How a lean startup mindset can drive cross-industry innovation

In this episode of the Decoding Innovation podcast, Ben Hafele, CEO of Lean Startup Co., explores the transformative power of the lean startup methodology in corporate innovation.

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The lean startup mentality epitomizes innovation and agility by providing a structured approach to developing products and services that truly meet customer demands. It emphasizes the importance of validated learning, rapid prototyping and flexibility in business modeling.

In conversation with host Brent Duersch, Ben Hafele, CEO of Lean Startup Co., discusses how startups and corporate innovation teams alike thrive on navigating uncertainty. Hafele emphasizes that corporate innovation teams inherently embody the startup ethos when engaging with emerging technologies in areas such as artificial intelligence (AI), mobility, wearables and electrification. This mindset is crucial for fostering innovation and maintaining a competitive edge in the rapidly evolving tech landscape.

With extensive experience in applying lean startup methodologies across various business landscapes, Hafele offers fresh perspectives on innovation, advocating for practical solutions and a “learner” mindset over a “knower” mindset. He explains how lean startup principles, with a focus on customer feedback and iterative design, enable organizations to continuously test and refine ideas, ensuring investments are made in concepts with genuine market potential.

Hafele envisions a future where the lean startup mindset remains essential, its principles guiding companies through the uncertainties of tomorrow's business challenges.

Key takeaways:

Lean startup is a mindset, focusing on what customers truly value. It's about systematically vetting and de-risking new ventures, applying the scientific method to business ideas.
For corporate innovation to succeed, teams must adopt the startup approach: embracing uncertainty, leveraging customer feedback and iterating rapidly in tech-driven markets.
Lean startup principles are set to evolve and stay relevant amid the uncertainties of AI and future technologies.
By combining the strengths of various methodologies, such as design thinking and agile, organizations can create a tailored approach that best suits their unique challenges and opportunities.

For your convenience, full text transcript of this podcast is also available.

Announcer

Welcome to the Decoding Innovation podcast series, brought to you by the EY-Nottingham Spirk Innovation Hub, where we explore the innovative technologies, business models and ideas that are shaping the future of industries. During each episode, we meet with stakeholders at the cutting edge to discuss innovations in their space, challenges they need to overcome and their outlook on the future.

Brent Duersch

Welcome to the EY-Nottingham Spirk Decoding Innovation podcast. I'm your host, Brent Duersch. I'm coming to you from the EY-Nottingham Spirk Innovation Hub in Cleveland. I'm really excited to have Ben Hafele today. He's the CEO of Lean Startup Co., and we're going to have a fantastic conversation around Lean Startup, what it means, the implications for all of you out there in the innovation world, whether you are in a startup or a big enterprise. Ben, welcome to the podcast.

Ben Hafele

Thanks for having me, I’m excited to be here.

Duersch

Let’s get to it. First of all, Ben, why don’t we start, give a little introduction to yourself, a little bit of your history and your story.

Hafele

My name is Ben Hafele. I’m currently the CEO of Lean Startup Co. as you mentioned. How did I get here? Back in the day, back in the 2000s, I was coaching startups, very involved in the startup scene in several different geographies. In addition, I started doing corporate product development, corporate market research kind of at the same time. So I was leading two different lives, if you will. And what was amazing to see was that whether it was a corporate innovation team, a corporate product team or a startup that was operating out of a garage or an accelerator, they encountered a lot of the same problems, right, which is, we’ve got this new thing. What do we do next? We could do an infinite number of things. Buy an office, get furniture or hire someone. But what should we do next?
I really became a student of innovation and startups. And then was lucky enough to teach entrepreneurship at the university level and eventually got a job at Caterpillar, the big, yellow construction equipment company, not just the boot company, to run the lead innovation programs. I was a founding member of that program. I grew it out and then I actually hired the Lean Startup Co. to come in and help with a project in China and thought, wow, that’s a really cool job. I saw a job opening online, I applied to it, without hope of actually getting the gig, and here I am today. And so, what we do today is help companies globally in the space of applying an evidence-based, customer-centric approach to innovation and product development and creating value with technology.

Duersch

As you went through the pivot from the corporate world to joining Lean Startup, what was your thought process, what was going through your mind, what did you want to accomplish as you went through that move?

Hafele

Well, what’s interesting is I was really happy at Caterpillar. It’s a great place to work and I loved it. When I handed in my resignation, I said to my boss, ‘Hey, I love working for you. I like the money, the crew, the culture is great. I just, if I don’t give this a shot to go out and do what I do for Caterpillar for everyone, I’d just regret it for the rest of my life.’ So I had to give it a shot and so far, so good. It was really about expanding my impact. So translating what I learned at Caterpillar to helping global companies in many different sectors, whether it was telecommunications, large industrials, software companies, you name it. It’s amazing how much impact you can have in the space of innovation and product development just with some of these basic principles and applying them to a widely diverse number of use cases. So it's been great. It’s been a fantastic experience.

Duersch

Can you frame up a little bit, a lot of folks have an idea of what lean is. And then you've got this variation of lean that is lean startup. Can you frame up a little bit the differences between the two, how they're similar and how they're different.

