How should your innovation board make decisions?

Welcome everybody to the Strategizer webinar. Joining us today is Alex Oswalder, Founder and CEO of Strategizer Tendai Vicky Partner here, Partnering Crime I Strategizer and myself and I will be hosting you guys for the next hour. The topic of the session today is do you know how your innovation board make investment decisions? In order to make innovation sustainable and repeatable, we really have to address innovation across every single level of the organization. If you're interested in the previous topic or any of our webinar, we have a fairly extensive webinar library at your disposal. Please go on to strategizer.com en webinars and have a look at our backlog of content, great case studies and previous webinars. Now onto today's topic. Alex firstly will take us through some of the key innovation metrics you should be using to make investment decisions and to benchmark your innovation projects. Then Tendai will take us through what it actually means to make evidence based decisions so that you are systematically de risking your innovation ideas. And lastly, why it is really important to kill innovation projects. How do you measure them and assess them so you are making those decisions based on evidence.

So first, one of the three elements that we're going to dive into is the four metrics that a company needs to look at and that the innovation board that makes the decisions in terms of investment decisions needs to look at. Very simple. And they map back to our explore portfolio. In the portfolio map, so we have two axis that we look at. Number one is the actual financial potential. How big is this idea? But that's not enough because as we know at the beginning, you know, it's a fantasy. Whatever we put up like a spreadsheet is a fantasy made explosion implicit. As I like to say, it's not evidence. So we need the second axis which is the innovation risk, the reduction of the risk of an idea or what we're working towards, a confidence score. How confident are we that an idea is going to work? So you start out somewhere here, you test it, you say, oh well, looks like the revenue potential is not going to be so good. You pivot the business model and you're able to improve the revenue projections based on evidence and, and pricing, et cetera through pivoting. So you're going to move that to the right and as far up as possible. Right. So those are the first two, the revenue potential. And that revenue potential would become more and more explicit and more and more realistic the more you experiment and decrease risk. Right. So we have Revenue potential and risk reduction or confidence. And then we need to look at two more. How much money did we spend spend to test this idea? And that includes the time people are working on a project and the out of pocket cost of running the experiments, which could be building something prototypes. But even before that, there's often we do Facebook ads, LinkedIn ads, whatever we make PDFs, documents, designs and spread logos. Those are things that don't even require building. So that's the money we've spent to test. And the second one there, so the fourth overall is how much time did we actually spend testing this idea? And I'm going to give you a silly anecdote before we go to a bit of an example. There's this company that had millions invested in a project, no evidence before we came in, so. And been working on it for over a year. What do you do with something like that? Because you'd actually have to either kill that project or start from scratch and go back and start finding the evidence. But that's obviously an extraordinary situation. But what you should never have is a project that you spend a ton of money on, a ton of time on where there's no de risking and only potential. That is not something that we should have. So if you look at how this looks in the real world, well, if we look at our Explore portfolio, you're going to have all these projects, you're going to place them in the portfolio map in terms of revenue potential and how much we derisk them. Right. So this one here still very risky, even though the revenue potential looks great. This one we de risked it a lot. But right now the business model kind of sucks. There's not a lot of traffic traction there, not a lot of money we can make. This one of course looks more interesting. But what we need to add to that to really make stronger decisions is to ask how much money did we spend on each of these and how much time did we spend? So if you start to add that, you have a better decision making layer that you can work on and naturally things that are up here doesn't always have to be the case, but you'll have spent more on it because you did some prototypes, you spent some more time, you went through three phases, so naturally they kind of end up there. So here we're looking at one that was not one cohort, but they were different in time. This one here is very problematic. You should actually kill it because the revenue potential doesn't look too bad, but we spend way too much time on it. And we weren't able to de risk it. So that is comes back to what we said. Right. Revenue potential, spreadsheets at the beginning. Yes. But if the spreadsheet looks good and we didn't de risk over, you know, 12 weeks or 18 months, we have to kill a project like that. Anything you want to add to that, Tenday?

No. Absolutely. And that's why the dimension of resources spent in time is really important. Right. A lot of businesses tend to make decisions only based on the expected return. And that's not a really great way to make decisions. I think what's interesting is to also ask the audience, like, which one would they kill? Like outside of Project 1, which other one would they kill? For example, would they kill Project 4 or Project 2 or Project 3, or would they keep investing in those? That would be interesting to just see what people say there.

