us what you're trying to accomplish from the time you make the incision until the time you wrap everything up and they go step-by-step on.
You know how they're trying to access, gain access into the vasculature and then they're trying to find the pathway to their destination and then they navigate through their, with their toolset and then they perform whatever procedure they need to and so on. But they could take you through step-by-step exactly what they're trying to do. Not, not how they're doing it. So we're not talking about products, but how are they measuring success along each step of the way, right. Because to get a job done better, you can get it done faster. More predictably higher output throughput. Just like a manufacturing process, right. How do you approve a manufacturing process faster? More predictable, higher output throughput. This is true of any process, right? So, what what we're doing is we're talking to customers and listening to the process that they're going through and extracting, how they're measuring success in each step of the way. Quick example, you know, everyone cooks meals, right? So what are some of the metrics you used to judge how well you cook the meal, let me say, well, I want to minimize the likelihood of over-cooking the meal. That's one metric. I want to minimize the likelihood of undercooking the meal. You know, I want to minimize the time it takes to cook it evenly across the entire dish. I want to minimize the time it takes to clean it up after the meal.
You could just start going through the process and saying, how am I measuring success without really getting at what products you're using, right? So we're trying to define everything in problem space before we get over to solution space, right. It's as if we're trying to define the problem at an extraordinarily granular level so that we can then figure out at this gradual level where are people struggling and once we know that, then we put the solutions in place. So and to further answer your question, Jeff, you know, I like what we call immersion sessions where we'll sit with 1 or 2 or 3 customers that are really experts in getting the job done and spend three or four hours with them and work with them to define exactly how they think about the job they're trying to get done. We create what we call a job map that we introduced in a 2008 HBR article and then we work to capture all these measurable outcomes. So it's a tedious process. But the beauty is once you've done it, you don't have to do it again for years because these needs are stable over time.
00:17:23 - 00:17:25
And also it's scalable, isn't it? Once you've done that.
00:17:26 - 00:17:27
It's very scalable.
00:17:27 - 00:18:29
Yeah, I love the term I came across recently and it's something that is a little bit of a free range sort of guy rather than assistant process guy because I initially trained to be an accountant and I realized I was not designed to be an accountant, which is very process driven and attention to detail. But the term was a phrase was systems and processes will set you free and they do because it becomes predictable and there's a process. So I've, in the last 18 months, two years I've fallen in love with process and systems and so it becomes much more predictable in terms of what we do from just even as simple as a process for publishing a podcast, from recording to marketing and there's a whole range of process in between, that's a product. So yeah, it's something I really, really have onboard with now.
00:18:30 - 00:18:45
Well that's a great example because creating a podcast is a job to be done, right, That's the job and you can break that down step-by-step. And so what are some of your measurable outcomes, like what's one of the more time consuming aspects of putting a podcast together?
00:18:46 - 00:18:52
One would be doing, reviewing the transcript, for example, for so yes,
00:18:53 - 00:18:55
Reviewing it for what purpose?
00:18:55 - 00:19:06
To make sure that it's accurate and we're not saying bad things or so in other words, is it, because we give it to a computer who does it initially and a good job.
00:19:06 - 00:19:25
So you're trying to minimize the time it takes to confirm that the information you you're about to state is accurate. Alright, So that's one measurable outcome, right? And I'm sure if we sat here for hours, I could capture 40 or 50 or 60 outcomes from that, that's the interview process basically.
00:19:25 - 00:20:27
That's great because what I used to, one of the reasons I actually bought the podcasting equipment about four years before I actually did the podcast was because I realized that basically it takes a village to raise a child. It takes a village to actually do a podcast, right? It's the truth. It's like, ah there's, I know there's gonna be a lot of work doing this podcast, we're gonna do it well. So we launched a podcast with a minimal viable product before we actually turn it into a video as well. So we just create a minimal and I also too, I think as an entrepreneur and that's both yourself and I and many others that will be listening to this is that if you're the one doing all the work, then you're not free. You are actually trapped.
And I think the job to be done needs to make sure that it removes the owner as much as possible because the inspiration there, the conductor of their should be leading the team not doing. That's the stuff.
00:20:27 - 00:20:55
That's exactly right. Yeah, that's exactly it. You want to be able to get the job done predictably, quickly without variability, without surprises and have a great result. That's true of any job. And that's true of any process. And that's why this approach works so well because all products are designed to help people get some job done. So, so this concept works across all industries and we've proven that practice as well.
