Strategyzer Webinar: Customers & Canvases In Healthcare Business Development

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All right, let's get going. Once again, welcome to another Strategizer webinar session. We've got a great session for you today and today's topic is Customers and Canvases in Healthcare Business Development. For those of you who do read our blog, you may find this topic familiar. We posted a Q and a case study on this topic with our guest today and I'll be passing that link around during the session. If you haven't had a chance to read it, I'm your moderator Kavi Gupta. I manage content and community at Strategizer. You may remember me from the emails from these webinars as well from the blog posts. Our host, as always, is Alex Osterwalder, Strategizer co founder and co author of Business Model Generation and Value Proposition Design. Our guest today is Toby Reed. He's the managing director of BioCity, which is a healthcare and life sciences incubator with multiple locations across the uk. At any point throughout this webinar, please feel free to mention us on Twitter with your comments, with feedback with questions. You can use the hashtag StrategizerWebinar to get in touch with us. Or of course you can also use the Questions box in the GoToWebinar application to submit any questions you may have as well. We always like to remind you that you can go to blog.stragizer.com for more tips, advice and content about the tools, the methodology and business model innovation. Throughout the session we'll also be mentioning some tools, some resources and some guides. You can of course go to our Resource library, which the link is here. I'll also pass the link through the GoToWebinar chat box and you'll find up to 30 plus different types of tools and resources available for free from our Resource Library So with that, I'm going to hand the reins to Holger, who is going to be visualizing the experience. Alex, in the meantime, could you maybe tell the attendees today why this is such an important topic and why we're covering it?

Yeah, I think there are a couple of reasons why we need to look at the business model canvas, the value proposition canvas and lean startup methodologies in the space of healthcare, pharma and life sciences. Because there's a lot of change going on. On the one hand, it's an industry that's changing with expiring business models. On the other hand, we have an aging population and healthcare is becoming increasingly expensive and we need to find new ways of. So I'm really excited that we have Toby with us to talk about this and make it very concrete and show how some of these tools and processes have been applied at his organization. Toby, thanks for joining us. Maybe you can tell us very briefly a little bit about Biocity and about yourself.

Thank you, Alex. It's a pleasure to be with you. Okay, so Biocity Group is the group organization. We have two brands that sit underneath that, BioCity and Medicity and four sites currently across the UK and Core and Common across those two brands and four sites. Is our overall aspiration to create an environment in which early stage companies in the life sciences, pharma and healthcare sector are more likely to be successful. And we try to achieve that by creating the right physical environment, the right support services, coaching and training, and the right access to investment to help them get started, grow and realize their potential.

So we're talking about a highly regulated industry and environment and a lot of people think that maybe in this space we can't do lean startup, we can't think about business models. Now you're proving the contrary. Where do you think the real value is in bringing these kinds of tools into, into this heavily regulated industry?

So for me, these tools. So in particular, the lean startup approach of challenging assumptions means you minimize the amount of time, wasted time traveling in the wrong direction, building the wrong product or service, or trying to build the wrong things business model. And given the kind of drawn out time frames to finally get something to market, I think it's even more important you're not wasting any time along the way developing something in the wrong direction or for the wrong end user or end customer. So the fundamental part of teasing out what assumptions might be in your business plan currently, robustly and thoroughly testing those and, and getting the evidence you need to demonstrate the commercial viability to your idea is Even more important because once you're on a certain tech development pathway or a certain regulatory pathway to get your product, service or therapeutic approved, it's difficult to change direction. So I think the rigidity and the importance or the impact of the regulation makes it even more important to tease out any incorrect assumptions and potential fault lines in your business at a later stage.

So given that we are in a regulated space, it is probably a bit more difficult to test and experiment than if you are a startup with a mobile app or a web app, even in the enterprise space. So tell us a little bit maybe about the challenges of testing in this space and how to overcome them.

