David Rogers - The Digital Transformation Roadmap Part 2

And, they're just layered up and unearthing to really solve the underlying problems. You've got to do some archaeology It's the same thing with the organizations, these like processes and budgeting and, and, and resourcing and, and metrics and KPIs and how meetings are run and all of these different things at different levels of the company that actually all impact your ability to change and transform.

And so just coming in and saying, well, we're going to change a piece here or we're going to have a team or a squad that does something different that may be your starting point that maybe you're like chipping into the rock and your entry into this giant edifice. But it's got to keep going deeper and deeper and deeper. If you're really going to drive the change.

That's so important as well, that maybe we'll just mention here, because we probably won't get to it today. . David Rogers: Yeah. That's the fifth step. And as I, what I call the roadmap in the book, , the framework is about what I broadly call tech capabilities. And that's really three, very interconnected things. It's about, do you have the right kind of digital technology? This is everything.

Information architecture in the cloud modular moving away from monolithic, one gigantic application to decomposing it into lots of small microservices using APIs to connect them and so forth. And that's a technical shift. But actually what I've seen and learned, it's much more profoundly an organizational shift because when you actually change The information architecture into these small components. , organization follows technology.

In this case, you have to set up individual teams to take ownership of each of these microservices. And that naturally brings about this kind of squad based or small multifunctional team, or this kind of problem defined organizational structure, which you see all the big Companies that are digital native that operate at scale that Google's the Amazons and so forth. They all are built around this.

So there's the technology, the talent, which is not just what are the technical skills we need, but also bringing in people with different backgrounds from inside or outside of our industry with entrepreneurial experience and not just experience working inside big companies. So what's the kind of range and mix of talent we need, the talent gaps we have currently, and how do we manage that? It's not just hiring people. It's not even just training people.

It's also, I find one of the biggest stumbling blocks in that talent life cycle is retaining the key talent that you are going to need for your digital future. Cause you can hire the smartest people. If you've got a paycheck the most talented Product managers from Roblox or Amazon or meta or wherever, if they are stuck in a morass of bureaucracy inside your big company, they are going to leave. and then in addition to the talent, it's the culture. Really being clear.

I know this is one of the things you talk about in your book , but really thinking about defining what is the culture we need as an organization or how does our culture need to shift, and evolve if it's really going to match our strategy and where we're headed as a company defining that clearly communicating it. Not just clearly, but in ways that really stick with people using stories and symbols and symbolic action and so forth. But then lastly.

Enabling that culture to actually happen by really looking carefully at all the processes in your company and figuring out which ones are blocking the cultural behaviors you want , how by changing those processes, can you make it easier for people to behave in the way that you want in the culture that you need? We're gonna take a step back and we're gonna start with vision. Then we were going to talk about how to select your priorities and then how to validate as well.

All key steps in the digital transformation roadmap, but one that often gets overlooked and one where so much of this all comes tumbling down is governance or step four. Managing growth at scale and i'm gonna tell you what a beautiful opening to this chapter as well you say, "as you start to apply the process of experimentation to digital ventures in your own business you are now ready to begin the next step of the dx road map.

Repeating this process at scale across your organization, major challenges must be addressed, which ventures should be funded, who will decide when to shut some down, what rules should be waived for new ventures at the start, how will the successes be handed off to the core business, what will you do with digital ventures that don't fit your current organizational structure. There are a plethora.

Of these questions that we don't consider because we just go straight into building or falling in love with an idea. After validation which is an absolutely core step you have to have a governance david's gonna take us through that over to you

We've got to test. We're going to define the problem. We got to keep building and speed shorten that cycle of sprints. But you take for granted the sort of. organizational infrastructure that was around you in that other business. And all of a sudden, you're like, wait, why is everything so hard now that I'm working in a a hundred year old consumer package goods company, right? It's because of the governance, right? The challenge for leaders here is it's not enough.

It might be your starting point, your kind of organizational or sort of cultural proof proof case to have a team build a great digital innovation that customers love and captures value for the business and then people start to get excited. But if you're going to repeat this, you're going to scale this across an established business with different priorities, competing priorities.

You have to look at these rules of how do we manage how do we manage different projects and priorities and goals and teams and experimentation at scale. So. Part of this is understanding. This is what we would call a portfolio as we'll talk about. And I know all the listeners to your show already know when you start an innovation journey, you don't know what's gonna work. You make, you place bets, right?