There's one more thing that came up here in the chat. Roger asks Alex, you want numbers at the start? Spreadsheets, evidence, de risking. So we're going to get to that. When I say I want numbers at the start, I didn't say I want evidence for those numbers at the start. Right. So I just want us to have a spreadsheet. Even if it's kind of fantasy, you know, back of the napkin. I want the numbers. I do not require evidence for those numbers in the first couple of weeks because that's just not humanly possible. What I want, we'll get to that is the needs. So it doesn't mean you need to prove everything at the beginning. That's not what we said. Right. Numbers doesn't mean we need proven numbers. There's no chance in the first couple of weeks you get proven numbers.

Yeah. So I want to dive into the question that people have been asking around. So how do you actually track this evidence of innovation risk? Right. And at the heart of the question is even though we do some early financials and we're not talking about like large spreadsheets with five year projections and payback periods and things like that, we're really just talking about what is the potential of the idea. Right. What is the, what, what is the potential upswing? What is the potential size of this, of, of the, of this opportunity? So we, we try and keep that as simple as possible as well. But over time we want people to be de risking their idea, reducing the risk in their idea. And that sounds like backwards language sometimes. What do we mean when we say reducing risk in an idea? But what we mean by that is how close are you to finding a value proposition that resonates with customers and a business model that works well. When I, when I, when, when we do these sessions, Alex, for, for Innovation Boards, I found myself saying to the, the heads of Innovation Boards or members of the Innovation Boards get a tattoo. And the tattoo should say, how close is this team to finding a business model that works? And that's all you should care about, rather than asking people, whether on time, on time and on budget. And so on this journey, right? From having an original idea down here and navigating your way towards success until you become so successful that you become part of the core business, there are various questions that we can ask, right? And so you could break this down into stages if you like. So you could have a stage called the Discovery stage. If you sort of focus in on this, on this innovation risk, you could have a stage called the Discovery stage. And what you focus on is customer understanding, right? So to what extent do you understand how customers, jobs, pains and gains, what they're willing to pay for, how much they're willing to pay, whether any idea around your value proposition really resonates with them? Because again, it's hard to be successful if you're making stuff nobody wants. And so understanding customers, jobs and pains means you're not competing against luck. You're really trying to find out and navigating your way to success. And businesses and ideas that understand this really well are on track to finding a business model that actually works. Then you can move to a stage that we might call validation, where now you focus on value creation and thinking about the value proposition itself. Do we have the right capabilities to create this value proposition? Are we starting to build prototypes that resonate with customers? Do we understand exactly the features customers want? Are we starting figure out channels through which we can reach customers, maybe start to test some of those dimensions, and then over time you can maybe move to a stage we call acceleration, where you now focus on the business model and whether or not you have a proven business model, but at a limited scale, maybe a small pilot in a small geography, but over time you're creating this evidence and moving further and further up the chain of evidence there. Go ahead, Alex.

Yeah, just one thing that came up, which is interesting from Bogdan, is could you clarify your definition of prototypes versus MVPs or different definitions around? So for us, MVP is more in the literal sense. Minimal viable product is something that you really can do stuff with. So it actually comes generally late in validation or early in acceleration. When we say prototypes, it could be as simple as a storyboard walking a customer through a service and how it's going to feel like that's not an mvp. Right. That just makes the thing more tangible or a landing page and all that kind of stuff, or a PDF spec sheet. Those are prototypes, but not of a working thing. It's just to make the solution more tangible. MVPs generally is really something that works, that you can do with. You really have to build. So it's a bit later, it's earliest in validation, generally in acceleration. It depends a bit on the industry as well.

