Latest / The Innovation Show / Alex Osterwalder — Value Proposition Design in the Age of AI (Part 2)

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Alex Osterwalder — Value Proposition Design in the Age of AI (Part 2) · The Innovation Show

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with AI, we build stuff way too fast because you can almost
0:03
make, perfect software with AI.
0:06
But you know what?
0:07
If you haven't started with a deep understanding of the customer
0:11
jobs, pains, and gains, you're very likely to build the wrong thing.
0:14
They'll say, "Oh, but we can build fast to learn." Well, it's
0:17
like running up the wrong hill.
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You're gonna run up a hundred wrong hills, and you're still not gonna
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get a good understanding of the map.
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Well, what if the first thing you did is you started to really validate your
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customer understanding, and I mean going down to a quantitative understanding.
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They say waiting is a pain.
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Well, how much?
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Five minutes, ten minutes, seven and a half minutes?
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You know, you need to get quantitative, and you need to have evidence
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that supports your understanding.
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You can get that evidence with AI tools.
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You can run, you know, synthetic interviews.
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Should still probably talk to real customers, but you can also run
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really fast experiments with landing pages that were put up by AI.
1:01
So You can compress the testing But you need to focus on the
1:05
customer understanding first.
1:07
Thanks as always to Kyndryl who support The Innovation Show, and sponsor book
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competitions on The Innovation Show.
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If you sign up for the Kyndryl Institute at
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and just send us the screenshot that you've signed up, you will be in with a
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chance to win a copy of Value Proposition Design by Alexander Osterwalder.
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It's a pleasure to have them as a sponsor.
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They're actually pretty cool people, good to work with.
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With a unique blend of AI-powered consulting built on unmatched service
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capability, Kyndryl helps leaders harness the power of technology for
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smarter decisions, faster innovation, and a lasting competitive edge.
1:45
You can find Kyndryl at KYNDRYL, kyndryl.com Many of us are using
1:51
generative AI, LLMs, or other types of AI to do tasks that
1:55
we probably shouldn't be using.
1:57
But sometimes we're using them to do way too much, sometimes way
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too little, or sometimes using them for the wrong task at all.
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One of those is in value proposition design, and many of us may think
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we can get rid of the entire team and replace them by AI.
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Not at all the case.
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We're joined today by a friend of the show.
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He was with us last week to talk about this idea of retiring projects,
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which projects to back, how to back them, how to see which metrics count.
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But today he's to talk to us about the idea of value
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proposition design in an age of AI.
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Friend of the show, my own friend, Alexander Osterwalder, welcome back.
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Thanks for having me back.
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Always a real pleasure to be here
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Great to have you back, man.
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Absolutely loved last week's episode.
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I'm just gonna hand over the mic to you and take us through what
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you're seeing and how your customers are changing, and what's changing
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particularly with this new technology, AI
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Yeah, I like the way you framed it, you know, like we use too
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little and too much of AI.
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We use it often for the wrong things.
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Now, the big topic that we get asked to work on a lot with our
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clients is value propositions.
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Many years after value proposition design, it was actually less popular back then.
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we get a lot of requests, and a lot of the companies that come to us,
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they actually mistake, you know, formulating your value proposition for
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a writing exercise, which it's not.
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So their AI can actually do a really good job.
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You give some inputs, and they can formulate a value proposition.
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But in order for AI to do a good job, or GenAI in particular, you need to do
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some of the homework you know, that you need to have to put into a prompt to
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get a great formulation for, you know, your value proposition, get a great
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website, great brochure, etcetera.
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I'll go a little bit into that, and I'll show you what our thinking is and how
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we started to turn that into a playbook.
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So I'll go back to the foundations of an irresistible value proposition.
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It's a bit of an evolution, but the same foundations from our book,
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but we constantly adapt what we do.
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So the first thing almost sounds trivial.
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What is the foundation and everything, you know, starts from there.
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do need to have highly relevant customer jobs, pains, and gains that you address.
