← Scrum Master Toolbox Podcast: Agile storytelling from the trenches
Scrum Master Toolbox Podcast: Agile storytelling from the trenches
BONUS: Why Large Organizations Struggle to Innovate With Elliott Parker
00:44:06
BONUS: Elliott Parker on Breaking The Illusion of Innovation and Why Large Organizations Struggle to Innovate In this BONUS episode, we dive deep into the paradox of modern corporate innovation with Elliott Parker, CEO of . Elliott shares his...
Loading summary
Transcript37 lines
- [00:04]
Vasco
Hey there, agile adventurer, just a quick question.
- [00:07]
Host
What if, for the price of a.
- [00:09]
Vasco
Fancy coffee or half a pizza, you could unlock over 700 hours of the best agile content on the planet? That's audio, video, E courses, books, presentations, all that you can think of. But you can also join live calls with world class practitioners and hang out in a flame war free and AI slop clean slack with the sharpest minds in the game. Oh, and yes, you get direct access to me, Vasko, your Scrum Master Toolbox podcast. No, this is not a drill. It's this Scrum Master Toolbox membership. And it's your unfair advantage in the agile world. So if you want to know more, go check out scrummastertoolbox.org membership, that's scrummastertoolbox.org Membership. And check out all the goodies we have for you. Do it now. But if you're not doing it now, let's listen to the podcast.
- [01:12]
Host
Hello everybody. Welcome to a very special bonus episode. And for today's bonus episode on the topic of innovation, or maybe we should call it the Illusion of Innovation, we have with us Elliot Parker. Hey, Elliot, welcome to the show.
- [01:27]
Elliot Parker
Vasco. Hey, great to be here. Appreciate you having me on.
- [01:30]
Host
Absolutely. So Elliot is the author of a recently published book called the Illusion of Innovation. He's also the CEO of Alloy Partners where he helps corporations and universities launch startups through a venture studio model. And we're going to hear more about that in a second. He's also a former innocent consultant and entrepreneur and he's passionate about bridging big companies with startup ecosystems to unlock real innovation and long term growth in an increasingly distributed world. So that was a short intro. Elliot, before we dive into all of the details, tell us a little bit about the origin story of this book. What was the moment, maybe an experience or a story that you kept going through that led you to write this Illusion of Innovation book?
- [02:19]
Elliot Parker
Yeah, it was probably death by a thousand paper cuts, as they say, that you don't want to write this. I think we all have a sense that our large institutions, whether their governments or corporations or universities, whatever they might be, are somehow less capable at dealing with opportunity and challenges than they once were. We hear stories of, you know, how it took three years to accomplish some big feat 100 years ago and you could never imagine something like that happening today. There's a great story here in the us The Golden Gate Bridge. It's a beautiful bridge in San Francisco, California that took, I think it took three years to create the bridge Originally, and then recently they wanted to put a safety net on the bridge. And it took seven years to add a safety net to the bridge that took three years to build. Something's happened where our large institutions just don't run the way they used to. And so it was that frustration and years of working with large corporations, specifically trying to help them be more innovative, and seen lots of failed attempts. Nothing seemed to work when it came to innovation. And so I, out of that frustration, wanted to write a book exploring what's going on. Why are these institutions less capable than they once were and what do we do about it? And the answer was somewhat ironic, actually, and unexpected. We can get into this if you want. But the answer was these organizations are actually better managed than ever before. They're just often optimized for the wrong things. They're optimized for safety, predictability, and in the case of corporations, capital efficiency. And that makes it really hard for them to do things in an agile way, to do things quickly, to do things that don't generate near term return on invested capital. And that's a real problem.
- [04:14]
Host
Let's talk about a little bit because maybe not all of our audience understands what you mean when you talk about capital efficiency. So break it down for us in simple terms. What does that mean in practice and how does it affect the decision making making in these organizations?
