How to speed up innovation

Companies are split into two worlds that need to harmoniously coexist, which is exploration, innovating, creating new products, business models, value propositions, and running the existing business. So we're going to focus on this now, today, and ask ourselves, why are so many companies so slow in exploration? And there are two things we need to look at. One is team behavior. Why are they sometimes slow? And then the blockers around the team that hold them back. And a CEO's job is, number one, to take away the blockers so that teams with the right behaviors can innovate, because innovators will innovate.

So one of the key characteristics of innovation is actually the whole notion of uncertainty. And so when you're faced with uncertainty, if you analyze, then you're not really going to be creating that much value in terms of actually making progress and actually going faster. And one of my favorite all time quotes is this one from Scott Cook where he says, for every one of our failures, we had spreadsheets that looked awesome. Which really shows you that having spreadsheets that look awesome is not a predictor of innovation success. Just a quick reminder of why that is the case. Well, what we're actually trying to do is not just work on our idea and kind of think about it. What we're really trying to do is transform our idea into a successful business. The only problem with this whole process is that it's not a linear process. It's a non linear process with a very messy back and forth that happens right at the beginning. This is a tangled up thread that you're trying to kind of untangle and try and find the right thing before you start scaling. And so the question that you must ask yourself is, can you really analyze that? Even if you were like, how would you even do it? It's a bit of a kind of a messy space. And whatever early signals you're getting from this kind of tangled up space could actually be wrong and could take you in very many different directions. And let me just illustrate that with quick stories. Oh, we spoke to the customer.

Wow.

They say they liked it. Ooh, maybe we're good to go. No, they didn't actually buy. And then you have to go back and start all over again. And so just that tangled up makes it really, really difficult for you to run any kind of analysis. And so what matters for us is following a process where you actually design and test your business models. But here's a fundamental principle that I think really matters as we kind of tackle this. You don't want to Spend too much time designing. You design like you're right. You don't design to be right, you design like you're right. Which means you say, if this thing is going to work, what is my vision? And, and then you, you sketch that out quickly. Because we know you don't have to be stuck in designing because we know that the next phase is testing like you're wrong. And it is in the testing like you're wrong that you start refining your design. And so that's why we say teams that can go through this process fast are the teams that can really find an idea that's going to work quickly versus teams that spend a lot of their time in design and overthinking and engaging in analysis paralysis. And so it's really important that you design like you're right, not designed to be right. And then you test like you're wrong, which then reveals to you. So getting started, actually, when it comes to innovation, getting started is actually more important than getting the first step right. Let's just assume we're going to get the first step wrong and then just, you know, correct it as we go. And one thing that makes this possible is the notion that we're not going to invest a large sum of money in the first step. We're going to, we're going to invest a small amount of money in the first step. Because one of the reasons why companies get stuck in analysis paralysis is because they usually make really huge bets at the beginning. So they want this solid business case before they make the first move. And so the money is not even set aside, it's not pre allocated. And so that makes it really hard. Now, many of you have seen this case with Bosch that we've presented several times. And you know the story of how they invested in large, a large number of ideas and then over time reduced the number of ideas that they kept investing in. But underneath the story are, is a set of principles that are really, really important for helping innovators go fast. One is limit analysis paralysis by making a small bet at the beginning. That's one principle. The second principle is the money that you use to make these bets should already be pre allocated at the beginning. Make it easy for teams to get started and then use the evidence they produce to allow them to continue onto the next phase. Another principle that sits right there is that even the funding for that next phase, so you can see here within the, within the Bosch study, that they got the first 120k and then after that they got, they got 30k what we see slow teams down in a lot of organizations is that this money has to be found again, like found anew. It's like we've invested in the first phase and then the teams are ready to move to the next phase and there's no funding. So what you really want to do is to have this funding already pre allocated and ready to go, which then frees you up to make evidence based decisions that are not entirely based on having to have a great analysis. Alex, I don't know what you think about that or if you want to add anything to those comments. No big one for you?

Yeah, it's absolutely that. And surprisingly we often see that they at the end don't have the budgets for this and that. And I think the biggest one for me is analysis paralysis. Trying to find the right idea. You cannot pick the winner. You can do all the analysis of the world. Jeff Bezos likes to say, if you know you're going to be right, it's not innovation. So this approach of having multiple experiments running in parallel so that the one team and idea that really is going to work can emerge. That's how innovation works. And the reason we're slowing down today is because we're spending too much time, you know, trying to find the right idea. Ideas don't matter. They really don't matter because they're wrong. If we're talking big, big things. So we can't say this enough.