So you're thinking about a variety a funnel, if you will, you're starting with pursuing a number of ventures, knowing that most of them will not work out. So how do we do this? Some of the key elements, one of the key elements of I'll start on governance is this relationship between what I call teams and boards. And it's obvious, say, in the startup world, but it's just not there in in most established companies.

So you've got two kinds of groups of people that have to work together and they have to have very clear decision rights. So the first is the teams, those are the ones who are actually doing the innovation, doing the experimenting and the rapid validation. And then you've got the boards, and these are the folks who sponsor them, who give them an initial green light, say, okay, we're giving you a little bit of runway. We'll time a little money, go for it, come back.

And we're going to make a decision on whether or not we continue to fund you. Right. They're the ones who, who, who sponsor, who green light, and then who iteratively fund that team. But they also should be doing a bit more, right? Like a great venture capital investor, they should also be advising. Right. They should be some of your wise counsel, giving you perspectives on the market, making introductions because you're in a big company.

One of the most important parts of this is actually acting as a liaison or an advocate within the organization. So all of a sudden you want to do something next and ah, you need something from legal or from supply chain, or you need an introduction to an outside partner who works with the marketing team. This is again, a critical role of this. Support this group called the board, and different names.

It might be an innovation board, a technology innovation board, a, a growth board is a term you'll hear what you want to avoid. And it's quite common still just with a whole group of different companies last week. And I would say the majority, when I asked them who sponsors innovation, they gave same, some version of the single sponsor model. Well, the CEO signs off like who, who approves when you do something different?

That's not just regular operations continue to improve the company, but like a big, interesting innovation that, oh, it's a CEO. You've either got one person who has the power. Oh, it's the CTO. Or you have a few different senior executives who each individually, if they want to step up and put their name on something, they can sponsor it. This is a terrible model, right? It's, it's sub optimal for the team because. It doesn't matter who that one person is.

They are not going to give you the support that a group you know, a diverse, interesting, well chosen group that that's on this board would do because they're always going to have more perspectives, more insights and so forth. It is much worse for the organization because when you have a single sponsor, they will go to bat for you, they will marshal the resources for you, and then they will never give They will never back down. They will never admit this idea is not working because it's them.

They're the only one who approved it. So whether it's because the classic pet project your sponsor has fallen in love with a solution you're working at, you're iterating, you're talking to the customer every day. You probably at some point realize this is not going to work. Like we should. Pivot or shut this down, but the sponsor will be like, no, no, you got to try this. You got to try this. They're so passionately they're, they're emotionally attached to it. Or they're just it's reputational.

They don't want to admit that this thing that your idea and they stupidly signed off on it, but now they can't let anyone know that it was a foolish of them to sign off. So the single sponsor model just, As a repeatable model, obviously anything you can, it could work in a given instance, but as a repeatable scalable model, it does not work. So you, you need to set up a really clear decision rights on like, what does the team do and decide on and what does the board decide on?

And that, that I would say is the first element of, of governance in large organizations.

They will decide on allocating resources not based on the idea but based on the person behind the idea and whether they have a track record of success so you can see why so many ideas die.

advise executives someone who's in the sponsor role, who's on a board ideally, to not try to pick the best idea. Because that puts you in the position of trying to think about what's going to succeed or not. And that is not your job. And it's not your job because you have no idea. You do not know. That's like the whole point of experimentation is you do not know what's going to work until you get out there. So it's not a bad idea to actually consider team, right?

Particularly if you've got a process where it's, I don't know, something like a hackathon or an open pitch shark tank for anyone in the company can bring in ideas. It's a lot of benefits of having that kind of open net. You got to consider, does this person really Do they have the right mindset more than anything? It's like, do they go in? Are they like passionate about the problem, but they haven't fallen in love with the solution yet?

Do they understand like what it's going to take to experiment? So, and, and test and learn. So, so considering the person is important considering strategic fit, we'll talk about that in terms of priorities is really important because this is an established business. So it's not, this would be a great idea for. Anyone to do, right? That's the question for VC. It's actually, is this a great idea that we in particular should do? It's a very different question for an established company.

So you've got to think about that in greenlighting, but the overall rule in greenlighting is what I call minimal deliberation and minimal funding, right? So you want to spend as little time. You want the process to be as lightweight as possible to decide who gets greenlit. And then you want to give those who get started as little as possible. In terms of time and money in the first round. So it's not this big high stakes.