Hafele

Absolutely. So we're taking the principles of traditional lean and we're just applying them to a little bit of a different space, right. So in traditional lean, as many of our listeners will know, you first identify what customers value, and then you look at how that value is created. And anything that doesn't directly contribute to the creation of that value is labeled as waste and is therefore bad. It must be eliminated. And so that works really well. That came out of a manufacturing type of mindset, right? Certainly a big theme at Caterpillar and a lot of the auto manufacturers where you say, for example, we've been building the Toyota Corolla. We know that customers value that.
So now we can lean out everything in terms of the manufacturing and the supply chain. And even though the new product development, because we know customers like the Corolla, and we can lean things out. Lean Startup is the application of those principles. So we're still very much, concerned with waste and value. But it's when we're not sure what customers value in the first place.
And so it's easy to say in lean, box one that you check is find out what customers value. It's very hard in practice. And so just going out and doing a survey and saying, do you like this is a really bad way of finding out what customers value. So we're hyper-focused on that kind of front end of innovation where we're saying what if we don't know what customers value in the first place? What's lean then and what's not lean then is to come up with an 85-page business plan in a three-ring binder that's riddled with assumptions and say, ‘Hey, we're going to go execute this. Like, this is what we think customers value. We're going to go do that.’ And unfortunately, that's still the incumbent process at most big companies around the world. Let's just face it. Now, are we on an adoption curve of moving to a more iterative, customer-centric approach? Absolutely. There's still a lot of companies out there that just think innovation is coming up with a big plan and executing it, or even asking customers what they want and executing it.
So Lean Startup then is really a mindset that's coupled with a process and some tools, to say, what if we don't know what customers value in the first place? The first big hurdle is we don't have to pretend like we do. There's nothing wrong with us if we don't know what customers value. We're not deficient as humans or employees or leaders. We just have to say, the truth is, we're not sure what customers value. So number one is admitting that we don't know. And then number two is what do we do next. And so that's what Lean Startup is – systematically vetting, shaping and de-risking entire new businesses, new products, new services, even new features on existing products.
Anything where we're just not sure exactly what customers value yet. It is the scientific method applied to business. We think this is true. Let's test it. We think this is true. Let's test it. Once you find out what customers value, then you can apply traditional lean to lean out, production, supply chain, all that kind of stuff.

Duersch

So in this context, we're using the word startup. But this is often within the context of a bigger enterprise, a bigger corporate environment. So how does that dynamic work?

Hafele

Thank you so much for bringing that up. It's one of those, it's a special sauce thing, but it also, it creates confusion. So, Eric Ries, who is the author of the “The Lean Startup,” in the book, he defined a startup in an extremely accurate way, and that is that it is a human institution. It's a team that is designed to deliver a new product or service under conditions of extreme uncertainty.
And so notice it doesn't say anything in there that we have to be in a garage eating ramen noodles. It doesn't say we have to be using AI. It doesn't say anything it doesn't need to say. And what's essential about it is the presence of uncertainty. We're trying to do something new under conditions of uncertainty. That's what makes a startup a startup. And so back to my early days of coaching startups and working on new initiatives in a corporate environment, new products, it was very similar. We were faced with almost exactly the same issues which is we got this thing we're thinking about, new product, new service, new startup business. But how do we test it? What do we do next? How do we vet, shape and de-risk this so that when we put the big bucks down, we have much more confidence that we're investing in the right thing.
And so we talk about internal startups all the time. So, at a company, let's take Starbucks. At a company like Starbucks, there could be an internal startup team at Starbucks who is thinking, I wonder if we should introduce mushroom coffee. That's a thing, right? I think, I've heard about it. People drink mushroom coffee. Should we offer that on the menu? I don't know. Well, guess what? That's a startup team. They happen to be at Starbucks. Now, if Starbucks uses their algorithm for, placing a new location, somewhere in New York City and they've got an algorithm that's been proven to be 99% effective and they use that algorithm to create a new location due to foot traffic and whatever.
I would say that's not a startup. That's an existing business model. Even though it's new, there's not uncertainty. They know it works. So it's really that presence of uncertainty that makes a startup a startup. And with that definition, corporate innovation teams are startup teams. A lot of corporate product development teams are startup teams, including ones that are working on new things like AI or mobility or wearables or all the other electrification, all the things that companies are looking at these days. Those are all startup teams. And same thing with technology teams. So we're looking to use AI. We're looking to use blockchain. Remember when drones were going to change the world? Every problem is going to be solved with a drone. Those types of teams are also startup teams.

Duersch

Excellent. So do you want to deep dive into some of those different use cases a little bit within the corporate environment. So you mentioned innovation. You mentioned product development. You mentioned this kind of tech space. How is the Lean Startup mindset and methodology and toolset. Is it similar in all those contexts, or is it kind of different in terms of how it gets applied?

