43. Marta Jakab: Aligning Strategy, Innovation, and AI

Marta started her journey in innovation in 1998 as the product manager of the first idea management platform, which became a market leader and served global customers such as Pfizer, Cargill, Belgacom and many more, to which she also consulted on innovation best practices.

Subsequently, Marta moved into corporate technology consulting, then back again into innovation management with a Spanish startup.

For the past six years, Marta served as a Strategy and Innovation manager at NatWest bank, where she implemented an intrapreneurship programme and oversaw the delivery of enterprise-grade AI innovation solutions.

Outside work, Marta is interested in social innovation and robotics.

She currently lives in Edinburgh with her family.

Transcript

Intro 0:00

What's up? What's up?

Simon Hill 0:09

Welcome everybody to season four of the Total Innovation Podcast. As always, I am your host, Simon Hill. Our guest today has spent more than two decades at the intersection of strategy, innovation, and execution, helping large organizations turn ambition into sustainable growth. She works hands-on with enterprise-scale AI in financial services and brings a refreshingly grounded, human and impact-written perspective to the role that AI can play in innovation. She's also recently a contributed to a new book, Shaking AI Without the Hype: How Women Turn Technology into Real World Impact. I'm going to quickly read the opening paragraph to set the scene. By the time you finish reading the sentence, a new A model, a new AI model, a swarm of AI platforms, and a handful of AI-native startups have probably just materialized. While wondering how things might pan out in this hyper-accelerated reality, we could celebrate the abundance of opportunities to innovate that AI has brought about. AI is also entering the practice of innovation. And this chapter will focus on how corporations can harness its power to increase their return on innovation. Rather than examining specific tools, we're going to focus on how AI can revolutionize corporate innovation as a whole. And the chapter builds from there. And with that, I'm delighted to get into this topic with our wonderful guest today. And welcome to the Total Innovation Podcast, Marta Yaco. Welcome, Marta.

Marta Jakab 2:08

Thank you, Sam. I'm honored to be here.

Simon Hill 2:11

It's a pleasure to have you. It's a pleasure to have you. We haven't known each other very long, but I've met you a few times and we've had great conversations built in the build-up today. And we're just going to dive straight in as we always do on this podcast. I know that you and I share a common frustration. In your chapter that I just read a little bit of, you're quite candid about this frustration. It is how innovation is often practiced today. So let's get into that. What do you think is broken and why does AI create a genuine opportunity to fix rather than just add another layer of theater to this innovation work that we strive to do?

Marta Jakab 2:47

Thank you, Simon. I think answering your question, what is broken, um, we need to unpick what in good innovation looks like as a whole. And this is uh what I address in the book itself. So um I dwell on four tenets of good innovation, and from there, um what uh whatever is broken is uh the opposite of those four tenets. So if you don't uh abide by those four tenets, that then uh your innovation will result in theater. And uh those points are strategic alignment, uh, firstly, and for uh I think for me this is the heaviest and and the most important uh tenant. The second is having good processes, good governance, good tools in place. Uh the third is leading with data, and the fourth is um people, talent, and culture. So all these points have to be carefully designed in order for your whole system to work. Now, if you miss any of these points, then innovation uh breaks. And uh that's what I try to bring along uh in the book. And my thesis is that if you take AI and try to apply it willine on in any aspect or in anything that you think it's uh it's interesting, it probably won't work. So it will only magnify the problem of or um just perpetrating that innovation theater, uh, making it worse for yourself. So the idea is first get your house into order and then apply AI where the friction is, where your biggest problems are, or where you need to lean in to really create the value that is relevant for your business or your company.

Simon Hill 4:38

Yeah, I think it I think it's great framing, right? And just to reiterate those four areas, it's to align corporate strategy and innovation. We're gonna get into that in a second, to implement a structured innovation process and governance to lead with data and to mind the talent and shape the culture. Right. I think no one's going to probably disagree with many of those points. And so a lot of it is in the the how and the real sort of on-the-ground experience and practice and frustration and eloquent tears and totally lack of willing willingness to put it to uh to deliver these things. I think this conversation of strategic alignment is one that's often often muttered and uttered, but I just think that's a real that's a real challenge here, right? Like I'm often astounded at how little conversations tend to happen between many innovation teams and strategy teams. I've had a moment where it's the innovation team is learning the strategy firsthand in that meeting with me, and that's not really the way it's supposed to be, right? It's going to be forcing these two conversations together. So you argue that strategy and innovation are inseparable. I agree with you 100%. Yeah, most organizations treat them as separate conversations. Let's just start with why why do you think that is? Why does this thing that feel so blindingly obvious to you and I so poorly executed in many organizations?