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you know, with AI, we build stuff way too fast because you can almost
4:27
make, perfect software with AI.
4:30
But you know what?
4:31
If you haven't started with a deep understanding of the customer
4:35
jobs, pains, and gains, you're very likely to build the wrong thing.
4:38
They'll say, "Oh, but we can build fast to learn." Well, it's
4:41
like running up the wrong hill.
4:43
You're gonna run up a hundred wrong hills, and you're still not gonna
4:46
get a good understanding of the map.
4:48
Well, what if the first thing you did is you started to really validate your
4:54
customer understanding, and I mean going down to a quantitative understanding.
5:00
They say waiting is a pain.
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Well, how much?
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Five minutes, ten minutes, seven and a half minutes?
5:06
You know, you need to get quantitative, and you need to have evidence
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that supports your understanding.
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You can get that evidence with AI tools.
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You can run, synthetic interviews.
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Should still probably talk to real customers, but you can also run
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really fast experiments with landing pages that were put up by AI.
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So You can compress the testing But you need to focus on the
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customer understanding first.
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That sounds trivial, but it's not the case for most companies.
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I can guarantee you, all of my clients, and these are world-class brands, they
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can't give you the evidence for their quantitative understanding of customers.
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And when I say quantitative, I mean, is it five minutes of waiting that is a pain?
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Is it ten minutes?
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Is it an hour?
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They cannot give you that evidence, and that's the case everywhere.
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So that's what we need to do first.
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Seems trivial, but everything starts from there.
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Then the second one, okay, now we have a good evidence-based
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understanding of the customer.
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Now we can start to focus on the benefits.
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say, well, you know, the benefit of our solution is you're gonna
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save five minutes of waiting time.
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Well, okay, again, show me.
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What does five minutes mean quantitatively for them?
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If I don't have to wait five minutes, I'm actually gonna be able to sell more.
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You know, I'm gonna make, , ten million more revenue from my sales
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force over the next six months.
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then you show the evidence that for a majority of your
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clients, that is the case.
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So before you even build something, you start to show the evidence that
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you have an understanding which benefits do they really care about.
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So that's, number one and number two of your value proposition.
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Okay, well, now we have an idea of what could go into the value
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proposition, but there's something else.
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Well, everybody wants to focus on differentiation.
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good.
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But show me the evidence your, focus of differentiation
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actually matters to customers.
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So again, here's how I intend to differentiate, and here is the
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proof that my customers actually care about that differentiation.
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So think of how many companies look at competitors, differentiate based on
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other solutions, and they never even talk to customers if customers care.
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So they differentiate compared to competitors rather than testing
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through the eyes, the lens, the glasses of the customer.
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Okay, so that's the third one.
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And then let's get to the last one.
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I formulate a clear and simple value proposition with a
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sentence or an image or whatever.
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I also need to go and test that.
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So four components of an irresistible value proposition, and I can
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guarantee you, if you have these ingredients, you will succeed.
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Now, let me kinda just show you how this looks like in a process view.
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So we did this last week, right, where you go from opportunity launching in
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the market, and then hopefully you can have a value proposition that succeeds.
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what you really want that- We gradually go through that
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thinking of the value proposition.
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I'll call it develop and formulate.
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Includes, you know, there's two phases if you want.
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Developing is product management, product development, and formulating is
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turning that into a marketing message.
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You need to test and iterate all the time, so you go through this double loop again,
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and again, and again until you actually hit the nail and you have something
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that really resonates with customers.
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So that is, let me get out of the way again here, that
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is a step-by-step process.
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So we built this playbook for a large, um, industrial tech company, and they're gonna
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roll it out to thousand product owners.
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So the first thing they do is they map out a business model canvas
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more for the context, but then they map out the customer profile.
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But here what's important is they also need to show the evidence that
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they understand the customer, you know, from an evidence point of view.
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They talked to enough, they ran experiments.
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Then they go to the, what we call value stack.
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That's a new tool that we created, um, because we saw that the
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tools we had weren't good enough.