- [04:28]
Elliot Parker
Great. Yeah. So corporations are focused on making profit and doing so in the near term. We see this in the kind of the results of companies over the last few decades. Collectively, we've decided that the most important metric for determining the success of a corporation is return on invested capital. Meaning I put a dollar into a company, I get $2 out or whatever it might be. That's the most important metric we use for determining how successful a company is. And when you optimize around that metric, it makes you do certain things. It makes you make decisions that may be good in the short term, but not in the long run. Let me give you an example of this. Return on invested capital has got a numerator and a denominator. We're looking at the amount of assets that we're using to generate a return in a company. Well, one way to spike your return in the near term is to have fewer assets on your balance sheet. And so you might, for example, close down a factory, which would be a decision you'd make to boost your return on invested capital. Return on assets. You close down a factory, you have fewer assets on your balance sheet, produce a return. Now that's great. In the near term, because it does make your numbers higher. But in the long run, that factory may have been important. And we see this in organizations. Think about global supply chains, how good we've gotten at managing supply chains. Look at supply chains and companies, especially pre Covid, extraordinarily efficient. Everything shows up from around the world just on time, very, very little waste in those systems. And that efficiency is actually, while it seems good in the short term, is actually really fragile because one piece of that system breaks, like during COVID the whole thing comes crashing down. So what I mean by capital efficiency is this idea that companies are prioritizing profits over all else, and profits specifically in the near. We see on corporate balance sheets right now, there's more money on balance sheets, more cash on hand than ever before. Within the last couple years, something like $7 trillion on corporate balance sheets. At the same time, we see large companies going out of business faster. On average, they're making more money, and they're also going out of business faster, which seems like it should be the opposite, right? You make more money, you last longer. Though that's not true, because these companies are focused so much on producing profit that they become very fragile. They're not very resilient in the face of crises.
- [06:58]
Host
That fragile idea is actually very important because very often, and I'm sure many of us have heard this, we need to be more efficient, perhaps not relating to return on invested capital, but other type of efficiencies. But efficiency is a word that is all the time in the corporate lingo. But of course, the side effect of that, the reverse of the metal or reverse of the coin, is that of course, by being more efficient efficient, you're also less adaptable, more fragile. Right. And I wanted to ask you about this. Is this like one of those beliefs that you held earlier in your career that then changed later and now you think about it completely different? Specifically in the area of innovation leadership strategy, what is one of those beliefs that you held early in your career that you have changed completely your view on?
- [07:52]
Elliot Parker
Yeah, I've changed my mind on this completely, actually. Yeah. So early in my career, I began my career working in corporate innovation, trying to take intellectual property out of large companies, spin it out in the form of joint ventures and licensing deals and startups and things like that, and then over time, worked in corporate venture capital. Years ago, I spent many years working. You mentioned the beginning of a company called Innosight, which was a consulting firm founded by Harvard Business School professor Clayton Christensen, who came up with the idea of disruptive innovation, wrote a book, a famous book called the Innovator's Dilemma, A.
- [08:30]
Host
Favorite here on the show, by the way.
- [08:32]
Elliot Parker
Oh, good. Yeah, it's wonderful theory that once you recognize it, you see it everywhere. This idea that companies, as they seek to serve their best customers in ever more profitable ways, leave themselves exposed at the low end for new entrants to come into their markets with good enough products at a cheaper price, grab a foothold, and then move up, market themselves and displace those incumbents. Right. So it's a pattern we see all over the place. And for a long time, the answer was Clay wrote that book in 1997. And for the last nearly 30 years, every corporation in the world now has set up an innovation team as a way to respond to this Innovator's dilemma idea. And in every case, these teams are given some form of a budget allocation, some degree of separation from the core business, and told to go innovate. Go identify opportunities for new business models, products or services that the corporation should pursue as a way to drive fundamental transformation in the corporation, ensure that we can endure for a long time as a company. Every corporation does this. And I used to recommend it. I used to be a part of these teams. These teams. I will caveat what I'm about to say by saying that these teams are extraordinary at driving core and adjacent innovations, meaning they're finding ways for companies to save money, which is really important. Efficiency, innovation is very, very good, or finding new products and services that fit within their existing business model. That is a very helpful form of innovation. But in most cases, that's not what these teams were set up to do. These teams were set up to drive fundamental transformation, to take that corporation from one business model to an entirely new business model. And I cannot find in all my research and in asking people, I cannot find a single example of an innovation team leading to that kind of outcome. And that's distressing. That's a problem. It's worrying for everybody, working for those teams, for everyone setting up and backing those teams inside of corporations. And for those of us who have recommended it to corporations.
