53. Deepa Krishnamurthy - The parts beneath the parts

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What's it worth?
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Uh-uh.
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Uh-uh.
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Uh-uh.
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What's it worth?
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Uh-uh.
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Uh-uh.
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Welcome everybody once again to the Total Innovation Podcast.
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As always, I'm your host, Simon Hill.
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There are hundreds of thousands of them scattered across America, small, mostly family owned, all privately held.
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They make the parts beneath the parts, the precision machine components, the specialty fabrication, the tooling and the subassemblies that quietly hold up the whole economy.
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And here's the strange thing.
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Most of them are very nearly impossible to find.
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We tell ourselves a tidy story about manufacturing.
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The factories closed, the work went overseas, the industry declined.
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Well, my guest today will tell you that that story is mostly wrong.
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Manufacturing did not disappear, it became invisible.
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The companies are still there, the skills are still there, the knowledge built up over decades is still there.
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What thinned out was the connective tissue, the dense local networks that once let manufacturers, suppliers, engineers, lenders, and investors find one another.
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My guest began her working life as a cost accountant on the floor of a tractor plant in India, surrounded by production schedules and inventory.
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From there, her path ran through finance, through real estate, through investing, and then onwards to Harvard.
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And somehow, decades later, all the way back, sort of, to the factory floor.
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She likes to say it feels less like a new direction and more like a great many separate paths that are finally converging.
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Her core belief is simple and I think rather profound that we cannot strengthen what we cannot see.
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Visibility comes before connection, and connection comes before integration.
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And most importantly, integration comes before growth.
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Before highways, there were maps.
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Before virtual marketplaces, there were humble systems that let people find each other in the first place.
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She's the co-founder and CEO of Enterprises, and her company and Wazoku have just begun working together.
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A collaboration I'm extremely excited about personally.
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And with that, please welcome to the podcast Deeper Krishnamurthi.
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Welcome.
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Thank you, Simon.
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Thank you for having me.
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I'm excited to have you.
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And uh with with so much exciting things happening in the world, I think you know this topic of the manufacturing industry and this invisible layer and everything is you know is is super critical.
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And so congrats on what you're doing.
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To set us up, you know, I give a little bit of background in there.
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Can you just explain to people who maybe haven't heard of enterprises what it is that you're doing and what gap that you're filling?
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Sure.
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Um we think of us as building the connective tissue.
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You brought that up in your introduction.
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Um, as you said, uh manufacturing didn't disappear, it thinned out and became invisible.
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There's 300,000 manufacturers, and they're all small businesses, but they do something super important that allows for manufacturing to actually happen.
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So the surprising thing what we found was it's not it's not that they don't exist, it's just incredibly difficult to find them.
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So if you're looking, if you're a supplier looking for a part, you're an investor looking for an acquisition opportunity, you're a bang looking to lend, you're an innovation partner, you are a manufacturer looking for a collaborator, even answering simple things, things like who makes this, where are they, what are they capable of, is very difficult.
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So we realized the problem was not just manufacturing, it was visibility.
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So what we're doing is you alluded to the infrastructure piece about roads and maps and highways and logistics networks.
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We're building that for manufacturing so we can create that digital network because the physical clusters have thinned out and um gotten fragmented.
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Amazing and super powerful.
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I it's interesting that you've, I guess not quite gone full circle, but maybe that's what it is, right?
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This this idea of multiple paths converging verging.
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Um so you started out as a on the shop floor of a tractor plant, it said, right?
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And and what does that young version of you understand that that maybe you only started to really appreciate now decades later as you've got back into this with the lens that you're that you're coming at it from now?
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Yeah, you know, um when I started off, um, it was uh about the physical world, about how, you know, unlike the services world or software world, manufacturing is constrained by the laws of physics and the physical world.
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But the connection that I did not see at that time, which kind of clicked for me much later, was that fundamentally it's a knowledge business, uh, it's a skill business.
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So the learning by doing is important to so many things.
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And it kind of ties back to even innovation.
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You know, when we get better at something, we improvise, we learn, we collaborate with people, some something that somebody says gives you an idea, and that becomes your next product line, or along those lines.
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So what I had not connected was the fact that even though manufacturing especially is constrained by the physical world uh from a scaling perspective, um, what scales faster and more like services or um the intellectual industry is the fact that it's really a knowledge game.
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Knowledge that comes from experience, knowledge that comes from context and doing.
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And that's what makes um makes that very powerful.
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And so that's the connection that uh kind of clicked for me, having spent time in um knowledge and services businesses, that ultimately it's it's a knowledge game.
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So, what is it about that knowledge game?
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And I think these numbers are kind of mind-blowing as well.
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If you look at it, you know, we're we're saying that the the the econom that you know things have become less visible, perhaps the overall sector has you know has become smaller, but still 300,000 firms, 2.9 trillion dollar, I think, sector, maybe, maybe even bigger than that.
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Um, the amount of money that's coming in from government stimulus around this and other things, equally mind-blowing at this, at this point in time.
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What is it about this that that sort of configuration of the industry and then this realization around the sort of knowledge share, knowledge economy piece of it that I guess people are getting wrong and that you're trying to address here?
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Yeah, you know, when you think manufacturing, right, before it was the story of scale and saying you need to make things at a large scale, so uh whether it's labor advantage or um and so on.
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Uh and then so manufacturing that stayed was focused on either logistics, you know, large mattresses, it's hard to ship them, or it is a regulatory play where you need to keep them locally.
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But uh for the most part, um, what I think uh we miss when we think about manufacturing is think of it as manufacturing at a large scale.
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But what manufacturing really is, especially now in this world of automation and AI, is going back to the skill point that I made earlier.
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It's about people making specialized products or specialized have specialized skills that allows for that connectivity to happen, that creates new products, new ideas, new innovation.
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And then there's a scaling challenge after that.
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But um when we think about manufacturing, it's not just making more of the same, it's making um, you know, one of the words that we used is it was production at scale.
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Now I think it's customization at scale, uh, which is possible in this new world.
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And in order for us to do that, uh it can be customization of uh, you know, something, a bioengineered part for a prosthetic limb, or it could be something for a defense, or it could be something for aerospace and something for the people heading to the space.
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But uh that allow that that that only happens when you have specialization, and specialization comes from doing.
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And so uh I think confusing scale um with um customization and innovation, I think is where the confusion arises when we talk about manufacturing, thinning out, or disappearing.