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But it basically, in a more analytical sense, allows you to prioritize which
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benefits matter most to customers, so we talk about the solution.
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Then you do the same for differentiation, and you show the evidence, and then
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the next one is willingness to pay.
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Now, this is what I'll call the ingredients.
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is stuff we need to do.
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It's the homework of a product owner or a marketing team.
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you have , made these ingredients, now you can formulate a brochure, you
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can fro- formulate a one-pager, you can formulate a marketing campaign
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with AI, you can now do these things really fast.
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And here's the key.
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They're gonna be extremely distinct because you have a
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distinctive customer profile.
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You have a distinctive solution based on real evidence.
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Because what companies do too often is they go right to AI to formulate
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a very lofty, high level value proposition, and it's gonna look
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the same for every single competitor because they didn't do their homework.
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you do the homework, and here you can use AI to test these things faster,
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but when you do the homework, here is where you're gonna get something
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extremely powerful, and then you iterate.
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So you'll get the best out of generative AI and iterating at lightning speed
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because you've done the footwork, the homework to actually create those prompts.
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And the problem is people don't like work, so they go do a
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shortcut, so they go right to AI.
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But the problem is, if you don't give the right data to your
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favorite AI, what's gonna come out is gonna be pretty high level.
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So kinda how we look at the world, and I can show you after how we designed
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a little, a simple playbook for that.
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But, you know, AI is great, but if you don't use it the right way, you're gonna
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get that doesn't actually reflect a customer's, you know, value proposition,
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and it's not distinctive enough, right?
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So how many of these marketing messages the same?
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Worse even, they'll use buzzwords because, you know, you have to train
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AI to actually use simple language.
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But if you use it right, it's rocket fuel because you can really
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go much, much faster, but you need to put the right things in place.
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I get super excited about this, as you can tell, because the opportunity is amazing
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I was talking to a leader from a big confectionary company recently, he was
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telling me that if you think about this, like you have a secret formula of a
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product you've created over many, many years, and now all of a sudden along
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comes, say, an enterprise AI offer, like an, an Microsoft or somebody like that.
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And there's this question of like, do I put my data in there?
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Do I put the secret formula in there?
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You know, and the whole idea of if I do that, am I I gonna
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be used as training data?
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And the other thing is, if somebody else comes along and just goes, "Here, make
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me a, a product," it's gonna draw on that content that it's already there.
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Even though may- you know, the whole idea of the terms and conditions that
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we all sign without really reading them all, I, I, I, what I have to
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tell you now, what I do is I actually put it into AI and go, what, is
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there anything to watch out here for?
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But of course, that's the AI giving me that work again.
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So it's a just a real dilemma, and I wondered if you had any thoughts
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about that or if any clients kinda pondering such dilemmas.
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Yeah.
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So two, two answers to that.
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The first one is a kind of very logical one, and, uh, there are ways today that
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you have open source AI that you can use, and you can run it on your own servers,
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and it's not gonna go anywhere, right?
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So that is possible today, and you don't necessarily need, you know, the edge
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models to, to do this kind of work.
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So if you're, if you're working on, you know, the next, protein
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for your pharmaceutical company, know, you need cutting-edge AI.
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You need, you need the most advanced models.
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But to formulate a value proposition, you can actually play it really safe
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with models that are not cutting edge.
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That's number one, right?
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So there are ways today for this kind of stuff to use AI that will
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not share with the entire world.
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Now, the second one is, does it really matter that much?
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Because, like, the key of a value proposition is a product per se
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and the product features do not create value in an absolute sense.
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It's for a specific customer segment a product will create value or not.
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every company is so unique in terms of which customers are they going
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after, what are their solutions good at, you can train models.
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You know, there's, there's no model that's gonna come up today, at
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least, that's gonna come up with the perfect value proposition for your
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competitor based on what you said.
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That's, that's a fear that I believe is irrational because it's very unique,
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and today, AI cannot, on its own, come up with a great value proposition.