- [10:42]
Host
Yeah. So this is actually an interesting point right about the same time, I believe. Let me just double check. But there was this, the new new product development game paper published by Take, Ushie and Nonaka. It was actually before, it was 10 years before, in 81. And when they write in the book, or they relate three concrete case studies of companies that were able to create products that were, at least from that perspective, disruptive and disruptive to their mother company. Right. And the way they did it was to more or less. There's a lot of details in the paper. People should go and read the paper, of course. But more or less what they did was that they set it up as almost as an independent company answering only to the CEO and the board, not answering to any of the other departments in the organization. Have you seen this work like this elsewhere? Is the new new product development game a possible antidote to that problem you just related, which is that these innovation teams end up just doing incremental small improvements in something that is already there and not really disrupting the original business models?
- [12:06]
Elliot Parker
Yeah, you're exactly right in pointing to the what is ultimately the solution. When Clay Christensen wrote his book the solution to the Innovator's Dilemma is to innovate far from your core. For example, as you just mentioned, through a separate team reporting directly to the board and the CEO. What we found is that most organizations don't go far enough and we've made compromises over time to say, well, you can't go all the way outside. You know, you've got to use our internal HR processes to hire people, for example, or we've got a set incentive system in the corporation that we use to, to give people bonuses. And the more you borrow, the more that innovation team or that new product, new business team borrows from the core business, the more that thing starts to look like what we already do as an organization, which again is optimized for safety, predictability, not learning, not figuring out new things, but for propagating what exists, for perpetuating the success that we've already had through the means, by the means which we've achieved it that's the problem. So yeah, to your question, have you seen examples of this? It's what led me ultimately to form my company, Alloy Partners, with the idea that we can build external independent venture backed startups with corporations as a way for those corporations to unlock those crazy anomalies and learnings, the lessons that they need to think about how to run their business differently in ways that they never could do on their own. Because these startups are set up with entirely different forms of governance and incentives and access to talent and processes that are all optimized for really rapid learning. Startups have nothing to preserve, nothing to perpetuate. In fact, to the contrary, they're trying to build entirely new ways of doing things. They're trying to understand different ways of enabling the world to work. And it's that discovery process that enables corporations to then rethink how they run their core business and to do things differently in our own portfolio. We've got countless examples of corporations that are meaningfully transforming their core business model, moving from one business to another because of what they're learning through these startups that we've built. It's really fun to see.
- [14:16]
Host
And how do you then kind of balance out? Okay, so. Because what I'm thinking is there's a lot of startup ecosystems out there, whether it is incubators or VC companies or groups of angel investors, there's a lot of people putting money into startups, perhaps more now than ever before, at least in some geographies in the world and in some areas of technology. But what you're saying is that the larger organizations that have the funds but are therefore also over optimized for return on invested capital can take some of those funds and invest them outside their organization, perhaps even creating their own vc, more or less VC arm. Right. If I understood you correctly. And then, and that is because if they bring in the innovators into the organization, they get kind of absorbed. Like Clayton used to talk about the organizational antibodies, right, that fight the growth of the new ideas and, and new business models within the larger organizations. Is that a fair way to describe what you guys are doing?