Hafele

Yeah. That's great. I mean, the underlying principles are the same, which is when you have an opportunity, decompose it into parts that make sense and then figure out which one of those parts you should validate first. If you already have high confidence in one of the components, don't waste your time with that. Move on to the next one. And then ask yourself after you've figured out what to test next, which, by the way, is the most overlooked part of lean startup. Everyone wants to get on with MVP's and experiments, but if you're not testing the right thing to begin with, you're wasting your time, which is not the objective of lean.
But after you figured out what to test next, you then say what's the most minimal and yet still viable way of testing that next most critical set of assumptions? And you'll notice that similar to a minimum viable product language. But that's what it means, a minimum viable product is the most minimal and yet still viable way of testing assumptions. And so teams will come to me and say, ‘Hey, we've got an MVP.’ OK, great. What assumptions are you testing with your MVP? ‘Well, we don't know.’ Well then it's not an MVP. It can't be because it's not testing any assumptions. What assumptions should we test next? How are we going to test that in the most minimal and yet still viable way. Then we run that test and say start over again if we need to. Let's go back to the beginning and say, ‘Okay, what do we need to test next? Do we still need to test this component or can we move on to the next component.’ And you do that until you have enough confidence to say, ‘You know what? Before there was a 99% chance that this initiative would have failed, and now there's a 30% chance,’ just because things happen, like COVID-19, for example. You can't control it. That de-risking is immensely valuable for companies.
So basically, Brent, you're asking me, are they different? Those components are always the same. The language that we use and the terminology and the types of leaders that we work with are different. So those concepts are wrapped in different clothing, right? They're packaged differently.
With innovation, we usually talk about growth and somebody has got a goal of X million dollars in growth by five years from now or something like that. That tells us it's more of an innovation use case.
Another thing that signifies whether it's an innovation use case is typically there's an upfront team that does some validation and then they would pass it to another team in a business unit that would actually execute it.
Sometimes we call that the exit strategy partner or the execution partner. We have one client that calls it a home room. But there's a separate team that then hands it to another team. That's really important to get that right, because nothing worse than a well-incubated growth opportunity that goes nowhere because we didn't involve the right people at the right time.
In the product space, it's typically the same team the whole time. And we don't talk about growth or X number of dollars. It's just good old fashioned, Hey, we want to make sure we're building products customers love. So we want some help on being customer-centric and iterating and testing our assumptions. So usually that team is the same team throughout. And then on the technology side, a lot of different use cases there. Obviously the biggest one right now is AI.
So our kind of Lean AI approach, which is specifically adapted for teams that are developing AI products, is really about, validating the use case and the technology at the same time, but not too much upfront. And so we've got cases where people are doing all this feasibility on AI. And then they say, ‘Okay, great. We've worked out all the architecture. The data is super secure. We've got all the ethical practices in place. The tech stack is ready, and then the one use case we had in mind for all that, like nobody cares about it. And so we've completely wasted all of our time and money.’
What I would say is all the principles are the same, but we're adapting it to each one of those use cases based on the customer need.

Duersch

So Ben, I know you've talked about multiple contexts in which lean can apply in the product sense, in the innovation sense, and kind of in that emerging tech space. But drilling down on to the innovation side a little bit, I know you've been on record before saying that innovation is a dangerous word. Could you expand a little bit what you mean by that statement?

Hafele

Yeah. So innovation in many cases is all about technology. So it's technology-driven innovation. And so we get really excited about a technology which by the way, we should, especially about AI. It's really exciting. I think we're all experiencing how exciting it can be and how amazing it can be. But innovation is a problem when we forget that innovation is about solving problems for customers. And so I always give a really kind of simple example where I say, let's say that we have a startup team, maybe an internal startup team at a big company and they've gone out and they've really done some good validation on a customer problem to be solved. We call that the customer hypothesis, right? And they come back and they say, ‘Okay, we've got this, problem statement. We know that this is something customers are struggling with and that if we could really move the needle on solving this problem for customers, then we would create value for them and potentially value for our company.’
Great. Then let's say they go out and they do some solution concepting and they start doing some minimum viable products. And they're working on a solution to that particular problem. And it all comes down to two solutions that could solve the problem. One of those is a 3D printing drone that's powered by blockchain and artificial intelligence. Okay. And the other one is we could hire a person named Sue. And the question is which one of those two solutions should we pick?
And the answer, of course, is whatever addresses the problem and maximizes value for the customer the best and maximizes value for the company. But when we're just thinking about “innovation,” we tend to pick the 3D printing drone powered by blockchain and artificial intelligence because it's “innovative.” And so, I think companies that are doing innovation well are aware of technology. They're aware of the things that are possible with technology, but they're still laser-focused on solving the problem the best way possible. I was at a great presentation a couple weeks ago at an artificial intelligence conference, and a speaker said, one of our biggest accomplishments was we didn't use AI to solve a particular problem because it wasn't the best way to do it. We just used some traditional analytics. And it was great because that's what innovation is, solving problems for customers in a way that creates value for our business, not just let's solve everything with a particular technology.

Duersch

So you're saying that maybe the 3D-printing, blockchain-enabled AI-powered drone is not always the answer.

Hafele

Not always the answer. If it solves the problem better than hiring the person named Sue, then please do that option. But if hiring Sue is a better option and is going to create more value for the customer and more value for the company. Then please hire Sue.