Marta Jakab 5:58

Yes, I I totally agree with with that stance that they they should be united, but uh we move too fast on onto okay, yes, we talk about it, everyone agrees. Uh, we know that 84% of leaders agree that innovation is important, that it has to be strategic. So we utter those words, but actually we don't stop to think about their meanings. And I think companies that do um take it seriously and get into it are really the successful ones at innovating and and being out there competitive and and and uh just uh um hitting the top of the charts. And uh it's interesting to know that only 12% of companies um align innovation and strategy. So I think that that that's an indicator that there's room for improvement there, right? So um I'm picking this. Um I would like to stop though for a second to to define what we mean by strategy and by innovation, because often we skip uh that step as well, and and we get into big misunderstandings later. So if you're okay with that, I I would like to dwell on the definition first, and then we can take it to um specific examples, and and then I'll propose an exercise as well to uh sustain my theory that uh they must be very tightly linked, and and then I'll provide the key as well. So I'll leave you on a cliffhanger there. So strategy. Uh I'd like to use Rita McGrath definition. There are lots of definitions, but this one is the one my favorite. So Rita says uh strategy is a central integrated concept of how we are going to achieve our goals, and that how is the um I think the key there. Um this is how simple it is. Was innovation, I'll use your definition because I love it, uh, and it's in your book in a big, big frame. Innovation is something new or improved that creates or redistributes value, it's change that matters. And I love these two. So, how do they come together? So, starting from the strategy um at city level, and and I think uh uh it's I'm going to look at this from the top to the bottom because it's important. Strategy is decided by the um the top of the organization and it's trickled down through the organization. So strategy comes as a statement, usually uh we need to reach our goal by doing X, Y, Z, and by not doing something else. And in this definition, uh if if we then apply it um to each um business function and say, okay, here's the statement, here's the strategy, it's it's the statement. Now take that and translate it into your own business um um to your own business area. What does that mean? How are you gonna contribute to to the strategy? Um and here's where I would like to propose the next slide. So we take the strategy, yes, the CEO, you take the strategy as a statement, and I ask my um manufacturer, let's say let's take the example of a car manufacturing uh company. So we unpicked the strategy and and we asked the um production manufacturing um function, how are you gonna um execute the strategy? What does this mean to you? My statement. And I'll give an example of the statement to bring it uh down to work. So um this is the imaginary strategy of a car manufacturer, and I'm I'm reading it because I asked uh Chad GPT what would be a good um strategy statement for a car manufacturer. And this is one example. Our strategy is to lead the mid-market electric vehicle segment by producing reliable, affordable cars with best in class battery efficiency using modular platforms and vertically integrated manufacturing while avoiding luxury customizations and low-volume specialty models. So that's a multiple there. But if you take this, put it on the wall, and ask, okay, manufacturing, what does this mean for you? And they unpick it. So now I ask them to draw two circles, or let's draw two circles, imaginary circles, by side by side. And in that, what it means for you, in that statement, what this means for you, we ask, do you know how to do this part? Yes, then we put it to business as as usual. I don't know how to do this other part, I put it into innovation. I have two circles. Go to marketing, do the same. What does the strategy mean to you? I have to do ABC. Do you know how to do it? Yes, business as usual, no, it goes to innovation. So this is how you you uh basically create a map whereby the business as usual is what you do, it's your core. You know how to do it, that's where your strengths lie, and and that's what you should continue to do. But in order to do the rest, you have to innovate. Innovation is is your tool or your vehicle to attain that goal. Otherwise, you will be doing what you're doing now and you won't get there. So that delta is your innovation, and and this is how they they are linked together. So without innovation, you only do the part that you're doing today. You you can do it a little bit better or a little bit cheaper or a little bit faster, but you will not get to that goal, which is probably more ambitious than that.

Simon Hill 11:59

And um, I stop here in case you have uh questions or you want to uh pitch into with with your own view of um no, no, that's I I I know I know how your mind works, so I'm glad that we kind of walk me through the this with a with a real with a practical example as well. And also, you know, we like to keep things in this hyper accelerating, hyper-complex world as simple as possible, right? So I think where you try and find simple definitions, the how and the you know, the certain versus uncertain, do we know how to do this, yes or no, is super important. You describe strategy in part of your conversation as something that pushes down and innovation as something that pulls in. Just talk to those two definitions within the context of what you just gave as well.