So that's absolutely the case. Often, I mean, there are healthcare businesses that have a business to consumer offering, but often your end user is going to be a healthcare practitioner or professional and it may well be that only a handful of key opinion leaders can make or break this potential business opportunity. So what you can't do is throw them all to the landing page and do some split testing and, and conduct experiments in that fashion. Instead, what we try to do with our companies is say, well, you know, we know you're making assumptions in a whole load of different areas in all the different sections of the canvas, but we want to start with the assumptions and therefore the hypothesis you have around who your customer is and what their problem is. And we force them to, we ban talk of solutions to begin with and we say go out and really evidence for us customer group that you know, look the same and behave the same who are describing a problem in the same way. And then once you've evidenced and validated your hypothesis, your assumptions in the area of who your customer is and what their problem is, you can then design, promote, present your solution from this direction of travel of I've understood the customer, I've understood the problem and therefore here's my solution. And you can do that with face to face interviews. You know, what are the problems associated with this? Why is that such an impact? What does that mean to your working life? What's that costing? What's the outcome for patients? Why does that matter? And you can, you know, you can form hypotheses and test them through a series of face to face interviews with a small number of people to still tease out and get that information rather than having, rather than taking the more traditional kind of digital approach to just throwing traffic at landing pages and seeing what you learn from it.

I really like this because in particular in science based industries, people always think about solutions and technologies first and you're pushing them towards thinking customer first jobs, pains and gains. Has this been something very unusual for the entrepreneurs who go this, is this some kind of an eye opener or is this just what they would have done otherwise anyways? But, but you're giving them a bit more structure. How do they react to these customer, you pushing them into the customer on the customer side.

So I think as you said, because of the sector we're in and because of our position, our relationship with a number of universities, a lot of people that come to us at the very early stage have a technology and so they have a solution, but they've never really stopped to interrogate the customer problem thing. They've done things like health economic studies and paid an outside consultancy firm to tell you that diabetes cost the UK healthcare service one point, whatever, a billion. And these sorts of top down studies, what they've never done is gone out and done face to face customer discovery. And so no, they're not at all prepared for it. We actually don't tell them, we do a two and a half day boot camp and we don't tell them what they're going to come into because we're worried they wouldn't turn up if they knew. But when they do, we very quickly force them to say stop talking about your technology and your solution and go and tell us whether there's really a customer that's suffering this problem. And to begin with, that's a real opener, a real shock. But what has been really encouraging is the way so most of these guys have a scientific background is the way that once they get it, they then do it very rigorously. They apply the same rigor that they would in their scientific discovery to their customer discovery. And once you've convinced them to drop the talk of technology and the solution, they get very rigorous and very accurate about really truly understanding the customer and the problem and not infusing that with talk of solution at an early stage. So there's a hurdle of, to overcome in the first place, but once they get it, they're extremely rigorous and very persistent in pursuing that.

Excellent. Right, because we all see those market studies where we throw around millions and billions, but at the end of the day that's just not concrete enough. We're not talking about the real stakeholders and what really bothers them, what motivates them. So I actually had some slightly different experiences sometimes with scientists when, when we talk business, it's almost as if they accept that they can be pretty. So their value proposition canvases would have very high Level jobs, pains and gains and pain relievers and gain creators. They would say things like, bigger, better, faster, very high level. And I often ask them, well, in your science, do you have that kind of lofty approach or are you more rigorous? And once you kind of framed it that way, they go in that direction. So it seems that you didn't have that experience. They immediately get very scientific and detailed about the jobs, pains and gains and how they create value.

No, I wouldn't say it was immediate. And it differs from individual to individual. It often also depends on how the emotional attachment to the technology that they've been working on, because they've got to drop that bit first before you can accurately go and do this free of that. And it takes different people, different lengths of time to finally grasp that and go out and apply it properly. The thing that I have found that encourages them though is I think prior to that they think business is this sort of slightly dark and murky world where entrepreneurs are born and not made and you need the gift of the gap and you need to be able to sell to be successful in business. And this process of combining the canvas with the process of challenging assumptions in each of the different areas gives them a way to be able to decode that world and understand it much more clearly. And then when they can do that, the blinks come off the eyes a little bit and they're far more confident in going out and doing it.

Yeah, I find that interesting. I've seen that a couple of times myself. It's this strange view on business and once you give them these types of tools, they completely change their vision of what business actually is. We talked about the tools a little bit and how you're using them, but I'd like to go a bit deeper so maybe you can tell us, because we have a lot of listeners from the life sciences and pharma listening in today. How specifically do you apply the tools, the business model canvas, the value proposition canvas, and how does that process look like at Biocity? Maybe you can give us a quick overview of the process that a typical startup would go through.