Duersch

So when you talk about the uncertainty that happens, you and I have talked about this before, the idea of the funnel and the tunnel. I love this concept. I've used it I don't know how many times since we first met. But it's really become a very helpful mechanism to help diagnose where different teams are having innovation challenges. So I would be remiss if we didn't talk a little tunnel and funnel here.

Hafele

I love it. So, let's start with the tunnel. By the way. The tunnel is where 98% of activity in big companies happens, right. And the tunnel is where we say we have decided to do X and now we need to execute X. And so in some cases, the tunnel, I'll just say that's the execute phase. Right. We've made a decision. We're moving forward. We've made a decision. We're moving forward. I would argue that most corporate activities should be that way. Because you're running an existing business with an existing business model, existing products, all that kind of stuff. There's a different phase, a different stage of innovation or product development which instead of execute is search, which is we're not sure what we should build in the first place if anything. And again, that takes courage to admit that. But for teams that can see that there is a thing called the search stage, a funnel approach is what is needed rather than a tunnel approach, which is appropriate for execute.
And so in the funnel, or in the search stage, we're asking ourselves questions like, is this even aligned with our strategy? Like, should we be working on this at all? Do we really understand customer needs? Do we have any evidence above and beyond people just telling us they like our solution concept that it's valuable? Do we have any idea how we grow beyond kind of nerdy early adopters? Do we have the right business model? On and on and on and on. All the things that happen in a startup or new product development or an innovation team at a big company.
And so a funnel approach is saying we need to have a process for vetting, shaping and de-risking opportunities. If you put 10 things into the funnel, the reason it's called a funnel is that it narrows. And for anyone that is familiar with lean startup terminology, we call those pivot, persevere, kill recommendations where by design, if you start with 10 things and you end with 10 things, then that's a tunnel, not a funnel.
And that is appropriate for the execute stage, meaning we started it and gosh darn it, we're going to end it, meaning we’re going to execute it and it's going to happen. In the funnel, the definition of success is very different. And it is please, please, please identify the weaker things at the top of the funnel and get them out of here as quickly as possible. So you're actually trying to prove startups or new products or initiatives, we'll call them initiatives, you're trying to prove initiatives wrong.
So teams are rewarded for making the right recommendation, not just getting everything through no matter what, even if it's a horrible idea. And so the funnel very deliberate, it’s shaped because of the kind of the pivot, persevere. kill. We call it park now. The pivot, persevere park framework. And in many cases, there's designed cut rates saying you've got four stages in your funnel. We're going to throw out half in between each stage. So it's not that the idea is bad or the initiative is bad, it's just not as strong as some of the other ones. So we want only the strong use cases to survive. So that's the idea of a funnel versus a tunnel.
And that way at the end of the funnel, you're not just on a wing and a prayer saying, gosh, I hope this works. You have much more confidence and you have evidence that the thing that comes out of the funnel is ready to go into the tunnel, and therefore you can invest the big bucks in it then. You can invest hundreds of millions of dollars and the years or whatever you need to do. But please don't do that for something that's really uncertain. This should just really be going into the funnel. That is kind of the message behind the funnel and tunnel.

Duersch

Do you have a couple stories that you could share maybe around where lean startup was applied and it led to a very positive outcome. And maybe conversely, one where maybe the circumstances weren't right and people got a little dangerous and that wasn't necessarily the best possible outcome.

Hafele

I would say there's two definitions of success that I would just categorize. One definition of success is we put something into the funnel. Maybe we pivot on it. We kind of beat it up a little bit, right? We change it, we invalidate some assumptions, we're iterative and it comes out of the funnel and it goes into the tunnel. And it's an amazing experience. We're all making money right, popping bottles. Everything's great. So lots of examples of that right there that are well-documented. And so that's what everybody's looking for. Maybe the most surprising type of success is when something goes into the funnel and it doesn't make it. I call that a success type two. I think I need some branding help. But a success type two is basically, hey, you know what? We vetted, shaped, and de-risked this and decided it wasn't worth it. And so we stopped it. We parked it. And there's a client I was working with where we did a 10-week sprint to go out and look at a new opportunity and, within six weeks, it was just clear as day that this was not an opportunity. I mean incontrovertible evidence. And so, in the report out to senior VP, the team said, ‘Here're the experiments we ran, here are the conclusions that we drew. And for that reason, we're going to make a park recommendation.’ And the senior VP basically did a backflip. I mean, she was just so thankful because she said, ‘Look, we've been working. We've been kind of thinking about this for four years. Thank you for helping us get on with our lives and we can actually just put this to bed and move on and spend our money somewhere else.’
And so, that’s maybe a surprising type of success. But maybe the story part of it is, after that report out, I emailed the team and I said to the team lead, ‘Hey, great job. It's an amazing success type two, an amazing park recommendation. It was the right recommendation.’ And the team lead wrote me back, copying the team in and said, ‘Hey, that's great. I just wished we could have like made it through the funnel and scaled and had a big growth win.’
And I said, ‘Well, you know, really, the type of success is dependent on the nature of the opportunity, not the performance of the team.’ And that's a big difference, right? So when you're in the funnel, the job of the team is to make the right recommendation. And so a high-performing internal startup team could make five park recommendations in a row. But if all of those are the right recommendation for the business, they should all get an A+, 100%, extra credit, gold star on their performance review because that's what you're asking them to do. You're asking them to make the right recommendation, not to go with the flow and say, ‘Yeah, anything you give us, we're going to turn into solid gold, even though it's a really bad opportunity for the company.’