Marta Jakab 12:45

Yeah, so um strategy has to trickle down because your whole organization has to lean in to execute that strategy, otherwise, it won't happen. So uh if that that's uh the natural and the logical way of doing things, whether companies can achieve this or are achieving this, um it's it's another question, but that should be the goal, right? And innovation, uh you have to pull it in at the level you you are at. So, for example, at um at C suit level, innovation means something different than at your level if you are working in a warehouse or if you're working in marketing, it you always need to calibrate it to what is your role in achieving that strategy, what is your delta, what what level your that your delta is. And to put this in practice, I I think um, and continue that uh train of thought about uh how you you uh land or or link innovation with your strategy. If you start mapping all these deltas, how you do this, how you do that, you you get to a portfolio of um challenges, problems. And and here's my my favorite topic, which is problems, but I'll come back to that. So I think this is how you pull it in. So I need to innovate. That that's that's how I build my innovation uh kind of plan strategy. And and I would also go as far as arguing that if you do it this way, so if you all always consider that innovation is is your vehicle to achieve your strategy, then your innovation strategy will almost write itself. I say almost because you need to do something else, but at least you have this map of problems. I don't know how to do this, I need to figure it out. And so the the reason I I like to uh phrase these kind of deltas as problems is because problems are have have a structure that avoid misunderstanding. So I know it's a contentious word, but if you call it opportunity, then you might slip down a slippery road because everything is an opportunity out there, everything can be an addressable market. But if you formulate it as a problem, you have the formula. We have a problem that affects X, Y, Z or number of people in such and such area, which, if solved, would create this amount of value, if carried on, will uh create this amount of damage. So you can quantify. A problem is something you can quantify, you cannot avoid. So that that is my way of building up this portfolio of problems that will feed into the innovation plan or execution.

Simon Hill 15:51

Yeah, there's a lot, there's a lot to unpack there, and I want to dig into this topic of problems and opportunities and challenges and needs. And I think one of the one of the I was gonna say problems, maybe it's opportunities one of the challenge, one of the things that we struggle with in all of the things you've just been talking about is language and understanding and storytelling to a degree, right? You know, it's not it's not hard for anybody to understand, and I think that you know most people should agree that there has to be an intrinsic link between what we're trying to do, how we're trying to do it, and what we do to create new value, right, as we go forward. Yet you get that stats up front, which is I think 12% of business business leaders, um, which means 88% are not achieving that. 88 out of 100 companies are not achieving this thing that on paper looks organically obvious, right? And so there's clearly a misalignment somewhere, and uh it could be in the telling of the how and the and the and the narrative of the of the um of the strategy. Sometimes hiding corners that don't necessarily get out into the real business, but they may be sitting there back on the table, disagreeing with me right now as I listen to it, but something's happening. And innovation teams are often similar, they tend to be slightly disconnected from the core and slightly away from the other functions. And so you've got two functions that are somewhat disconnected from the day-to-day operations, working on you know the how of the future and the what of the future, if you like, but not communicating with each other. I mean, maybe there's the answer to that problem, but the simple answer is we'll just talk, right, and understand what people are doing. And we have 88 out of 100 in 2026, right? This isn't 1972 or something, this is 2026. There's no reason for us not to be able to find a mechanism to assimilate that data. We're going to get on to more topics around data and I later. So what why? What do you think is the is the fundamental problem that's going into that piece with this, right?

Marta Jakab 17:59

Yeah, so we're we're getting meta with this. Uh, what's the problem with the problem? Um, yeah, so I I think the answer uh I I would like to drive us back to uh to your book and and your theory about expected value, right? Uh you you have a brilliant formula there, and and um as I said to you earlier, uh I I was wondering how could we live without it so so long, so uh three decades in, and and we uh only now we we figured you figure this out. So in your formula of expected value, because that's what we measure, that's what we want from strategy and innovation, right? To to produce value at the end. So in your formula, you say expected value is confidence times predicted value times times sensitivity times strategic fit. So if your strategic fit, if you're not linked, if that number is zero, then guess what the final number would be? It's it's a simple uh multiplication. Anything multiplied by zero is gonna give you zero. So the expected value, for sure, it's given. And I think um this is where you you have to to really be intentional about making innovation part of your strategy, because otherwise it it will produce that zero value, it will result in theater as we've seen it for so long.

Simon Hill 19:27

Yeah, I don't know. I appreciate all of your support and feedback on the book. Um, you know, it's very humbling. I think if you and if I unpack that that um equation in another way, what it's trying to answer in its composite parts is in the first part, is it a good idea? Do I have confidence in it? Do I think it can create value? The time sensitivity is it a good idea now? And then the final part of strategic fit, is it a good idea now for us as an organization? And I think that potential disconnect is what we're talking about here, is there's lots of great ideas, but if we haven't got the how aligned to the what, then it can be a great idea for somebody else, but for not for not for this organization. And I think that that 88 out of 100, or you could call that $88 out of every hundred that's being wasted, is what it is, really, I think, right? On theatre, is it's not through lack of effort, want hard work or anything else, it's through this absolute disconnect from what from what you're talking about. Um, and I you know I think that's what we're both fighting passionately to try and to try and break that gap down. We think about that then in terms of you know, you've got your problems, right? And I I have no issue with the word problem. I think there are different parts of the value chain to help us to get to the whole part of like, is it a good idea now for us as an organization to double down on and hopefully go and deliver value from there's lots more to it, where the book's this big and not and not this big, but um but but it's not about promoting that really here, it's about thinking about what we've got this push down of the of the what and the how, and we've got the pull-in of the innovation teams and it's and it's just disconnect. How do we, with that set of good problem statements, and it's and it's innovation strategy that's now started to define itself, and these are bigger functions for many of these organizations as the data shows us. How do we start to turn this into real value? And and are there any examples that you can bring to bear where that we've got all these pieces laid out, and I think many organizations have said that once I have those things, I think I know what the strategy is. I think I've got a good innovation strategy, but I'm still in the 12%. I'm not in the 12%, I'm in the 88% of businesses, like how and why, even though this has all started to come clear. And I guess to look into this, what role do you think that the AI might be able to play in any of this? Or is it just another another shiny object that that we think can help fix the fundamentally broken processes that we've been talking about?

