Nic Humphries is Senior Partner and Executive Chairman of Hg, Europe's largest software investor managing assets across nearly 60 businesses. Over 25 years Nic has helped transform Hg from a small division of Mercury Asset Management into a hyper-specialised, institutional-grade platform that has consistently delivered strong returns with the vast majority of realised investments returning multiples of invested capital. Few people in European private equity have seen more technology cycles, made more consequential bets or thought more carefully about what it actually means to build a firm that compounds over decades.

In this episode Nic traces the pivotal decision to go sector-specialist in technology at a time when most of his partners thought it was career suicide. He gives a remarkably candid account of blowing up his first two investments in the early 1990s and what that taught him about the circle of competence, why he walked away from being CEO because he had passed the threshold of managerial incompetence, and how Hg's engineering mindset has shaped everything from deal execution to succession planning. He also gives the most direct and considered take on AI we have heard across this series, framing it as a once-in-20-year platform shift and an execution game pure and simple.

Key themes from this conversation:

• The founding decision to go sector specialist and why it took two years of internal debate to get there
• Why most private equity is extractive and why product innovation is the only true path to long term compounding returns
• Hg's Catalyst program, 100 AI engineers on the balance sheet loaned directly into portfolio companies
• How blowing up two investments in 1993 led directly to the inch wide mile deep philosophy
• Succession done right, servant leadership and why nobody at Hg actually wants to be CEO
• The AI platform shift, why Hg sees it as an execution game and what the portfolio is doing about it today
• Building a firm that treats investors, founders and counterparties with equal respect over 25 years

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You know, that was pretty indiscriminate at the time and it was our job to discriminate, our job to find things that were not, you know, the result of things that happened at the dot com bust and were actually going to be valuable businesses for the next five to ten years.

And bluntly we were able to do that in a period of time where most people are running scared.

The only true way to build long term compounding businesses that are growing at well above the market is essentially to launch new products, product innovation that customers desire.

This is a major threat.

You have got to be good in the new world.

However, we think as incumbrance, you know, we're the backer that's prepared to invest in product and has a whole history of product innovation at hg.

We think there's a good probability that we can actually be the leader in that new world.

Hello and welcome to reedcast, a podcast series sponsored by Reed Partners featuring founders and thought leaders in the private markets industry.

I'm your host Scott Church, a senior partner and co founder at Reed and it's my distinct pleasure to welcome today, for today's session, Nick Humphries of hg.

Nick, thanks for being here.

Delighted to be here Scott.

Really, really pleased.

I've had the pleasure of knowing Nick and working with his exceptional team at HG for well over a decade now.

And to borrow a phra of my British friends, I'm truly chuffed that you accepted our invitation.

Let me first provide a brief rundown of Nick's career.

Nick is the Senior Partner, Executive Chairman of HG and head of the Saturn Fund.

He has ultimate responsibility for HG's strategy, management and governance.

He focuses on larger software investments that provide daily use mission critical B2B applications in several end users industries.

Outside of investing, Nick is passionate about helping the planet and those who have had less of life's luck as a core supporter of the Duke of Edinburgh's International Awards, the Royal Foundation Impetus and the Nature Conservancy on hg.

Briefly, if you track tech and software, you'll certainly know the name and it needs no introduction, but.

Formerly known as HG Capital, the London based Powerhouse has evolved from a generalist firm into the largest software investor in Europe.

Now managing over 110 billion in assets.

They are hyper specialized, focusing almost exclusively on on those mission critical B2B platforms.

The kind of tax payroll and ERP software that keeps the global economy running behind the scenes.

With a constellation of funds addressing a full spectrum of EVs.

HG has backed some of the biggest names in the game like Visma, Iris Software Group and the Access Group.

They've essentially written the playbook on how to scale enterprise software at a massive level.

So, Nick, let's get into it.

It's HG has been.

Sorry, let's get into it.

HG is 25 years old and now one of the largest technology investors.

But it hasn't always looked that way or hasn't always looked like it looks today.

Looking back, what was the founding vision and how much of what HG has become was by design?

First of all, thanks for having me here, Scott.

And it's a very, very good question.

And when trying to cast my mind back kind of 20, 25 years to get where we started, yeah, things were very different.