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Can you unpack that a bit more?
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Because I think it's profoundly important, but probably quite hard for people to get their heads around, right, in terms of what what it means.
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And this idea that it didn't disappear, it became invisible.
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You know, there's it in some senses it makes sense, but what is that what does that kind of mean in sort of a lived lived experience and and how should people conceive it?
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Because then we can get into the solution inside of it a little bit more.
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Yeah.
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And I think you know, let's imagine you're an engineer who's trying to prototype something.
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You just had an idea, and you're, you know, typically if you had a density of people that are in your industry or adjacent to your industry, you find your cohort of like-minded people, even if they're not doing exactly what you do, there's ways in which you can connect, and then you get an idea and you get something from an adjacent domain, and before you know, you've solved your problem when that visibility doesn't exist um in order for ideas to flow, because you know, we only get better at what we do when we are inspired by ideas that come from all places.
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And when the idea pool shrinks because of lack of density or lack of access, then your um, you know, your ability to sort of do something about it gets limited, your imagination gets limited.
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So when I say that um, you know, let's say you have an idea for something, and if you're not able to go uh prototype it quickly or try to fail fast, as they say in the startup world, then it's much harder.
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So you, you know, you can say, oh, why don't you just go overseas?
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But it's not as simple as that because there might be other uh things.
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You need an entire ecosystem for this to really work.
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And the challenge is, oh, the point I'm making is that this ecosystem has not disappeared.
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Has it thinned?
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Absolutely.
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Has it uh gotten uh very tenuous for certain industries?
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Absolutely.
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But does it exist um in a way that it could be uh rebuilt?
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Uh the answer is yes, especially for things that are critically important.
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I hope that makes sense.
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Yeah, no, it does, it does make sense.
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And I think that word ecosystem is something we can we can pull a little bit more on as we as we talk through all of this.
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One of the things that you've mentioned, so I'll come back to that.
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One of the things that you've mentioned, and I mentioned it briefly, I think in introduction, is is the kind of private market paradox, right?
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Like that lots of these firms are private firms.
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Many of them are you know SME in the truest form of SME in many senses.
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And the idea that that privacy, in many ways, it it it in maybe historical senses, it was the thing that protected the owners, but it also isolates them.
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And do you think that's part of the I guess systemic shift that needs to happen here?
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Isn't just that we need to maybe reshore and re-ecosystem things, but actually that that that there is a whole structure around the way that the private market in this industry, in this sector, has kind of evolved that maybe is now less of a defense and ad advantage and and much more of a threat to the to the whole sector and whole the whole way this ecosystem these ecosystems are working.
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I don't know if that's a well-framed question or not, but you know what I'm trying to ask, I think.
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I I do.
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And I think uh before that, I just want to uh elaborate just a little bit more on what we talked about earlier in terms of visibility and what that means in terms of thinning.
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Um and I'll get to the private uh market issue um in just a second.
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So another way to think about it, I just want to give some something tangible, right?
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When we talk about visibility, it feels like a very academic, intangible word.
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But um, you know, it's not not manufacturing, it's not just making the final component.
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I call that parts beneath the parts.
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It's specialty fabrication.
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It could be a coating, it could be a plating, it could be a welding, it could be tooling.
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These businesses don't make the headlines, but they're absolutely essential in order for you to manufacture something or prototype something.
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And what makes them remarkable is that they're not just products, it's the craftsmanship and the accumulated experience behind them, right?
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And these capabilities is what we're focusing on elevating and making visible because rebuilding them takes decades.
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It's almost like if you atrophy, you have an exercise for a few days, you know, you realize what's what has happened to your muscle.
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So it's the same thing if these muscles are not used, you know, they atrophy.
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So these capabilities, our goal is to make them visible in order for us to really have a chance at rebuilding that manufacturing base.
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So that's kind of what I meant by the visibility.
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So it's tangible in terms of what we're talking about and what these people are doing.
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Yeah, thank thank thank you for clarifying that.
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I know you'll get onto my private market point, but I think there's also an important, perhaps, perhaps, point in that, in that, or sub-point in that as well, around our perception of skills and specialism in the new age that we're moving into as well, right?
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Like there are a lot of new skills that actually are quite old skills in some ways, and they're different mindsets.
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And so if, and maybe this is part of that private market paradox question as well, if if my understanding's correct, is we need to almost shift from these small firms being very specialist for a very specific production, you know, often one or a small number of customers as well, into looking at how those particular skills and capabilities might be re-imagined for the new industrial age, right?
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For a whole suite of different things.
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And that I think that's what you're saying, right?
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Is those capabilities are almost there in many cases.
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And it's not that we have to build them from the ground up, but it may, but it requires both sides to be willing to flex a little to think through that that that challenge.
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Absolutely.
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It's almost like you know, you talk about general purpose technology.
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These are general purpose skills, general purpose specialization specialized skills that could be repurposed to any number of industries.
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You know, the same skill could go into a slight, it could go into a medical device, it could go into an airplane, a submarine, uh, or your uh you know, fence in your home, right?
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So it's just one of those things where um the general purpose skill um becomes a superpower because it could be uh it could respond to the need of the hour.
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Uh it's just a matter of reimagining uh you know the use of that skill and repurposing purposing it to industries um that are relevant in our new age.
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Super powerful, super powerful.
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So did did we get to this private market paradox or did I keep it?
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I think that might be a uh I think uh ultimately again to sort of demystify that concept, it's really about trust.
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You know, we talked about these networks, right?
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Before um, you know, you take any cluster, take Detroit, take uh Providence, Rhode Island, there were 500 jewelry manufacturers.
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They all sort of met in bars, they kind of met on the street, they just exchanged information and trust got built because people knew who they were, people knew their knew the relationships, and trust got built and people knew how to share.
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In order for efficient markets, markets to be to work efficiently, you need to have trust.
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You need to have participation, you need to have trust, and you need to have a way to share information where you're not vulnerable.
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And so uh so privacy is essential for markets to function.
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And when we talk about manufacturing, especially private businesses, private businesses, at least in the United States, do not have a disclosure requirement.
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They don't need to uh you know talk about who they are, what they do, and you know, um uh or their financial information.
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So what what happens is the more, the less information you have about somebody, it's hard to know not just who and where, it's hard to know hard to know what they are capable of, and more importantly, why they matter to you, right?