Well, we've got to like, look at the data and we've got to know, at least does it have a chance, what's the odds of success of this versus that you don't know, but don't sweat it. You're giving them five or 10, 000 in 90 days. It's like, it's fine. Just like say interesting strategic problem. I wouldn't have thought of that solution, but you have a reason why you think it might be worth exploring. Go for it, right? Let's go for it. So green lighting.

And then we go into the other part of of, of resource allocation, which is this iterative funding. And so you've got the problem here is that all of a sudden companies will set up a green lighting process, and then they just fall back into traditional BAU business as usual budgeting which is like these long cycles, typically annual budgeting. And, It's complete mismatch for experimentation.

So you have to create a parallel funding model where you've got dedicated pools of resources that you're pulling from. And they're being given out on these short commonly, depending on what you're building. This is one of the things I know from different industries and companies if you're building a lightweight app, you could give them two months, not even 90 days of resourcing between rounds. If you're building.

Something for an industrial sector, you may say, or where there's a whole lot of stakeholders. Even before you build the very first illustrative MVP, there's like a lot of people you're going to talk to. You might give them a little longer, but short rounds come back. Each meeting with the board, you define. Okay, if we approve, we're giving you another round of resourcing and time. What do we need to know next? Right? So we agree with the team. What do we need to validate next?

What do we need to learn next? Come back with this data at our next meeting. And then based on that, what The board, and here's where those decision rights come into play. Until the next meeting, the team has complete autonomy and control of its work. Guardrails, don't break the law, right? But, give some very specific guardrails and then it is up to them. Who's the customer? What's the feature? What do you build next? Every iteration, it's entirely up to them.

They know the definition of success. They know what they've got to bring back at your next meeting, right? They know what they're held accountable for. And then. It is the board's decision on whether to refund, whether to fund it again in the next round.

They need different perspectives and insight. They can advise the teams. They need some understanding of iterative funding and experimentation and, and, and how to how does this kind of process like a venture capital funding model work. But they also need to have the bandwidth. Right. And this is the problem when you get too senior, you get people, it's like they have, well, it's two things you need. You want clout. You do need to have at least one person on the board.

Who's got some clout in the organization who can go to bat for you. Right. But if you get a whole bunch of the people from the top tier one, you got your overflowing with clout, that's great, but they have no bandwidth to actually pay attention to and like, listen to you and give you advice. And that's it. That's the problem with, with going to senior. And I do see companies try that.

How much time, money, people, did we get any value or learning out of it? It's just like, oh, it was shut down. That must be a disaster. It's a sort of psychological assumption. Whereas if you are doing smart shutdowns, You're going to have most of the shutdowns happen with very little cost and with a significant amount of learning.

And then the last part is this sort of if you are the one being shut down, right, you're on the team, it's seen, it's, it's perceived and may very well be in fact a strike against you in terms of your career, right? And your next, what's available to you next inside the company. So those are the things we have to address.

You've got to make shutdowns, first of all, be a norm an expected norm that You have to understand that if you're shutting things down quickly and cheaply, which is the first rule of what I call a smart failure, right? It's not just enough to fail fast. If you're in a big company, you have to fail smart. And the first thing there is, that means, did we fail? It's okay. If the idea didn't work as long, did we fail as cheaply and as early as possible? And you keep pushing yourself on that.

So you don't want to get to that point and say, gosh, we should have been able to see this six months ago. And a million ago the data was all there. We just finally admitted it today. If you're doing that the costs are not high at all. So smart shutdowns, you make it a process, you make it a norm. You go in and you start with projections of survival rates. You say, here's our innovation process for this set of. Projects or efforts or initiatives in the company. And, and here are the milestones.

And we expect 50 percent will stop at milestone one. And then another of those who make it through another 50 percent will stop at milestone two. And after that, we've got some pretty good, strong ideas. Remaining milestones will probably shut down 10 or 20 percent more. So you, you, you set up this expectations. People are comfortable with it. Then you go out of your way to As I say, celebrate smart failure, you spotlight and recognize.

And I have stories in the book of companies who do this extremely well. That a well managed product project that you shut down is actually a great thing and something we should all learn from. So you, you make it not just something people have to hide on their resume, but something you actually literally in public forums, get up and praise when you're talking about innovation and growth. Yeah. And not even at some separate failure party, you can do that.