Yeah, absolutely. So we run a number of programs to take teams and their ideas at the very earliest stages help to move them towards investment readiness, startup funding and hopefully eventually then moving into our facilities and growing. And what we do at the very early stages is put them through a, for the most promising looking opportunities, put them through what we call our develop program, which is a 12 week program. And we use the canvas as a framework for the timetable of the program. And we basically work through different sections of the canvas week by week, essentially using it to go out and challenge assumptions in each of those areas. But we have. So in addition to the canvas, we also, we use the value proposition canvas as well, the process of challenging assumptions. And the fourth tool that we have is the, what we call a customer problem wide scan, which is this tool we often have to use just for people who come with a solution, come with a technology. And we have to say, well, let's just go really wide here and think about all the different permutations and combinations of customers with problems and do a quick test in all these areas and work out where the most immediate need and opportunity is to be able to apply this technology. We call that kind of detecting the signal from the noise. It's very easy get blinkered in terms of where you think this can be applied. And our customer problem Wide scan helps them to do that. Once they've narrowed down into two or three areas where they think there's a real need and opportunity and a customer with a checkbook that can pay for this. And the problem is in the kind of top few things that keeps them awake at night. We then use the value proposition canvas to really understand why people might buy this. Not what they buy, but why they might buy it. And then that kind of that value proposition canvas, and effectively the same process of challenging and testing assumptions in terms of what the motivations are for these people, why they might buy, why it's important and what the impact is, helps us then start to shape the description of the product or service. And then, and this is directly from all your materials, but that gives you product market fit. And then we use the business model canvas not only just to challenge the assumptions that we're also making in other areas, and there's some very dangerous ones that you can gloss over, particularly in our sector, around things like time to get through the regulatory approval, eventual cost of your medical device, these sorts of things. There will be assumptions at every level within all of those that you need to go out and thoroughly test. But once we finally get into the stage where we are hopefully mitigating a good percentage of risk by going out and challenging the assumptions, we then use the canvas as well to really think about how we can innovate on the business model. So, you know, do you sell the device or do you design some software to go with it and rent it out? These sorts of conversations start to come in because often, and we've seen it before, companies that have got clear product Market fit, manage to get a product to market, managed to get it manufactured. But actually it's not generating cash and really capturing and realizing value because the business model is wrong. So it's that kind of sequential process of customer problem wide scan to find out where to apply it. Value proposition canvas to understand why people would buy from you. And then business model canvas to test the assumptions in the rest of the areas of the business model. And then finally business model canvas to help us innovate on the design of the business model to really capture value.

Excellent. And that's a very nice and well described process. So I'm pretty sure that to get to this point, knowing what works and what doesn't, you had to iterate and pivot yourself to figure out what's working. Maybe you can tell us first, what were the biggest insights for you applying these tools with med tech, health science and pharma startups? What were the biggest insights and maybe even what were the biggest mistakes you made so others don't have to make the same mistakes? I know it's always a bit tricky to admit to certain mistakes, but I'm pretty sure you couldn't get to this point without actually doing a couple of things really wrong. That's how we get to a great process, by experimenting.

So I think to take the insight first, I think I probably paid the lip service to the value proposition canvas when we first started thinking about using it because I made the assumption that, you know, people in something as scientific as drug discovery or you know, as engineering based, as developing medtech devices or those sorts of things, or even, you know, people making decisions around patient benefit, their decisions would be all functional, you know, it's obvious, you know, that's better than that. So therefore that's what we want to do. And the kind of, the social emotional part wouldn't have a role to play. Their ego didn't come in and all those sorts of things. And at the end of the day, of course we're all, you know, we're all human beings and everybody's making decisions based on a whole range of different things. And we've discovered some instances where people, you know, behave in quite unexpected ways when it comes to buying and making decisions in quite scientific areas. But if you, as I say, on a lot of our programs, people, people behave in a rational fashion. But if you observe enough of them for long enough, you'll work out that we behave in a predictably irrational fashion. So I think the big insight was that actually this isn't just B2C stuff, you know, people in, people in corporates, people in business, people in healthcare, make decisions often based on things that sit far outside of their functional job and the things that they have to do. That was a real insight for us. I think the mistake perhaps we've made along the way is, is, you know, we used to say, well, you know, we can't really help with the technology because that's not our specialist area. So we're just going to focus on market risk. In any business in our sector, there's the market risk and the technology risk. So, you know, is the market there to buy it and pay you money for it and can you make the technology work? And I think we, we downplayed and didn't look into and investigate the technologies behind some of the opportunities that we were supporting in the early stage and just focused only on the market. So, you know, customer problem, our solution might look like this. And therefore this is a big opportunity. Yes. And only a later stage. We realized that actually there was little to no substance in the technology or it was a million miles from being able to deliver what we thought it might be able to deliver. And so therefore you've done a whole academic exercise, but not actually got any thought to delivering a business because the technology development bit is just far too big. There isn't enough substance to what's been developed so far. And so it's a good thing to do, but it actually becomes academic if you can't get a solution that can go and solve that, that problem for that customer. And so now we try to spend a bit more time, you know, understanding the tech development and understanding the risk associated with that and doing it in conjunction with assessing the market risk rather than leaving the doing, you know, doing one in isolation from the other.