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And so our goal, uh I we believe in order to recreate an efficient market, you need to solve this privacy paradox, which is it's not an obstacle.
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Privacy is how you succeed because inefficiency is what gets you your excess return, if you will, but is not to expose them, but to create this trusted participation so owners can decide what they wish to share.
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It's not about giving competitive information away, but knowing when to share with who under the right circumstances while remaining in control.
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So that when we talk about privacy, we mean it's about being visible without being vulnerable, if that makes sense.
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So the idea is in order for you to truly engage the lecturers, especially those that are privately owned, in a thinned-out market where you don't have that physical cluster that allows for contact, which allows for trust building, you need to mimic that digitally in order to allow for participation and trusted engagement, in order for you to unlock the market efficiency.
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And and within that, then let's let's I think it is a there's a re-ecosysteming piece of all of this, but also a lot of these firms are um they're quite traditional in in many senses, right?
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And so I guess that's part of the challenge of this visibility piece is on is on both sides, you know, visibility for for business development purposes and for discovery and this sort of mass generalization of skills, but also visibility on your side for mapping them, right?
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And so you've spoken about visibility, then connection, then integration, then growth.
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Um I guess why is that order the right order from your perspective in terms of doing things?
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Um, and I think it'd be nice to then unpack how that is impacting how you're actually going about building what I can't, I'm I'm not sure if people will be listening thinking, is this a really hard thing to do or has it been done before or whatever it is?
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But let's get to that, right?
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Yeah.
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No, I think I think every complex system I think works that way.
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Um, because you know, when you think about simple things, um, you know, you have binary outcomes.
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When you have complex things like sending, you know, a satellite uh or sending man to the moon, uh I think I'm not saying it's uh it's it's complex, it's probably more complicated than complex because it's a binary outcome, laws of physics and everything else, and you can recreate what went wrong, you know, black boxes on airplanes, that kind of thing.
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But what ecosystem building uh by its very definition is complex.
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Of course, we're talking about people, policy, we're talking about places.
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And um, in order for that, um, you know, when you think back to infrastructure, we think of ours as connective infrastructure.
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I think we brought that up.
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You know, we talked about that as we started this conversation.
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So if you think about the world, you know, at the when we started the modern world industrial revolution and we started building these uh businesses, um, you needed to have uh roads to get to each other.
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You know, there were you need to understand, and a cartographer came up with a map and said this is the east coast and that's the west coast, here's the ocean, here are the rivers.
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And so then navigation was even conceivable.
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And then after that, you know, in order to apply it on the roads, you need to have addresses so you can actually reach somebody.
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And so for marketplaces to exist, you need to have a gathering place, you need to have a way to get goods over, you need to have a way to uh travel, and you need to have a way to find each other.
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Unless you find each other, nothing scales.
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And so otherwise it's just gonna be you, you know, exchanging a cup of sugar with your neighbor.
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Um, and therefore, to be visibility is important.
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And then visibility allows for that connection because when you have the when you have visibility, you can exchange information and connect, and therefore the trust gets built.
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And once trust gets built, then you can integrate the ecosystem that you can say who else should belong here.
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And then when that happens, it unlocks growth.
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So that's why I believe it's it's um the paradigm requires a certain progression because that's it's not just us, it's that's just how complex systems have been built.
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We wouldn't have Uber if people didn't know where to find people on roads and have addresses.
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You wouldn't have um uh you know Airbnb if you didn't know where the homes were.
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So it's one of those things where it's it's impossible if you don't have um, it's not so much impossible.
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I think it's um it's the right order uh because uh that's what happens in infrastructure building.
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In order to scale something, you first need to have the trusted visible layer of both um uh discoverability and then connection.
00:20:13.359 --> 00:20:25.200
Yeah, and I and I think I I totally agree as as as as as I'm sure you will not be surprised, but I think what's possibly hard for people to understand is why that visibility is so difficult.
00:20:25.200 --> 00:20:32.400
We can we can go onto our computers and we can tap anything we want into Claude, and Claude will blow your mind with a whole bunch of detail and information.
00:20:32.400 --> 00:20:38.000
And so, and I can, you know, we've given these numbers of you know hundreds of thousands of these firms.
00:20:38.000 --> 00:20:42.880
We've spoken about them being private and quite traditional, but what is it about the visibility in this space?
00:20:42.880 --> 00:20:46.240
It feels like there must have been lots of things happening and lots of mapping.
00:20:46.240 --> 00:20:49.440
And so, as you've unpacked this, what have you learned?
00:20:49.440 --> 00:20:51.839
And then how are you guys coming about it?
00:20:51.839 --> 00:21:01.759
And what I know is a very sort of state-by-state uh way as well, in order to drive that that evolution that we've just spoken about.
00:21:02.720 --> 00:21:13.200
Yeah, I think um, you know, the who and the where probably um exists in the world, or who, you know, because there are directories, if you will.
00:21:13.200 --> 00:21:22.079
Um, probably the where to some extent, even though it's not always a simple question, because you may be located somewhere, manufacturing someplace else.
00:21:22.079 --> 00:21:28.720
And so you maybe have you may have multiple plants, you do something here, you do something completely different there, especially with these cards.
00:21:28.720 --> 00:21:32.319
So, you know, it it all the it's not as simple as it sounds.
00:21:32.319 --> 00:21:35.200
And so context becomes super important.
00:21:35.200 --> 00:21:45.200
And whether it's cloud or whether it's any of the AI tools, they make um they're very good at interpreting um when there is structure and context.
00:21:45.200 --> 00:21:59.759
So the reason they're so good at um a lot of things, because there's been codification and structuring that's happened for a variety of um knowledge, if you will, that uh has been contextualized in a sense.
00:21:59.759 --> 00:22:04.000
In a way that makes sense in order for interpretation to be powerful.
00:22:04.000 --> 00:22:15.839
Whereas here, the big issue is understanding what somebody is capable of and what can you know, and to build a trust.
00:22:15.839 --> 00:22:19.039
AI cannot build trust or build participation.
00:22:19.039 --> 00:22:23.440
It cannot accurately identify everybody or validate their capabilities.
00:22:23.440 --> 00:22:45.039
And so for me, AI is a tool or natural language, large language models are tools that allow for interpretation and wisdom unearthing, if you will, when the data is structured in a sense that's completely contextualized to what is going on.