Marta Jakab 22:00

Well, I I think that first of all you should fix the broken process and and then pull in AI. But yes, AI has a role and it can help in in many ways. First of all, excuse me, if you have the problem, starting again from the problem, you can assess whether it's aligned with the strategy. Hopefully, if you went in in the order I explained, so down from strategy to all those problems, then you don't have a problem. So you've done your exercise, you know that you're linked with the strategy intrinsically because your problem statement comes from there. Now the next point to decide is how am I going to solve this problem? And we know that there are so many ways in innovation uh to address a problem, but I think in many uh companies, uh this the way they address problems or the way they do innovation is already fixed. So either you have a big um internal innovation program uh and and uh not much of the external view. So you try to address the problem with what you have. And I think that's a point where where AI could help uh potentially. So instead of um addressing your problem with with the tool at hand, how about thinking about what what would be the best way or the best levers to address that problem? Is that internal uh innovation, entrepreneurship, is that open innovation, uh, or is that by acquiring a startup, or is that the uh client uh um venture clienting or um a combination of those? So it it starting with with uh looking in into different ways of solving that problem is is a good uh good way of addressing it, I think. Um I don't know whether you you agree or disagree with this, but uh I think every problem has its best match of of um innovational lever to to pull.

Simon Hill 24:16

Yeah, I I I definitely do think that. I also think it's getting cheaper and cheaper to pull those levers. And so with the right processes, and we'll get on to that a little later, you can do many of these things in parallel, right? And I think the cost of experimentation is coming down, the cost of failure should follow it because we can pull risk forward earlier into the process and learn faster and fail faster. Um, but we've got to get better at killing things as as well and recognizing when we've got strategic misalignments, which can happen very quickly, right? You know, I've got lots of examples of things that started with strategic alignment, but the strategy shifted. And we have to get good at recognizing that if we're in a boat going this way and everybody else is going the other way, that we should either have to turn around or we have to stop, right? And we're not necessarily that great. In many functions in the business, innovation just gets this very pointy piece of analysis because it gets so much uh capital thrown at it that's you know, that if it doesn't drive value back, it's very tangible, right? In in terms of in terms of the work that it's done. Can we get a little bit like more tangible in terms of some examples then? So, first of all, you mentioned problems. I know you have a strong belief in these. Let's talk about what you've done within the realm of problems inside your professional life, and you know what, what what do you do, right? I think it's one of the initiatives that you've got. And then maybe you can share some examples of how you've gone from problem to value in this in this world that we've we've been talking about, strategic alignment as well.

Marta Jakab 25:45

Sure. So um I would like to lightly touch on on something I experimented with um in in the past during COVID, which is uh I I created a problem marketplace because uh I had a challenge. So we were trying to do some grassroots innovation, and we knew that uh um grassroots innovation wasn't uh the leadership's favorite. So, but we wanted to do it anyway. It was COVID and and we were trying to do something meaningful. So um instead of trying to get uh, or in a way of trying to get the leadership on board, was uh instead of pitching ideas to them, uh, was um how about you give us your problems? Because uh you you probably have problems. So um that that's how we warmed up the conversation, and and also we didn't call it innovation, we we called it entrepreneurship. So I started a mini entrepreneurship program as a side of desk activity. So by doing that, um leadership started to realize that hey, uh, if I have a problem and and these guys are are happy to solve it and they have resources, I I get a cheap way of getting my problem solved. So that that was one example of uh um that I tested how how this problem, uh starting with a problem and creating a marketplace works. And and uh that worked, uh it was nice, but then uh I moved on and did something else. But another way, uh, and and this is where it gets interesting, of testing uh or bringing in AI, um it was through a simulation. So uh the last summer in 2025, I I attended an immersive uh training course for innovation leaders, whereby uh the guys at uh strategy quest it was called, uh they simulated a whole uh C suit um uh and within a company. And the the challenge, the quest was to create a five-year strategy by interacting with AI agents who were all this C-suit uh simulation. Um and it was uh really eye-opening because that that's where I realized that uh um I missed so many things in in my career. Uh I had so many blind spots because it brought out this uh perspective of of interacting and trying out and failing and doing it again without any cost. So you you could test your assumptions, you can test your innovation strategy live in in real time, and and you you would get immediate feedback. So this is where AI becomes magical because you you interact with these uh synthetic personas who have their agendas and and you you put your ideas out there and they just hammer you and and then you realize, oh, I haven't considered that. So that was actually interesting. So I I tested this approach that I I talked to you about from uh let's unpack the strategy uh and and cascade it down and uh create a tool. So I I put the assumptions of these tools, we have this platform, and this is how it works, and this is the marketplace, and this is how it works. And uh I created a plan, we created a yearly plan every every week. So, in the end, that that's how I I have this confidence that it might work. Obviously, if you want to try it out for real, you would spend several years to to see whether it works or not. So that was the interesting part of using the AI.

