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Innovation for a Funeral Company and Many Others: Georgii Martsinovskii image

Innovation for a Funeral Company and Many Others: Georgii Martsinovskii

S1 E7 · Months and Millions
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65 Plays4 months ago

Georgii is a world-class inventor, author of more than 30 patents, PhD in laser physics and helps companies to make successful innovation predictable and within deadlines.

With over 25 years of experience in development of new products, services and technologies he worked for Pepsi, Mars, Siemens, Novartis, Medtronic and many other world's leading companies. His key to success is innovative problem solving.

The conversation is full of practical and insightful examples from Georgii’s experience where he shares his approach to making innovation real. We also discuss how innovation process changes in AI era, what tools and methodologies help from our personal experience and if it is possible to capture a lightning in a bottle again and again.

Check this episode to learn about innovation projects from Funeral Insurance Company, Breakthrough Medical Devices, consumer electronics, oil and gas and many other industries. Pay special attention to the final chapter of the episode where Georgii, as an innovator, shares what he anticipates as the next step of innovation.

This is a personal podcast. The views and opinions expressed here are only those of the author and do not represent those of any organization or any individual with whom the author may be associated, professionally or personally.

Transcript

Topic intro

00:00:15
Speaker
Hey, welcome to Month in Millions, a practical and inspiring show about innovators and emerging tech practitioners. I'm the host of the show, Alex Babko Around 3% of the Earth population consider themselves innovators. It's 240 million people give a take. There are tons of books written and millions of videos out there with experts who promise you a moon, predict the future and pretend to tell you everything about innovation, especially if you buy a course from them.
00:00:49
Speaker
However, real, meaningful innovation is still a rare gem. While some people are waiting for a muse to strike with a breakthrough idea, others, like my today guest, develop a systematic approach to innovation to make sure it is predictable, feasible and has significantly higher chances to make a paradigm shift with real impact on business and on our lives.

Guest intro

00:01:16
Speaker
My guest today is Georgii Martsinovskii a world-class inventor, author of more than 30 patents, PhD in laser physics, and established innovator. Georgii has 25 years of experience in development of new products and technologies for Pepsi, Mars, Siemens, Novartis, Metronic, and many other world's leading companies in the fields of medical devices, consumer products, logistics, beverages,
00:01:44
Speaker
and other industries. His key to success is innovative problem solving And today we will have an exclusive and very interesting and insightful conversation, both making success and successful innovation predictable, repeatable and valuable to business.
00:02:01
Speaker
We will talk about practical examples of developing disruptive concepts and bringing them to life. We will also discuss why and how companies innovate, what tools and methodologies can help facing practical examples, and if it's possible to capture lightning in the bottle again and again.

Systematic Approaches to Foster Innovation

00:02:22
Speaker
Hi, everyone, everyone, Georgi, we've been working with you very closely for the last five years. And I must admit, I'm a big fan of yours when it comes to making innovation repeatable, clear, understandable, and valuable to business. And I've learned a lot from you during our collaboration, because you have a very interesting mix of skills and experiences. In your opinion, what makes you a good innovator?
00:02:48
Speaker
Well, I would like to tell about what makes basically every person a good innovator because it always depends on the particular a person. But there are still something that that is applicable to everyone. And ah what I like about innovations is that you do not need any any special education, any
00:03:16
Speaker
specific background, so if you are smart enough, you can just come up with a great idea. ah But the question is, what if you are not the genius and you need some some kind of guidance or work frame to do the innovations? And specifically, if you are doing innovations for for for the business, you always have a certain deadline and you always
00:03:53
Speaker
have a usually have a team that you work with. And not always this team includes that that kind of genius in terms of innovations. So you have to survive somehow. And ah answering the question, I would say that what helps to be a productive innovator Probably not the best one, but productive in terms of being able to deliver by the deadline some reasonable solution.
00:04:30
Speaker
ah is using some kind of framework that guides you through this innovation process and but makes sure that by the end, you would have a choice of solutions, maybe not the the best ones, potentially possible, but still practical and feasible just to solve your particular business problem