- [15:27]
Elliot Parker
Yeah, it is. Yeah. Let me, let me give you a framework to think about this with. And for your listeners, you might, and this is, this is oversimplifying, but in business you encounter two types of problems. They're what you might call execution problems and what you might call learning problems. By execution problems, what I mean by that is we know what the problem is, we know what we need to do, we just need to go do it. Corporations scaled global enterprises are exceptional at those types of execution problems. Now if you're working inside a corporation, you might say, ah, it takes us forever to do things. We meet by committee and we move so slowly. Yes, that is all true. That is a feature of corporations, not a bug. It's the corporation operating very carefully, avoiding risk. Most startups fail. Corporations are trying not to fail, and so that's how they operate. But when they decide to do things, they can do it very, very efficiently. They go execute. They're designed for execution. Learning problems, on the other hand, are problems you spot where you know what the problem is, but you're not sure what to do, you don't know what the solution is. There's a lot of ambiguity. Startups by nature of how they are run and operated, the Incentive systems they use are very well designed and optimized for learning problems and will beat corporations at learning problems all day long. So when we think about what types of opportunities or problems we're encountering, if it's an execution problem, corporations are going to be startups. If it's a learning problem, startups are going to be corporations. So our idea is, our thesis as venture builders is let's marry the best of both worlds. Corporations have deep insight into their markets, their customers, the opportunities that they see. It's just that they can't act on some of them with the speed of a startup. So we can build startups with that insight. And then with the corporation providing some form of advantage to the startup, that startup's more likely to succeed in the end and help the corporation learn and develop strategic optionality for the future.
- [17:27]
Host
And I really like how you phrase it, because investing in a startup idea, potentially disruptive business model, it is about creating that optionality, right? Like it's the old saying that either disrupt or be disrupted. Right. And we see this a lot in the tech world, in the innovator's dilemma. Clayton used the example of the hard disk industry and how they quickly developed and new technology was coming up that was far cheaper and far more efficient than what was there. But the incumbents didn't want to change because of course that would cannibalize their own business and they are not set up for that. And so the new entrants were able to kind of steal the market from them by doing, as you said a minute ago, starting low at the market, but then going up value chain and ultimately taking over the market. And we see this happening still today, right? Like if you rewind the clock a couple of years to 2023, nobody would ever think that Google was under any kind of threat. 2025 comes along and AI is being used so often, many people are migrating their use of search into AI. And people are starting to look at Google a little bit of doubt. Can they survive this shift in interaction with the Internet? Right. And so this is very important. But we also have the problem that even when startups bring this disruptive, innovative perspectives, there's still the, what Clayton called the antibodies within the organization. Right. So what have you seen specifically in terms of structure or in terms of approach that even though it allows you to use the best of both worlds, that you just said a minute ago, does not make the startup idea, if you will, the venture fall into the same patterns that the corporate is already, you know, has already inbuilt and kind of fundamentally absorbed, which is this efficiency, slow, risk avoiding and so on.
- [19:39]
Elliot Parker
Yeah, yeah, I'll give you, let me give you a good analogy to use that I found helpful for thinking about this. The corporations, again. Yeah, the framing is exactly right. They are, they're optimized for that. Safety, predictability. And so everything that they do when they look at new innovative opportunities, we focus a lot on communicating that broadly across the organization. I'll give you a good example of this. I remember hopping on a call with a bunch of innovation leaders inside of corporations. The topic of the call, the meeting was how do we ensure more alignment and more communication across the organization for the things that we're working on? And for me, the entire premise of that line is false. It's wrong. There's a famous story. Jeff Bezos, when he is running Amazon is the website was. Was growing, the team was growing. They were running this problem where somebody would change one part of the website and then something else would break over here. And so they realized as we're designing new features and thinking about new buttons on the site, we need to have these committees meet and get aligned to ensure that all this stuff is going to work together. And innovation was slowing down to an absolute stop in the organization. And Jeff Bezos said to his team, what if we thought about communication around innovation as something to be avoided, not encouraged? Now that's a revolutionary idea.
- [21:12]
Host
That's quite counterintuitive, right?