Simon Hill 29:35

Yeah, I think there's something else to unpack in all of that. One is the simulation piece, which I you know, it's quite hard to simulate real life unless you do it in real life, right? But actually, now we're finding there are better ways of doing that. But but I think also on the flip side of that, and maybe you can talk to this, maybe you can't. I think that if you ask a room of people what their biggest problems are, or what their problems are full stop, our brains are not, unless we've been thinking about something, our brains are not that well wired to know the answer to that question. You think of something that comes to mind, but actually it's something that the the computer, the computer's better at, right? Like it can see huge inefficiencies, it can see gaps in the market. That once you stop and think, you put yourself in a room like you were just talking about, or a conference or whatever, and your mind frees up a little bit, and you hear outside stimulus that's correlated or uncorrelated to the things that are frustrating you in your own mind, the fog. You start to see these things, but you don't capture them at that point in time or correlate them back to organizational context, they're kind of gone again because the busy day gets in the way and you don't really know the answer. And I think that I love the idea of a problem marketplace, but I struggle with the idea of it because it ends up often being the thing that's bothering you right now rather than the thing aligned to strategy, as we were talking about earlier, or the real problem, right? And there's a lot of work to do to get under under the skin of the real problem when it's aligned to the real strategy, to align to the real need to get to the real value, right? And I think that yeah, I I believe I I think my back hope that that the that the age of of data and big data, which we can get into a little bit more in a second, that we're coming into, is actually going to lift the veil on quite how many problems to opportunities that there are to have meaningful value creation because we've created these highly inefficient sets of processes and ways of working. Um and the solutions lie just here, but we don't quite see that that that problem space in the right in with the right level of clarity yet. Do you do you agree with that? Do you do challenge me on that? Do you think it's you know there's this optimism in the future if you do agree?

Marta Jakab 31:49

Yes, I I do agree. And and uh I I would like to highlight that um I I wouldn't recommend to go and ask people what their problems are. I would go uh down from strategy. So what what are you how are you going to implement your strategy in your area? And that's where you do that exercise of I know how to do this part, but I don't know how to do the other part. So that's uh that's where the link stays. So uh just asking for problems is is just doing a little bit of problem theater, if you will, because people will bring all sorts of uh things that they struggle with. However, I think you have to have a little bit of of that as well, because uh those little problems that your say frontline um employees um have and and and they reveal, those might be the weak signals that it's time for you to jump the S-curve, that something is happening, uh, that your customers are showing some uh tendency to do something differently, and and those signals might be important. So I think a combination of both listening to your workforce and bringing in the strategic problems uh could uh work in a in a nice blend. And AI is really good at at quantifying, qualifying those problems. So it would know what is your biggest strategic problem, uh, what the urgency is. So it could suggest, and at the end of the day, you as a human have to say, yes, yes, I think this is my biggest problem, let's address that. So prioritizing, it can suggest priorities and it can bring in the the risk, the the cost, uh it can suggest uh according to its own uh data, underlying data, uh what the the uh the urgency or the gravity of the problem is. And the more data you feed in into it, if you if you have this uh system that uh helps you with with your strategic fit, then uh if it's uh uh personalized to your company, to your circumstances, then that that kind of suggestion and problem assessment becomes better and it it can lead you to the solutions.

Simon Hill 34:14

Yeah, I do like I like this topic of synthetic as well. There's lots of you and I could probably unpack on that. We're gonna I'm gonna move us on from the strategic, the alignment between strategy and innovation. Um, it is the meat of this conversation, but it's only one of your four points. And so let's let's spend a little bit of time on each of the other three. So the next one is implement a structured innovation process and governance. I think that's that's again one of these, it's a great statement. Lots of people will be trying to do it. So we've got strategy and innovation aligned, right? Our innovation strategy has almost written itself, and and AI's helped us to tidy up the edges of it as we get there. What now, right? What does this next bit of the process need to look like in terms of a you know a nice streamlined innovation process? And what typically, especially inside large organizations where you've been working, tends to be the things that that bring friction in or bring complexity into the process. And how do we work around those?