The Power of 'Stupid' Questions

00:04:59
Speaker
All right, of course, we will delve into the frameworks, into the skills, into the team composition. So, of course, we will delve into that. But to start the conversation, um when and how you realize that ah innovation is your discipline.
00:05:18
Speaker
It's an interesting question because I do not remember a particular moment when I saw I am the innovator now. It was a gradual process of becoming an innovator. I used to be a scientific researcher, so I already had a kind of logical mind mindset to do some analytical work, to solve some scientific problems. And that was my starting point. So after that, I just tried to apply logical approach to solving different kind of problems but problems, technical problems, business problems. And I saw that and it is possible to
00:06:06
Speaker
to understand the the key problem that must be solved. and you always have You always can build a kind of model. If you want to be able to get some consistent results, so you you have to to use some kind of algorithm.
00:06:29
Speaker
when analyzing the problem and finding the solution. And basically, you are just building models of the system you are working with. It could be a technical system or it can be ah just a whole business or some social system, whatever. But you are trying to to build a model for yourself. And within this model, you are trying to localize the issue and understand what actually makes ah it so complicated to resolve and just to get around those obstacles somehow.
00:07:15
Speaker
you you should be able to find some or possibilities inside or outside or outside your system to solve this problem. So when you have all those things structured and organized in the form of a model, it helps you to find a solution faster. The problem of any professional is that they all know what is possible and what is not possible.
00:07:40
Speaker
So they they think in terms of, in in the industry, it's something like the the gold standard, because every subject matter expert knows that there is some experience and knowledge accumulated in the industry for tens of years, and people know what should be done in which way, what is the best what is the best way of doing things in their industry, and they know that If you change something, you most likely make it worse, not better.

Understanding System Boundaries for Effective Innovation

00:08:17
Speaker
and because of this It's great to have such a knowledge, and this is what makes them professionals. But ah the backside of this knowledge is that ah you you cannot ask the question that would look stupid for the professionals because they know that there is no sense in such a question. So if there is some technology, for example, and everybody knows that
00:08:54
Speaker
the technological steps must be done in certain order. If you ask why you are doing this in this particular way, most of the professionals answer just because it's based on our previous experience. and they They never ask themselves what What would be the change disorder?
00:09:17
Speaker
but In many cases, the ability to ask such stupid questions is very important because you you're trying to change the the paradigm, basically, ah which is settled in the industry, in a certain field.
00:09:35
Speaker
ah And you should not be afraid to look stupid. And i'm I'm not talking about, you know, trying to change the laws of physics. ah But still, if we are talking about technology or we are talking about design, there are a lot of things that that which we should doing in particular way because it's a kind of traditional way of making things. And ah you should be able to to ask the questions that would
00:10:18
Speaker
challenge these gold standards that would challenge the traditional ways of producing something, confusing something.