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That's why I'm going back to ask, you know, like, for this customer segment,
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design the best value proposition.
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That's not gonna work.
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What you actually need to do is you could use AI to start to do market
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research, which one is the most, you know, the best growing segment.
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Then you define in that segment customers.
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You still need to go and test the jobs, pains, and gains.
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So it's gonna be so unique that even if you trained an AI based on your
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solution, it's gonna mean nothing.
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You know, it's not gonna be usable by competitors in any way.
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So we-- Not today, right?
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So today, we believe AI is gonna give you the solution.
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It will not.
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With the right ingredients, it will give you the solution.
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The human in the loop and the uniqueness of what you're pursuing is still today,
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we don't know for how long, is it a year?
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Is it two years?
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But today, and for the foreseeable future, AI will not give you the solution per se.
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You need to do that homework.
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And I can tell you, I did try, and I do have a lot of, you know,
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colleagues working in this space with AI and advanced AI agents.
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Today, it's not possible.
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So I
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I think the fear today short term is overstated.
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longer term it could be a different story
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It reminds me of the quote by Henry Ford, "If I asked AI what my customer
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wanted, it would've said a faster horse." And it would've told me
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how great I was for thinking of it
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So the, the problem is we, we overestimate and underestimate AI or Gen AI.
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So AI is pretty good at some tools, pattern recognition,
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all that kind of stuff.
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Definitely world-class on formulating value propositions if
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you give it the right ingredients.
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I'd be less worried about the copying aspect.
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I'd be more worried about are we using AI to its max, because I
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still see today marketing teams that spend time on wordsmithing.
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Well, are you serious?
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Today, your websites, your brochures should be constant iterations with AI.
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You shouldn't be writing a word.
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Like, you should be giving ingredients, meaning…
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So this is, this is actually a good segue.
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Let me show you how we do it with our playbooks, because it's actually a, a
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pretty powerful way of working, right?
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So we say, okay, we created this thing.
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It's very simple.
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It's very delimited to, you know, we, we call this thing strong value propositions
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and differentiation with Gen AI.
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How do you use your favorite AI tool, create value propositions
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as a sentence, as a landing page?
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Well, first you need a product description, you actually need, know,
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the analytical point of view, customer jobs, pains, and gains, and the value
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proposition, then you need a favorite AI.
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What you do is, here's again, it's kind of more formulated in a, a playbook sense of
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way, and I'll show you how it looks like.
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First, what you do is the homework, and this is what playbook focuses on.
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How do I describe my customer that I'm targeting on jobs, pains, and gains?
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How do I test those jobs, pains, and gains?
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Okay.
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Once I have that, I have a validated customer profile.
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That's an ingredient.
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Next ingredient, how do I come up with the benefits?
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How do I test those benefits?
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Are those really things that people want?
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Okay, now I have validated benefits.
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Now all I need to do, this is super powerful.
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I take a neutral product description, I take screenshot of my customer profile, I
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take a screenshot of my value proposition, I throw that into an AI, and I have a
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prompt, and out comes whatever, you know, description, landing page that you want.
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So it's really about the ingredients more than anything else, right?
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So I kinda show you that,
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You know I don't like to be salesy, but I gotta show this, right?
18:49
'Cause it's pretty cool, and I, I know you'll be down with it.
18:54
So, so I'm gonna show you this looks like.
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I showed you the playbook library.
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You get access to all these playbooks.
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Here's one called Strong Value Proposition and Differentiation with Gen AI.
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So all of the steps work you through how do I formulate a customer profile?
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How do I test a customer profile?
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Everything that I just showed you on a slide, show you how to do it, but then
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this is the cool thing with playbooks, you have workspaces where you actually do it.
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So this one says Map your customer understanding.
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So that's exactly what I'm gonna do.
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If I click on this, watching a couple of videos, it shows me how to map
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out my customer ecosystem in a visual workspace with sticky notes, how
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to pick the most important customer that I need to focus on, then how
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to map out a customer profile.
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these are all the things that we discovered teams are not good at.