Duersch

Is there an example that comes to mind where you've seen a team kind of go through the motions, maybe, but they haven't fully, they're not fully living the principles the right way?

Hafele

I think I mentioned this before, but lean startup is a mindset. And then once you have that mindset, it's a little bit chicken and egg, right? It's a mindset. And then there's some process and tools that help you kind of live that mindset. And so a great example of what I mean, I was working with a team, this is a long time ago. Working with a team and it was an internal innovation team at a company. And then there was a sponsor, this person was actually in the C-suite of the company. And we always have that, the sponsor plays kind of the venture capitalist. And the team plays, is the internal startup. And so after the team runs experiments, they make a pivot, persevere, park, recommendation to the sponsor, and then the sponsor can make an investment decision.
So I couldn't get the team to do anything, Brent. So we went through all the tools and everything and like their eyes lit up right in the training, like, wow, like, I totally get this. But then, you know, they didn't do any interviews, they didn't run any front door tests, they didn't run any pricing tests, they didn't create any MVPs until like the last two weeks, where they did just enough to kind of say they did something. It was very frustrating. Right. And I thought, bad team, right.
In the meantime, I was working with the executive, because we always work both with the sponsoring executives and stakeholders and the team. And we were talking about, hey, your role is different here. We're in the funnel, not the tunnel. And your job as a leader is different.
Your job is to pressure test the evidence that the teams present to you and make sure that they've covered all their bases and then basically agree or disagree with the recommendation that they give you on whether to pivot, persevere or park.
Yes, yes I understand.
We get to the report out, it's an hour long. The team gets about three minutes into their presentation. They're on slide two and they've got 10 slides. And the leader cuts them off and said, ‘No, that's not right. Here's why you're wrong. And here's what we're going to do instead.’ And then it hit me. It wasn't a bad team. It's a bad leader. And so the reason the team wasn't running experiments and wasn't generating a real pivot, persevere, park recommendation is because they knew it didn't matter because they were going to get steamrolled by the leader. And so why would you put yourself through all that if the leader is just going to tell you what to do anyway? So they were basically saying, ‘We just hold our nose for 10 weeks, this is all going to go away, and we can just get back to being told what to do.’

Duersch

Wow. So culturally, what has to be true from a leadership standpoint for this to work and what has to be true from a working team standpoint for this to work. And probably ideally, culturally, they're the same thing.

Hafele

Yeah, I mean, I would say it starts with leadership. Right. And so our best clients and the ones where we have the most impact are where leaders bring us in and say, ‘Hey, I know I'm part of this.’ The ones where we have less impact or we even just refuse to do now is where a leader comes in and says, ‘Just train my teams and don't bug me.’ Because lean startup is a system. If a team is running experiments and they come back after the 10 weeks, for example, make a pivot, persevere, kill recommendation to a senior VP, and the senior VP says, ‘What's a pivot, persevere, kill recommendation? What's an experiment? And why are you here?’ That's a disaster, right? The system is broken. The leaders, sponsors, stakeholders. Sometimes it's a growth board, sometimes it's a product council. We'll call it whatever it needs to be called. That governing person or group has a legitimate role in lean startup. And so, making sure that they're on board and that they've got the right mindset, that's the fundamental piece. And, what it is, is that leader saying, ‘Look, I know we've done things a certain way for a long time. For these particular projects right here, we're going to act differently. Here's why. And here's what I'm holding you accountable to do. So if you come back here and you haven't run any experiments, and you give me a made up pivot, persevere, kill recommendation, I'm going to find out and you're, not you're going to be in trouble, but you will not have done what I asked you to do.’ So, one of the, there’s a startup way triangle that Eric even included in the Lean Startup book. And the base of it is accountability. So, most people think of Lean Startup as a process. It's not just a process. If nobody's holding a team accountable for running Lean Startup, why would they be? Why would they just go out and run experiments if they knew that no one's holding them accountable for running those experiments? And, nobody's going to do anything with the results. You'd be crazy to run experiments if you knew that. And yet that's precisely what a lot of listeners are asking their teams to do.

Duersch

So I'm going to bring up the F word, failure. How as a team leader, how do I set the right tone with my team members that are working in this ambiguous space? Because I've seen everything during the course of my career. Everything from failure is not an option to failure is a wonderful thing. Fail all you want. How do I set the right tone with my team in that case?