Questions an innovator should ask

00:10:30
Speaker
And I think that the the moment when I learned how to ask those questions was the moment when I kind of made the first step into being an inventor.
00:10:48
Speaker
Right. That sounds very interesting. how What are those questions? How do you think? like What are the most critical and important questions? If you see something that happens in the system that you you want to improve, the first question is why. It is designed this way. ah You always deal with with a certain instance or certain implementation of some operating principle, ah when you analyze the problem, first of all, you you you need to understand what exactly ah we need to do. And you you should somehow get to another level of
00:11:35
Speaker
perception from the particular ah design to the the main function of the system. You still have to provide the required functions, but you have to get rid of all those components which you produce the problems which create some obstacles or which reduce performance, whatever. So you you have to understand what is really needed for o to deliver the value, to deliver the main function of the system and what are the
00:12:16
Speaker
just ah consequences of particular implementation. ah And this is why you always have to to ask this why question because you shouldn't consider everything as given so you have to to go outside and we will talk later about it I i think but ah is that in in most of the projects the the complexity resulted not from the real complexity of the problem but ah from
00:12:59
Speaker
wow from the fact that our clients are trying to ah solve the problem within seeing a very narrow frame.
00:13:12
Speaker
So if they consider, for example, a technological process, so they consider one particular operation, and they're trying to solve the problem within the separation. Even though the reason of some problems may be related to previous separation or successive operations, the same in design. If you are focused on some particular component trying to improve the component,
00:13:38
Speaker
And you believe that once you do it to to to make this to to make this component better, to improve the design of this particular component, you believe that the whole system would work better and performance of the whole so of the whole system would improve. But in reality, it turns out that you even if you ah improve this component, but you do not see the result at the level of the whole system.
00:14:04
Speaker
just because you you were focused on a very particular part of the system, but the system by itself as the
00:14:16
Speaker
result of operation of all the components interaction of all the components and it has some kind of feature which none of the components has individually and this is why it's very important to to look broader and to um to understand where is the boundary of your system, what is outside the system, what kind of environment is there, and how the system interacts with the but with the environment. All right. Yeah, that sounds very interesting. And I like your point about like this lack of understanding bigger a picture, something that we are
00:14:58
Speaker
Quite frequently struggling when working on like some innovation engagements with you. So one interesting aspect that I also would like to discuss with you is sir like basically the the the definition of innovation because for some companies like you the change a phone so on there on a beverage bout bottle that's already like an innovation.
00:15:18
Speaker
for others like trying to save planet from ah waste or from plastic and they call it innovation. Probably both are right. But um in your opinion, um why companies innovate and how they decide if it's like a real innovation and if it's successful or not? The innovation is always a change.
00:15:42
Speaker
And the reason why every company has to think about innovations is that that if you um want to keep your business alive, ah you have to to make those changes to respond to the changes in the world around. Otherwise, your business will die pretty soon. If you want to be ah better than competitors, you have to innovate even more. And for me, innovation just changed. And again, yeah back to your question, what we should call ah true innovation and what is just you know incremental improvement, it doesn't really matter because as far as you keep your business running,
00:16:43
Speaker
It's fine. so You're doing the right level of innovation. The criteria for me is the value for the business we should bring with your innovation. If you solve your business problems, so this is the innovation for your particular business.
00:17:01
Speaker
whether its It may be very little change in your production process, but if it improves performance and it makes your products more attractive for customers,
00:17:21
Speaker
That it means you you've done the right innovation. We had a client who is a large company producing pet food for cats and dogs.

