How to measure risk reduction with innovation metrics

Here's a quick video to show you how we judge and compare innovation projects and measure risk reduction with strategizer innovation metrics. So let me go quickly through this because we've been working on this for quite a while and tested this with several clients around the world. So first thing is that you have levels of evidence. So when you've just done a spreadsheet and you know, a beautiful PowerPoint deck, well, you don't have evidence yet. A spreadsheet is basically making a fantasy explicit, but it's not evidence that something's going to work. So now if you talk to customers and ask them about their jobs, pains and gains and their budgets, well, you start to have first light evidence. We call that evidence level one. They tell you things, but now that's still pretty abstract. And you know, what people say is they're usually not what they do. So so now if you have a visual artifact that could be a storyboard with visuals, or we have very different, you know, simple ways to make a concrete a product and service a bit more concrete with a prototype that, you know, could just be as simple as a drawing, well, that is already light evidence with real artifacts because the customer understands a lot more. And this doesn't just apply to customers, could also be the supply chain. Now those two first evidence levels are 1 and 2 are about what people say, but you know, we want to know what people actually do. So the level three is light call to action evidence from call to action experiments where you get people to do something so they invest time, energy and maybe money. So for example, putting up a landing page with a product or service and getting people to sign up with their email, that's a very light investment. They just give their email, but they wouldn't do that if they're not interested at all. So there's a call to action. And that is something that happens in an anonymous space so the interviewer won't influence that. So that's level of evidence 3. You get people to do something stronger. Call to action might be a down payment. Or so you might remember how Tesla, with the very first car they launched, the Roadster, they actually asked for a hundred thousand dollar down payment. And then later on with the Model 3, they asked for a $5,000 down payment. That's a lot more than just an email already. It's not the full price still, you know, the customer knows they can get the money back and it's just an experiment, but it's much stronger evidence. So that's level four. And then if you really want to go all the way. Level 5 is when customers or even potential partners don't even know that this is an experiment. Pop up shops could be something like that in business to consumer or there are other ways of doing things where you simulate a service. You do it very manually, without it's not scalable. But on the customer side it feels very real. They don't even know it's an experiment. This is not just for B2C, it's definitely also for B2B. So here, strong call to action would be letter of intent being signed by a customer. Not legally binding. But when people sign something that's already a lot more in terms of investment than just saying things. So this is the foundation. So we have levels of evidence which, you know, show us do we have strong evidence or light evidence? We used to call it weak evidence, but it's not weak, it's just like lighter. Now to really bring this together, you want to bring back in the business model canvas because there are different types of risk. You want to score all of those so you have desirability, looking at the front stage of the business model, value proposition, customer jobs, pains and gains, all of those things. But also how you're reaching, customer, acquiring customers, retaining customers. Feasibility, probably not the first thing you're going to test. But can we actually build it? Can we scale it? Can we bring in the right partners? Can we do it? And then viability, you're going to score revenue streams, pricing, will customers actually pay that? But also cost because you're going to experiment backstage with your supply chain, with partners, and then obviously you can, you know, figure out the profitability before you even built the whole thing. And then we add something that we call adaptability, has to do with market timing, with the environment, with regulation, et cetera. So four different areas of risk that we look at, this is what we call the Innovation Project scorecard, which the teams and the panel of judges who are judging an idea or the growth board use to understand the risk profile of an idea, which makes ideas also very comparable and can even be done before the testing starts. So if we look at, you know, this whole idea that when we start risk is high, we need to reduce risk and when we start we do cheap experiments. So it's okay to talk to people and get some light evidence, but at one point you need to build your first minimal viable product. That's not the first thing you build. Never, right? So you go to valid discovery, validation, acceleration, and you only make the investment if there's Evidence at every stage. So how do we do that? Well, we bring it together with the scorecard where each phase, the growth board, the panel, the decision makers are going to look at the idea, score it or score it together with the team or the team presents a score and the leadership, the growth board looks at that score, does their own score and then they understand, okay, well pretty good. We're going to give more investment for the next experiments to go to the next phase and then all the way to the next phase. So discovery, validation, acceleration, where you only get follow up investment when there is enough evidence and you define what type of evidence you want at each stage. So that's where it gets interesting. Right, so we have this scorecard and, and you definitely can't in a first sprint fill out that scorecard and arrive at a level five evidence everywhere. So now let's look at that. So besides the strategic fit, now we're starting to look at scoring desirability. So here first customer things, value proposition, channels, relationships. So we're going to score what kind of scores can you kind of expect after maybe something like 12 weeks? And definitely has to go a little bit beyond first light evidence where people say you probably want to have the first visual prototypes not yet an mvp. You don't need a minimal viable product at this stage, but you probably want some first light call to action evidence, getting people to do something that's for the customers, understanding their jobs, pains and gains. Number one, understand the customer. Then first understanding could your solution, your value proposition create value for that customer. But you need to understand customers first. That's why in a first sprint of about 12 weeks the solution will still be relatively light, maybe level two and definitely for channels and retention relationships, you don't need to have anything yet. When we go to viability down here, we definitely want a bit more all around, you know, key resources, key activities, key partners. We don't need anything yet because we don't want to focus on can we build it. But when it comes to revenues we definitely want first conversations of willingness to pay. Could even go a little bit further, you know, if we have a full time team, depends a bit. You don't need to look at costs yet because that has to do with the backstage. So that is the first phase which we call discovery. And then you decide if you're going to invest or if you're going to retire the idea. And the brutal word would be kill. And that's okay when there's no evidence. Now what happens when we go to validation? We need to move everything more to the right. Much stronger customer data evidence, much stronger evidence for, for the value proposition. And we'll start to move the channels and the relationships. Definitely. And for pricing and revenues, we will also have much stronger evidence, which means more experiments and more and stronger evidence from these different experiments. And then, okay, we go to the next phase. We're going to move everything to the right in, in acceleration. But that's how we do the scoring of different projects. So we can decide if we invest evidence based investments based on the risk profile, based on the evidence that teams bring to the table at each phase. And what's really interesting is if you start to work like this, if you start to work like this, there'll be a very strong alignment between the team because they understand what, where they have to land after a sprint and the growth board or leadership or whoever decides because they know where the team should arrive. So very, very good, very, very strong way to do evidence based investments and to compare innovation projects and to manage expectations of the teams and of the leadership. This is what we do with strategizer innovation metrics.