00:20:56 - 00:21:36
So there's some of the things you've got a process for it, which is 10 points, which I don't think we need to dive into. But what are some of your, let's go back to where you actually started, you know, Strategyn. So you've been IBM, you've observed a major funk up like two lots of $1 billion dollar product failures. And you started looking at, you know, how you could turn innovation of a product into a process. So after our IBM, what happened?
00:21:38 - 00:22:57
Well once I had that epiphany if you will in Australia and I thought well if we studied the process, people are trying to execute. I attempted to use that thinking at IBM a couple of times and I left a couple years later in 1991 and started Strategyn. It was good timing for me. From IBM, unfortunately, all that played havoc on their business because IBM at one point had 0% market share before they entered, they went up to 85% market share in the heyday and by 1991 they were down to about 10% market share. So they were shedding people left and right and they were kind enough to pay people to leave, which was
pretty much unheard of at that time, but I've had a no layoff policy. So this was the first time they had to lay people off and I opted to take that program, which was great that funded me, funded start-up basically. So I could then go secure, I quickly secured the assignments with Corvis Corporation, with Pratt and Whitney and with Allied Signal, which was still around at the time. So that got me started and I've never looked back.
00:22:58 - 00:23:07
It's almost like it was IBM, the original venture capital fund. A range of investors and they didn't know it basically back then.
00:23:07 - 00:23:09
Yeah, exactly. It worked out well.
00:23:10 - 00:23:16
Maybe they should, maybe they should have taken the thousands of people laid off the bright minds that because, IBM had great education and training.
00:23:17 - 00:23:18
00:23:18 - 00:23:37
It was like, I think best in world, from what my observation, the salespeople that IBM were incredibly well trained but they laid all these people off, maybe they should have said, start a business, we will fund you, through this fund and we'll actually take 50%. I think they could have done all right out of that.
00:23:40 - 00:23:42
So they messed that up too, right.
00:23:42 - 00:23:53
And they should have turned a problem into an opportunity, but that's okay. Okay. So you started Strategyn and you started applying your process driven innovation method?
00:23:55 - 00:25:32
That's right. Yeah. I started flying it right away. I had clients right away. In fact, one of my first successes was my first client was Cordis Corporation. They make angioplasty building products and they were down to about 1 1/2% market share. They were struggling. Everyone came in around them and started beating them. So they had one last go at it and said, you know, we need to create products that are gonna win in the marketplace. So I approached them with the idea, they hired me. A year and a half later, they introduced 19 new angioplasty balloons, all of which became number one or two in the market and their market share went up from 1.5% over 20%.
And I say the other really interesting thing that happened there is that there was one unmet need called minimized, the likely to re stenosis, which is the recurrence of a blockage. It was off the charts in terms of the way we quantified it. It was very important, very poorly satisfied. And they said, well we have, we're working on this device called the stent that can do exactly that. So we suggested that they double triple down their resources on that product and get it out to market. They did their first market with that product. That product was a billion dollar, product within two years. So yeah, they're stock went up from, I think it started at about $12 a share. They were acquired by J&J at $108 a share a couple of years later. So it was, it was a great story. It was a great story.
00:25:32 - 00:25:34
Did you get a performance fee?
00:25:34 - 00:25:42
I did not. No, I still kick myself in the butt for not asking for, thanks, thanks for rubbing salt into the wound, Jeff.
00:25:42 - 00:26:23
That's my job. I'm a rubber of salt in the wounds including my own sometimes.
So, yeah, this is something I agree with you. It's like everyone tries to think that, this is mentioned earlier in our off air conversation, is that we think that innovation is in a high moment on top of a mountain. What you've reduced it to is a process driven that happens in a boardroom or meeting room. That's more innovation by doing. And is that correct?