Medical Device Innovations: Impactful and Simple

00:17:35
Speaker
and we are addressed two issues. One was relatively small innovation, but which which was very important in terms of improving the production performance. and The problem was related to making oh pet food, they made it from meat, so they prepared minced meat, put it through the extruder, formed some kind of bars, long bars, going on a conveyor.
00:18:20
Speaker
And this conveyor goes through through an oven, those bars get cooked basically. Then it ah cut into pieces and after that there is a but packaging machine that put those pieces into pouches and adds some gravy.
00:18:46
Speaker
And the problem was that they had a lot of different recipes with different flavors. And um after changing the flavor, and they need to clean the whole conveyor belt. And the conveyor length was like 20 meters. Pretty long one. And the conveyor belt was really huge. Pretty wide. And it took several hours to clean the conveyor belt or during changing the recipes. And one of the ideas that we proposed was to
00:19:28
Speaker
ah form a certain shell around the bar. So the bar, we propose to use co-extrusion and to form a bar ah which would have a kind of core with flavored meat and the shell with unflavored meat. In this case, every recipe when it goes through the conveyor It would have the same composition on the exterior part. The shell had the same composition, so you don't have to clean the belt.
00:20:08
Speaker
and ah Once you already cooked ah this bar and slice it, the only thing you have to do is to clean the knife that cuts the bar, which which is relatively easy. It takes a little time. And you can add some extra flavor to the gravy and just to let the this flavor diffuse into this unflavored shell during pasteurization and storage.
00:20:39
Speaker
So, by doing this relatively simple thing, you saved a lot of time for cleaning and significantly increased utilization coefficient of the equipment. So, it's a very simple improvement, very simple change. But the effect for the business is pretty considerable because you you you save a lot of time of the equipment.
00:21:09
Speaker
operation. And the this is the example of incremental innovation, which we would call incremental, because change is not that significant. And as an example of more dramatic innovation, with the same company, we consider it approaches to replace animal protein with protein from from data sources. and The problem of such companies who produce pet food is that they usually get this meat at sports sales and the the quality of the raw meat is not very consistent. It's very difficult to normalize it just to provide the consistent composition of the final product. and We did some innovation work regarding selection of potential technologies for producing
00:22:21
Speaker
proteins from plants or from fungus or from insects ah with a consistent quality at reasonable cost. I think this is the example of dramatic innovation in terms of changing the whole industry basically.
00:22:43
Speaker
we are try to analyze existing technologies to benchmark them to get some vision of feasible industrial technology for the purposes of pet food production. Technologists are known, but first of all, you have to provide the reasonable cost production rate. You have to develop the technical implementation for selected technology in such a way that the the quality of the final product will be stabilized. Otherwise, you would have the same problem as they had with animal meat. I can give you an example of innovation in medical devices. I like this example because
00:23:31
Speaker
The ah changes itself were relatively small, but the overall effect was very considerable. The problem was related to special tools for surgery, ah which is used to in laparoscopic operations to seal and cut vessels. Such an instrument this looks like a gun with ah with a long shaft with two jaws at the end of the shaft. so you Those jaws just you know hold the vessel. You apply some radio frequency to the electrodes of the jaws. ah They heat the tissue of the vessel. so Basically, they seal it
00:24:20
Speaker
Then there is a blade that goes through through the shaft and the blade cuts the vessel. So during separation, you seal the vessel, cut it so you can just proceed with making into the human body. And the problem is that the ah doctors who are making those separations, they must be trained very well to a identify the tissue just by looking at the image of the laparoscopic camera. And the image looks very fuzzy. So you have to, you see that you
00:25:07
Speaker
ah grab some piece of tissue, but just you have to no you have to know the anatomy so well that you just by looking at this picture, you should know if there is a vessel inside this tissue or not.
00:25:30
Speaker
ah And ah what we proposed, as soon as we we had two jaws with electrodes, so we we can ah use the same radio frequency, but with much lower power, and not to heat the tissue, but just to measure electrical properties of the tissue.
00:25:56
Speaker
at this radio frequency. And during the operation, we always monitor the heart rate of the patient. So we know the heart wave pretty well. So if we measure the signal of the electrical properties of the breast tissue,
00:26:20
Speaker
if we have some ah harmonics of this some modulation of this signal at the frequency of the patient heart rate, it means that we got a vessel between the jaws.
00:26:40
Speaker
And if we if there is no vessel, so we wouldn't see any modulation because you know the the properties is the same. it that they They do not change with the ah blood circulation.
00:26:52
Speaker
ah So, just adding a very simple feature to this instrument just to measure the basically the other permeability of the tissue.
00:27:05
Speaker
and the frequency at the radio frequency, we we can tell if there is a vessel between the jaws or there is there there is no vessel inside. So, we are help the surgeons to ah oh but reduce the risk of cutting the vessel.
00:27:28
Speaker
because they you know have a very limited view of the tissue through this camera during operation. And this very simple change in the instrument ah had a quite significant effect in terms of the safety of the the operation procedure overall. are I remember that some time ago you were at the summit of innovators in Graz.
00:27:56
Speaker
And of course, like the approach to innovation also evolves like the overall you nature of innovation. um So do you think that people innovate in the same manner as they used to do like 50 years ago? Yes, of course. Everything is changing and the ways of renov innovations is also changing. There isn't why yeah people are looking for some some new methods or techniques in innovation, so they believe that
00:28:35
Speaker
There is so some kind of magic knowledge that will help them to make innovations faster and easier. And you do not need to think much, but just supply some methodology and get the result.
00:28:53
Speaker
This is the the belief and it's pretty understandable. Now, we we see that we we just got another very promising opportunity for making such a technique or methodology that would help us make innovations really easily and even without any effort from from the human at all. so i I mean the artificial intelligence.
00:29:24
Speaker
ah because we are seeing a lot of instances where artificial intelligence produces a lot of interesting results in terms of creating some some new designs or pieces of art. I think one of the most interesting topic during this conference was discussion of what actually artificial intelligence is capable of in terms of innovation.