Yeah, no, absolutely. And you're absolutely right, Mark. Right. It's not necessarily the case that the flow of an idea is going all the way up. As we reduce risk, expected return also increases, can also be flat. Right. So it's the values right there, but you're moving across the risk stages. And it's just a nice visual to present it the way we do because it allows us to just then get to the point where we move it to the, to the exploit portfolio. But, but you're absolutely right. There's no, it's not, there's no correlation between this dimension and that dimension. They're independent of each other. They just allow you to make, to make, to make better decisions. So the question then becomes, well, how do you assess an idea to make sure that it's on track? Like, what sort of evidence are you looking for? And this is where our Innovation Project scorecard comes in. And this is what we use to score ideas. And so it allows us to zoom in on ideas and really focus on the amount of evidence that teams are producing that the idea is on track. So, for example, if you think about the customer segment, do they have job spins or gains? You either have very light evidence around what people say or you have strong call to action evidence around what people do, or even irrefutable evidence from the market around actually actions. People are saying, especially around, like, willingness to pay and things like that. Having irrefutable evidence from the market is actually better. And I just want to tell you a quick story. When Alex and I first started designing this tool, our scoring went from weak to strong. And it was just like 0, 1, 2, 3. And people always scored themselves as strong, nobody wanted to score themselves as weak. So we thought we need to really say what we mean when we say strong and weak. And we make this clear line in the middle that separates what people say and what people do. And the more you get people to actually do things, the stronger the evidence, because what people Say what people do does not necessarily correlate. And so that's what we really need to be tracking and evaluating as innovation boards. This evidence that we're getting, is it evidence around what people say or is it evidence about what people will actually do? You know, we know how much customers are willing to pay and how they will pay us. Again, is it because they say they would pay or is it because we have a landing page that means that people are actually starting to give us their money early? And so we actually measuring behavior. And so over time, you can start to sort of use this scorecard to score ideas and score ideas and make decisions. And when on the scorecard, a lot of the scores are like, towards the end here, you really have an idea that's ready to start moving into the, into your exploit portfolio. Yeah. And the Innovation scorecard. Yes, Samuel, it's in the invisible company. And if you Google Innovation Project Scorecards strategizer, you'll just come up with a. It's a. It's a free tool that you could. That you can download and use. Just one last thing to say before we move on to the quiz and if Alex has other comments, is using the Innovation Project Scorecard. And these Innovation Stages is also a way to make investment decisions where you start with small bets that increase over time, but only on those ideas that are showing traction. Right. Which takes us to the next section.

One thing. When you presented the scorecard at different stages, the scorecard doesn't need to be complete at the beginning. You'll actually only have completeness on the customer side. That's where it connects back to the questions. While you have a spreadsheet, a spreadsheet is no evidence. So you show the spreadsheet to show the business potential. But the evidence for that will come in slowly. Right. Maybe a little bit of willingness to pay in interviews. But real pricing experiments are going to happen earliest in phase two. So the scorecard gradually gets more filled out. And I just also want to emphasize, people always ask, when do I know? Well, it's a gradual. No, it's not like you turn the light on, oh, now it's clear I'm going to scale. Like, no, it's a gradual, you know, more and more and more and more over time. You'll actually never really know until it's a real business, but you'll gradually know more. So people need to remember. It's more like your glasses are getting sharper and sharper or the spotlights are getting stronger and stronger. It's not a Light switch on and off. That does not exist in innovation and entrepreneurship. That's a complete illusion around people who've never done it. Ask that question. When you've done it, you'll see it's a gradual, stronger light that will show you the path. But there's also conflicting data all the time, so you'll still have to make leaps to get there. But the evidence will start to show you the path.

And part of the work we do, by the way, is to make teams and leaders comfortable. So the team's comfortable with presenting an innovation project scorecard early, where everything is low, but they have a path towards testing that. They're asking for investment and the leaders to go. Okay, yeah, I'm happy to accept that this is not yet fully validated. Here's the initial phase of investment to go and do that validating. So it is really a difficult conversation to have, but if it's not adopted, then you really don't get into world class innovation practices.