00:22:45.039 --> 00:22:48.720
And so the intelligence can then power it.
00:22:48.720 --> 00:22:58.240
So for me, um AI is a means to an end, is not, it cannot do this on its own because it cannot get people connected to each other.
00:22:58.240 --> 00:23:09.920
It cannot just go and say it can come up with things, but how do you know what the context is unless you understand somebody in the context of what they're doing relative to somebody else?
00:23:09.920 --> 00:23:12.640
So it's the participation that it cannot do.
00:23:12.640 --> 00:23:23.839
So it's not just an AI solution where you can just solve it with AI or just do it with a search.
00:23:23.839 --> 00:23:26.079
You could, you know, you could do one-off things.
00:23:26.079 --> 00:23:29.200
Maybe it's really good at that when you specifically know what you're looking for.
00:23:29.200 --> 00:23:38.079
But half the time, uh, you know, one of our um manufacturers had a quote that says, um, um, you you know what you want, but you know you don't know who it is.
00:23:38.079 --> 00:23:39.920
You know, that's one way to look at it, right?
00:23:39.920 --> 00:23:42.960
And somebody else call doesn't always on trade show.
00:23:42.960 --> 00:23:50.640
So those things are not um uh AI artifacts, those are people artifacts, um, those are place artifacts.
00:23:50.640 --> 00:23:53.359
Um so that's uh you know one way to look at it.
00:23:54.079 --> 00:24:14.160
So so one of the one of the things that I've I've heard you we've spoken about and you've mentioned before to sort of contextualize, I think you've used sort of the Yelp example even in this poll or podcast, is you know, Bloomberg helped to organize finance and financial data, LinkedIn organize professionals and and people, et cetera, et cetera.
00:24:14.160 --> 00:24:20.960
What does you've spoken about a little bit in terms of what it actually involves, um, but maybe you can unpack that a little bit more.
00:24:20.960 --> 00:24:25.279
Um, but why do you think no one's yet done it for manufacturing?
00:24:26.559 --> 00:24:33.599
I think um so let me kind of uh unpack it and then kind of get to why uh it may not have been done.
00:24:33.599 --> 00:24:41.680
I think the first thing is um when people are talking about uh manufacturing, there's a lot of resources that exist for the top 1%.
00:24:41.680 --> 00:24:48.880
And when I what I mean by that is we talked about how majority of the manufacturers, because of the fragmentation, are small and medium businesses.
00:24:48.880 --> 00:24:55.519
So the median number could be as low as 20, you know, and uh 98% of the companies probably have less than 100 employees.
00:24:55.519 --> 00:25:10.799
So with most things that work at scale, um, you know, the way uh investment flows, it flows to things that um have the uh, you know, the the 1% with the budgets and 1% with um the information, so to speak.
00:25:10.799 --> 00:25:13.599
So that could be part of it, it's just in terms of capital allocation.
00:25:13.599 --> 00:25:15.839
That's one part of the answer, perhaps.
00:25:15.839 --> 00:25:17.279
And these are just conjectures.
00:25:17.279 --> 00:25:26.160
And then the other part could be um is likely that um our focus was uh when we think manufacturing, we never thought of it as an information and a connection problem.
00:25:26.160 --> 00:25:32.400
We probably thought of it more as um building factories where you know it doesn't pencil out, so you need to build it somewhere else.
00:25:32.400 --> 00:25:34.160
Or it was focused on national defense.
00:25:34.160 --> 00:25:36.559
You know, there are these narrow silos in which we put it.
00:25:36.559 --> 00:25:45.519
So what happens is when that when you take a narrow lens to something like this, the solutions that come, and there are a lot of great solutions out there for certain niche issues, right?
00:25:45.519 --> 00:25:57.680
There's this, there's a great, there might be great solutions for supplier sourcing, or there might be a great solution for um business sales, uh, or there might be a great solution for some private market intelligence and so on and so forth.
00:25:57.680 --> 00:26:09.440
So these are all sort of niche specific things that don't solve the whole ecosystem problem of creating this rich cluster that allows for this whole industry and the markets to go get more efficient.
00:26:09.440 --> 00:26:21.599
So I think that it's led to either solutions that are focused on the top end without much focus on the long tail, which is uh a very long tail of 98%, 99%, what that's one part of the problem.
00:26:21.599 --> 00:26:29.200
And the second part of the problem is there also it's also led to siloed solutions that work for the 1% for specific tasks.
00:26:29.200 --> 00:26:43.279
And I think um with the evolution of with our focus on this as a knowledge infrastructure to be able to enough insights and a connectivity infrastructure and rebuilding that trust and participation, um, I think is it's a much harder thing to do.
00:26:43.279 --> 00:26:46.079
You know, we're trying to recreate what happened organically.
00:26:46.079 --> 00:26:49.920
Uh it we try to recreate what used to happen just because of density.
00:26:49.920 --> 00:26:58.720
Now we're dealing with sparse um, you know, a number of companies, and we're trying to connect them across borders, across nation states, and so on and so forth.
00:26:58.720 --> 00:27:02.160
So that by its very nature is a harder lift.
00:27:02.160 --> 00:27:10.240
So I think a combination of these things um just um creates this friction, if you will, uh to solving this in the right manner.
00:27:10.240 --> 00:27:15.839
It's not for the need, because the need exists, because everybody we go talk to talk about how they wish this existed.
00:27:15.839 --> 00:27:29.519
Um, but I think a combination of capital and patience and persistence in order for this to happen, it just takes time and it's not um necessarily a clean thing that pencils out pretty quickly.
00:27:29.519 --> 00:27:32.000
Um, I think that would be my sort of a long answer.
00:27:32.000 --> 00:27:35.039
It's it's a multi-part answer because I think the answer is nuanced.
00:27:35.039 --> 00:27:36.960
Um, it's contextually nuanced.
00:27:37.279 --> 00:27:38.319
I think I think you're right.
00:27:38.319 --> 00:27:57.119
I think it's an interesting sector that perhaps somewhat the challenges of the thinning out and the others exemplify quite how it has been treated as a sector and how it has therefore led to some of the challenges that we're seeing in national bases and the skills and other things that come with it.
00:27:57.119 --> 00:28:12.400
Because if it was seen as quite a centrally core, perhaps to in the way that it is from ecosystem skills, value creation, and we'll get onto it innovation perspective, perhaps we wouldn't have shipped quite so much of it, quite so far from home over the last several years as well, right?