Will AI replace innovators?

00:29:57
Speaker
How can how can we use AI for innovation? Is it capable enough to replace innovators completely? I think this is the similar discussion as for programmers.
00:30:14
Speaker
And the situation is similar ah because model behind the artificial intelligence is based on different principles than the usual ah frameworks for innovation, which is based on some modeling and logical analysis. What we have with AI is a new opportunity to make a lot of trial and error attempts.
00:30:41
Speaker
based on a huge bulk of data. and We can do it really quickly through these models, but we do not guarantee that we we are getting the conscious solution to the initial problem. so we are We can get some hints ah based on the ah known solutions to similar problems or similar solutions. But it doesn't work in a way that we identify the the problem itself and we found the solution find the solution for for this particular problem based on certain rules or patterns.
00:31:27
Speaker
And this is why we try to apply AI just by formulating the initial problem. It's very unlikely that we get all the possible solutions. And it's not clear if we are getting the the best solution at the end. So the the answer is that it's very unlikely that AI would completely replace the inventor. But on the other hand,
00:31:55
Speaker
During the analysis itself, AI can help a lot. Specifically, it's very interesting to when you try to combine AI and pattern databases.
00:32:09
Speaker
Because in but in patents, the solutions are described in a very structural way. So when we apply these AI-based tools to patent analysis, you you get very interesting results that help you to get another view of your problem and to ah ah restate this problem and to see the principles of similar solutions to similar problems. Artificial intelligence is one of the hardest topic related to innovation processes.
00:32:48
Speaker
Yeah, for sure. I recently was listening to another podcast and the idea that I liked from there was that i it's not that AI will replace the jobs, but the jobs will be replaced with new jobs of those who can use AI as an additional tool to their skills and competencies. And I think that very much aligns with the but what you just said and aligns with the next topic that I wanted to discuss is like actually people, like that might be like most likely the secret source of the problem solving, just like the people who know
00:33:32
Speaker
ah how different systems works, how different models work, who analyze, who can think creatively, who can think holistically, and and not trying to like only focus on incremental improvements. So um what kind of team composition or a skill sets are required to come up with a innovative idea and like making it real?