So the brief history is we were a very small division of a large asset management business called Mercury Asset Management back in the 90s.

Yeah, we were like five or six partners, 30 people.

We managed a single fund of about 400 million.

And at the time we were actually a generalist essentially with five sectors that we specialized in, but really they covered 80% of GDP.

So for that first kind of five or six years, from 01 till 07, we pursued those five or six sectors.

And really what happened was that one of those sectors, which was tech and tech services, ended up becoming a larger proportion of the business.

It was about 50 to 60% of the business.

Sure.

So most people were just scared of technology, quite rightly, because they'd had a lot of losses.

And frankly, at that point in time, me and the small team I ran had done enough in software in the 90s to know that some parts of software are deeply scary and risky, can be big losses and big gains.

But other parts of technology, tech services could actually be pretty predictable.

They had recurring revenue streams, they had very sticky customers, et cetera.

So things that today are pretty well understood by most people in the market.

And we just had this extra knowledge from having had an extra 10 years working through those things that we could basically apply that knowledge in a period where most people were just scared and put off by technology more generally.

Yeah.

So I suspect we may, in this discussion, come back and talk about the present and AI and how AI is going to destroy everything in the world.

And of course, that was pretty indiscriminate at the time.

And it was our job to discriminate.

Our job to find things that were not the result of things that happened in the dot com bust and were actually going to be valuable businesses for the next five to ten years.

And bluntly, we were able to do that and a period of time where most people were running scared that enabled us to basically kind of make some good investments in that period.

Healthcare, consumer, etc.

Did we want to pursue that strategy and essentially be 80% of GDP, five or six sectors, and expand geographically across Europe, which was what most of our competitors were doing, or did we want to specialize?

And it took a long while.

A lot of debate.

People probably think we just kind of like, oh, it's obvious you decided to be a specialist, and you like a month or two.

But remember, for some of my partners, there's an element of like turkeys and Christmas.

Sure.

Or having to adapt very dramatically.

And so it took us probably a couple of years to kind of work through those decisions.

Ultimately, we were helped a lot by looking at the US which had been a core part of our understanding.

We'd been traveling to the US consistently for a decade at that point in time, understanding tech and the landscape.

And we could see the specialists were starting to rise in the US And I think we were probably the first or certainly one of the first in Europe to say, the specialist model will probably apply here as well.

Right.

Yeah, in hindsight, a great call, but some brain damage, I suppose at the time it was.

Yeah, it was.

It was difficult.

It was difficult.

For a lot of people, you know, I'm an engineer by background, and so the level of EQ I applied to that probably left a bit to be desired.

I was like, the stats are obvious.

It's a growing sector.

Better returns, lower volatility, better for our clients.

Nobody else is doing it.

We can be number one.

To me, the logic was super compelling.

But obviously to other people, that took a bit of time to get their heads.

Sure.

Well, under your stewardship, HG has grown into something that feels, I'd say, greater than its parts, than the sum of its parts.

A genuine institutional platform rather than just a series of funds.

How much of that was deliberate architecture?

And how much emerged from the compounding of good decisions over time?

It's a really good question.

I was trying to reflect on it.

I think it's a little bit of both, if I'm honest with you.

So because of my nature as an engineer, I always wanted to build something that had consistency and scalability.

Every single deal you did, every single investment you made was.

I used to describe it as like Henry Moore, the sculptor, going into a field with a lump of granite and a chisel and a hammer.

And like, everything was like handcrafted, you know, from the start.

Every legal document was bespoke, every deal was almost bespoke, etc.

And that just didn't feel like realistic if you're going to scale a business.

And so I've always applied a kind of engineering mindset to how can we make a lot of these things standardized?

How can we make them like a basic process so that we can actually apply most of our brain to thinking creatively about growing businesses, not about creating legal documents or about creating tax structures or creating kind of senior debt structures.

So today, a lot of that is much, much more standardized.

And it was the same with our business.

If we could find types of business model that replicated, that means we could teach people how to originate those type of business models.

We could teach people how to kind of like, prosecute the exact execute the investments.

We could teach people how to create value post investment.

And we could learn from prior experiences.

So if we're buying the same Type of things, B2B, recurring revenue software services, high gross retention, high net retention, et cetera, we could basically teach people how to learn from the prior experiences.