Hafele

It depends on the company. The message is the same. It's how you wrap it that's important. If you go to a company and they're always talking about, hey, we want to fail fast, fail often, fail early and everybody knows what that means, then, you know, that's great. Most of the time that's not the case, especially in the companies that we work with.
And so I would say look, in the innovation tribe, the product tribe, the technology tribe, we get it, we know what we're talking about. But please don't use that language with the senior executives because they're going to look at you like you have four heads. If you say, ‘Hey, we want to fail. We want to fail often and fail fast.’ It's like, ‘Get out of my office.’ Instead, it's how do you define failure? And, I would say just like there's two types of success, I'd say there's two types of failure. One type of failure is we get through the funnel, and we're like, ‘Wow, we've got this really cool thing.’ Something makes it through the funnel. But then it never gets into the tunnel. It just kind of fizzles out. Right? I'd say that's a failure. There's a lot of different drivers of that. We didn't involve the right people in the project. It wasn't aligned with strategy to begin with. We didn't charter the project and kind of bring the exit strategy partner team along with us. A lot of best practices there. So that's a that's a failure type one maybe. Failure type two is we found out that we shouldn't do something in the funnel and we're like, yep, we invalidated it. And then we just did it anyway. And I'm sure for our listeners, that's never happened to your company. But in other companies, it happens because the highest paid person in the room has conviction or it’s somebody's pet project or we said we were going to do it anyway or there's the sunk cost fallacy, which is we already invested so much in this, we've got to launch it because if we don't, we're going to get in trouble.
And so I would say if those are the two definitions of failure, then failure is not an option. What we're going to do is we are going to either identify great initiatives that should go into the tunnel, and we're going to get them through the tunnel, or we're going to kick out initiatives in the funnel that should never get to the tunnel. So we're only going to succeed. What we're not going to do is, we're not going to invest in things that we know we shouldn't invest in and we're not going to incubate things that are great and then have them just die on the vine. And so with those definitions of success and failure, I'd say failure is not an option. Because we have an empirical, evidence-based approach to which things should go into the tunnel.

Duersch

Earlier you described lean startup is a mix of both mindset and toolset. Right. So help me think through the mindset piece a little bit, right. If I'm bringing together a new innovation team or a new technology team. What sort of mindset am I either looking to recruit as part of that process or looking to create as I bring that team together?

Hafele

There’s an entire book that could be written on this subject. I'll simplify greatly and I'll just talk about maybe two axis that we can think about. One would be having a learner mindset versus a knower mindset. And just the other day I heard someone talk about a know it all versus a learn it all, which I loved. So I might start using that in the future. But you can be a 30-year veteran in a particular craft, let's call it engineering, and still have a learner mindset, which means instead of saying, I know the answer, here's what we're going to do. It's, ‘Oh, that's an interesting idea. Let's go test it. Let's learn whether that's true or not. Let's go find out together.’ Right. So we want that learner mindset not a knower mindset. On a startup team, if you've got five cross-functional people that know exactly what we should do, you're in trouble, because, it's never going to be the same thing and they're just going to argue with each other the whole time. You want to have a, ‘Hey, here's what we think. Let's go test it and find out. And we're all going to learn together how wrong so that we can launch the best possible product.’
So learner mindset is one. I'd say the other one. There's kind of an owner or a founder mindset as opposed to maybe a learned helplessness mindset. An owner or a founder mindset is, if you're a startup, a traditionally defined startup. And you've got two weeks’ worth of funding left and you know you’ve got to go interview some customers, you're going to interview customers. You're going to figure out a way to do it. And that's that ownership mentality. We're going to take ownership. We're going to find a way through. And in the large corporate context, if legal challenges us, that's our fault. We should go to legal and say, ‘Hey, we're both in the business of reducing risk. Thank you for doing your job. I didn't clearly explain why we need to run this experiment. Here's what we're doing.’ We don't want to have a public humiliation. We want to run it on this little control group and we're not tricking anyone. And then nine times out of 10, that works, right? But you’ve got to take ownership. You can't just say, ‘Well, they said we couldn't, so I'm going to sit here with my feet up. So it's the combination of an owner or a, founder mindset and a learner mindset, and, those aren't personality traits, by the way.
Just today, I'm sure I've exhibited learned helplessness and I've also exhibited, know it all. So it's when you're on the team, you're constantly trying to drag all of your team members and yourself back to that kind of founder learner quadrant.

Duersch

So Ben, you talked a little bit about pivot, persevere, kill or pivot, persevere, park. I'm still retraining myself, on the frameworks that are used within the lean startup context. Could you expand a little bit, one of the other ones that is really big is the concept of build, measure, learn. How does that come to life?