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So if you're in B2B, let's say you're selling whatever, jet engines.
19:57
So you know what?
19:59
You actually have several customers, users, influencers,
20:04
channel partners for whom you n-need to have a value proposition.
20:08
once you map all of those out, then you ask which ones are gonna be the
20:12
most important in the decision-making.
20:15
You know what?
20:15
Teams mostly focus on the users, but the users rarely make the decisions in B2B.
20:21
all of their value proposition is gonna be around the user
20:24
rather than the decision-maker.
20:26
So what we do in these playbooks is just guide people through the right
20:31
steps so they can do it on their own.
20:34
now when we work into, in a B2B context, we can custom design those
20:39
playbooks based on their needs.
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But what we try to do, because we're passionate about it, we take everything we
20:46
learn in the best and biggest companies, and we share it in our public playbook
20:50
library so everybody can get access.
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So what I showed you, the, you know, , formulate your value proposition with
20:56
GenAI is accessible to everybody, and it benefits from those projects we
21:00
do with some of the strongest brands.
21:02
And, and for all of your listeners, know what?
21:05
The best and biggest brands are not getting the basics right either.
21:10
So they need to remember, we need to go back to the customer.
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We need to test and validate the customer jobs, pains, and gains or the problem.
21:20
That's the ingredient, the marketing ingredient we then use for AI.
21:24
So what's astonishing is that these best brands on the planet are not further
21:31
than the small and medium-sized company.
21:33
Now, the advantage for smaller companies is your, decision path
21:37
is much smaller, so you can put this stuff in place right away.
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All you need is the playbook.
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So I think there's a huge opportunity with AI.
21:46
gonna see a lot of cool new value propositions emerge.
21:51
Some are just formulations of products without AI, and some
21:55
are gonna be new products and services with AI embedded, right?
21:59
So there's… It's an amazing space that's going on.
22:02
It's like the age of innovation and entrepreneurship
22:05
And Alex has kindly given us for the Innovation Show audience, as well.
22:10
INNOVATIONSHOW20, if you put that into the coupon code on the Strategyzer
22:14
website, you'll get 20% off on that site.
22:17
And also, I'm gonna link to it where you can find out more about that content.
22:20
Alex, one more question, 'cause I know you're doing a, a webinar with friend of
22:24
the show, former guest, Tendayi Viki, your friend and collaborator with Strategyzer.
22:30
Maybe you'll tell us a little bit about that as well, but just, I, I was thinking
22:34
here about, say there's a regular listener to the show, a guy called Corey Rollins.
22:38
Shout out to you, Corey.
22:40
And he's building a prototype.
22:43
He's built it, a prototype pillow for people who get, like, numbness in their
22:47
fingers and, you know, we've all had this cold feet and ver- vertigo type symptoms,
22:54
and I was telling him about your work.
22:56
So say somebody like him, how, how does he, somebody who has an idea,
23:00
somebody at home who's just kind of going, "Hmm, I have this idea,"
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how do they get started with this?
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So remember I was differentiating between product development
23:13
value proposition formulation.
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and this is actually, you know, for everybody, but like with the big client
23:20
I'm working with right now, we distinguish these two phases because in both phases
23:24
you need to test and iterate, but you don't test and iterate the same thing.
23:27
So when you already-- when you have an idea, well, guess what?
23:32
You should go through that process of first, you know, validating customer
23:36
needs, jobs, pains, and gains, validating the benefits, validating
23:40
the differentiation before actually working on the details of your product.
23:45
So the problem is people go too fast towards a prototype before having a deep
23:52
understanding of the priorities, right?
23:53
So that would be if your product is just an idea.
23:57
now the big challenge is, and I'll tell you, Strategyzer is not
24:01
good at that either, so we we're doing this for ourselves as well,
24:05
is you have a product that works.
24:07
You actually know that people like it, but you haven't formulated it
24:12
in the right way that resonates.
24:14
So what you actually need to do is you go a little bit
24:18
further, and this is much faster.