Yeah, exactly. And there's just a couple of questions and a couple of comments I just want to reach out to here on the group. One is like, how do you make sure you're not stuck in analysis while at the same time ensuring that you do no harm. The cool thing about making small bets at the beginning is that you limit the blast radius of the work. You only increase the blast radius of the work as you get more evidence that it's actually going to work. So, so, so, so, so, so that's the one thing. And then David is asking whether you set aside 300k for all 214 teams. No, the assumption is that some of the teams are going to fail. So you set a limited amount of time, like you have to really use evidence to say we're going to stop these ideas and we're going to continue with these ideas. And most of the time more than half the projects should stop after that first phase and then you double down investment on, on the remaining so you don't have to set aside money for the whole thing. Go ahead, Alex. And then I'll actually hand over to you anyway to take us into the second phase.

Cool. Well, just one thing that we deeply believe in is because there's also this, you know, okay, we got 30 ideas in our idea competition or whatever. But you know what, why don't we just let everybody start with a small budget and 120k is actually mainly their salaries and then the best ideas will emerge because after three months we'll kill at least half of those. And you can see it was way more in the Bosch case. Right. So our conviction is let everybody start and then be really good at killing. Do you want to summarize?

Yeah, just a quick summary. So for new ideas, even the deepest analysis is not going to help prevent your risk. It's just, it's not really going to help. You just prioritize testing over analysis. Generate data insights from quick experiments so that you can make evidence based decisions and then make sure that you have an evidence based budget sort of for the entire portfolio that you can then start to reach into as you, as you're running your, as you're doing your work.

Innovation is not a hobby. So we were looking for some interesting taglines and Tendai came up with this one because I think it's very fitting because it's still treated like a hobby, right? When people say, oh, 20%, everybody should get 20% of their time. Well, that sounds like a hobby to me. Innovation is 100% job and we'll see. You know, you can't just call it black and white. There's a little bit of refinement there. But the question of course is, well, what is actually most important for innovation teams? Money or time? And if we look at our experience, there's a little bit of confusion here because people say, oh, innovation is expensive. And because often when you say innovation, people think technology and they think R and D first and that kind of stuff is expensive. But what is innovation really? It's about creating value for customers and for your business, with or without R D and technology. So at the beginning, innovation is extremely cheap because as you've seen those 120k, that was salary, that was not out of the pocket. So it's not free because, yeah, putting people on a project that costs money in terms of their salary, but that's the bigger challenge. So today what we see mostly is that the time allocation is a much bigger challenge than money and that's what's slowing companies down. And then you take this one right with Google. So the dirty little secret that Google 20% of your time. Well, you know what, they do their full job 100% of the time and then maybe they'll have the energy to do another 20%. So does this work? Is this a model? We believe, you know, that might have been a model that kind of worked, but today it doesn't anymore. Today you really need teams that are dedicated to exploring ideas. But then if there's nothing there, you kill it quickly. Right? And a sprint looks like this. We start to onboard people, we protect or try to get leaders to protect their time. First they just understand the tools, they shape the ideas. And then most importantly, red and yellow, they shape, test and iterate. Then they make an evidence based presentation and present that to the leadership. And their time needs to be protected. With all the companies we work with, I'd say 90% of the time it's the time that's lacking. They do not have sufficient time during the week besides their day job. And Tendai and Carol, I think you've seen this a lot. Right. So the struggle, despite the company saying innovation is important. So give us, give us a quick maybe kind of recipe of how we can break that time lock.

Yeah, I mean it's actually fascinating. And some of the comments that have been going on in the chat is like time is money. Which is. Yeah, exactly. Time really is money. But what we learn from the work that we do when it comes to innovation, money is not time. We have sometimes organizations spending money on coaches that end up just sitting, waiting to coach teams that don't show up for coaching meetings because they're busy doing other things that the leaders have. So they're spending the money, but then, but it's not buying them time. And so you really do need to make sure that you're really protecting the teams, you're separating them from their work or you're protecting them from being pulled away from the, you know, you have to really create all of that, all of that protected time for them to be, to be, to be able to do the work.