00:26:24 - 00:28:59
Yeah, well it is, it's, it's really at a high level, It's very simple. Let's understand a problem that the customer is having and understand it in really deep detail and then come up with solutions that will address that problem at a high level, that's what we're doing. But you've heard the saying, I think Einstein gets quoted as saying this, that, you know, if I had an hour to save the world, I spend the first 55 minutes defining the problem and then the solution will become obvious and that's exactly the same thing here, right? The way I like looking at it is, you know, what are the chances that a team, the product team is going to come up with a solution, randomly come up with a solution that addresses the top 20 on that needs in the market, if they don't know what the top 20 on that needs in the market are yeah, it's slim to none, right. But if, if you could say, hey, these are the top 20 unmet needs in the market, let's go solve them. There will be crafting solutions in a day that will help you get the job done significantly better. And so we're just flipping it around in his head, you know what we're saying is, you know, innovation doesn't have to be an ideas first approach, just like in the lean startup movement. You know, they suggest that people hypothesize the market, the needs and the product all at once and then you go do customer discovery and try to find product market fit.
But you're iterating on the market, you're iterating on needs, you're iterating on the product offering all at the same time. So chances of trying to solve that equation are pretty slim. What we're suggesting is, let's just do this sequentially. Let's go pick a market that we want to go after. Like surgeons who were trying to restore blood flow in an artery or parents were trying to pass on life lessons to children. If they're groups of people trying to get a job done right, once we know that that's a good market, let's go understand all the needs, all the metrics that people use to measure success when getting a job done right. And now, now that we know all the needs and which ones are unmet. Now, let's come up with a product solution that will address at least 15 or 20 of those unmet needs. Because one thing that you did on Jeff, people are going to buy your product, if it just gets the job done 1% better, or 2% better has to be meaningful if you put the threshold somewhere in the 15% range. So if you can help someone get a job done 15% better, then they'll often, you know, look to adopt your product or at least give it a chance, right?
00:29:01 - 00:29:25
So what you're sort of saying is that innovation is really not one big aha moment or thought it's more like meeting 15 unmet needs and putting them all together and that becomes where innovation really happens. It's the intersection of many unmet needs that are brought together to provide that, an incredible solution. Would that be a good summation of it?
00:29:25 - 00:30:04
That's great. I love hearing you say it like that. I've never, I've never said it like that. I don't think I'm gonna lift that one from you, but I think that's exactly it. Because it's, it's not just, you know, the aha moment from one idea. One idea usually satisfies one need, right? That's not good enough, right? What you, what you need is ideas that satisfy many on their needs and then that goes into a product that gets the job done a lot better, right? Because when you think about it like this, you know, people buy products, get jobs done, they're not gonna switch from their product unless the new product gets the job done a lot better.
00:30:04 - 00:30:08
I must an overwhelming, I have to buy this product.
00:30:09 - 00:30:24
Yeah, exactly. It's so, so it gets it done so much better than that. It's worth switching to. It's worth learning the new product. It's worth having to go by. It's worth, you know, learning how to interface with it. It becomes worth it, right? At that point.
00:30:25 - 00:31:12
So, if we want to still the process into a few points and hopefully I'm putting maybe a little bit on the spot here. We don't, we don't want to do 10 or 12. So you mentioned some of them along the way, but just like trying to distill it into I suppose a pithy few points. How to describe going from sitting down with a customer number one, you're going to sit down with a customer, and you're going to look at and customers that are already trying, I've got a process in place and they're very good at it. How to describe the process as simply as possible to go from meeting unmet needs in the marketplace to coming up with innovative product that launches?
00:31:12 - 00:33:34
Yeah. So, you know, you know, when you hear this, you're gonna go, that is very simple because this process is simple because all we're saying is, let's go take a market. That's the first step. What market do you want to pursue the most companies already in markets? So they don't even have to ask the question. You know, should we pursue it? They're already pursuing it. The question for them is how should you define your market? And again, we're gonna define your market as a group of people getting a job done. That's the first step, Right? Second step, now that we know the job, what are all your customers needs and needs are defining the special outcomes. That's captured through qualitative research, then we ask the question. Well, what should these are unmet right? And by how much, well that's where we do a quantitative survey. Figure out what needs to amend by how much, there's one next step that we haven't talked about yet, and that is we asked the question, are the segments of people with different unmet needs? Now, the reason we ask that is in nearly every market we focus on or have investigated over the years, people don't agree on which needs are met right? There are quite literally segments of people with different unmet needs. So the way we discover them is to segment around the unmet needs those measurable outcomes. Right now, companies generally can't do that. This is why they segment markets by demographic psychographic sat itunes behaviors, some data that they have because they can't
directly segment around unmet needs. Because for most companies, there's no agreement what in deed is, what the needs are or which are unmet. So those first four steps, I went to find a market to find the need to figure out which meant I asked the question of their segments of people with different needs and with that information you can do a whole bunch of things downstream. You can better position the products that you already have when the courts released there, we got their data back, we realized that some of their current products actually address three or four customer needs better than competing solutions. So we suggested to them that they just messaged restraints that got them from 1 1/2%, about 4% market share. So even that was a bonus.