Marta Jakab 35:12

Yeah, so you have to have the structure to enable this innovation to happen on a continuous basis, and and also you have to oil that machine to make it uh efficient. Um to ensure that that um it works smoothly. So um let's imagine the the process and and and governance and tools as as the production line, uh, invisible production line of your innovation activities. What you have to ensure is is that you know what happens at each stage of the life cycle. So where problems or or solutions come in, where do they go? Under what condition? Uh um entry criteria, exit criteria, go to the next station. So if if we imagine a production line, each station is a a part of this life cycle, um, things get handed over, how do they get handed over? When, under which conditions, that's your governance. And how do you ensure that that handover of uh, say again with the car manufacturing, if if you're putting together uh the the doors and the wheel and and all the other components, how do you make sure that there are no um points of uh no blockages on on that line, that you don't get accumulated a lot of doors in one place and and the car is emitting the doors in the other. So you you really nicely describe it in your book, the governance that goes around it um at different levels and and depending on on the um nature of uh your activities or solutions is crucial in this setting. And then the tools to make that work, to to make this uh machine work automatically as fast as possible, as cheap as possible, um, and uh continuously improving and and uh uh feeding back on itself to improve further.

Simon Hill 37:23

So how do we how do we know then, do you think, whether that process is actually working? Because we know that we're often quite good at experimentation phase, or at least we're good at generating lots of ideas, and hopefully those ideas are aligned to a need that's aligned to a strategy that's you know to things the business wants to do. But we're not particularly great at getting from those early experimentations into real value, right? Sort of delivered into the core or replacing the core or whatever. That's that that that pathway from this is great to actual value being created and scaled value being created. I think that's where the 12% do well and the 88% do poorly, right? Is that it's not upstream, it's sort of lesser midstream and downstream that we're that we're really struggling with. And one of the one of the voices in the back of my head is back to my boat analogy, is AI might help us just to grow faster in the wrong direction, right? So it might just help us to go further and further away from what we should be doing when we need to just kill things faster. But also, but it could help us to get to value faster as well, if we make sure that we know what the business is doing. And part of this comes from this communication piece again, is like if you don't really understand what you're being told and you don't really understand what value you're disrupting or creating, and it's not aligned to the near-term incentives that you're you know rewarded for, then who cares, right? It's like nothing's gonna change, right? Someone cares somewhere, the the poor innovation person doing all this work. But otherwise, how how do how do we know? And so I think this is where data starts to come in, right? And it weave us into the third part of your of your piece, which is data. How do we start to use data to get beyond the of course we care? And of course, this is like we want to invest in future value. That's the definition you read out earlier. You've taught me this is your strategy. And so, how do we help? How does data start to help us? And how do we get beyond the black boxes that we know exist across organizations, particularly when it comes to innovation data, which isn't this neat, tidy set of data, like a set of sales data or marketing data might be? How do we start to bring that to life for the innovation value creation that we're trying to get to? A nice small question as we come towards the end of this, Martha.

Marta Jakab 39:43

Yes, of course. So I I think um it you have to do it uh through continuous monitoring. So what you you measure, but first of all, you have to to design your KPIs. What you want to measure. And that starts with the question: where are we going and how do we know we we are getting there? And how do we know we have to stop, which is the the killing part of it. So um KPIs can can be set up in in different ways for different organizations, but I think if we go by your expected value, I I would recommend that as the strategy for your data. So make sure you you know you measure at every single point how your expected value is doing. So are you moving, is your trend upwards or are are you falling downwards the uh the hill and and you you you better stop now because if that trend uh points downwards, if you stop now, you can reshuffle your resources and and invest them in into the next problem or next activity on on your line, which is prioritize, obviously. So it's a good way of monitoring the the health of your activities and making sure that uh your money uh gets the most out of uh uh what you're trying to do.