Can I dive deeper there for a moment? Because it's something that I see very often, right, that it's not a linear process. It's not as if you would go from one to the other. Market validation we like to call proving the desirability and then moving to the feasibility in terms of looking at the technology. It's a bit of a back and forth. You want to probably go very fast on identifying the real jobs, pains and gains, the problems that are out there with the stakeholders, then play around with the technology, see what's feasible, how much does it cost, and then you'll learn from there and probably you'll have to go back to cost customers. Do you see that some entrepreneurs have struggled with this? That they would like a linear process like all companies and scientists actually like to have, but it's much more of an iterative process where you go back and forth between talking to customers and stakeholders, going to technology and then having to go back. Have you seen that struggle going back and forth between problem solution, problem solution all the time? We've seen that quite a bit, yes.

It's an ongoing risk for any early stage business or opportunity in this area. On our 12 week programs, we try to stress to participants that we may come to the end of this process and have killed all opportunity here and we've got to go off in a different direction. And so it's as much about giving them the tools and helping them practice the techniques to allow them to do it after that. Because you're absolutely right, this is a completely ongoing process. The tech development has to go in hand in hand with the market risk mitigation. And often when you do your tech development, you suddenly discover that, hang on a minute, not only are we getting the results faster, but we're getting them in a way that presents this as a potential benefit as well. So we need to go out and discover what are people interested in here? Are they interested in speeds to results or presentation of the information or whatever it happens to be? So often the tech development throws up another potential benefit that you then, rather than just including, you have to go out and do your customer discovery to work out whether that's of interest to people or not. And of course, even when you launch and you're funded and you're bringing your first product to market, we're still navigating uncertain waters all the time. And so holding this kind of slightly cynical approach and working out where you're making assumptions and going out and testing those is just a good way to conduct business full stop.

I know you applied the tools and the process to your own organization, to Biocity. Maybe you can share a little bit. For folks out there who are either doing this inside a large pharmaceutical company or who run accelerators and incubators, what were your learnings in terms of the business model and value proposition of Biocity?

I mean, there were a large number to list. It is amazing turning the spotlight on yourself and forcing yourself to do it because you think you've, because you're a slightly more established business that you've got this nailed, you must do because you're up and trading and being reasonably successful. Therefore it's only incremental benefit you could add by actually turning the spotlight on yourself and forcing yourself to go through the same process. But if I just take one example, you know, I found that we were describing our 12 week program, for instance, as, you know, a 12 week program where you robustly test the commercial viability through evidence based entrepreneurship and use of business model canvas and Lean Startup. And, and I'd suddenly looked at it, I thought, I'm not describing any of the value to potential customers here, I'm just describing what the program is. So I haven't understood at all why people might buy, why people might want to come on this program. And so we did a value proposition canvas for potential participants of a program like this and try to understand what are they worried about. And they're not looking for evidence based entrepreneurship tools. That's not the thing that's keeping them awake at night. If it would be lack of experience of having done this before, connection to capital and money to help them get going, and connection to industry contacts that can short circuit and fast track the development of their business. And so using that value proposition canvas, we've then started to just describe the program in a totally different fashion. Because whether it's 12 weeks one to one or 15 weeks, two days, that's all kind of irrelevant. It's the what you're buying, not the why you're buying. And so yeah, we were sat there delivering this program, having not taken any of the medicine ourselves. And so just the process of using the value proposition canvas for potential program participants was extremely telling and totally changed how we describe the program to people.

I think we've all been there, right? I mean, we went through the same process with strategize where we describe what we're doing, but we're not describing. Once you do a value proposition canvas, you're actually forced to describe how you're creating value. You're making explicit why do your products and services even matter. So I think we've all been there. Now, you described a value proposition to one segment, the entrepreneurs. Maybe you can tell us what would be the killer arguments you would have for pharmaceutical companies or big players in the health care sector to apply this approach. What's the killer arguments to those organizations to start working like this, which is pretty different from their established way of innovating.

Yeah. So you mean the value proposition of biocity to a large pharmaceutical company.

Exactly.