Yeah, they messaged around those unmet outcomes.
00:33:35 - 00:33:37
With marketing messages or surveys or?
00:33:38 - 00:35:49
Well just in their marketing communications they would just say, hey, our product is better than others said this, addressing these outcomes will help you do this faster and more predictably. We're talking to the unmet needs right? The same set of inputs can be used to improve your current products as well, right? Because now, you know where the weaknesses are, it can be used to assess holes in the product portfolio. Like the stent was for Cordis Corporation, right? There was a new product that really generated tremendous amount of new growth.
We have companies use the information to make M&A decisions, investment decisions and R&D investment decisions because if they know where people are struggling to get the job done and they can't figure out how to do it now. Well, maybe a competitor figured it out. Let's buy them. Maybe there's a new technology coming down the pike that could address it. Let the R&D folks figure it out. You know, it turns out that the whole company is dependent on understanding the customers unmet needs, right? And once you have all that together, there's alignment across the organization.
This is one of the, you know, we talked with Clive Meanwell, who's the CEO of the medicines company. Well, he was before they got acquired by Novartis, we worked with them for about five years on applying outcome driven innovation at scale and we asked him what was the biggest benefit of this approach? And we said, it was rather fascinating. He said it brought transparency, it brought discipline and it brought trust to teams that typically operate in silos and so and line them around the common understanding of customers and their needs. So it kind of went from, we don't agree on what the need is to, hey, we agree on what we agree on what the needs are, which are unmet. We agree that the segments of people with different needs. Now all we have to debate is what's the best solution, he said, that's, that's where you want your folks, that's what you want them debating, right? You don't want them debating the problem. You want them debating the solution. That was the biggest benefit in his eyes.
00:35:52 - 00:36:08
So what are some of the, you mentioned a few case studies, what's your, it was one of your best, I suppose results and success stories, you might have a couple. So who are they, what companies are they, if you can mention them.
00:36:08 - 00:36:25
Sure. Published a number of case studies over the years. A couple of my favorites one was helping a company called Ontrack enter the electronic evidence discovery market. This was back in the early 2000's before there was electronic evidence discovery.
00:36:26 - 00:36:27
What is electronic evidence discovery?
00:36:28 - 00:39:19
Oh good question. So when legal teams, when there's a lawsuit within the corporation, the legal teams go conduct discovery which means they asked each other party for information and that information is often stored on hard drives all the above right? So it's going to get all that information and making it usable for the legal teams. So that's what it's all about now. The Ontrack folks thought they had a leg up in the competition there because for years they've been in the data recovery business which allows them to take data off failed hard drives. So they had great technology to take data off hard drives. They said well let's just apply it to this other market.
So they failed at it twice before they reached out and talked to us and we helped them along. And the reason they failed is they didn't recognize that they had a new customer and the data recovery market their customer is the IT Department generally and they receive hard drives from them and they take data off them and give them back to them and so on. Well they thought that was what was happening here. You know they have to go to the IT Department to get data off the hard drives which they would then give it back to the IT Department. But the IT Department then had to go give that information to the legal teams, right?
And then the legal teams had to search through it to try to find information and they couldn't. It was not searchable, right? So what we discovered is that in order to get the job done, the legal team, they had to create a solution that would not only extracted data off the hard drive but make it searchable because the job to be done was to find information that would support a refuted case. And once they realized that that was their customer and that was their job that changed everything. So third time was the charm, they successfully released the product to market. And what I like about this story is that they lead that space for about 15 years. And the reason they did is that we discovered all these unmet needs that were in the market and the first release of the product satisfied maybe half of them. But for the next 10 years every year they would take the next most unmet needs and work to address them. It was like clockwork, right? They were, the way like saying this is they were on the most efficient path to growth, right? Because they were always focused on the next batch of the most unmet needs. And while their competitors were still trying to catch up on the other needs they kept addressing, the next batch of unmet needs and the next batch. And to me that was extraordinarily exciting, rewarding, watching them achieved that call.
00:39:20 - 00:39:28
So essentially, they can continue to succeed because they kept iterating meeting unmet needs in their product on a continuous basis?