- [21:14]
Elliot Parker
Counterintuitive. Right. Now let me be clear. If you are working on something inside a company that is fundamental to the core operations, again, you're working on an execution problem. You do actually want to broadly communicate that. You want to make sure you've got alignment. The organization is designed to do that. But if you're working on something that is really disruptive in the Clayton Christensen definition of the word, challenges your core business in some way, you actually don't want to communicate it. You want to be operating in a silo. Go figure it out, get it going, get some traction and then tell people about it. That's why building these things in startups outside works really well. The analogy that we use I think about a lot is how innovation happens in natural ecosystems, in nature. Think about the Amazon jungle for a second. The Amazon jungle is incredibly resilient. Almost no matter what we do as humans, the Amazon's going to continue for a long, long time. In part because it's so good at innovating and innovating in quotation marks. But the Amazon Jungle Innovates through evolution, all these myriad forms of life inside the Amazon are, are mutating at the level of cells or organisms and discovering new ways of living in that ecosystem. There's a defined set of constraints. There's only so much, so much sunlight and water and air for these animals or these plants to compete with, to complete compete for. And so as a result, the most viable organisms survive in this ecosystem. Not all of them survive. Right, but the most viable ones do. And that process of experimentation at the level of individual cells or organisms leads to this complete explosion of different forms of life. And as a result, an incredible amount of resilience inside our corporations in every way. We innovate differently.
- [23:14]
Host
I really like the Amazon metaphor because if you develop the metaphor a bit further, you also see that innovation is happening at a nearly infinite level of granularity, right? Like from the single cell innovation or all the way to the ecosystem adaptation. That also happens because there are many different ecosystems within the one Amazon jungle. In your book you also talk about like a very concrete, specific tool that you bring to organizations that are starting to invest in these potential ventures or disruptive ideas. You introduce the idea of what you call the controlled burn. What does that look like in a modern company? And why is it so hard for leaders to tolerate near term risk?
- [24:05]
Elliot Parker
Yeah, I'm going to mix metaphors a little bit here, but yeah, the goal for organizations, if you want to learn, let me start with this. We can't predict the future. At least we're really bad at predicting the future and inside of large corporations because again, we're optimizing these things for safety. Before we make any big bet or take a move. We want to gather as much data about the as we can and we want to have as close to 100% certainty as we can before making a decision. The problem is there is no data about the future. Any data that we have tells us about the past. At best, it tells us a little bit about the present. It doesn't tell us anything about the future. The only way to get data about the future is to go create it. You create data about the future by taking action and seeing what happens. Action creates data. Corporations are really bad at that. And so you have to find ways to run experiments that generate that data. Run as many experiments as you can at the lowest possible cost per experiment inside an organization. And in the book I use this, this example of wildfires and wildfire management. In the western United States where I'm from, we've seen record fires, number of quantity Fires and the kind of the. The severity of fires in the last decade have been worse than ever before, at least in recorded history. And it is, in fact, an output of our really good, effective management of fires. Believe it or not, that this is happening, and what's occurred over the last 150 years, 170 years, is people have settled in the western United States in greater numbers. We've gotten very good at putting out fires as soon as they arise. And you can track this in the tree rings to see the data, the frequency and severity of fires over time. Very good at putting out fires when they. They pop up. Now, the problem is, in doing that, the forests have gotten more dense, there's more fuel for fires, so that when they do come in, we're not successful at putting them out right away. Fires burn with greater intensity and faster than ever before. The forests in California, for example, are 10 times more dense than they were 150 years ago. Ultimately, it's a problem of incentives. We all know what to do to solve the problem. If you are a land manager, what you need to do is you need to engage in a strategy of what's called controlled burns, where you map out an area of land into a checkerboard and you burn certain parts of that checkerboard on purpose to reduce the amount of fuel for fires and the ability of fire to spread when it does pop up. Now, if you're a land manager, it's so risky to do that. The chance that a severe fire is going to occur on your land while you are the manager during your career is very, very small. The chance that that fire that you set on purpose may spin out of control is a real risk, and so it's easier to do nothing. Similarly, in California in particular, there are regulations, for example, around if you're going to do a controlled burn, you have to file all these reports and things ahead of time to get approval because we want to manage, make sure the air is clean. Now, when an actual forest fire burns in California, the air is very, very bad. The sky turns orange, it's terrible for people's health, and undoes all the work that we might be trying to do anyway. It's a very similar situation inside our corporations. If you are a manager of a corporation, the chance that a crisis is going to occur of that magnitude on your watch is actually very small. The chance that running some experiment in the form of the equivalent of a controlled burn could go awry on your watch is very real. And so it's easier to do nothing and that's what happens. We all know what the solution is, but nobody seems able to act. We all know that corporations need to run more experiments, but nobody seems able to take action. And that's the fundamentally, it's a problem of incentives.