But I prefer where it's at the same place where you're talking about innovation successes. You're also talking about your successful shutdowns and what was done right and how we need to learn from that. So, and then you have to follow through. You have to really be that the people who are on those projects don't get then cast into the wilderness or they're not allowed at least to do an innovation project anytime soon. You actually put them on the next one. Right.

This is what good companies do that Google, Susan Wojcicki went from a disaster. It was as a product disaster. It wasn't that expensive, but Google answers was her project. It was going to be like Quora. Exciting new product, completely flopped in the market. They, they pushed, they pushed, just couldn't get it to work. Okay. She did not get like sent back to do boring stuff. She was put on the next interesting new product they were working on. Or one of the interesting ones was Google AdSense.

AdSense went on to become one of the biggest sources of profit for Google, right in their core business model. So. They might not have found that without they weren't willing to take the talent that had just been on a project that that did not work in the market and reassign them. So you gotta have that mechanism where the people who are working on if the project. Doesn't pan out. The venture proves out to be just proves the hypotheses. There's not a market for this.

As long as that was managed properly, that's not a failure at all for the person. It's like as Vanessa Colella, when she was at Citi and was talking to me about innovation, she said it's distinguishing people from projects. The project is being shut down, not the people. So you reassign the people to the next interesting project. Doing this right, make shutdowns much easier. And it overcomes all these biases that we have inside of organizations. And it's so critical.

Innovation stack and i'm gonna share that on the screen now for you and david's gonna kindly take us through it this is something this whole governance element that is so overlooked. That we abandoned all my other notes for today's session, because this is so important that I really want people, it's kind of like, I often think about David as I call it the Disneyland queue effect. You think you're at the top of the queue and then you realize, Oh no, there's a whole other side over there.

And then it bends over itself and you're not, you're miles from the end or else you get to the end and actually it all tumbles down and you go, what did I just spend the last year or two doing? So many of us, so getting this part right for the organization. And this is why the whole organization needs to be involved is absolutely core. So over to you, David, to take us through the corporate innovation stack.

Each team at any given time is focused on one, what I would call a growth venture. That could be a product innovation. It could be a process innovation. It could be something external facing to your customers. It could be internal. Right. I was just working with the head of supply chain for a major healthcare company. And her whole focus was about digital innovation of their supply chain for internal stakeholders. But you've got a team who's working on a venture. The second layer is the board.

So we talked about this. This is the innovation board, the growth board or whatever you want to call it. But this is a small group that is Overseeing a group of different teams, right?

So one board has a few members and they are looking at multiple teams, greenlighting them, advising, counseling them, and then going through this iterative funding where they decide each time they meet with one of these teams, do, does it make sense to give you more resources and more time to keep going forward on this, or is it time for a smart shutdown? And then this all sits within.

What I call at the third layer of the stack and innovation structure and innovation structure is basically provides two things to the board and the teams. One is it provides a pool of resources. So this is the first question I hear when I tell, especially CFOs you've got to have this iterative funding model and so forth.

And then they say, Hey, Okay. But where are they as they're making all these agile decisions on every, every week or a month or so, as I have meetings with teams outside the annual budgeting process, where are they getting the money from? Well, you have to have a dedicated pool of resources. That's going to be money. And it may be people who are full time working in this process of innovation and exploration.

And then in addition to the resources, You need to have governance rules because different kinds of innovation opportunities are going to have to be managed differently within different within an established business. I talk broadly, I think we touched on this in part one about three paths to growth. So the key here is first path, right? This is The easy part. This is innovation within the core sort of low uncertainty, well defined problems in your core business.

You manage that according to your usual processes. That's like, go for it. Don't need to change anything. Don't, don't, if it ain't broke, don't fix it as the saying goes. Right. But a lot of innovation cannot work with that normal business as usual management. So then you've got. Two different kinds that need to be managed differently and will require this kind of innovation stack path to is any opportunity that is. Part of your core business, right? But the uncertainty is high.

And then path three is things that are actually outside of your core business. So each of those needs actually somewhat different management support, as I would call it. In terms of path to the challenge here is. You've got to actually, well, the broken model is to say, let's give it to an innovation team. They'll go build this thing for us for we're the core business and then bring it back to us. That's what in the it delivery business is called build it and throw it over the wall, right?