So I think you open this seminar up by talking about, you know, the challenges of rising costs of care and aging population. And I think all of the larger companies accept now that a number of those solutions to those challenges are going to come from outside of their organization. And so as well as internal R and D. And they are reducing the amount that is done internally. There's also a growing acceptance that a large and increasing percentage stuff that they eventually own is going to have to come from outside of their organization. And so the people who are challenged or tasked with strategic acquisitions, sourcing external R and D in licensing, those sorts of things, have a very particular problem, which is sort of like finding a needle in a haystack to a degree. You know, how do you cast your net sufficiently wide, but sufficiently woven, thinly woven, on a limited budget to capture, you know, the good opportunities, number one. So how do you cast your net wide enough? Is problem number one for them, I believe number two is how do you triage sort them? Because often it's very difficult on a couple of interviews and I look at a business class to work out whether there's really something here or not. And when you're looking at a very large number, it's difficult to work through those. And then thirdly, often they have to make a decision as to whether they're going to invest, whether they're going to buy, whether they're going to get involved in this opportunity at a specific point in time without having seen any of its development over time. Often the best due diligence in early stage businesses to watch them over time. And so we believe that our value proposition to the large pharma, large healthcare companies can be each of our programs running at each of our sites with multiple connections to multiple universities, feeding good numbers of opportunities into our boot camp, into our 12 week develop program, and then into an investment readiness piece that gets them funded and gets them in means that they can cast the net wide, see a large number coming through for a limited amount of effort, feed in their requests and things that they would like to see from those opportunities as they develop, observe them over time, and use the program to triage and filter the good quality opportunities that they might be interested in in the future. And so it's in those kind of three areas that I think that, you know, what we could do and what we can offer starts to appeal to the people who are the heads in licensing and strategic acquisitions in large pharma and large healthcare companies.

So I want to move to the systems level for a moment and maybe let's talk about the healthcare sector and pharma life sciences in general for a moment, tackling maybe the bigger challenge in order to come up with new business models and new value propositions that tackle some of these big issues that we face in life Sciences in healthcare. We know now that these approaches work. You've proven it. How can we scale, how can we really get these methodologies out there into the right hands, into the right companies, into the right government institutions? What is your vision on that? How we can scale this to really create a better system overall?

Big question. I don't know. I mean, I think from our perspective, I think all we can do is just carry on doing what we're doing and hope that the ripple effect means that, you know, you get more people subscribed to this approach, more people signed up, more people, but believing in the value and more people actually experienced and practiced in the art of applying the tools as well. We've probably been running these programs for two, three, two and a half years now. And we're just starting to get to the stage where we've got graduates of opportunities that number in the tens, but putting them together and hearing them still two years afterwards, talking in a certain vernacular that they share now in terms of, you know, the different segments within the business model canvas, the process of challenging assumptions, challenging each other and saying, are you not making an assumption there and how are you going to test it? That's very gratifying. But it does start to have a wider effect in terms of changing a wider industry's mindset. But I think you've got to. Well, our approach is you've just got to roll your sleeves up and get stuck in and hope that what you're doing slowly ripples out and everybody gets there. Because, you know, we're not precious over. People don't have to come on our program. If everybody knew how to do this straight off, all of our facilities it would be full with well funded, fast growing opportunities immediately anyway. So yeah, we just want to see more people subscribing to it and more people using them. And one of the things we're doing quite a bit of is doing it with universities and not only the tech transfer offices, but some of the departments and some of the professors that lead certain departments to their researchers to say, think about things in this way, do a bit of your own customer discovery, work out what the potential impact of the technology you're working on is and could be, and try to understand it from this perspective, such that when opportunities start to bubble out and come forward, they're in a much better shape with a far greater amount of customer discovery done before we get involved.

I like that. Producing results, rolling up our sleeves and I think that's the way forward and showcasing it. One of the reasons why we really were excited about showcasing BioCity on our blog as well. Do you see beyond the accelerators, incubators, maybe pharmaceutical companies, do you see government stakeholders, policymakers also starting to get this, or is there still some resistance there? Because some of them still insist on business plans, right?