Hafele

So again, kind of a frequently misunderstood concept, much like the minimum viable product. But, they're actually very kind of inextricably intertwined. And so build, measure, learn. Let me just take you through the steps. From the perspective of a team that is practicing build, measure, learn. You'd actually start with learn. What do we need to learn next? That just ties back to what we talked about before, which is we've kind of decomposed this new product, this new business, this new feature, whatever it is, into some components that make sense to test. And so now it's which one of those components should we test first? Should we test the customer problem? Should we test our value proposition? Should we test our growth strategy? Should we test a certain part of the business model? Which one? What should we test first?
And a lot of that is well, if this assumption or set of assumptions was invalidated through an experiment, would we have to test the rest of these or would they just become irrelevant? And so if there's one set of assumptions like that then you should test it first. If you don't know the answer, you should test out those assumptions first. So learn is about identifying the right assumptions to test next. And that is a huge part of lean startup that everybody loves to gloss over as I mentioned earlier. So it starts with learn. And coming out of learn is here is the assumption or the assumptions that we need to test next. Then build is what's the most minimal, yet still viable experiment that we could build to test those assumptions?
So I'll have teams come back to me and say, ‘We're going to run this experiment.’ They've got their experiment design template filled out. But the assumptions that this experiment tests are not filled out and like, how could you possibly design an experiment if you don't know what you're testing? It's impossible. And so then, the experiment part is the part everybody tends to glom onto, which is, what are we going to do to test these assumptions? So if we do this, then customers will say or do something in response. And so there's a big difference in terms of what people say versus what people are willing to do. And so that has to do with the strength of evidence of your experiment.
If somebody just says, ‘Yeah, that's great, I like it.’ That's good. It's usually a good place to start, but that's really low strength of evidence. Is there another call to action that you can add to your experiment that's higher strength of evidence, meaning they have to put some skin in the game. They have to send you their data. They have to sign up to meet with you at a really inconvenient time. They have to wait for an email and respond to it. They have to sign a non-binding letter of intent. There's an infinite number of higher strength of evidence calls to action above and beyond just tell us what you think. So that's build. Measure is run the experiment and then go back to learn and capture the data systematically. Go back to learn and say, ‘What do we need to learn next?’
So learn, build, measure is what it feels like for the teams. And we talk about learning velocity. It's how quickly can you do that? In some cases the norm right now is it would take us six months to validate some assumptions. How do we do it by tomorrow? How do we do it by next week? Well, it's not going to be statistically significant. Okay. What if it wasn't statistically significant? What if we went and talked to 10 people and got some idea of whether we're pointed in the right direction? And by the way, if you interview 10 customers and they all say the same thing, do you need to have a statistically representative sample? Probably not. So, so build, measure, learn or learn, build, measure as it applies to a team, super powerful. And that's really at the essence of what lean startup is.

Duersch

So if I've got a short list of assumptions that I want to go test right, where do I start? Do I start with the easiest ones to prove and disprove? Do I start with the toughest ones to prove and disprove because it feels really satisfying to check the box on all the easy wins?

Hafele

Well, you're very kind and I know you're throwing me a softball here. The correct answer, of course, is it’s the most critical assumptions that we call the leap of faith assumptions, the LOFAs. These are the ones that we're the least certain about that are the most important to our project success. Stated differently, if we're wrong about them, we either need to park or pivot. And so a big part of lean startup is not only which part, you've divided it up into components, which assumptions, and then you would do an assumption map, which is actually identifying those specific LOFAs.
And this is just the essence of lean. Because if these aren't true, everything else doesn't matter. Those are the ones you test first. Your leap of faith assumptions.

Duersch

And I want to drill down on the word minimum. Because when you talk minimum viable product, like just how minimum can minimum be.

Hafele

I love it. That was great. By the way. This is going to help a lot of people, right. So minimum in minimum viable product is what is the most minimal, yet still viable way of testing these assumptions that are the next most important ones to test. And so it's the essence of lean to say that it is minimum. It’s still viable, but by the way, the viable doesn't apply to the product itself, meaning it needs to be a viable product. It's a viable way of testing the assumptions. That's the common misconception. And so it's basically saying if we need this information, what's the quickest and most affordable way we can get it? And then as soon as you state that, now you've set the bar, is there an even quicker and more affordable way of getting that information? And so there's always a better way. That's the beauty. That's the art of experimentation and of build, measure, learn is there's always some better, faster, and yet still viable way of testing the next most critical assumption. So that's what minimal means. It's not just minimal in a general sense. It's the least we need to do to test the next most important thing.

Duersch

So, Ben, one thing that we can maybe clarify here today is there're groups of lean startup practitioners out there. You've got design thinking practitioners out there. You've got people who are like all in on agile. How do these things fit together? Like, do they play nice or are they mutually exclusive? Do they overlap? Take me through that a little bit.