It's like, give us the specs, tell us what you want. We'll go off for six, 12, 18 months, build some digital thingy, and then say, here it is what you asked for, right? This always fails. So. Instead, you need a governance model where both the funding and the people actually doing the innovation have to be a mix of some representation and some funding from the core business. So they both have skin in the game, right?

That's the money and their perspective of what is and is really not going to work in the core business is there. They're sitting on the team that is Part of the team, the team doesn't have to go outside to get that perspective. And you plan from the very beginning that there's going to be a certain point, certain milestone where you've gone far enough in iterating the solution that you're going to hand it back to the core. Now it's ready for them to actually run with it and scale it up.

You've taken out most of the uncertainty, right? Then path three innovations. They have different challenges. Remember, this is an opportunity, a growth opportunity that is outside of your core business, right? You are a journalism, a business, a newspaper business, and you see an opportunity to spin out your games, which used to be crossword puzzles. In the print edition, now you realize this could actually be a separate app with a separate subscription and create a new revenue stream, right?

That would be the New York Times, or you're a retailer doing pure e commerce and you're rebuilding your tech, their own technology infrastructure. And somebody proposes, Hey, this new system we're building works so well. It's very scalable. It's resilient. Couldn't we sell this as a service to other people, right? Go into a B2B kind of cloud computing services offering. Whoa, this is Amazon Web Services. First day it was proposed by Benjamin Black and Amazon way outside the current business.

Current business is retail, right? So those kinds of ideas have to be managed differently as well. Don't need the core involved. The whole problem is there is nobody in the core to whom this idea would fit or own. They would be a natural home for it. So you need to manage those differently and they need to have a different kind of oversight and thought from the very beginning about if this actually succeeds, if this really goes to scale, where does that go inside the organization?

How do we, how do we think about creating maybe even a new business unit for it or maybe merging it back in eventually into part of the core business? So. This is why we need that top level of the, of the innovation stack. Innovation structures are set up to either manage. I suggest either the mandate should be path two. So this is tackling innovation opportunities in the core business, maybe one particular business unit of the core, right? Cause you can have different innovation structures.

And really working hand in glove. With the core business on every one of these ventures, none of them get started, no team gets greenlit without the approval of someone from that part of the business, that business unit, right? And people from that business unit are part of maybe probably not all of, but are part of the team that goes out and iteratively builds the solution.

And then you would have different, innovation structures that are set up one or maybe more to go after ideas outside of your your current core business. And these can take different shapes. Sometimes that's just through venture capital investing or it's MNA, right? You've got a strategic MNA team that's looking for how do we, you. Opportunities to buy a firm that's going to give you an entry point into a new market or something like that.

It can be startup accelerators, it can be innovation labs it can be hackathons lots of different kind of processes. But all of these have what they should have in common to be an effective innovation structure is they've got resourcing attached to them and they have governance rules. that are specific that are suited to the kind of innovation that they're trying to do in that mandate.

And then within that structure, they've got one or more innovation boards and they've got the ability to form innovation teams. And that's how these sort of three layers, you have to have all three layers of the stack coming together. If you're going to have this really work on a repeatable basis in an established business.

We touched on that a tiny bit, which is so, so important trying to whittle down where you actually do decide where to place your energy, and we're going to go into validation of new ventures, because this is the stuff that comes before. Scaling and it's such an important aspect there's a case study david opens up with here much like we talked about in part one about cnn plus and about your times.

This is the great story of walmart a company that is doing a great job of validating you event new ventures and trying things iterating etc etc frugally as well i might add so we're gonna. Open with that story we've only got ten minutes left and then we're gonna go into the four stages of validation

Now they were smart in that they knew they would not know what would work. They did not try to go out and do a whole lot of benchmarking and business case writing and third party data and come up with a big detailed plan of how is Walmart going to do online grocery ordering. They said, no, we're We don't know we're going to have to test. We're going to have to learn. We're going to iterate. We're going to try different approaches. Right. They tried different things.

They looked at different delivery models, right? Do we find that out? Do we have a third party an app, a delivery service, like an Instacart or a door dash or somebody they do delivery part, we create the ordering experience and blah, blah, blah. They looked at, do we hire our own drivers, right? They looked at who will be a Walmart force of people driving around, delivering your groceries. They even. Tested a model where they had employees.

You're checking out people who work in a store, you're leaving the store at the end of the day. And you, you check out your, your timestamp with your, with your phone and you enter, where am I going to next, right? You're in the location and you get a message says, Oh, if you're going there, maybe your home, maybe someone friend's house, if that's where you're Would you take this delivery? On your way and drop it off at this customer's home. And, and you'll be paid.