24:19
That's the cool part.
24:20
Your product exists, you know it kind of creates value, but then
24:23
you still need to have validated jobs, pains, and gains, validated
24:27
benefits, validated differentiators that you take and you feed into AI.
24:33
And here's the key.
24:34
Now you would come up with three alternatives, and in the market you
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test the three alternatives, one that emphasizes this feature, one
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that emphasizes that feature, and one that emphasizes a third feature.
24:47
Or it could be the pricing.
24:49
then you do so-called ABC test.
24:52
So there are different types of things you test in different
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phases from product development all the way to marketing messages.
25:00
So if that pillow exists Now your task is to, you know, if you don't have
25:06
the price yet, you gotta test actually the pricing, but you also wanna test
25:11
the differentiation that you, you know, put on the website, and that
25:14
should not be a logical conversation.
25:17
It should be evidence-based.
25:19
Evidence from product development and evidence from conversion rates.
25:24
So if I have three websites and the only thing that I change is the
25:28
differentiator of the product, and I see, you know, very strong, conversion
25:34
rate differences, I already know this message resonates more than this one.
25:39
So these are the kinds of things you test your messaging even, not that hard once
25:45
you know how the playbook works like.
25:47
But we tend to overthink and under-experiment.
25:51
Corporations even worse.
25:52
Like, they will think for ages and business cases.
25:56
But even entrepreneurs, they tend to overthink and under-experiment.
25:59
So get started with the right experiment depending on where you are in your, in
26:04
your project, and this sounds like the project exists, right, with the pillow?
26:09
It sure does, but I, I, it's so interesting.
26:11
I was thinking about the parallels between what we talked about on
26:14
retiring business ideas last week, because this is a discipline again.
26:19
Like, people think about entrepreneurship and innovation roles as creative roles.
26:25
They are, but there's a huge science now and a discipline, and it's actually
26:28
the discipline that carries you through.
26:30
The analogy I have, and I know you're big into your own fitness
26:34
and health, is the same thing, is that you can't outsource that.
26:38
You, you can, you can, you can be healthy, but you still have to show
26:42
up, not eat that thing, eat that thing, go to the gym, make sacrifices,
26:49
have only one beer, all that kind of stuff that makes a huge thing.
26:52
And it's the exact same.
26:53
It's, it's a discipline to get to the end, and the creativity is not enough
26:59
and I love that.
26:59
Let me take that and, I'll tell you.
27:02
We did a pitch for a big company probably like two, three months
27:06
ago, and it was just the season of Roland-Garros, and they were looking
27:12
at training, and we were pitching the playbooks and, and, and we kinda had
27:16
to tell them, like, "Why do you…
27:17
we need playbooks in another platform?" And then I took the, I took that
27:21
sports analogy and I said, "Okay.
27:23
Well, you know what?
27:24
Um, Roger Federer, he was pretty good.
27:26
He won Roland-Garros, I don't remember which year.
27:29
So think of it this way.
27:30
If we did e-learning- To teach you how to become a Roger Federer.
27:35
We wouldn't go very far, right?
27:36
Because we would, we would show you videos of how to hold the racket, and
27:40
then we would ask you, "Is Roger Federer holding the racket right?" And we'd think
27:44
that that's gonna change the behavior.
27:47
That's not gonna happen.
27:48
But now think of it this way.
27:50
So Roger Federer had a coach, a youth coach, who unfortunately passed
27:55
away in the middle of his career.
27:58
imagine if you had the playbook of how that coach trained Roger Federer,
28:04
videos to show, so you do need to see that, but instead of then filling out,
28:09
you know, like a, a multiple choice how you hold the racket, what if it
28:13
got you to play that move right away?
28:15
So the sports thing is the same thing.
28:19
You cannot become really healthy, if we're talking amateur sports,
28:23
or you can't become a world-class athlete by watching videos.
28:27
Does it mean you're not gonna watch videos?
28:29
Of course not.
28:30
Roger Federer, you know, watched hours and hours of training videos.