00:39:28 - 00:39:47
Right. And they knew what they were, you know, back in the early 2000s and they just worked the year after year. And they came back to us about 10 years later and said Tony, I think it's time to refresh our data. We're out. We've satisfied all the needs that you discovered 10 years ago. What do we do now?
00:39:48 - 00:40:58
Yeah. Yeah. It's interesting looking at startups as well. And I don't know if you've been involved with startups in terms of helping create products that meet unmet needs. Yeah, it sounds like you've been working a lot with companies that are working in the set market. They're just, and they're quite bigger corporations. But I'm involved with startups over time because of the space has been working in a lot and interviewed a lot of startup founders and CEOs, and what I've always had discovered, there's two things that startups are quite often in a war with and there's two walls or two battles are actually fighting. Number one is a technology battle.
In other words, they gotta keep iterating a product until it's the best in market, in other words, meeting the best, meeting the most unmet needs of the marketplace. And number two, it's a market share battle as well. So you've got to be trying, and these are not separate, they're working at the same time. So the startup is in two battles. Number one technology battle, and number two, they're in a market share battle as well. And that's a challenge. So do you get involved with startups at all or have?
00:40:59 - 00:43:54
Yeah, well, we certainly have, we worked, we've worked with a number of startups over the years and it's, it's exciting. They do have different challenges, but they have no legacy, which, which, which can be good too. Yeah, because they start with a clean slate. They don't, they don't have, they don't have to, they don't have the constraints that big companies have, they’re starting from scratch so they can create a brand new platform or architect something that's brand new, that is out of the box, thinking the same principles work though. You know, what their startups are trying to achieve? Product market fit, right? And it all starts with a great product. They have to go through the same steps. They have to make sure the market that they're in, that they've chosen, is attractive. You know, are there a lot of job executors, are they underserved?
How frequently do people try to get the job done, but we have, like 42 questions that we ask to help identify if the, if the market is attractive to a particular startup or not. And then once they pick the market, then again, let's go uncover the needs, right? Let's figure out which are unmet and then find segments that there are people with different needs and then go target the segment that you want to go after so that you're, because, like you said, they're in the market share battle. They're not going to win the broad market with their first release. They should go after the most underserved segment.
You always have the term early adopters say, oh, people are early adopters. What we've learned is that there's no such thing as early adopter. It's not like they're, they love technology and they want to adopt technology. What is, is that those are the people in the market that are struggling most to get the job done, they're the most underserved, right? So we've shown statistically, and when they're highly underserved, they're willing to go buy a new product or try a new product to get the job done better. So going after that most underserved segment is usually the fast path to product market fit. So, so the segmentation is very helpful in terms of that. Another thing I was going to mention, you know, startups, they're always looking for the next round of funding and I tell you what, when the startups, you know, the CEO shows up and the, at the venture firm and they show them a plan that says, here's why we're gonna win. This is the job that customers trying to get done here are the top 20 unmet needs. Here's the one we've addressed. We know they're willing to pay this much more to get the job done. This is the segment that we're going after. Here's how we want to position to them and they have all the data that justifies why they're gonna win. That's remarkable. Because what they're doing is they're mitigating risk in the, in the minds of the funders, right.
00:43:56 - 00:44:22
And yeah, that's really interesting in the sense that you are revealing almost a replica process that can create trust. Because there's a system behind, this is not just a crazy idea or something that is just a fly by night type of thing. Here's a reputable process and system that has been proven to work and this is what we're going to succeed because we're using proven systems.
00:44:23 - 00:44:43
Exactly right. Now, if you can, if you can convince the investment team that you're going to win and show them exactly why send them much more likely to give you that next round. And we've seen that in practice as well. That's one of the top questions we get from startups. Can I use this information to get my next round of funding?
00:44:43 - 00:45:28
Yeah. Look, I've talked to quite a few and a good mate of mine has been involved with it. He's actually, he's the founder of the startup and it's always this, what's your runway? In other words, what, how many months left of funding do you have? And I've seen it happen, flow from 12 months to two months. And I said to him, I'm going mate. I don't know how you live on the edge of chaos and destruction and failure. But he's, it's amazing. But the funding the ramp, there's different, different comfort levels I think for different entrepreneurs in terms of what risks they want to live with.