Whereas if you're a private equity firm that is one day doing a restaurant investment, the next day doing a distributor, the following day you're investing in a kind of industrial business.

There's very, very little that you can learn from one to take to the other.

So one model felt very scalable and it should allow you to industrialize over time.

The other model felt like it will never really scale industrialize, maybe on the kind of capital supply side.

Yeah, spoken like a true engineer.

Sorry to interrupt.

The thing we obviously didn't figure out was and where will that take you in terms of the business growing?

Right.

So we had this thesis that we could standardize, we had this thesis that that would make us scalable.

We knew that the sector we were in would probably grow for 20 or 30 years, which it has.

That's Moore's law.

And basic physics wouldn't tell us that.

Obviously what we didn't know was we'll start with a mid market fund, then we'll add on a kind of smaller cap fund which replicates where we come from in Mercury.

Then we'll do a larger cap extension.

We'll get clients that over time get comfortable with us retaining some businesses for long periods of time so we can actually scale businesses over 10, 15, 20 years, not just over two or three.

All those things came out of the second part you described which is trying to then think innovatively about what we can do in this market.

They evolved kind of organically.

Okay, so a bit of both.

Yeah, you mentioned AI, so let's go to that now since it's on.

I'm so surprised.

I know it's on everyone's minds.

We have to talk about it.

There's a view increasingly loud in the public markets that AI is going to hollow out traditional SaaS.

Seat based models get disrupted, new entrants can spin up in weeks.

You've got some nearly 200 billion of enterprise value across nearly 60 software businesses.

How worried are you about that?

We see it as a once in 20 year platform shift.

Just in the same way that mainframes moved to kind of wintel and desktop and then desktop moved to kind of SaaS and mobile.

So these things happen roughly every 15 to 20 years.

They're driven by kind of fundamental changes in kind of underlying technology, physics and those kind of things.

So we 100% believe this is one of those platforms.

And you know, by the way, sometimes you get things that appear like they're going to be that and then they're innovations, but they're not fundamental shifts.

So crypto or blockchain or these kind of things have been interesting things along the way, but they haven't been fundamental across the board.

Global platform shifts.

Right.

Those are the ones I've just described.

This is one of those 100%.

Certainly it may be the biggest ever.

That's debatable.

We'll find out in 15 or 20 years time.

But we're certainly thinking that it kind of applies in that kind of sense.

And so what we have to do is make sure that we are building and buying some of the very best AI native, which today means agentic products and businesses, and that those businesses are going to be leaders in this new AI world and buying them.

We figure out, frankly, it's not like we've got an absolute kind of pinpoint accurate investment strategy now.

And I think anybody that tells you they have is lying or just deluded because these things evolve over time in markets that are moving very rapidly.

So we're thinking very carefully about that from a new investment point of view.

We're making a number of investments that we think have a very high probability of being those new AI winners like business called OneStream that we just recently closed and then into the portfolio.

It's pretty simple.

Those portfolio companies have to become the agentic leaders in their markets.

And so they have to be great at building new products.

They have to be great at engaging the customers with that new product.

They have to be first to market and they have to be first to kind of get customer engagement at scale.

And if they fail to do that, then we'll fail.

Right.

So in that sense, this is a major threat.

You have got to be good in the new world.

However, we think as incumbents, we're the backer that's prepared to invest in product and has a whole history of product innovation.

At hg, we think there's a good probability that we can actually be the leader in that new world.

So we 100% subscribe to what the market believes, which is like AI and agentic is a major change, a major shift and we think it's an execution game, simple as that.

Our companies have already been building agentiq product for years.

In most cases they're accelerating that they're getting product in market and we got to execute on the majority of our businesses.

If we don't, we'll be in trouble.

If we do, we think we'll be in a great place with A larger market opportunity.

Okay.

Yeah.

I've done a little research on kind of the house view at HG on incumbent software.

Businesses with deep data, domain expertise, distribution, deterministic workflows have a structural advantage.

Can you bring to life maybe with a concrete example from the portfolio, a business that is mobilized versus one that hasn't perhaps?

Yes.

So two examples that I think are the most tangible.

We can talk about dozens of businesses that have got product in market, that have got customer acceptance, that have got revenues.

That's happening across a lot of the portfolio.

But the most tangible example we have investors, those investors quite like cash back.