28:34
But it's the combination between learning, visualizing, theory, and practice.
28:40
And today I don't think we're doing that well enough, so a lot of good
28:44
content out there, books and, you know, tools and… But at the end of the day,
28:49
it's how do we get to that outcome?
28:51
And you get to the outcome by learn, do, learn, do.
28:54
Another pract- An- another, profession that's good at that is, medicine.
28:58
So you're not gonna become a surgeon by reading books.
29:01
Do you need to read a lot of books an- and understand anatomy and all of that?
29:05
You bet, but it's also practice.
29:08
So I think in business, you know, we underestimate that this is a profession
29:13
that requires you to learn and watch videos, also requires you to apply.
29:19
And again, in our case, we figured out a really kind of efficient way with
29:23
the playbook, so I'm excited about it.
29:24
That's why I wanna get this out there, because I do want people to change,
29:28
because the way we do things today is not fully professional when it gets to growth.
29:34
I think we're world-class at running companies for some aspects , supply
29:37
chains, when it comes to growth initiatives, we're kind of acting as if,
29:43
you know, it was just a creative thing.
29:45
And if you're creative enough, you're gonna come up with
29:47
great value propositions.
29:48
You nailed it when you said this is a profession, and professions you learn.
29:53
Now because we don't have enough time, we need a very efficient, effective way to
29:57
learn fast, so we can't, you know, do the six-year internship of a, of a doctor.
30:03
But we can do things that, that resemble that but that are highly effective
30:07
and another way you're teaching people is through webinars as well.
30:11
I mentioned that one with our friend Tendayi.
30:13
Do you wanna share a little bit about that, and then we'll land the ship today?
30:16
What, what dawned on us at one point is that we're known for content and
30:22
tools, and we're seen as a consulting company, but then we realized, well,
30:26
our most powerful thing is playbooks.
30:27
So all of our webinars are now showcasing playbooks.
30:32
How do you actually apply this?
30:33
And with Tendayi Tendayi has done a lot of projects where he calls this his
30:38
party trick where a company brings him in, and then they ask him, "Assess if
30:43
this is a good project or not." Now, he knows that you can't analytically just
30:49
by looking at it say it's a good project or not, but there is a technique, and
30:53
that's what we talked about together in your last… in our last show, right?
30:57
You can the evidence.
31:00
So what we're gonna do in the next, webinar is we're going to show you
31:04
with a real project, how can I apply this, apply this playbook to assess the
31:10
evidence that will show me if this is a project that should be retired or if this
31:15
is a project that we should invest in?
31:17
Because it's possible, right?
31:19
So you just need to know why.
31:21
So we're super excited about showing these techniques down to here's not the
31:26
theory, here's actually how you apply it so you get the same outcome that we
31:30
get, you know, when we work with clients.
31:32
And Tendayi does this a lot with clients, assessing, you know, projects, and he
31:36
calls it a party trick, so we're gonna reveal the party trick, if you want.
31:40
Brilliant.
31:40
And you can find that at Strategyzer.com/events/business-idea-evaluation,
31:49
and I'll put that in the show links as well.
31:51
It's always a pleasure, man.
31:52
I look forward to the next in our Strategyzer series as well.
31:56
Friend of the show, author of, those who are watching us, all those books behind
31:59
me, and I should have actually taken it.
32:01
I have Biz for Kids . Where is it?
32:03
Of my favorite
32:04
I told ya, Biz for Kids.
32:06
Biz for Kids is there as well, signed.
32:08
I have a signed, special signed copy as well from Alex.
32:12
Alexander Osterwalder, thank you for joining us
32:14
Thanks for having me.
32:15
Keep up the, the great work, my friend
32:18
With a unique blend of AI-powered consulting built on unmatched managed
32:22
service capability, Kyndryl helps leaders harness the power of technology for
32:26
smarter decisions, faster innovation, and a lasting competitive edge.
32:30
You can find Kyndryl and the Kyndryl Institute at KYNDRYL.com