- [28:06]
Host
When I hear that story, first of all, it's very familiar because I'm from Portugal, which is one of the countries in Europe where we have historically had large catastrophic fires. Every few years, five to 10 years, there's a big fire. And exactly for what you said this year, it's been a cold spring with lots of rain, which means that summer is going to be brimming with opportunity for intense fires because there's a lot of fuel, just like what you said. Now, in translating that metaphor to organizations, what I see is that these experiments that you are talking about, you call them controlled burns, but it's more like controlled self burn. Right? Because the manager who runs the experiment will need to take a risk. They will need to put money into something that they are guaranteed in most cases will not succeed. Because that's why we run experiments. We're exploring the unknown. I very often use the metaphor of the maps in the Middle Ages, where maps were so important that people got murdered because they had a map at their house that could be used by somebody else. And maps were kind of even a currency, if you will. Like gold, right? Like digital gold. These days we talk about personal data as gold. In those times, maps were gold. And what I'm thinking is that the organizations create the policies that lead people to be afraid of failing. Right? So we have this environment, these organizations, where it's not safe to fail. And safe to fail is a. Is a phrase we very often use here on a podcast because we're encouraging software teams to do a lot more of that experimentation, just like you are doing for corporations. So what have you learned in your research and also in the work you do at Alloy Partners? What have you learned about creating that safe to fail environment in the organizations you support?
- [30:03]
Elliot Parker
Yeah, this is another area where I've changed my mind. I thought you could reform these organizations. You could establish within them the right structures for governance and incentives and talent access and processes optimize for experimentation. What I've realized over time is that's nearly impossible. There are some circumstances where it is possible. You see it where in large corporations where the founder is still in charge, for example, or in corporations where the organization's facing existential threat, you have to change or we're going to all lose our jobs and go out of business, then you see amazing things happen. Most companies aren't in either of those circumstances. They're kind of in the middle, where you've got managers in place, the company's doing reasonably well. It's in those situations where it's the very hardest to run experiments to challenge the status quo. So, yeah, I've seen this quite a bit in our work. It's a real challenge. And I think for teams, you ought to consider new ways to develop new structures to run these experiments in. Now, in our world, we do that through startups, because startups are optimized to do the things we're trying to do. Learn quickly. Startups are a perfect form of business model experimentation. One way to think about it, you can optimize an organization for the magnitude of correctness or the frequency of correctness. And what I mean by that is, inside a corporation, we optimize these corporations for frequency of correctness. Don't ever make a mistake. You want to always be right 100% of the time. Startups are very different. We're optimizing startups for magnitude of correctness. You can be wrong a lot because when you're right, it can have a massive payoff, right? This is how we think about things as venture investors versus investing in public stocks. The public stocks, you want to be frequently correct. Incremental improvements over time produces a steady return in venture investment. It's the magnitude of correctness that matters more, where you can be right one or two times out of ten, and it pays for everything else. And so when you're innovating, innovation is a lot more like venture capital investing than it is like investing in public equities. The problem is we get the activities mixed up.