Simon Hill 41:00

Yeah, I and I think I think there were there are battles being won here as well, right? Hopefully you can see that inside the place that you're working now, that there is an understanding that data underpins everything, that the innovation data set is a complex data set, but actually it's not a it's not a new data set, it's just a different lens on an existing data set in many cases, right? That as we've said needs to be aligned to things that the organization wants you to care about because it believes that is the greatest path to it's creating value for everybody. Um but there's still a huge hurdle to go on all of that, and I think there's a lot of training and skills that need to come in to understanding that innovation isn't big and scary. In some ways, when I hear people say, Well, we didn't call it innovation, a bit of my heart sinks again because I've had these existential battles, right? I've stopped using the word innovation and and I've I've run as far away from it as possible and use different language and found myself coming back to it over the course of the last little while, I guess, underpinned with the concept of value as well, but very much recognizing that the two are bed fellows, right? Innovation is the vehicle by which we create this new value. And I think that rather than it being, you know, the poison pill, we need to find a way of upskilling and training people in all the different tools of innovation at a much broader level, right? One of the things that I've spent my time on in the last year or two is really trying to create this, you know, let's try and make the 99% a little bit better in innovation skills and understanding rather than the quite elite level of innovation that happens to a very small percentage of a very small percentage of business leaders and innovation practitioners because it's a ground swell, I think, right? It's this grassroots piece, it's this mindset shift that needs to come through. But maybe we can just talk about that. And I was at a business school last night talking about how I think that one of the big advantages of this new industrial era that we're moving into, underpinned by artificial intelligence and automation, is it's a great level, right? It actually puts a lot of people, irrespective of background and financial circumstances and education and everything else, at a much more even playing field because knowledge sits here, wisdom is now how you apply that knowledge, but we're still run by organizations that were built in the you know in the quarter area and and and and and others that think that you know and it shifts very slowly, right? Very, very slowly. And so leadership is going to move very, very slowly, and disruption is going to happen elsewhere. So, how do we view that, right? You know, your your chapter and your focus comes from large corporates. Like, how do we do that reskilling and upscaling that needs to happen for this you know innovation at scale in the age of AI? This is our big closing question of what does this need to look like, and then we'll come into a conclusion.

Marta Jakab 43:52

Sure. Uh and I think you you you you said something there that that uh made me part my my ears, uh, which is uh leadership moves slowly. And I would like to drive this back to a statement that uh uh Dr.

Simon Hill 44:08

Nadia Jeksimbaeva is uh supporting and and trying to to open uh the consciousness of of the sea suit uh about the need of reinvention so I think we need to reinvent how how we do innovation, how we do leadership, because uh those quarter rules and and the tools we use from uh that era were valid when uh when your cycles were 75 years but now um i I think uh uh Nadia showed that uh that cycle is reduced to an average of three years so as a leader how how are you prepared to jump the S curve every three three years if you're not prepared to bring in that innovation muscle that will help you with your growth with with doing things differently with adapting to that uh uh that need to reinvent uh and and reinvention is is about your business model let alone the the way you do things done on a daily basis so that's the big challenge and I think uh if uh leadership comes to the conclusion that yes we we need to reinvent ourselves that often then they probably will embrace uh this the mechanics of of bringing innovation into the picture yeah I I hope so I hope so and I and you know you cited a number of good friends mutual friends across this who I think do a fantastic work in all of this um I still feel like there's great voices shouting from you know from from the from the edge quite often and the core is this very very resilient concrete impacted like part part of the business that's very hard to shift but if we are I'm gonna do an episode later in this series with um Alexander Osterwelder on business model innovation and I think that we are entering a phase of probably the the greatest business model transformation that is going to happen reinvention will be the word that comes to the fore but you know I think in the you know to to think about that in terms of an exponential change or an exponential shift it's going to whack a lot of businesses not leaders businesses over their head very very quickly at some point in time in the next 10 years or so I think and if we're not preparing for that then it could be quite savage for a lot of organizations. But it's a huge period opportunity as well right and really trying to balance that that piece maybe you can well you can round us off and it's been a great conversation with um with some examples right of of what you've done. And you mentioned earlier grassroots innovation maybe you can just define that in your mind for people just in case they're not familiar with the term but then maybe you can give me an example or two of uh of work that you've done and then we'll draw into a conclusion.

Marta Jakab 46:56

Yeah so grassroots innovation I I don't have a written down uh definition but it is basically innovation that comes from from your employees so uh there's a theory that every employee wants to work uh make sure that uh their workplace is is good is and is getting better so there's this uh uh volunteer kind of of uh predisposition to contribute to to your business to make it better and capturing that uh uh it doesn't only mean that that you capture free value because uh their their intelligence knowledge is is there for you to to tap into it also means that they get more engaged because it provides a meaning so so that uh if you can bring that together uh you create a a good uh kind of environment for people to want to contribute and and uh that contribution can um um add add to the the um mechanics of of creating value so uh an example of of that is uh and again this this was in in the simulation we tested this out was uh asking people uh at the front at the front lines uh what are the friction points they notice so uh in instead of asking them for ideas we again ask for friction and uh it turned out that the um these people frontline employees are happy to to share those observations because they feel uh listen to they feel noticed they feel they are important so just by asking those questions you involve them excuse me and and nowadays um as we see in in startups uh you you can see a one person startup with with ai so if you project that into an organization one employee could do uh a huge amount of value creation uh with ai so if you enable that if you allow people to bring in uh their knowledge their talent and if they use ai to do that know how they how to use it then you will get a a a mini startup within your organization from every single contributor who who uh wants to to do this grassroots innovation yeah and as I said earlier I'm quite passionate about this idea of trying to open it up to the many rather than the few um particularly not just because you know there's lots of people that want to get involved in that I think there's some very nice examples of that being the case you know lots of organizations um are more than just a job for the for the brand and the thing that people turn up for right whatever the functional job that you do you kind of want to make your place of work as you know as as vibrant and future resilient and resistant and exciting and innovative as possible.