00:28:12.400 --> 00:28:15.119
Like we may have treated it, treated it differently as well.
00:28:15.599 --> 00:28:20.319
Yeah, I think you know, I was just gonna say uh just to put a point about you talking about Bloomberg and so on.
00:28:20.319 --> 00:28:25.440
You know, the the thing about those things with this uh LinkedIn, LinkedIn was a was purely participation, right?
00:28:25.440 --> 00:28:27.920
It came through organic participation word of mouth.
00:28:27.920 --> 00:28:29.519
That's uh an example of that.
00:28:29.519 --> 00:28:33.920
And then on Bloomberg's side, they didn't create financial information, they they organized it.
00:28:33.920 --> 00:28:42.400
And uh because of disclosure laws and so on, um, at some level, it was um, I wouldn't say any nothing's easy, but at least it existed, right?
00:28:42.400 --> 00:28:59.680
The same thing with uh real estate records in the United States, it's public record, and therefore information exists in a form that's already um um of higher um uh credibility that allows for um these intel um you know information and connectivity uh to happen more naturally.
00:28:59.680 --> 00:29:08.880
But when it when we brought up the private market issue before, and then you talk about the fragmentation, it creates the perfect combination of not just fragmentation, but the invisibility or opacity.
00:29:08.880 --> 00:29:11.839
And when you combine that together, it becomes a more complex problem.
00:29:12.640 --> 00:29:14.160
So, what do you think?
00:29:14.160 --> 00:29:24.240
I'm just gonna sort of chew those two things together a little bit and talk about this sort of thinning out that happened, this context we've just been setting as well.
00:29:24.240 --> 00:29:33.920
Um, as that happened, we lost this kind of real-world marketplace, this kind of coming together in an ecosystem that could easily access each other.
00:29:33.920 --> 00:29:42.480
And no longer, therefore, did the roads and the maps work because we were separated by by oceans or even more than that in many in many ways, right?
00:29:42.480 --> 00:29:48.079
And also it became inherently more complex, the supply chains that we work in as well.
00:29:48.079 --> 00:29:56.880
How do you see a platform recreating or reimagining that for the new era?
00:29:56.880 --> 00:30:12.720
And you've mentioned trust many times, and like how are you seeing that in the in the you know the early in the early iterations of this from an enterprise's perspective materialize in the eyes of people that are probably quite skeptical, right, when they when they first come to it?
00:30:13.279 --> 00:30:13.839
Yeah.
00:30:13.839 --> 00:30:20.079
I think imagine if we're trying to rebuild a city or build a city, you know, you can't just scatter houses randomly, right?
00:30:20.079 --> 00:30:25.680
You have to build neighborhoods and you have to connect them, kind of going back to our roads and highways and so on.
00:30:25.680 --> 00:30:30.799
And um there's something very regional about uh manufacturing.
00:30:30.799 --> 00:30:38.960
Um, that doesn't mean that they don't do global scale um collaboration, but when the physical act of manufacturing, the relationships are local.
00:30:38.960 --> 00:30:40.079
You know, it's who knows who.
00:30:40.079 --> 00:30:44.319
And when I say local, it may not just be your neighborhood, but it's people in your network.
00:30:44.319 --> 00:30:45.839
You know, people know people.
00:30:45.839 --> 00:30:51.759
And even when it comes to uh capital access, you know, how does risk get underwritten?
00:30:51.759 --> 00:30:54.079
It's not just a random score.
00:30:54.079 --> 00:31:05.759
Um, you know, uh this is an intangible business uh that people need to understand the tangible aspects of the business, but also understand that the intangibles in order to be able to lend to somebody.
00:31:05.759 --> 00:31:10.400
Economic development is uh you know cares about communities and how does workforce work?
00:31:10.400 --> 00:31:11.359
Because that's local.
00:31:11.359 --> 00:31:18.400
You know, this is not a work-from-home workforce because manufacturing, by its very nature, we talked about the laws of physics and the physical aspect of it.
00:31:18.400 --> 00:31:21.039
Um much of it gets done in a place.
00:31:21.039 --> 00:31:25.680
So place by by its nature lends itself to density.
00:31:25.680 --> 00:31:33.519
But then even if you have a few, if you connect all of them, um, you know, the person who makes uh an important component also needs packaging.
00:31:33.519 --> 00:31:35.519
Uh, they need uh tape, if you will.
00:31:35.519 --> 00:31:38.799
So it's not, or they might need a finishing that needs to come from somebody.
00:31:38.799 --> 00:31:44.640
And and you can't just ship it and wait for you know for it to come over the straits and the oceans.
00:31:44.640 --> 00:31:48.000
It needs to be done at speed and at scale close by.
00:31:48.000 --> 00:31:54.480
So I think it naturally the industry lends itself to that physical um uh ecosystem.
00:31:54.480 --> 00:32:05.440
And so for me, that that it happens naturally in regional, local uh spaces or in spaces, uh not just in some random scatter.
00:32:05.440 --> 00:32:16.559
So about the trust building, and when it comes to the digital digitization of this, we're not trying to recreate relationships digitally or replace software for relationships, right?
00:32:16.559 --> 00:32:17.920
We're trying to strengthen them.
00:32:17.920 --> 00:32:29.839
So the idea is you uh find somebody and then you connect with them, and at that point, uh the the knowledge will move uh in a in a digital sense.
00:32:29.839 --> 00:32:33.599
So you're you can't try build trust overnight.
00:32:33.599 --> 00:32:35.359
It happens through interaction.
00:32:35.359 --> 00:32:53.920
And in the way in a place where people are disconnected, um, they may not even know of somebody who lives who's about 200 miles away, but it's important to their network, you it allows digital, digital uh software or digital platform allows for that connectivity to naturally emerge, and then you could still go and uh meet them in person.
00:32:53.920 --> 00:33:06.799
So we're not trying to replace industrial communities, we're trying to connect those communities digitally so that way they can sort of uh, you know, uh somebody who's a clone uh close by or a collaborator close by somewhere that they didn't even know existed.
00:33:06.799 --> 00:33:13.279
So I think once you connect and people know and understand each other, understanding lends itself to trust, right?
00:33:13.279 --> 00:33:24.319
So our goal is to make them visible, connected, and understandable uh digitally so that way the trust kind of gets built and those interactions happen in the real world in these communities.