One more thing, talking about professionalism, because sometimes people ask, do innovators only do innovation? Right. Because if it's not a hobby, it's a profession, then they should do this all the time. And you do get better at innovation. But it's, I'd be very careful with saying that. So the way we like to see it, and that's how Bosch did it. They had people coming here from the core business, from Exploit going into this process, which is, yes, it was called an accelerator, was mainly about the process and their time. Was protected. Now they come in as amateurs and they explore for the first time. So they're not professionals yet, but they can do this again and again and again. Then you get better at it. But here's where I'd be super, super, super careful. The handover thing, where all professional innovators are going to explore and then they're going to hand it back to the core business. That never works. And we'll get that theme a little bit later on as well. So you have to be really careful when you talk about pros, non pros. So the way we like to see it today, so things don't slow down is professionals that are in a team and professional coaches that coach the teams so they don't get stuck on the wrong things like analysis paralysis. So you need professionals as part of the team, but you generally need people from the core business because they have the knowledge. That's what distinguishes existing companies, small and large from a startup, because you have the skills, the ip, etc. Right. So it's a mix between professional innovators and people from the core business. So just to quickly summarize this one as well. Well, innovation projects actually take longer if teams are not given sufficient resources and time. And the time aspect is the most important one. It doesn't always have to be 100 upfront. We actually believe 60 is safer because then it's easier to kill project. It doesn't have to be 100, but 20%, definitely not enough. Three people, 20%, that's not going to work. So teams that are working full time or at least 60% with maybe one person working full time, they go so much faster. And today we do not see that sufficiently. That's why teams are so slow today and because often they're still learning they're doing the first time. And this is the one I really want to emphasize. You get better at innovation over time. So you should have people who can navigate into innovation out of innovation, but the second or third time they'll be much faster. So you need to see innovation as a profession that you get better at. And some will do this 100% and be in mixed teams because they'll be really good at it. We need to see innovation as its own profession that is different from managing is different hard. And if we don't see it as a profession, we're actually not going to acquire good innovation talent either.

And what I'm interested now is in addressing the first question, which is the handover question. Handover is not a really great idea. And Alex, I Actually wanted to say when we're having the discussion that sometimes even the innovator think this is great. Like, yeah, I get to work on the cool side. And then I hand over to the executors. Know, like, they don't really grasp this. This concept that a successful innovation is actually finding a scalable, profitable business model. Otherwise, it's just, it's just invention. But in most organizations, and I was going to actually call this. You're not Ellen Musk. And then I changed my idea. You have to find a home for orphan ideas. You have to collaborate with key functions within the business for your idea to succeed. So I just want to ask a quick question in the, in the chat, and you can just type before us, like, which key functions do you think are the hardest for innovators to collaborate with in your company? And I'm really curious to see whether the same characters, Legal. There we go. The same characters. Finance, hr sometimes. But yeah, co, Technical, it. Finance. Finance, Legal. Yeah. Right. The engineers. Quality assurance, for sure.

Sales.

Yes. Because they won't let you talk to customers. The CEO, that's the hardest function to collaborate with. Compliance. Right. So you can see that, you know, collaborating across the. Across key functions is really difficult inside large organizations. So the solution for most innovators is, okay, I hate MBAs. So if you just set me up in an innovation lab, far away from Everybody, where the MBAs cannot interfere with our creativity and invention process, then everything is going to be great. And actually what you find is that this is not really the right approach to actually take. We need to collaborate. Right. And so, you know, MBAs do work on the key functions and they work on the core business. And that creates, you know, your salary. But. And of course, innovators pay attention. So you really want to, I love Jeff Haynes calling it burn that shirt, please. So it's like, yes, you really do need to burn that shirt because you do need these two functions to collaborate. And one of the stories that I often tell is a story that when I went to, when I was working with TD Ameritrade and the Innovation Lab and how they used to call themselves the home for homeless ideas. So if nobody in the company wanted to work on your idea, if you weren't getting any support, you'd come there because it was a home for homeless ideas. And they then said to me that what they learned is that when an idea is homeless, when it comes to the lab, it's usually homeless when it actually leaves. So we spoke about the barrier of analysis paralysis. We Spoke about the barrier of budgeting and making investment decisions. One of the biggest barriers that we often see when we're trying to run an innovation sprint is that the idea is stuck in some function. For example, sales won't let us talk to customers, so now you're slow. For example, legal won't approve the experiment, so now you're stuck. For example, compliance won't approve working with a particular experimentation tool to create landing pages. So now you're stuck. So it is virtually impossible for innovation to succeed, a single person, just by yourself, without really collaborating with key functions within your organization, because they often act. It's a very difficult blocker. It's almost like the civil service. They can just push your paper around and time is just ticking, right? And they. And you're not actually, actually making progress. So you really do need to figure out a way to, to collaborate. So one of the principles that we teach is try and avoid your idea becoming an innovation orphan that, you know, nobody's actually, you know, paying attention to. Innovation does require collaboration with key functions. You don't want them to be blockers. So please build alliances.

Talking about killing your zombie project. And if you don't like the word killing, retire or successfully eliminate or something like that, you don't need to use the word kill. But we need to start really taking those ideas that have no evidence and consume a lot of resources and get rid of them. Because there is a huge disadvantage of being an extremely well funded innovation project. I think, Tenda, you like to say the CEO's pet project. So maybe in the chat window, what are the disadvantages? Because we always say how it's all about money, right? Great idea, money and innovation. We lack money. If we had the money, what's the disadvantage of being an extremely well funded project? I have an idea and the CEO hands over 5 million bucks to actually build that thing. What's the, what's the challenge? Sunk cost fallacy. Yeah, Hippo effect. Not very resilient. Interesting, right?

The.