Innovation Dream Team

00:33:57
Speaker
So typically, like what are the people that you are working on?
00:34:01
Speaker
and I know that that sometimes is a combination of the ah team on the client side and team on the agency side, so how would you see that?
00:34:13
Speaker
yeah i think that you If we look from the perspective of a company who wants to oh organize some team for innovation, for making innovations, I believe that, the of course, there there must be some subject matter experts just to to provide the knowledge the basic knowledge of the processes, the products. Also, they there should be some people who have some logical mindset
00:34:45
Speaker
ah but who are not limited with with the ah specific knowledge of the technology or the product. So those people who would be able to ask those questions why. ah And I think that that the most important requirement is just to to be have some kind of logical mindset.
00:35:10
Speaker
ah You touched a very interesting topic of like these are right questions, right themes and so on, but how to understand if it's right or not. One of the way ah to understand is to use root cause analysis.
00:35:26
Speaker
This is what we are using usually at every project. we We saw that the problem which the customer came to us initially in the beginning, it's never the the right problem to solve. Because when we did this analysis, we've always found that i it's not the way just to try to solve the problem you see. You have to make sure that this is the problem that ah helps you to get your desirable effect at the end.
00:36:01
Speaker
and ah This is why we usually build this short-cost analysis because we we collect all the problems that we can see in the beginning. Then we have the ah our clients' target, what they want to get at the end in terms of the the business effect. and We have to make sure that If we solve this particular problem somewhere at the bottom of this root-cost chain, will this solution help us to improve the the targeted performance which we are looking for in terms of the business, for example?
00:36:43
Speaker
And very often we we we do not see this connection, or sometimes we saw that there is a connection, but on this way there are some other problems that must be also solved. And unless we solve those problems, even if we resolve this particular one, ah we will not see the effect as a whole. ah So this is why oh I think that this it logical way of thinking in terms of the in terms of identifying identifying the oh root cause connection, it's very important to make sure that you get this right problem identified in the beginning.
00:37:31
Speaker
And ah again, innovation is always an iterative process. So you you should not think like if you go like in a waterfall manner, you can get you you you you you look at your system, you look at your problems, you identify the right one. ah Then you try to find a solution. ah You should be ready that at some point you will have to get back.
00:38:00
Speaker
to look again at those problems to change the priorities because this you know you're understanding the the system that you are working with is changing during the project. So you you should always allocate some time in this innovation process for you to to return and look again and made some analysis again to refine it.
00:38:27
Speaker
And usually it takes several iterations just to get the precisely right problem to solve.

Timeframes and Iterations in Innovation Processes

00:38:34
Speaker
Speaking about iterations and time and month, not yet millions, but still, are so are typically how how much time is required like to get from ah initial conversation and idea like, hey, we need to change that as an input.
00:38:56
Speaker
to actually finding the right problem and making sure it is the right problem. to yeah So how much time it takes to identify that typically? We can look at this yeah to your question a different way. What we can get in a month, what we can get in three months.
00:39:13
Speaker
but ah
00:39:16
Speaker
What is the minimum time that it makes sense to spend? I think it could be like a few days ah because you if you have the right people,
00:39:30
Speaker
ah subject matter experts that can help you to to learn the um specific context faster. ah You can get ah some feasible ideas in a few days. But again, it depends on the complexity of the system and the the level of accuracy of your analysis.
00:39:58
Speaker
ah Our projects, typical projects usually takes it takes about so two or three weeks to to get to the right problem, ah provided the system is not really complicated. complicated ah But again, for for some cases where we we're working with some high-tech products, it may may take longer. But usually it takes two, three weeks just to to to build those root cause analysis to get this a key problem, the the right problem to solve. All right, of course. And then and then it takes significantly more like to elaborate on that, like to

Prototyping: Testing Hypotheses Effectively

00:40:49
Speaker
deliberately work out every single aspect of that before it can be turned into something tangible, desirable, feasible, and and ah and other stuff, right? Yeah, and ah again, I think the the most successful
00:41:08
Speaker
solutions that we had, ah when whenever I got it, like, for one run, so we always had iterations, because you after you test your prototype, you you have a lot of a lot of insights that may change the idea completely. And again, when you plan for innovation,
00:41:34
Speaker
you should allocate some time for these iterations as well. Oh yeah, yeah the iterations and prototyping is also another topic that I wanted to discuss with you because that's a very integral part of the innovation process when um at early stage you need to validate an idea or solution if it's if it's viable, and so on. And I think and think we need to gather dozens of those prototypes, if not more. And always one of the key questions that you both discussed is what you're trying to test. like right So what what is the hypothesis? So what's your take on that and how to avoid getting pitfalls of prototyping the wrong thing?
00:42:20
Speaker
what what What helps you to organize the prototyping properly is to start from the use case. When we build a prototype, there are a lot of things that we may want to check. The the most important one that we want to test is whether the solution would work for for this particular use case. In order to reduce the prototyping time and the the prototyping budget, we need to ah focus only on the most important feature that we would like to test.
00:42:55
Speaker
And this is why this is why it is important to prioritize. And this prioritization, I think it should be based on the use case. This is why, again, we always have to go beyond the initial technical issue that our clients come to us with, because If they ask to to change to make some technical improvements, we always have to to figure out why they' are doing why they are doing this. So what is the use case? What is the the business expectations for that? And whether it works for the business.