00:45:28 - 00:45:36
Yeah, exactly. All I can say is two months runway is not enough.
00:45:37 - 00:45:47
Yeah. Especially with what's happening around the world at the moment. There's going to be a bit more fear and pause, I think at the moment. So at any level.
00:45:48 - 00:46:31
You know, what we see is that, you know, companies are great at creating products, right? There's somebody comes out there creating products. They're just not great at creating the right products. Just like, I'd be just like IBM, you know, they could, they could invest a billion dollars in the product. Just not the right product. If they could only define the correct product. Everything else will take care of itself. And that's what we've been focusing on for all these years is, is doing the right thing. Like what is the right product, only invest in products that, you know, will win in the market. How do you know they win because you can prove in advance that they'll get the job done 15% better or more along these dimensions with that set of features. That's, that's what it takes.
00:46:31 - 00:46:55
Okay. So just to sum things up basically here a bit of your wisdom from what you've learned along the way since you started, and you've been in business nearly 30 years, you've been running a company as the founder, what are the biggest lessons you learned along the way as an entrepreneur? And also lessons that you learned from observing other businesses along the way that you think you could share with our audience just to wrap things up.
00:46:56 - 00:47:20
Sure, Well the biggest lesson is pick something you like. Yeah, the only reason I've been in this space for 30 years is because I like it. I love it. It's exciting, it's, you know, it's my passion and that, that helps overcome a lot of the other obstacles that stand in your way, is trying to run and grow a business over a period of time. So that's certainly the top lesson.
00:47:23 - 00:47:36
Yeah, and reason I love it too is because being an entrepreneur is a long journey. It's a marathon. Yeah, and if you're doing something you hate just to make money, it's going to be very hard to sustain that passion and energy, isn't it?
00:47:36 - 00:47:37
00:47:38 - 00:48:13
And I call that discovered phase and discovered phase is beautiful intersection of experience, expertise and passion that people are to launch a product that people are willing to pay for or a service. And I love what you mentioned because that gets to the absolute core of what I believe about being an entrepreneur, life is too short to do something you hate for the rest of your life just because you want to make a few dollars, you need to do it because if you can get, if you can get that switch turned on that will sustain you for the rest of your life.
00:48:14 - 00:48:18
Yeah. And so far so good.
00:48:18 - 00:48:32
Well it doesn't mean that you don't evolve what you do, but I certainly think that you've got to discover why you're on this planet as an entrepreneur and as an individual and if you can, if you can discover that, then the rest is a process.
00:48:32 - 00:49:00
Yeah, exactly. And it's been fun. You know, I'd say for the first 25-ish years or so of this, my goal was to perfect the process. Let's make sure it works in every situation. So we've done that. For the next 25 years, what I want to do is to help people install the process and use it, so to use it as part of the innovation capability programs as opposed to us doing it for them, teaching people how to do it themselves.
00:49:00 - 00:49:27
So maybe the best way to wrap it up then is to tell people where can they find this information to do a bit of self education about your system. I believe, that's a couple of your books plus your website. Where can you go in and discover the fundamental elements of basically the process for getting jobs done? So what are some resources I can use and how can they contact you as well?
00:49:28 - 00:50:16
Sure. Well, they can contact me at [email protected]. So that's that's easy. There's a number of sources for information, one is our website at strategyn.com. There's a lot of information and resource center there. I also have a medium site where I published some articles at and that site is called jobs-to-be-done.com with hyphens. And then we have a site called jobs-to-be-done-book.com that allows you to download for free the audio version of Jobs to be Done: Theory to Practice and also e-book version of that as well. So, those are some of the best sources of information to take the next step and get started.
00:50:17 - 00:50:38
Well, thank you for your time, Tony. It's been an absolute pleasure. You've just confirmed the evolution of my journey over the last two or three years, which is processes and systems will set you free and make you successful. So if you're not very good at systems, hire someone who is.
00:50:39 - 00:50:47
Exactly, you don't have to invent the process. Just follow a good process, right. That's what matters.
00:50:47 - 00:51:05
And I think what I love about what you revealed is that you had an aha moment watching a huge failure. You learn from that and then worked out your own processing systems that you've turned into reality and helped many businesses along the way and thank you for sharing your gift with the world, Tony. It's an absolute pleasure,
00:51:06 - 00:51:08
Jeff, it was my pleasure. Thanks for the invite. I appreciate it.
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