The challenge is too big to fail is another one. Love it. Love it. So maybe, Tenna, when you say CEOs pet project, what is the disadvantage of CEOs pet project?

Well, nobody wants to tell the CEO the baby is ugly. I know how hard it is to tell you that your babies are ugly.

See, I built a team where everybody tells me my babies are ugly. My kids are. My kids are usually pretty, pretty. You know, they get compliments, but my ideas don't.

Right. That's the hard thing. It's like, now you're like and, and you're gonna talk about that just now? Now you're a lighthouse project like that?

Yeah.

And everybody's looking at you and there's too much emotional attachment.

That's the big one. Right. And, and people are talking about the sunk cost fallacy. Right. So we invest so much into a project that they're condemned to succeed. And small anecdote. I was with the board of a large bank, you know, 50,000 people at the executive board with me and I was just starting to talk about innovation and evidence based investments. And one person was really pushing back and I didn't really understand why until I understood stood. He had a really big project under his roof that had zero evidence. So that actually became a big kind of tension when we introduced, you know, evidence based decision making. Would we kill that? You know, with dozens of millions of euro funded project we figured out a way to, to do it both ways. Right. To kind of get the evidence to see, you know, is there something there could have gone the other way and we would have had to kill the project. It's not because you already put money into it that you need to send more behind it. Now good companies understand that failure is part of the journey and you actually want failure. So Jebes has used to say always like Amazon is the best place in the world to fail. He even said we need to grow the size of our failures with the size of our company. Now when we're talking this kind of failure, we're not talking about warehouses that don't work and we're not always talking about lighthouse projects. But it's kind of slowly investing more now. Why can he talk about that? And is a good example because, and this is One of the CEOs babies, the Kindle fire phone. One of the biggest, most expensive failures in Amazon's history. But it was okay. And what was interesting, if you Google it, read a little bit about the story. Jeff Bezos didn't fire the team behind this failure. Pretty clearly showing you are not condemned to succeed. What came out of that is he used to tell journalists this was my, you know, most expensive failure. We learned so much. Why would we fire those people? Amazon Alexa came out of this. It was the same team, right. So they have multiple projects at the same time all the time. So we use Bosch as an illustrative example because they have the right numbers there and it was is measured. But every company that's world class at innovation systematically over years and not just a stunt like Nespresso is a great example we use. But it's, it's, it was a stunt. It was 40 years ago. Like, that's not a system of innovation. So we have a lot of projects that we invest in and some will make it to the top. Right. And on the process here we have small failures, here we'll have bigger failures, but here we'll have over 200 small failures. Here we might have 10 relatively big failures for some that come out. Right. So you do need to have this in the system. That's also why in innovation you don't look at return on project, you look at return on portfolio like venture capitalists, and then the whole idea of failure actually goes away. Because when you manage a portfolio well, like in finance, normally you do this in a way that you have some winners that come out. The less risky, the more money you put in. Same like in the financial theory. And that's the contrary of the lighthouse investments that we still see. So one to ten day and you, Carol. So CEOs often don't understand this portfolio approach yet. What do the both of you do to kind of get them on board with this whole idea of Lighthouse projects maximize the risk of failure. Business plans maximize the risk of failures. I still see CEOs asking for business plans and business cases analytically, kind of de risk, but it's not de risk because it's just analytically thought through. So how do we get senior leaders to buy into this?

Yeah, I mean the, the biggest thing is showing evidence. Right? And that's what we talk about with our, you know, discovery sprints and our IDE videos around business design test loop. It's actually going out, prototype something, go out and talk to the customers, test your hypotheses, come back with evidence. And once you have that evidence, then you can actually make some, some decisions that aren't just about what you're, what you're thinking, what, what you'd like to see happen and that kind of thing.

Yeah. One of my favorite conversations is asking them a Scott Cook type question, which is, tell me a story about when you had a really good promising business plan and then everything went crazy. And they're like, yes, because it's emotional for them. Then they'll tell you, this team, we spent millions, then we launched and nothing happened. And then, and then you have another one and they tell you that story and they tell you. Then you go, okay, so if these things keep happening, don't you think that it's actually better to try a different approach? So it's almost like trying to kind of bring them around to see that, you know, the approach that they've been using is not always successful. And, and, and, you know, if they give you a chance and you can show them to how to make evidence based decisions like what Carol is saying, then you tend to get, you tend to get buy in.

You can't move fast. Like, how are we going to connect this back to speed? It's a big one, actually. When your people are tied up in big projects, you actually tie up a lot of resources. You can't go fast and you're not running on 10, 20, 200 ideas like Bosch and Peril. That's a big thing. So we underestimate this aspect. So the resource allocation in zombie projects slows us down phenomenally because it's like a magnet sucking everything up, rather than the big projects are the consequence of a funnel.