Learn. So last one is about killing. And when it comes to killing, we have this beautiful quote that Tendai got from Fred Wilson which really shows that in any portfolio, well, guess what, of all your projects, one third is very likely to fail, extreme high probability. One third is going to underperform. They're going to deliver some success, but not the success you really expect or need. And one third roughly is actually going to return the whole portfolio. So we need to keep that in mind. And in venture capital they know that, so they invest in that way. In businesses we tend to think, well, if we invest, it needs to be a winner. But that then also means we don't have the right capital allocation. We need to remember that it's very similar to venture capital. We start with many ideas, little investment, and then many of those are not going to turn out well. And that's fine. After 12 weeks we're going to discard those. Right. So when you look at this kind of portfolio, what you really want is to say we're going to start with a lot of teams. I put 10 to 50 here as a starting point. If you get really big, corporation should be more than like 200 teams over one to three years and you give them little time, maybe three months, maybe a budget, maybe it's just their time, which obviously also costs money. And then after 12 weeks you kill or successfully retire 50% of the projects. Not because you don't like the ideas, but because the teams were unable to produce enough evidence. So that becomes less an opinion based conversation. But if there's no evidence around customer jobs pains and gains. Easy. Even the teams will say there's nothing there. Right. They couldn't pivot to a different segment and show evidence. So only 50% go on. So you take those teams, you probably give them more time and more budget because now they might make prototypes, which could be storyboards, which could actually be MVPs. If you're in the digital space, you build some real stuff. That's why you need a little bit more time. The experiments run for longer, but again, you kill projects. We could argue that here we maybe bring the kill rate a little bit down because we already have more evidence, so better ideas in terms of evidence went on. So maybe we only kill 30%, but again, that depends a bit at the, you know, the percentage should not be driven by the percentage. The percentage should be driven by the actual evidence. So it could be lower or higher, depending on the quality of the evidence that the teams bring to the table in the scorecard. And then in the last phase, you're likely to kill again less in the early stages. But you do need to kill because now it's going to get resource intensive. Now you're going to start scaling, you're going to start investing in marketing, and you just won't have enough money to invest marketing money into a lot of ideas. So you have to really pick those with the best market potential and the best strategic fit. So at the end, you'll have few ideas that you're really going to bring to scale. So this funnel approach is incredibly important and it should be driven by evidence. And this is what real capital allocation looks like at the beginning. You invest in many ideas, small amounts of money, you're going to kill a lot of those projects to free up capital to invest in those that actually have evidence. So you're gradually going to invest like that and you accept that you can't pick the winners. Because if venture capitalists can't pick the winners, and that's their job, guess what? We business people in companies cannot do it either. We should stay humble, because as I like to say, you know, venture capitalists are not the most humble breed and they admit that they can't pick the winners. So let's just admit we need to build a system for that. So if we kind of summarize this and ask, why should we kill ideas? That sounds like a bad idea. Well, number one, capital allocation. If we don't systematically kill projects that don't have sufficient evidence, we won't have enough money to invest in those that have Legs that have evidence. So that's number one. And this you can use to really convince your senior leadership that this funnel approach is important. The second one, I have a lot of CEOs that ask me, Alex, I don't get, you know, business model innovation. My teams don't, they don't explore bold ideas. My question is always, well, how many ideas do you allow to fail? How many projects do you kill? They say, what do you mean with that? They all need to succeed. Oh great, you just condemned the teams to succeed. So they're going to play it safe. Now if it's normal that projects fail because the experiments didn't yield the, the return we expected in terms of evidence, if everybody sees that as normal, guess what? People are going to go for bold innovations. Last one, if you really want to create an innovation culture, you need to do this evidence based investment. That means not based on politics, but based on evidence in a scorecard. And that does mean you're going to rigorously kill projects with no evidence in the scorecard. Super, super important. I don't know if you have anything to add, Tendai, but this is our battle, right, to explain to leaders why killing or successfully retiring projects is a good idea.

Yeah, no, I mean absolutely. And not only successfully retiring projects or successfully parking projects, but also ensuring that the whole world knows that the team in which these ideas were successfully killed. The killing of an idea is not the killing of the team, the killing of their days, not the killing of a career. So like communicating these messages and living out this culture is really important for making sure that teams are then willing to take more and more risks. And by the way, I just typed in chat, that's one of my things I call off the algorithms and condemn to succeed is one of my, my favorite of the altruism.

Thank you everybody. Thank you Alex and Tenday for sharing your thoughts and your point of view with us. And for everybody else, the chats will really, really lively and we love the debates and discussions. So thank you very much for your participation. And lastly, as a way to say thank you for joining us from all around the world, a 10% discount code for our upcoming masterclass. And if you really want to understand how to make evidence based decisions and how to incorporate innovation metrics and the scorecard into your organization, please reach out to us as well and we can help you with embedding it in your and everything that we've shared with you today as well. So thank you very much everybody and thank you for joining us.

Thanks for being a great host, Lucy. Bye, everybody.

Thank you. Lucy, wonderful.