00:33:24.720 --> 00:33:27.279
Yeah, and I think that's beautifully articulated, actually.
00:33:27.279 --> 00:33:42.000
And I a part of the strength of getting under the skin a little bit more of these skills and specialisms and other applications is to create that those that visibility and connections that otherwise may not happen, right?
00:33:42.000 --> 00:33:50.799
And as we look at that through the lens of innovation, so net new value that we're creating, new products, new services, new ways of working.
00:33:50.799 --> 00:34:04.880
Um, you know, from a Wazoku in a sensitive perspective, a lot of that new value creation is is is by is through the recombining of skills and knowledge into a new collective whole.
00:34:04.880 --> 00:34:12.639
Often those skills in you know in the age we live in are coming from quite diverse spaces that you know they wouldn't exist in those traditional clusters.
00:34:12.639 --> 00:34:15.199
And so you've got to find new ways of putting them together.
00:34:15.199 --> 00:34:17.360
Um so what just let's talk a little bit.
00:34:17.360 --> 00:34:25.039
I mentioned earlier that that uh enterprises and wazoo are collaborating, and what I think is quite an exciting piece of it.
00:34:25.039 --> 00:34:33.039
What do you think that door opens or changes for for the manufacturers that that are being represented to enterprises?
00:34:34.239 --> 00:34:35.760
Um I think it's twofold.
00:34:35.760 --> 00:34:46.320
Um for me, uh I do believe that manufacturing is um we're going back to the point about knowledge, it's continuous knowledge, continuous learning that then leads to innovation.
00:34:46.320 --> 00:34:50.559
So innovation and manufacturing are inextricably intertwined.
00:34:50.559 --> 00:35:05.039
And um, as these companies are small, and especially with these thin clusters we talked about, uh access to knowledge, um, they may have some knowledge close by, but may not need that, may not have that particular knowledge close by for a variety of reasons.
00:35:05.039 --> 00:35:15.920
So this just opens up that space to a global network of access to ideas in order for innovation to occur, in order for learning to occur.
00:35:15.920 --> 00:35:32.639
Uh for me, the the ability to access that um in a digital fashion, to create that equal of a knowledge network and then leverage what you have locally and then combine it with what's available uh globally, I think becomes super powerful and uh is incredibly exciting.
00:35:32.639 --> 00:35:33.920
So that's one piece of it.
00:35:33.920 --> 00:35:39.840
And the other piece is um, you know, if you look at manufacturing, there's two or three, uh you can put them in sort of buckets.
00:35:39.840 --> 00:36:00.800
One is those legacy businesses where that might have been at, you know, four generations ago somebody had a great idea, patent, and then now it's become more of an operations business and scale business, where it's not necessarily somebody is filing patents every day or some new IP, it's more business process innovation and they've increased their market, they've organically and inorganically grown, and so on and so forth.
00:36:00.800 --> 00:36:09.840
So they may not have uh as much of an RD focus because they couldn't afford to, or because that's not the core piece of their um advantage.
00:36:09.840 --> 00:36:19.679
But this uh again, something like our uh partnership allows uh RD access to somebody that might not even have considered it an RD problem.
00:36:19.679 --> 00:36:24.000
Um they might just say, hey, I don't I'm not able to do this and therefore not going to pursue something.
00:36:24.000 --> 00:36:38.880
Um but if they have access in a non-friction way to something that opens up ideas for them, so then it allows them to pursue growth opportunities that they would have otherwise said no to because they didn't have that capacity or could not imagine the capacity without high friction.
00:36:38.880 --> 00:37:00.320
So I think it's a combination of two things uh that access to the knowledge networks and um that God created uh before organically because of density, and then also access to uh the RB or problem solving that you probably put on the back burner and said, nice to have, but I can't do it because the friction's too high.
00:37:00.320 --> 00:37:07.440
I think those are the kind of things where I see um uh this as super exciting for our small and medium manufacturers.
00:37:07.760 --> 00:37:08.639
Yeah, I agree.
00:37:08.639 --> 00:37:24.800
I think that there's something in that recompetent piece as well, that ability to almost say, look, if we could find three three sort of SME manufacturers with this set of skills that are willing to come together and collaborate, then we may be able to drive something true, truly new and novel in these areas.
00:37:24.800 --> 00:37:38.400
That not not not one of them may think they work in that space right now, but the three together can create sort of this this new product, new molecule, new way of thinking, new way of working that that is you know the real sort of bleeding edge innovation.
00:37:38.400 --> 00:37:44.320
And in much of the work that that I see right now, that's you know, there's a lot of demand there, a lot of complexity.
00:37:44.320 --> 00:37:47.599
And the skills are, as I said earlier, they're sort of new and sort of old.
00:37:47.599 --> 00:37:54.880
We're having to reapply a lot of the way that we understand the world, bringing in these mindsets and then reapplying them in a slightly different way.
00:37:54.880 --> 00:38:06.159
I think that whilst there's a lot of threat out there in terms of what does that mean for certain industries and certain types of talent, there's a lot of opportunity in many ways for more legacy, legacy skills at this point in time.
00:38:06.800 --> 00:38:11.119
Yeah, and to add to that, I think there's also the issue of um, let's say there's a common problem.
00:38:11.119 --> 00:38:24.719
It's not necessarily a trade secret, but there's a common thing that, you know, if we can all get together, I'm just gonna use a uh just it's just a metaphor, like say, you know, you're building a boat and there's corrosion because of salt, let's say.
00:38:24.719 --> 00:38:26.800
And there's a common problem every boat builder has.
00:38:26.800 --> 00:38:30.639
It's not that you're something special, you know, it's just a common problem.
00:38:30.639 --> 00:38:40.159
And maybe there's a way in which to have almost create commons, if you will, of collaborative solutions that can come from this larger universe of talent that everybody could share in.
00:38:40.159 --> 00:38:44.880
You know, it's not necessarily a trade secret, but it's an impediment in order for any of you to do the business.
00:38:44.880 --> 00:38:48.159
I think there's way the recombination can happen in a variety of ways.
00:38:48.159 --> 00:38:55.199
It can come from other domains, it can come from a common problem, it can come from a common opportunity, or it can come from a unique insight.
00:38:55.199 --> 00:38:58.159
You know, all of those things are possible with recombination.
00:38:58.960 --> 00:38:59.440
Absolutely.