Crafting Compelling Value Propositions

00:43:34
Speaker
Oh, yeah. I like this concept of like shifting left. We're trying to move from left to right. And then every time we like
00:43:44
Speaker
get to unanswered questions, we like shift left. If we still don't have clarity on some aspects, we shift even further to the left and so on and so forth, getting back to like initial so initial like value proposition, like the initial reason why the business exists. And I think we both have been in situations when we helped young and established businesses to create innovative digital and physical products.
00:44:09
Speaker
And one of the most important areas that is quite often overseen is a competitive value proposition, because some build or some innovate because they can. Others just intuitively get to some breakthrough ideas, but that may also like sometimes lead to failure later, if not properly done with this exercise. So what is your advice based on your experience?
00:44:35
Speaker
how to create a compelling value proposition, then further down the road does not require any kind of like root cause analysis, like why we are doing that, like what caused that and so on, like how to do it right from the very beginning. Yeah, what do we want to get at the end? I think...
00:44:58
Speaker
It looks like the simplest question for the innovation process. At the same time, it's the the most difficult for the customers usually to answer because they feel the need for innovation because they they want to outperform their competitors. They they see that the you know they their customers are looking for something else that they don't yet have. But it's very difficult to to formulate this value proposition properly.
00:45:31
Speaker
ah But I agree that before you have this value proposition formulated, it doesn't make any sense to try to to to design anything. I do not have a kind of universal advice for ah regarding how you should shape your weather proposition. Most of the projects we did, of course, they they were related to some technical innovations as a base, at least. We had a couple of cases when we worked with completely non-technical customers ah with their completely non-technical problems. One of the customers was
00:46:18
Speaker
oh Funeral insurance company. and it It was really challenging for us because it's it's hard to imagine more conservative type of and industry.
00:46:36
Speaker
and We were surprised how many startups companies exist in this field trying to provide new types of services.
00:46:54
Speaker
Actually, considered themselves as an insurance company, first of all. so They had this specific value proposition for funeral insurance, and they did it for tens of years. and They are considered it as a very well-known company.
00:47:16
Speaker
in this specific area. The challenge for us was to find alternative to the usual interaction between the insurance company and their customers. Usually, there is a conflict between the insurance company and their customers because ah the customers would like to get as much as they can from the insurance company in case of some incidents and in in our case in in case of funerals. On the other side, the insurance company is trying to wait to
00:47:54
Speaker
to stay yeah profitable and just to basically to make the customers pay more. From many points, this is a kind of conflict and you have to resolve it. We believe that if we work would be able to resolve this conflict, it would be a base for a new weather proposition. And what we did, we tried to change the scene completely.
00:48:21
Speaker
So, we we tried to find something common both for the insurance company and for the customer just a to be a find some win-win solution for both parties. We we saw that both sides are very interesting and that the customer would leave as long as possible. Longer the customer leaves, of course, it's better for the customer because everyone wants to live longer.
00:48:50
Speaker
The longer they leave, the more they pay to the insurance company because they are paying basically for their threat of dying sooner and not being able to provide enough money for organizing their funerals.
00:49:12
Speaker
and Once we look at this model from this point of view, so immediately we come up with a new ah approach to or formulating the value proposition because the value is the long life of the customer.
00:49:32
Speaker
ah And it means that the developer position should be based on some services that will help the customers live longer.
00:49:44
Speaker
at at the same time to provide them with the insurance. But the the focus is on how to make their lives longer. And again, it's it opens a new completely new set of services for this insurance company in addition to just regular insurance ah products. I think this is an example when you're trying to build your value proposition as a result of solving certain problems or contradictions in existing business models, like in this case. Returning back to your question of what I would recommend, what kind of approach I would recommend for making value proposition, I think that ah the most efficient value proposition is based on resolving some issue of the customer.
00:50:36
Speaker
So you have to ah understand which particular problem you would like to solve for the customer. And then it would be much easier to formulate the developer position itself.
00:50:50
Speaker
But again, you have to make sure that you you've chosen the right problem for the customer. Again, because there are a lot of different problems and you somehow have to prioritize them.
00:51:05
Speaker
and ah no but Once you have this problem identified, then it's much easier to come up with an idea of new value proposition.
00:51:22
Speaker
And again, I think that if you look at the most successful innovations ah ah for specifically for B2C businesses, oh they all were successful because every innovation ah resolved a certain customer's problem.
00:51:47
Speaker
Efficiency of the company ah was related to ability to identify this problem before the their competitors would realize that this problem exists.
00:51:59
Speaker
And the first company who identified the problem and come up with a product that addresses this particular need, it takes the most of the market. And this is why it's very effective to, if if if you are thinking about you know ah building a new product for a customer.