Hafele

It's a great question because there's a lot of, I don't want to call it clickbait, but a lot of maybe more heat than light stuff out there on minimum viable products and build, measure, learn and this: What exactly is lean startup versus design thinking versus agile? And I mean, it's a good debate to have. But, what's valuable? And what's valuable is we need a way of deciding, we need a way of operating in the search stage that's different from in the execute stage as we talked about earlier. Basically, we need a funnel approach in the search stage and we need a tunnel approach in the execute stage.
And one of my favorite quotes from Eric Ries, who of course, is the author of The Lead Startup and our founder here at Lean Startup Co., is if it works basically in that search stage, then it's lean startup. And if it doesn't work, then it's not. Because it is the scientific approach to business. We have an idea. Let's test it. And then if it's if it's valid, then we can move forward with it. And so I would say many of the things that we help our clients with are design thinking in the sense that we're always encouraging empathy. Empathize, define, prototype, ideate, test. We do all those things. And it's like is that lean startup or design thinking? I don't think it matters. What matters is that we have a systematic way of weaving all those things together so that teams know what to do next. And then just as important as we talked about Lean Startup as a system, there's a language and a cadence of what leaders need to hold teams accountable for doing so that they can make investment decisions based on the team's recommendations. So much of what we do is straight up design thinking. A lot of the books that I have back here are design thinking books. And then with agile, agile also kind of extends into the search stage quite a bit, a lot of iteration and things like that. But the way that a lot of companies have implemented agile, they say, ‘Hey, congratulations, you're the product owner and it's your job to know everything about the customer and manage backlog.’ But they just don't get any tools to actually do that. And so agile and lean startup and design thinking kind of click into each other. What I would say is there's a lot out there where you could you get lost in the in the blog posts and everything. But in reality, very similar or congruent approaches. And right now, I'd say maybe a fourth of our clients, we're helping them. They have an existing safe or, modified agile process of some kind. And it's, hey, how do we do the front end of this so that things that go into our safe portfolio, we know they're the right things. So it's very complementary and very, non-confrontational.

Duersch

And actually, since you mentioned process. A good follow on here: Is lean startup a process that has to be followed very specifically or as you work with your clients, maybe that's a giveaway, but how do you think about customizing it and fitting it into the processes and the language and so on that your clients have?

Hafele

We do have a kind of a general framework where teams are like, we just want to dip our toe into this and see if this is the right thing. And so we have a general framework which is really effective. And we get really high Net Promoter Scores and people are excited and the excitement about lean startup starts to spread through the enterprise. Most of our work, though actually customizing it for each client, because not only are there different use cases we talked about before, like innovation or product or technology, including AI, there's also just different company cultures. And so if one company is running you scaled agile and another company is running waterfall, then that takes a different approach. And so we've learned what it takes and how to wire things into existing processes so we're not completely reinventing how the company does business. And so yeah, I would say the principles are always there, but we always try to customize it based on each customer's needs.

Duersch

So Ben, looking to the future, looking to your crystal ball three to five years out, where the world is going, where the industry is going, where's Lean Startup going?

Hafele

Well, it's interesting, I would say that, it'll probably be called different things. It will probably be called, it already is starting to be called lean innovation or lean product or lean AI. But the core principles remain, which is it will still be the scientific method applied to business, and it will still be the art of dealing with uncertainty. And let's face it, I think the future is going to be more uncertain, not less uncertain. I don't think there's any going back. So I think the need for this mindset, and the associated tools and process are going to be stronger than ever. Of course, AI is a big factor.
And so both in the sense of it helps to reduce the bandwidth you need to run lean startup because you can automate some of the more onerous things like how do we create this discussion guide or how do we organize our assumptions that we can just kind of throw them in to the model and it pops out the other side. That used to take time. But what I would say is there are things that kind of run their course. So think of an adoption curve. And so there's certain things that come up the adoption curve and then go to the other side. And right now, AI was on the upswing. And so everybody's excited about that. There's other things which are farther to the right like blockchain. People are less excited about that. There’re still some exciting use cases like radio or whatever is from the 1920s is probably way over to the right. People are like, okay, we've pretty much figured that one out. But, what is 100% certain is there's always going to be something coming up the curve. It feels like AI today and tomorrow, who knows what it's going to be. And it kind of doesn't matter, because then that's going to be the most uncertain thing and people are going to need to apply lean startup to that.

Duersch

So for our listeners who want to learn more. Where should they go? How should they approach getting more information around Lean Startup?

Hafele

Yeah. That's great. So, I think the best place would be our website at learnstartup.co, not .com. In addition, because of just the prevalence of the excitement and the waste that's happening in the AI space right now. We have a lean AI practice and associated podcast. So you can just go look for the Lean AI podcast, which is presented by Eric Ries and hosted by me. You can look for that on Apple Podcasts or Spotify or YouTube. But then another one is you can just go to LinkedIn if you're interested in connecting with me. And I try to respond to people as quickly as possible on LinkedIn and it's Ben Hafele.

Duersch

Absolutely. Well, Ben, it's been a pleasure talking with you. I knew this was going to be a fun one because you know, we always have a good time whenever we get to hang out here in Cleveland. So, really appreciate your time today, and looking forward to continuing to collaborate with you all.

Hafele

Thank you so much. Appreciate it.

Announcer

The Decoding Innovation podcast series is a limited production of the EY-Nottingham Spirk Innovation Hub based in Cleveland, Ohio. For more information, visit our website at ey.com/decodinginnovation. If you enjoyed this podcast, please subscribe. Leave a review wherever you get your podcasts and be sure to spread the word.

Presenters

Brent Duersch

Managing Director, EY-Nottingham Spirk Innovation Hub, Ernst & Young LLP

Ben Hafele

Ben Hafele
CEO, Lean Startup Co.

Podcast

Episode 30

Duration

54m 38s

In this series

series overview

EY refers to the global organization, and may refer to one or more, of the member firms of Ernst & Young Global Limited, each of which is a separate legal entity. Ernst & Young Global Limited, a UK company limited by guarantee, does not provide services to clients.