00:38:59.440 --> 00:39:09.039
And I think you know that that idea of you know ideas being more open and more available for us to kind of co-create around those.
00:39:09.039 --> 00:39:23.440
And yes, there is protection and IP at certain parts of that value chain, but but not unilaterally across it, is a mindset that perhaps is a little bit harder for more traditional businesses that, as we said earlier, have kind of kept their head down to now get around.
00:39:23.440 --> 00:39:26.400
But I think that's where the real opportunity lies going forward.
00:39:26.400 --> 00:39:35.920
There was there was a quote that I think you shared with me recently as well from Secretary Scott Besson, when in which he argued that you cannot separate innovation from production.
00:39:35.920 --> 00:39:43.440
Uh, for someone that spent a lifetime fighting against innovation theater, I think that's uh you know, a profoundly accurate statement in many ways.
00:39:43.440 --> 00:39:44.960
We've got to do things.
00:39:44.960 --> 00:39:49.360
Um, and and that with the learning that we do comes from making these things.
00:39:49.360 --> 00:40:02.960
Um I'm sure to a degree you you agree with that point, you know, kind of unilaterally, but how do you see that playing forward um in the work that we're doing now from uh, you know, from so it's not just about talk, right?
00:40:02.960 --> 00:40:06.559
It's really about getting to value and productivity and growth.
00:40:07.360 --> 00:40:11.920
Yeah, to me, um, it's a point about innovation and production not being separated, right?
00:40:11.920 --> 00:40:17.920
And how that's tied to growth, you know, I think that you learn something when a machine behaves unexpectedly, right?
00:40:17.920 --> 00:40:19.360
It's not just in the manual.
00:40:19.360 --> 00:40:20.800
Uh a material doesn't respond.
00:40:20.800 --> 00:40:22.000
It's a humid day today.
00:40:22.000 --> 00:40:23.920
It's responding in a certain manner.
00:40:23.920 --> 00:40:25.360
So that is practical knowledge.
00:40:25.360 --> 00:40:27.119
You say, oh, I need to lower the temperature.
00:40:27.119 --> 00:40:30.079
There's too much humidity, or it's gonna not bend properly.
00:40:30.079 --> 00:40:34.159
I mean, these are things that don't happen in research labs, it happens on the ground.
00:40:34.159 --> 00:40:38.880
It's a reaction and insight that comes from feedback that's constant and immediate.
00:40:38.880 --> 00:40:40.159
And it happens every day.
00:40:40.159 --> 00:40:44.480
And we underestimate how much ingenuity there is in the act of doing.
00:40:44.480 --> 00:40:53.440
So when we ship away the act of doing and say we're just gonna theorize in isolation, you could come up with sort of um basic research, you know, that's possible.
00:40:53.440 --> 00:40:58.480
But when it comes to applied, I feel like manufacturing is applied research in a certain sense.
00:40:58.480 --> 00:41:03.360
And so for me, that's that's the reason why I believe they're intertwined.
00:41:03.360 --> 00:41:10.800
But then when we then you get inspiration from other domains and uh you see um clones like you know, talk about biomimicry, right?
00:41:10.800 --> 00:41:17.199
There's so much so much inspiration that we humans get from other things where innovation has occurred when uh we've looked at some other things.
00:41:17.199 --> 00:41:19.840
So I think that that's true for manufacturing as well.
00:41:19.840 --> 00:41:27.119
So I think that I do believe that those are intertwined and not in ways that forces and saying, oh, the future is about innovation.
00:41:27.119 --> 00:41:29.840
It's not just that, it's always been about that.
00:41:29.840 --> 00:41:38.079
And um it's just a matter of uh characterizing, you know, we can get lost in the semantics that innovation always feels that something is new and uh you know cutting edge.
00:41:38.079 --> 00:41:45.840
But innovation is really a smarter way or a efficient way or a more creative way to address a problem.
00:41:45.840 --> 00:41:51.039
And that's part of what makes us um you know who we are as humans.
00:41:51.760 --> 00:41:52.639
Yeah, exactly.
00:41:52.639 --> 00:42:01.519
And it's at the heart of all of it, it sits the idea of production and creation and getting to value more quickly, um, not just RD, right?
00:42:01.519 --> 00:42:02.239
It's much more than that.
00:42:02.639 --> 00:42:02.960
Exactly.
00:42:02.960 --> 00:42:03.599
Exactly.
00:42:03.599 --> 00:42:05.440
It's applied, you know, it's applied.
00:42:05.760 --> 00:42:06.159
Applied.
00:42:06.159 --> 00:42:08.719
Applied, applied and tangible, exactly.
00:42:08.719 --> 00:42:11.599
Um last couple of questions then.
00:42:11.599 --> 00:42:13.920
Um time flies when you're having fun, as always.
00:42:13.920 --> 00:42:14.320
Yes.
00:42:14.320 --> 00:42:21.360
Um if we wind forward, um, maybe 10 years is too long, maybe even five years feels like a lifetime at this point in time.
00:42:21.360 --> 00:42:27.119
But and and enterprises has got this all mapped and all of the integration and value creations happening.
00:42:27.119 --> 00:42:32.400
What do you think this looks like for American manufacturing in those sort of five plus years from now?
00:42:33.440 --> 00:42:44.480
You know, I think we'd have um I would love to see manufacturers become more easy to discover, to finance, to transition to the next generation, to connect with innovation, to be integrated into resilient supply chains.
00:42:44.480 --> 00:42:50.960
You know, and also young people view uh manufacturing as a place where technology, entrepreneurship, and craftsmanship come together.
00:42:50.960 --> 00:43:02.800
You know, I think the young, uh, because of what's happened, especially in the Western world, um especially in America, with the thinning out, uh, the visibility to manufacturing as a career choice that's exciting, is less apparent.
00:43:02.800 --> 00:43:10.079
I think if uh they come to view it as a place of opportunity and forward growth, career and wealth and income, I think that would be amazing.
00:43:10.079 --> 00:43:18.079
And I think if we've helped American manufacturing achieve that visibility and connection to become more resilient, I think would have contributed something very meaningful.
00:43:18.079 --> 00:43:28.719
Because at the end of the day, we're not trying to create something new, we're trying to strengthen what's um what's gotten thin and then uh supporting the American uh economy uh along the way.
00:43:29.599 --> 00:43:31.679
Yeah, and I think we're gonna make a dent on that.