You'll get a bonus overtime pay for, for doing that. If you do, that was another delivery model. So they tried different delivery models. Didn't know which would scale, which would work. They also tried a different pricing. And this is critical. This is the difference between the Instacart between the venture backed business. That's it. Expect to take seven, maybe 10 years to reach profitability, right? That's the name of the game with VC capital.

You're a Walmart, you're any established business. You don't have that long for the idea to prove out that it's actually not losing money, but making a profit, adding value to the company, right? So they say it's gotta make money. It's gotta make money. Not immediately, not first quarter reasonably soon before we know it's a scalable profitable business model. And we don't know what's going to be the right path. So they sent out and they said, we're going to try different things.

We're going to be willing to try is it different price points to order to pay for delivery? If you don't want to pay, they said, well, we're What if we offer a different minimum basket sizes? They tested each of these things lots of different price points. They also tested a membership model, right? Well, maybe people would rather pay one upfront some for a year long membership, then every grocery delivery order is free, right?

The one thing they knew they couldn't afford to do is just say, oh, it's free, any size order. So they tested all these things. And well, one of the things they learned was there was a segment who liked the idea of the membership model. It's like Amazon prime, right? You pay the annual fee, unlimited delivery, and then there's some extra benefits that they added in as well to sweeten the deal. So they got some customers on that and they found that was actually a scalable, profitable model.

But then there were other customers who didn't want to do that at all. They said, I don't want to pay. I don't want to pay per delivery. I don't want to pay annual fee. I just don't want to pay at all. So. They said, okay, what if you meet us halfway, so to speak to the customer we will give you a great online ordering experience, right?

An app that you can pull up and it's got your data and remembers your past orders, makes recommendations, makes it very easy to put together your list of all the things you need right now. saves all your your information. You just tap go. And then our people in Walmart will go up and down the aisles of the grocery section and we'll pull off all the products, put them in the bags. We'll get everything ready for you. There's just one thing you have to do. You have to drive to Walmart.

Now, part of why Walmart, this was a good strategy or why they were uniquely well positioned to deliver this particular strategy is because one of the unique strategic advantages of Walmart is their close proximity. To the customer in North America and the U. S. 90 percent of the population lives within 10 miles of a Walmart. So this is not such an unfeasible, ridiculous ask of the customer. Okay, just drive by a Walmart right now. You don't even have to get out of the car, right?

You park in a special parking spot. We bring the groceries out. We put them in the back of your trunk and off you go. That really hit with a different segment of customers who really like that experience. Mhm. This was actually already in testing and deployment before COVID hit. Now, of course, when COVID hit demand with quarantine demand for online grocery ordering skyrocketed the first model, they could not scale fast enough.

You could not hire enough delivery people to suddenly meet all the demand. But the second model, the what's called click and collect buy online, pick up at store was something they could scale. So that became really important to the business. Customer behaviors, expectations keep changing. They keep iterating and experimenting new things.

One of the more recent models they tested, they found that there's a certain customer segment who will pay a premium not just to have you deliver the groceries to them and leave it on their doorstep where the ice cream might start to melt. Or if you're me, your sorbet starts to melt. You'll pay extra to actually have a uniformed Walmart employee bring the The groceries into your home, put them away in your cupboards, your freezer, your grocer your refrigerator for you, right?

They call this Walmart in home. So they continue to experiment, try, see what works, see what doesn't change, shut things down, start new things up, continually learning from the market. , Aidan McCullen: so there's two final pieces. We're going to have time to share. The first is the four stages of validation that we mentioned.

And then I mentioned all those tools that David has, he's worked on these for years through the scar tissue of experience with executives and also their scar tissue of failing with so many transformation efforts. So first up, we have the four stages of validation, and then we're going to share The rogers gross navigator over to you david Great.

So the four stages really arose from a common problem I found, which is once teams and business leaders and corporate innovators really embrace the idea of experimentation and that you don't know going in what's going to work and you've got to test and try things and build iteratively and short cycles and really. They embrace society of Not writing a business plan, but writing down all your unknowns, your hypotheses, right? Your business model hypotheses.