Funeral Insurance Innovation

00:52:22
Speaker
So it always makes sense to to look at and the problems and issues which the customer are experiencing. Try to understand which one is the really key one. And if you focus on solving these problems, you would eventually get a really good base for new weather purposes. Right. Thank you. Thank you for that. Another example, we did a project for a company who produces some chemical products for carpets. In the United States, they use carpets a lot as a floor material. With time, a carpet gets fluffy. The customers would like to get it back to the initial state, so it would look much more
00:53:17
Speaker
need. and The company produced very good products for processing those carpets. Customers, they it looked like they did not appreciate the product for some reason. What we found out was that the problem mostly was related to the way how the customers perceptive the carpet itself. Because when you have a fluffy one, your processes with this product, with this chemical product, then the carpet changes its appearance.
00:54:01
Speaker
But you cannot compare to what it looked like before, because you have already processed it. And it turns out that if the customer would have a way how to compare the cupboards before and after, so it would help to appreciate the product itself and to apply it properly.
00:54:25
Speaker
ah and the The product that we proposed was just an app that helps the customer just to take care of their cupboards. So they um just take a picture of the cupboard and be the the application guides the customer which particular products they have to use to clean it, to condition it, and it also demonstrates the effect.
00:54:56
Speaker
how it looked before and how it looks after application of the product. It helped the the company to increase their sales because now customers, they they knew what actually they're paying for and they also ah understand the which product and which amount they have to apply, how often they have to apply, just to get the best result. Basically, we improved the overall value proposition Because now ah from the the product that potentially ah cleans and fixes your cupboard, you get a product where you can see the result, proven result of application of this product.

What's Next?

00:55:49
Speaker
I think I have only one question remaining to you. OK. Georgi, what's next?
00:55:57
Speaker
You know, in in the theory of inventive problem solving, there is a notion of ideality. I think that the next is to making the products that improve themselves. So we do not need to ah you know spend so much effort on innovation and improving ah new products because of the the old products would do it for us. Partially, we have already
00:56:33
Speaker
we can We can see this approach already already in certain industries, ah in particular when certain products IT products. When they collect some data about usage of this product, they're basically building the foundation for understanding the new generation of the product because the product itself actually monitored the behavior of the user.
00:57:07
Speaker
ah collects this data and helps the developers to come up with a better version, right? Why don't we do the same for other products? The same ah applies, I think, for technology for production lines, for example, in for some technological processes. Once we design a process, we always have to think how we collect the data regarding its operation that will help us in future to come up with a new idea or a new product or a new solution. So make make the product smarter.
00:57:57
Speaker
That was Georgii Martsinovskii a world-class inventor and innovation consultant who sets up systematic and predictable innovation pipeline for global brands. Thank you, Georgi, for an insightful conversation. I really enjoyed it.
00:58:12
Speaker
thank you thank you very much hey Thank you for tuning in to the show. You've been listening to The Month and Millions, a practical and inspiring show about innovators and i emergent tech practitioners. Please subscribe to make sure that you don't miss a new episode. I'm Alex Babko and you've been listening to The Month and Millions. Goodbye.