- [32:29]
Host
Yeah, I really like that metaphor. About six months ago, I wrote and produced a podcast called We Must Start Investing in Software, calling attention to the fact that that return on invested capital and traditional management practices actually prevent us from learning what actually works in practice. And without going too far into the details, software presents a completely different opportunity from other mediums of value production, right? Like manufacturing, for example, is another medium. But in software, we can innovate fundamental aspects of the business model. The go to markets, the packaging very simply with just small changes to the software. Sometimes bigger changes, sometimes smaller, smaller changes. But we don't allow ourselves to do that. We very often fall into this just an incremental improvement to offset maybe the normal depreciation in value of an existing software product, right? And we end up with this typically bloated but not very interesting Pieces of software that get to be maintained by hundreds of people over many years because that's how the companies are structured. And I think that this idea, this VC perspective or investing, right, like making bets and investing in different changes to our software can help us unlock this perspective that we really need to find some high impact or large magnitude, as you called it, investments in our software by making a lot of small, not so successful experiments. Right. And when you're selling this idea to the large corporates, let's say you're in a negotiation with a client or a partner and you want to help them kind of shift their mindset to learn and take advantage of investing with you. With the VC perspective, what kind of conversations come up? How do you help these people understand that actually what you're trying to do cannot be done by just having better project management? You need to shift your mindset and start thinking about having maybe two or three startups investigating these areas that you care about to find disruptive business models.
- [34:47]
Elliot Parker
Yeah, two things that may be of use to your audience. I think number one is getting aligned on the objective, which you've stated really well as an organization. Long term resilience comes from learning. So you need to optimize and set up these activities so that they produce knowledge on behalf of the organization. I'll step back just for a second. There's a wonderful thinker in the UK named David Deutsch, has written some outstanding pieces. He's a quantum physicist actually, but has done a lot of work about how we learn as societies, how civilization advances and innovates. What he's discovered is that all civilizations through history have failed for the same reason. They failed because they didn't innovate fast enough. Meaning problems stacked up until ultimately a problem came along that was so big in the form of invading people, internal strife, natural disaster, the civilization lacked the knowledge and wealth needed to deal with the problem. His proposition is that if you have enough knowledge and wealth, you can deal with any problem that arises within the laws of physics, of course. So your goal as an organization to build long term resilience is to collect as much knowledge and wealth as you can. As much knowledge about how the world works and how the future is going to play out, and as much wealth as you can to be able to deal with, make the changes and investments that you need. So long term resilience comes from gathering knowledge and wealth. The core operating organization, the core business in a corporation is optimized for wealth generation. That's great. Let it enable, let it function. To go gather wealth. It's not designed for knowledge gathering. This is where innovation teams, or even teams of software developers who are trying new ways, can learn on behalf of the organization. You need to make sure that all of your systems, the metrics you use to measure your success, are all tracking how much knowledge you're gathering on behalf of the organization. And so if you can shift the conversation around our hoped for outcomes away from wealth generation. I see this often with innovation teams. The goal for the innovation team is to produce $100 million in new revenue in the next 18 months or whatever. That is a terrible call for an innovation team. The innovation team is designed to produce knowledge they can hand over to the operating business. The operating business is really well positioned to go generate that new revenue. So that's number one. Corporations need to understand that we need to be gathering that wealth and knowledge. Innovation teams, these teams running the experiments should be out there focusing on what they're learning on behalf of the organization and the strategic optionality they're developing for the future. Number two thing that's important for these teams is the funding mechanism for this type of activity. We run our core organizations again with that focus on return on invested capital. And so everything inside the organization, all the decisions we make about how to invest our time, money, resources, is oriented around what type of return on investment is that investment going to produce. And rightfully so. That means the organization is producing the capital that the wealth needed to go out and be ready for problems that might pop up in the future. Gathering that wealth is useless though, if you're not also gathering the knowledge along the way about how to deal with problems that come. So you have to find