What happens is you've got a lot of unknowns at the start, right? They're like, wait, well, which feature should I build first? Price should I charge? Who's my customer? Who's my competition? Does anyone actually care about this problem I think I'm solving, right? Is the technology going to work? Will regulators approve is compliance and legal and so forth. So many questions you don't know. And so then the problem becomes at the start of the journey, it's where do we start, right? What do we do?

How do we sequence all this iteration? You can't run a hundred different MVP tests in your first 90 days. So it's like, well, what do we do first? And this is where I found it helpful. To develop this model based on studying the innovation process of many, many different companies in different categories of what I call the four stages of validation.

And the point here is all of these things have to be learned before if you're going to have a repeatable, scalable, profitable business model, but you don't learn them all at the same time. So the first question you have to, this is very high level, and there's a lot of details under each of these, but the first broad question you have to answer is, are we focused on a genuine problem for an actual customer? You have to go out and get data to confirm that.

And that is the stage I call problem validation. That is actually the one that is most commonly skipped over. People start just jumping to doing wireframes or building a working prototype or. Gaming out the pricing and blah, blah, blah. You got to confirm what is the problem you're solving? Who's the customer? Do they see it the same way as you next, as you start to get some confirmation, some data, a lot of conversations with customers, and you're starting to confirm that.

And okay, what do we need to learn next once we were getting some. Confirmation on the problem and who the customer is. Next is, does the customer see value in our proposed solution? And I'll underline the word proposed. You are not yet building a working solution for them. You're just sketching out.

Hey, we're thinking of building, an app like this, a dashboard like this creating a service like this, a training program like X and you Define what is expected and you see what is the level of demand that generates is the customer knocking on your door and saying, how soon can I have this? What's the price? Send me the bill. Or are they saying, Oh, that's nice. Keep you posted translation. I don't care. I'm too busy to worry about this thing. You're planning right?

This stage is what I call solution validation. Once you start to confirm that you start to really show there's there's demand from the market classic sort of indicators of product market fit. They want it. They're willing to put in even down a deposit. Perhaps they're putting some skin in the game. Now you're ready to start what I call product validation. That's the third stage. And here what you need to discover is can we deliver a solution that customers use?

So now this is an important shift in kind of MVPs or that you're building. So before it was things like wireframes, just illustrative mock ups explainer videos, things that sort of show what the thing would be. Now you actually have to deliver your very first just barely working product. I think it's Mark Randolph Co founder of Netflix who calls it the minimum unattractive or ugly or I forget MUP.

It's like the, really not a very attractive, compelling product, what I say is it gives that baseline value proposition actually has to give the most. Slimmest version of the benefit to the customer. And then you actually see how do they really use it is very different often between what people say they want or think they want. And then you give it to them. How, how do they adopt it? How do they use it? Where do they use it? When do they use it? And can you deliver it?

All sorts of operational issues start to emerge here. And you learn all kinds of things. You will not know until you're actually in the market with a limited number of customers in a very first pilot where they're actually using it in the real context, right? Once that. Starts to happen, and then you keep iterating and building it out from this really crummy early, ugly what I still call a functional MVP.

It does actually do the job that gets better and more full featured and more polished and more scalable. Then you're ready for the last stage of validation, which is to ask, can we capture sufficient value from this innovation? Right. It's not just can we make money, right? Can we generate revenue? This is corporate innovation. It might be a cost savings. It might be mitigating a risk to the company. There's some way you're capturing value and it's not just enough.

You capture some, you got to say, look, given the scale of our business, what matters to us strategically, what other opportunities we have to invest where our core businesses and so forth. Is this worth taking it further? the question of business validation, the fourth stage. So These are all iterative. Each one keeps going. So they layer on and build on top of each other. It's not a stage gate.

You don't finish one stage and then start the next, but you, you begin with problem validation as you get some confirmation there. Then you start up solution validation as you get good data there and know the path you're on. Then you start product validation and then you start business validation. And what I've seen in experience is this brings a lot of clarity to the process for teams and established companies.

. David Rogers: Cheaply you can actually start the journey so maybe we'll share just his example so mailing the dvd and then diapers dot com which is a great example. Sure. And I'll just say, since you've got on the screen is you can see if you zoom in that the growth navigator tool, it's just a visual tool to guide you through these four stages.

And what I find is so helpful is everybody on the team and also those sponsors that the board, the innovation board, you want everyone to have a shared set of facts. So this tool allows you at any given moment, every iterating and pushing along further to have one place where you say. Here are our business model hypotheses, right? This is what we're assuming. We don't know. Here's what we data we have. Here's what we have actually validated now up to this point.