Yeah, absolutely. And banks do, and a lot of venture capital organizations and firms do as well. You know, there's a lot of traditional approach still and many of the problems I described in terms of, you know, assessing opportunities from within large pharma and large healthcare. I think VC firms have the same challenge. You know, you're making a decision at a point in time based on two or three interviews in the business plan and it's difficult to know whether they've really got the right solution and whether they couldn't have done something different or isn't a different way of delivering this business. So I think there's a number of organizations that would benefit from adopting the approach and the mindset. I think the slight risk is, and I see this a lot, you know, oh, yeah, I've used Business Model Canvas. I know about that. And it's kind of, you know, tick done. We once completed one. And I think the strength of Lean Startup and Business Model Canvas and Value Proposition Canvas, their simplicity. The difficulty is as soon as you step a little bit away from the rigor of applying them properly, you're now just going through the process without getting any insight or any learning. And I think the bigger challenge is how do you up everybody's skills in applying these tools rather, because a lot of people I think say, yeah, no, we've done that. You know, it's the same as they've added it to SWOT analysis and a number of other things that they have kind of standard business assessment tools without, I think really understanding the potential power of them.

Yeah, I like to compare this to heart surgery. Imagine if our heart surgeons would operate the same way we kind of operate with these tools.

Right.

There's a learning process. The first time you're probably not going to get it right. You don't know how to do the testing.

Right.

In particular, in a difficult environment that's heavily regulated, is over time that you learn this. And I think what you mentioned before also is that when you have alumni who share among each other who say, this was difficult, we did it this way, that's when we really start increasing the quality of how we apply these tools and the whole lean startup process. So we're only at the beginning and I do hope we'll go Deeper. And we'll have more of this. Maybe a quick question. I'll dive back into the practical parts for a bit before we take audience questions. When a team starts out, let's say they start at Biocity, they're focusing maybe on a market opportunity or a technology that they have. What are the three things that you would tell them they should watch out for the three most important things that they want to keep in mind throughout the process, throughout these 12 weeks when they're going through the methodology.

So I think one of the. So one particular one for me is are you really listening to what your customer's saying? I think to a lot of customers and oh yeah, I've spoken to 10 surgeons now. But there's a big difference between talking to people and actually really listening. And listening means looking at people's body language, understanding what they're saying, and also phrasing questions in a way that you can't really lead them down a path that confirms what it is that you want to hear. The classic confirmation bias risk that you have when you're wedded to a project and have been for a while. And so I think that really listen to what people are saying and isn't the first thing. Second thing is, don't allow your current suggested solution to flavor your questions and flavor the potential outcome of all of the customer discovery, because it's very easy to do. And the third is not just there's a risk people start to over analyze this as well. So kind of we lay all of this quite heavy on people and to begin with the program, and then they sit there a little bit paralyzed, thinking, I've got to phrase the question perfectly before I go and talk to somebody. And sometimes you just get momentum just by going out and having a conversation and letting it range freely. And then you can kind of retrospectively form hypotheses that you want to test with further people afterwards. So definitely really focus on listening to your customers. Don't let the solution sway or artificially change the outcome of those interviews. But at the end of the day, just get out and talk to people because it's better than sitting in a room going round and round in circles. We talk about the interviews being like the teeth on a cog. The interviews are things that give you traction, help you move forward. And if you don't do any interviews, you're a toothless cog spinning around, not going anywhere.

And I'm sure you probably also teach the art of interview skills, right? Because we always think it's just about talking to customers. But if we frame the questions wrong, we actually get the wrong kind of results. Right. We get opinions rather than facts. Or we might try to sell rather than figure out what is really bothering customers. I really liked your emphasis on listening. Maybe one last question just before we go to the audience question, Then I'll hand over to Kavi. What is so far, would you say your favorite example of an organization that went to Biocity, where you'd say, they really got it, they did a great job, or maybe an example of a company that had to pivot. Give us one case maybe that you liked in particular before we go to audience questions.