alternative structures, ways of making these decisions around investment and for tracking the results. When we recommend to corporations that they ought to build startups as forms of experiments, it's with this in mind. Most innovation teams are funded out of operating budgets inside of companies. And so if you're running an innovation team, you need to go, let's imagine it's a budget planning cycle for the next year. You go make the case, we need $10 million to run our innovation team. The immediate question you're going to be asked is, and what type of return is that going to produce? The innovation manager says, I don't know, I can't predict it. Well, okay, you're going to need to show something. So the innovation manager then goes and produces a spreadsheet that models out and create some kind of hockey stick. And in terms of return, and we're going to put 10 million in. And we know, we think this is going to produce this type of return. And the CFO says, well, that's not good enough. And the innovation manager says, well, okay, let me change the hockey stick a little bit. I'll make it look better. And they go back with a new model and they get their budget approved. Now the problem is they're competing for investment against things like marketing spend. We know with some degree of certainty if we invest a dollar in marketing what type of return that dollar is going to. It's got a very clear roi. Those things with a clear ROI are always going to win the budget argument over time. Innovation's always going to lose because it's not an activity that is optimized for capital efficiency. Learning is really capital inefficient. We don't know whether it's going to work. We don't know when the payoff is going to be. So you've got to find alternative ways of funding that type of work. What we found is out in the market. Venture capitalists do this every day. They're investing as charge without a clear understanding of when or how much things might pay off. But as you said earlier, they focus on a portfolio approach, making a lot of bets with capital that is really patient. Well, corporations are sitting on more balance sheet capital on average than ever before. They don't know how to necessarily invest this. They're doing things like making acquisitions, building new factories. That capital is patient. That's the type of capital you want to use to fund innovation. But if you're running that innovation inside a company, it's structurally challenging to take balance sheet capital and deploy it into those types of things. So what we recommend to these corporations is let's go set up outside entities that can receive balance sheet capital. You can invest in these things with your balance sheet rather than as a tax on your operations. Now these things are competing against acquisitions, building that new factory where the timeline is long, the payoff is uncertain. That's a much better comparison than comparing that innovation activity against marketing spend.
- [40:56]
Host
For example, adding a new feature to the product. Yes, El, it's been a pleasure. I mean, we could definitely talk more about this and more about experimentation for quite a while, but unfortunately we're getting close to the end. So before we go, do tell us where can people find out more about you and the work that Alloy Partners is doing today?
- [41:19]
Elliot Parker
You can learn more about our company@alloypartners.com Best way to get a hold of me is on X Twitter. I'M erparker.
- [41:27]
Host
Very good. And we'll put the link to that in the show. Notes for people to go and why not reach out to Elliot and ask a follow up question. Strike up a conversation. Elliot, it's been a pleasure. Thank you very much for your generosity with your time and your knowledge.
- [41:43]
Elliot Parker
This has been fun. Thanks Vaska. Appreciate it.
- [41:48]
Vasco
All right, I hope you liked this episode, but before you hit next episode, here's the deal. This podcast is powered by people like you, the members who wanted more than just inspiration. They wanted real tools and real connection to people who are practicing Agile. Every day we're talking Agile access to over 700 hours of agile Gold, CTO level strategy talks, Summit keynotes, live workshops, E courses, Deep Dive interviews, books. And if you're into no Estimates, we got the pioneers of no Estimates in.
- [42:27]
Host
Those Deep Dive interviews as well.
- [42:29]
Vasco
Agile Business Intelligence, creating product visions, coaching your product owner courses, you name it. You'll get invites to monthly live Q&As with agile pioneers and practitioners, plus a private Slack community which is free of all of that AI slop you see everywhere. And of course without the flame wars. It's a community of practitioners that want to learn and thrive together. It's the best place to connect with community and learn together. So if this podcast has helped you before, imagine what you will get from this podcast membership. So head on over to scrummastertoolbox.org membership and join the community that's shaping the future of Agile. We have so much for you, so check out all the details the of@scrummastertoolbox.org membership because listening is great, it's important. But doing it together, that's next level.
- [43:37]
Host
I'll see you in the community.
- [43:38]
Elliot Parker
Slack.
- [43:41]
Host
We really hope you liked our show. And if you did, why not rate this podcast on Stitcher or itunes? Share this podcast and let other Scrum masters know about this valuable resource for their work. Remember that sharing is caring.