Simon Hill 49:55

And so putting people in small boxes defined by a very narrow job description that doesn't allow you to get involved in future value creation seems like a missed opportunity in many cases. But that drum's been beaten many times and I think we're we're we're getting we're getting better we're getting better at opening that up we've just now got to get better at aligning it to things that matter to the organization um which is one of the failings I think of too many of these sort of grassroots level um initiatives that you um that you talk about. I think I'm gonna wrap us up there and maybe I'll ask you to try and synthesize your thoughts into a a closing conclusion to warm you up while your brain raffles on this as well because I can I can step in between I'm gonna ask you to if you've got a book that you recommend and this is not a warm-up you're not gonna recommend my book I know you're a big champion of it but another book that's not mine that you think you that you found very useful or valuable to other people I didn't warn you of this in advance it's uh it's a it's but if you've listened to other episodes you may know that I do it um but if you don't have one it's fine but if you do I think it's a great recommendation for people but just quickly how would you synthesize your thoughts from everybody and then we'll we'll ask the question of the book.

Marta Jakab 51:06

Sure.

Simon Hill 51:07

I would like to add something to to what we discussed here that which is if you make um your process transparent if you make your challenges transparent your problems transparent to everyone and you are open about how you go about uh solving those things then then uh the business uh people who who who do their uh business as usual and the people who want to innovate they will come together because uh they will see that they all work towards the same objectives and towards the same meaning so they see how and where they can contribute to it all excuse me and and and so if if you want to to orchestrate it in in a way that it becomes a symphony you have to make this transparent you have to to make everyone see where the value is created and and if you can show that value the realized value as as you call it in in your book and as we know which uh is what matters at the end of the day then everyone is is is very conscious of their role they have to play in this i yeah I agree and I think the more we can democratize these things there's real evidence to suggest that people are quite often nervous about opening these things up and that nervousness is massively misplaced um and almost unilaterally creates more value quite often boiling away anything that might have been perceived to be sensitive or risky because it's not particularly useful right in in in many in many instances it gets in the way of governance and politics and risk. And actually and actually it doesn't taking it away taking away the sensitive stuff often doesn't mean that you can't still get to value. In fact quite often it removes the noise to help you get to the signal of what you're trying to do. So that's a marta thank you and what about the book do you have a book of recommendations for people that's not mine well uh you caught me unawares but I I always tend to to recommend uh Elvin Turner's book Be Lad Zombie um because it inspired me um the strategizer series are also very good so those are the fundamentals and and uh there are lots of flavors and and lots of topics so those are my favorites yeah and I I'm a I'm a voter for Elvin's book it's fantastic and I think the idea of you know of it's a bit like my boat rowing off in the wrong direction right how do we kill the zombie project the ones that are eating resources and and other things and try and get into as we've said things that are strategically aligned or value creating. So listen thank you Master thank you very much uh this has been a great conversation grounded in practical and very timely advice for lots of people built on as I said plenty of experience and the book's great um as I as I mentioned as well um so congratulations on that chapter and your on your work that you've done. I think what really stands out from this conversation is that whilst AI is moving fast, the path to value hasn't changed nearly as much as the hype suggests. Alignment discipline data and people still really matter the fundamentals of of of what things are AI can simply amplify the consequences of getting these things right or wrong right there's a lot of opportunity in there to get things right or wrong and we have to keep reminding ourselves of that. I think if there's one key takeaway it's that solving the right problem is still the most powerful starting point for innovation. Thank you for reminding us of that um the problem of problems as we said and when you combine that clarity with the intelligent use of AI that the potential for real impact is enormous right and that's the opportunity side of the AI coin I think that we're working on so Marta thank you very much for joining me on this episode of the Total Innovation Podcast. It's been an absolute delight talking to you and to everybody else listening thank you very much. I'm sure you can find Marta online on LinkedIn and I guess that's the best place for people to connect with you if they're if they're interested always happy to share an opinion on there. And for everybody else remember this is just one of many exciting episodes that we've got lined up in season four of the podcast you can go back and listen to all the three previous seasons beforehand and wherever you pick up your podcast hit subscribe and I'll see you again in future weeks. Marta thank you once again.

Intro 55:23

What's up uh uh uh uh what's up uh uh uh uh