And here's what we need to learn next. Having that, that visual tool gives you that shared viewpoint of, okay, where exactly are we on this learning journey and where are we going to go next to iterate great point about These are, it is so iterative. You can learn so much very early on in some cases. So Mark Randolph and Reed Hastings, this is very early days of, Netflix. One of the things, remember their first business model.

This is what they're trying to validate at this point is the DVDs by mail, right? That was the original business model. And It's about that operation. Remember I said in product validation, it's not just the customer will use, but we can deliver it. Well, they had to figure out what's it going to take to be sending all these DVDs. One of the key questions was, can we just use regular us postal service, right?

The cheapest rates available for sending and will it go through without breaking, right? Are we going to have to have lots of expensive padding, which then adds weight, and then there's a higher charge for everyone we send. So, All they did was they took, they didn't even actually take a DVD. They took a physical disc. It was a music CD ROM. It was Patsy Hot, Patsy Klein's greatest hits, right? So they, I don't know, that's what they had on the, in the car. They put it.

In a pink greeting card envelope that they bought at a store and then they just took that and they dropped it in the mailbox on the street corner in their town and Santa Cruz had mailed it to themselves and they just wanted to see like, does it get there and is it broken or not? Super, super cheap test, super simple, 24 hours. And they learned something that was really critical to thinking about, okay, can we take this idea forward? The other example you gave diapers. com.

So this is in the earlier days of, e commerce. Amazon was already up and running, but Amazon started as a bookstore and they were gradually starting to move out into other categories of things you could order and have delivered, but they were not yet the everything store. Right. So e commerce is still growing. These two dads Mark Laurie and Vinit Barara. So they're new dads. They've got babies at home, right?

They're both married and they're thinking about all of a sudden they're buying all these diapers and other baby stuff, all this stuff they didn't buy until all of a sudden right now. And they're entrepreneurs and they're thinking, Hey, there ought to be an e commerce solution for this. Cause there wasn't one at that point. And so they said, yeah, it'll be like diapers. com and you can order the diapers. All the diapers you need and then we'll add on extra all the other baby products you need.

But we start with the diapers because that's the thing everyone knows they need. And you keep needing it. Frequency of purchase is always a key element in e commerce. They knew that. So they said this could work, but I don't know, would it? So the very first MVP, the first test that they built was just this, the two guys, they posted on Facebook, that was the top social media at this time four accounts, their two personal accounts and their wives, two personal accounts.

So just their friends and they just posted, said, Hey, Mark and Vinit are starting a new business. We are providing online delivery of. Diapers. If you'd like to save yourself your next trip to the to the store just message us and tell us what brand you want what model you want what size you want and the quantity and tell us the best price that you've seen at another store. We'll match it and give us your address and we'll follow up to charge you over the phone and we'll get it to you.

And they went to bed and they woke up in the morning and they had I think it was 240 orders from just their personal network. So when you have babies, very typically you have a lot of peers arriving babies around the same time. So they're like, Oh my gosh, we got to get to work. So the two of them and their wives spent the next day driving around to every big box store in their area.

And buying up on this list of all the different models and types that they needed and then taking it home and then getting boxes and packaging and packaging them all up and then driving in their minivans to the UPS or the FedEx, whichever it was getting the, all these orders delivered now. Obviously, you don't yet have a scalable model, right? That's the thing about early MVPs. They, they work, but they're not scalable.

You don't really know the economics yet, but they, they learned a lot in 48 hours. A most important, they learned there is a market, right? They weren't just smoking something this isn't something they imagined or just, they're the only ones who want it. Customers want it, but they even learn other things like which brands do people order?

Which which models do they like right classic merchandising questions are critical to any to any retail business but also like frequency if you give people this option, do they order? Diapers for a week, or do they order diapers for a month, right? How large are the order size? So a lot of data they got very quickly, very cheaply.

And that's the mindset when you're building these iterative as I call them, it's not, you got to shift, particularly in the early days, shift your thinking, you're not building a product. You are building a test. You're trying to learn the next most important thing you need to learn about this business opportunity. And that's really what this process of iterative of validation is all about.

I was just thinking about if that was me and we just had a baby and I decided to start this business and then my wife has to help me fulfill the orders. I can imagine her just staring at me going. I am going to kill you. I'm barely keeping up.

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