Okay, so there was a company at our site in Scotland that they're called Bioascent. And what Bioascent have is a compound against which you can screen to try to get an initial hit, to help you to find a starting point for a particular drug discovery. And the offering effectively is you can screen against our compounds. We can select them from the library, send them out to you, you screen against them, and then if you get, you know, good success, you get a hit, it's IP free, and so you can start, you know, developing your potential drug from that starting point. And so we sat down and went through the customer segments with Simon, the CEO, and we kind of. There was a fairly traditional approach to that. We. So, you know, with this, customer segments were small biotech universities, research institutes, and kind of small pharma companies, all involved in drug discovery, but not sufficiently financed to have their own compound library that they can screen against. And we try to understand some of the challenges they might face. But we know that the device, that's a compound management library with repository retrieval. So we know that it can select things in small amounts, compounds in very small amounts. And we know that we can put together bespoke selections for people, whereas a lot of the competition sell you larger amounts with fixed plated sets, they're called, so fixed ranges of compounds. And so we went to these customer segments and told them a little bit about, you know, what we can do. And we weren't really getting any kind of. We weren't getting any startling insight in terms of, you know, would it be of interest? Why would it be of interest? Why might they buy what was going on here? And we went through it for quite a while and still no trends were emerging. We couldn't quite work out why everything was kind of split the whole time, almost kind of 50, 50 in terms of why people might buy and what the issue was. And when we looked at it again, we realized that actually we got our segmentation completely wrong. That despite what you might think, the people working in drug discovery and biotech and university, small pharma and research institutes operate in very similar fashions, have similar budgets, buy and procure in similar fashions. The fundamental difference, however, the fundamental segmentation that we arrived at is actually the difference isn't between small biotech universities, research institutes and small pharma, it's between biologists and chemists. And when we split the results and all the conversations that we've had today and regrouped them into biologists and chemists, really strong recurring themes started to come out in terms of the value proposition to the biologist and the value proposition to the chemist. And fundamentally the biologist was, with a relatively small budget, had to come up with their assay, their bioassay, the thing against which the compound would be screened. And the thing they were really worried about is once you get screened, if it's not successful their project or if it is successful, but the chemistry of that compound isn't very good and the chemist just kills it and it doesn't go any further. So they put all this blood, sweat and tears into something, it doesn't go any further. So they were most bothered about their project continuing off the point at which they screen. The chemists, on the other hand, realized that, you know, they're often the bad guys, they're killing the projects because they don't like the chemistry, they don't like being seen as the bad guys. But chemistry is a very personal thing and different chemists think different compounds or think about compounds in different ways in terms of the chemistry and whether they think it's good or not, or whether they'd want to work with it or not. And so too often they were getting a hit with the biological assay and a compound that worked. But chemistry, that compound they didn't like and they were interested in could they pre select some compounds before the screening such that if they did get a hit, they were happy with the quality of the chemistry and would continue to work with it afterwards. And by fundamentally changing a this customer segmentation and then realizing that people were making this on emotional and social decision making, we totally changed how we describe what it is that we offer and totally changed how we target people. And there's now, if you look at a new brand called Compound Cloud and if you look at the Compound Cloud website, it is very strongly targeted at biologists and chemists, irrespective of their overall employee organisation and background.

That's A brilliant example of customer discovery and then taking action. Right. Because just talking to people and not learning and then taking action is not what we're talking about when we see Lean. So I'll hand over to Kavi. There are tons of questions that came in. We'll have maybe, I don't know, time for a couple. Kavi, tell us.

Yes. So just to the audience, there are so many questions to get through. What I think Toby and I will have to do is do a Strat chat podcast segment so that we can cover all of the questions. So Toby, I've selected a few. Let's start with this one. How has the approach that you've been talking about with Alex today, how has this approach saved you money and time?

I think it has probably it's the businesses that we're supporting for whom it has saved the most money and time. We lot of businesses, I mean, Biocity has been going for 13 years now. We've got 200 companies across the four sites. And so we've seen a lot of companies come through our facilities. But you know, we've seen a lot of companies develop, you know, Secura and Innovate UK grant or you know, the old kind of smart R and D grants, whatever it happens to be to develop a product, got very excited about developing their prototype, spent two to three years and £150,000 developing that prototype, only to discover that, you know, the clinician isn't bothered about this bit. They're more bothered about whether it'll fit in their top pocket when they do their ward round. And so, you know, there's a countless numbers of examples of people that were at the stage of very nearly going into the regulatory approval process and manufacturer and we've saved them three years and a six figure sum by realizing that gps aren't the end user of this or the person who's going to write the check for it and that you've got to go and find a different way to apply it. So I'd say regularly companies saving several years and six figure sums on product development, not building things that people ultimately don't want.

Awesome. So that means that there has to be a lot of managing of not only short term hypotheses and expectations, but also long term hypotheses and expectations. Do you perhaps have any advice on how people in this industry working with these tools can focus on those two different spectrums?

I think in the longer term the difficulty is you can't be absolute about it. And often we see companies developing technologies, everything that they asked when they started developing the technology was true, has changed because it's a fluid and moving landscape and in the two to three years they've been working on it, things have moved on. And so actually you have to just continually, just as Alex was saying, keep doing the process and keep applying it, such that you're constantly checking that your direction of travel is still aiming at something that will eventually have product market fit, rather than just doing it once at the beginning of that process, that tech development process, and then keeping your eyes shut and hoping that when you get there you hit the bullseye.