00:43:31.679 --> 00:43:36.000
Like we didn't really get to talk about succession, and it's a big problem within the sector as well.
00:43:36.000 --> 00:43:48.800
But if we can if we can bring the sexy back a little bit to this space and get it, you know, get it to the innovation engine that it really is at the heart of the economy and all those things, then I think that we'll go a long way towards towards achieving that.
00:43:48.800 --> 00:43:53.280
And you know, congratulations for taking on what is not an easy task in all of this.
00:43:53.280 --> 00:43:56.880
I know the amount of blood, sweat, and tears that you guys are putting into building it.
00:43:56.880 --> 00:43:58.880
So um thank you for that.
00:43:58.880 --> 00:43:59.679
Um, as I know.
00:43:59.679 --> 00:44:01.599
Listened to this podcast before, you know.
00:44:01.599 --> 00:44:07.280
I like to end with a different question as we feed our reading list for ourselves and for our listeners.
00:44:07.280 --> 00:44:21.679
So, um, my usual standard question is any the one book that you may wish to recommend to people, either that you've read or are currently reading, that is inspiring you or challenging you in some way within this broad topic of innovation, transformation, change?
00:44:22.239 --> 00:44:29.119
Um, you know, it's it's always hard to pick a favorite because um there are so many that run the gamut.
00:44:29.119 --> 00:44:34.800
Um I um uh you know I read Breakneck by Dan Wang that many have read.
00:44:34.800 --> 00:44:38.800
It kind of contrasts, compares and contrasts China with the United States, especially.
00:44:38.800 --> 00:44:43.760
In the United States, there's a lot of talk about China, you know, how are we competing with them, how do we maintain our edge.
00:44:43.760 --> 00:44:51.920
I think it does a great job of contrasting and comparing the pluses and minuses and the strengths and strengths and what we could do better uh for both the countries.
00:44:51.920 --> 00:44:57.199
And I think it's uh it's an eye-opener to put things in perspective, especially for those that haven't visited China.
00:44:57.199 --> 00:45:10.320
I think it's um it opens your eyes to um what uh what are um you know what China has done uh well or what it can do better and what we can learn from it and how we can amplify our strengths here in America.
00:45:10.320 --> 00:45:11.519
So that's one.
00:45:11.519 --> 00:45:32.159
And then um there's another one that I started reading, which is incredibly interesting and also um uh quite about AI, a book called Intelligence by a vice president at Google Deep Mind, which was recommended to me recently, which I think is um yeah, incredibly interesting because it makes us think about um intelligence.
00:45:32.159 --> 00:45:43.039
We talked about innovation and we talked about making is the question is like what is intelligence and how does it how is how does it fit into our mission here and what it means to us as people was also very interesting.
00:45:43.039 --> 00:45:52.960
And for those interested in policy, about manufacturing policy in the United States, um Luis Umchitel uh wrote a book called Making It, Why Manufacturing Still Matters.
00:45:52.960 --> 00:45:56.800
It's a great history lesson into what happened here in the United States.
00:45:56.800 --> 00:46:04.800
And I think that's another one to pick up if uh somebody's interested in the history of how we came to be uh in the why we are at this juncture.
00:46:06.079 --> 00:46:06.559
Amazing.
00:46:06.559 --> 00:46:07.840
Three books for the price of ones.
00:46:07.840 --> 00:46:09.440
That's why I love this question.
00:46:09.440 --> 00:46:13.679
Um I always throw this at people in the podcast, not preloaded either.
00:46:13.679 --> 00:46:15.039
So three books, there you go.
00:46:15.039 --> 00:46:16.559
You must be a big reader, Deeper.
00:46:16.559 --> 00:46:21.519
Um thank you for people that are interested in finding a little bit more out about the business and about you.
00:46:21.519 --> 00:46:22.800
Um, where can they connect?
00:46:22.800 --> 00:46:24.320
Where can they find out more?
00:46:25.440 --> 00:46:31.199
I think um we are at enterprisers.com, N-T-E-R, P-R-I-S-E-R S.
00:46:31.199 --> 00:46:33.920
There's no in the word enterprisers.
00:46:33.920 --> 00:46:45.360
Um, you know, so people can check us out, and uh we hope more will join us um in our mission because I think uh we're excited at the work we're doing with you, and I hope uh we're able to bring innovation to our manufacturers.
00:46:45.840 --> 00:46:46.400
Absolutely.
00:46:46.400 --> 00:46:47.360
Well, listen, thank you.
00:46:47.360 --> 00:46:49.599
We'll share a link out to listeners as well.
00:46:49.599 --> 00:46:50.960
Thank you for your time today.
00:46:50.960 --> 00:46:52.719
It's been a really great chat.
00:46:52.719 --> 00:46:56.400
As always, thank you to everybody for listening to this podcast.
00:46:56.400 --> 00:47:05.599
The instinct is to celebrate the visible parts of any economy, the factories, the new robots, the semiconductor plants, the AI, the net new exciting things.
00:47:05.599 --> 00:47:17.039
And Deeper's argument is that beneath all of that, it sits a quieter layer, the connective infrastructure that lets manufacturers, communities, and ecosystems actually find and strengthen one another.
00:47:17.039 --> 00:47:20.559
Maybe the core of what it is to be human and the core of it is to be community.
00:47:20.559 --> 00:47:24.320
That is the layer that she's trying to build successfully, I would argue.
00:47:24.320 --> 00:47:31.840
And is a useful reminder for anybody working in innovation that you cannot connect, fund or improve what you first cannot see.
00:47:31.840 --> 00:47:33.519
So let's leave it with there today.
00:47:33.519 --> 00:47:35.679
Thank you everybody, as always, for listening.
00:47:35.679 --> 00:47:37.280
We value every single listener.
00:47:37.280 --> 00:47:38.480
Please hit subscribe.
00:47:38.480 --> 00:47:42.800
There's many more exciting episodes coming, and do check out the back catalogue, as always.
00:47:42.800 --> 00:47:43.679
Thank you.
00:47:44.000 --> 00:47:44.880
What's it worth?
00:47:45.599 --> 00:47:46.000
Uh uh.
00:47:46.960 --> 00:47:47.440
Uh uh.
00:47:48.239 --> 00:47:48.719
Uh uh.
00:47:49.440 --> 00:47:50.400
What's it worth?
00:47:51.039 --> 00:47:51.519
Uh uh.