So let's talk about a bit of that process. You know, what's your experience getting teams into this more creative process as opposed to kind of going straight towards business planning?

Well, that's what we do in our programs is try to give people this mindset and these tools to say, you know, you've got to keep testing these assumptions, you've got to keep iterating on the design of your business model and you've got to keep going back out, getting out the building and talking to people and getting the evidence to show that you're still on the same track. People used to say a business model is a dynamic document that's constantly changing. It's just much more difficult to change something that's bound, printed and you've written it for the seventh time. Whereas putting up a canvas and bunging up a load of post it notes and putting some question marks against some of them and then working out the questions you need to ask to go and test those is far easier. And it means you don't get locked into a trajectory where you're trying to execute a plan. And it's a tricky balance in this sector. You've got to be executing some tech development work to a plan, but you need to be constantly sense checking such that you're not, you know, you're not targeting a problem that has moved on by the time you've completed the tech development.

So you've probably experienced scenarios where the prototype business model or the prototype value proposition did not work out. How did you redirect efforts or how do you motivate the cohorts or even just internal biocity people to continue on to go look for something new.

I think what you have to try to help them do is stop, take stock and take the time out to go and start a bit of custom discovery. Again, right back from square one. I think the temptation is to alter your direction of travel and lurch slightly to what you think is the most immediate, next best opportunity. And out of kind of time pressure and cash burn and investors saying, why haven't you hit these milestones? You lurch and you don't stop and take stock and do the process again and try to work out, try to work out where you're best pivoting to, you just kind of go for the nearest and most obvious. And that's not always clearly going to be the best. And so helping people stop and take stock and take a breath and say it's okay to sit back and try to do this process again, and it's worth the few weeks you're going to invest in doing it, because you're more likely to salvage something out of this than if you just lurched the next most and nearest opportunity.

I'll make time for one more. This is an industry where having existing domain and technology knowledge could be very important. But how relevant is that existing domain and technology knowledge when it comes to finding the jobs, pains and gains of potential customers? Is that something you say to keep at the back of your mind or to kind of go in with a fresh mind?

So there's two, there's kind of two parts or two answers to that question. So first of all, absolutely. And a number of people come to us with a certain technology or certain technical expertise. And so this isn't like the digital world. You can't discover that this customer has this problem over here. Redesign your app or your website overnight to target a totally different sector. You have what we call a technology anchor. That means that you can basically kind of rotate around a certain fixed point based on what your technology and what your technical expertise is. Nonetheless, it's still important to know within that range of movement, within that kind of overall sphere, that you can draw that you've got a customer problem once what it is that you're offering. So that's the first part. The second part is that. Sorry, just capture the question again for me because I had a particular thought there on the second part.

So we talked about the relevance of having existing domain knowledge or technology knowledge.

Got it? Yeah, got it. And the risk is, however, having said all that, the risk sometimes, however, is, you know, your technology might be in the area of, you know, the device you're trying to develop. And fundamentally, there are a handful of, say, really influential neurosurgeons in the UK that ultimately are going to have to say nice things about what it is that you're developing. Getting time in their diaries is incredibly important and very, very difficult to do. And what you don't want to do is walk in to that interview and start challenging really basic hypotheses with them and sounding completely uneducated about the environment in which you're operating. So you have to start the customer discovery on the periphery, maybe with the nurses or some of the written research that tells you about this space or those sorts of things. Because what you can't do is you need to, you need to keep your solutions separate in terms of understanding the customer and the problem. But you can't be completely uneducated about your area when you're talking to very busy, very well informed and time pressed people. So it's a balancing act constantly.

Awesome, Toby. Thank you so much to Alex and Toby for being part of this session today. I'm just going to quickly remind the audience audience that a recording of the session will be made available to all of you in about 24 to 48 hours. You'll get it directly to your inbox as well. I'll provide you links to our resource library so you can access the free tools and guides and other types of testing and business model or value proposition resources that are available to you for free. And I'll also be sending you guys a link to our enterprise offerings where a lot of what Toby has spoken about today is something that Strategizer offers to large companies. Especially similar to what Toby had mentioned around the 12 week innovation sprint cycle. That's actually something that we do. So I'll pass those links on to all of you in the next 24 to 48 hours. Gentlemen, thank you so much for taking your time. Holger, great work with the visual. Really appreciated having all of you here.

Thank you.

Thank you.

Bye everybody.