So we sold two businesses in December, January, so literally a couple of months ago, both of those businesses got paid very large premia by trade buyers, strategic buyers and they got paid those premier because of agentic products that they developed because they were viewed as being leaders in the marketplace by their large incumbents.

Both of these are billion dollar plus EVs.

So these are not tiny things.

People were paying like many hundreds of million dollars premium for good businesses, but also businesses that had developed agentic product.

So I think best example intellirad, the business had a really strong position in software for radiologists healthcare market, enabling them to both understand, collate and diagnose images.

Clearly AI was likely to be a major impetus for that whole market.

Helping healthcare physicians, radiologists to actually diagnose better, faster, be more accurate.

Pretty proven that that's going to be a major use case.

IntelliRad have been ahead of that game because we in the management team had invested in the right kind of AI products.

They launched in the marketplace, they got customer traction, they got revenues.

And that's one of the key reasons we believe that we had two strategics competing at very high multiples.

We're talking kind of like 30 plus times EBITDA multiples versus the market today is trading at maybe 15 or 16 times for that business.

So again back to what I said before.

If you launch great AI products, if those AI products are getting customer traction, probably ahead of your competition, we think there's very big upside to a whole number of business in our portfolio.

Now if you don't and you fail and you're on a legacy product, five years from now, the opposite will be true.

Well, that's a great endorsement from trade.

So that speaks louder than anything, I suppose.

Another of HG's views I believe is that pricing will shift from seats to outcomes.

Tasks completed, labor time saved.

That's a fundamental change to the SaaS revenue model.

How far away Is that and what does it mean for how you underwrite businesses today?

I think it's going to happen at different paces in different markets and for different type of products.

And I don't think there's going to be a single this is the solution and this is the answer.

And I think in many markets might actually be a blend of something that is seat related with some outcome based as well.

So I don't think there's a simple go to, here's a solution and we see that very live.

So this is not something new.

So a number of our businesses, if you take Visma for example, which is in software for SMBs across 38 countries, Visma recognized that this was an issue years ago.

And the vast majority of Visma's revenues are not related to seats anymore.

They're related to kind of outcomes or usage or API calls or other things already.

So we've seen that happen.

But even within Visma, because it operates in many kind of products in many countries, we can actually see quite stark differences between one country and another.

So what's acceptable in one country and one particular type of customer base actually changes and is different in another country, another size of customer.

So we think it'll orientate away from seats and orientate towards outcomes.

But we think there'll be lots of different variants of that depending on what your customer base wants, what's important to them, what the product provides, etc.

We don't think there's a simple single bullet.

Got it.

Let's flip it around.

Where does AI create net new opportunity for a firm like HG beyond the portfolio?

Does it change how you source, diligence or run the firm itself?

Yeah, I mean, if you're not already adopting these kind of tools across your entire business for every single person we think you're behind.

And so obviously as somebody that is deep into kind of AI for our portfolio, it would be crazy for us not to be adopting that ourselves.

So yeah, we've got ubiquitous usage across every single person in hg.

We monitor that usage.

We're very big on rankings and being open about things.

So we literally can put up usage how people are using it across the board, show people where they are on rankings of usage versus all their peers and those kind of things.

We got some quite competitive people.

They don't want to be kind of media n bottom.

So you know, that encourages people to use it.

We spend a huge amount of time every single week.

For example, our kind of head of AI is putting around notes about how to TWEAK the usage, what best in class looks like, et cetera.

So yeah, we're applying it across every facet of our business from finance to kind of client services, client support, deal origination, deal execution, you know, PowerPoint production, investment note kind of production, checking our investment notes and our investment committee kind of decision making against it or all those kind of places.

But we're still in a lot of experimentation mode.

As with any technology that's early on, you know, is this kind of perfect in every place?

No.

Are we yet at optimal?

Definitely not.

You know, but it, but it's something we're kind of really, really heavily into.

And I mean, just put in context, we've got an operations team, portfolio support group of about 80 people.

20, 25 Of those people are AI specialists.

They were called machine learning or analytics.

If you go back kind of 10 years, they've been with us for a huge amount of time.

So these guys were already well ahead of ChatGPT, using kind of beta versions two, three years ago, well before it came out.

Wow.

So it's been a big investment we've made in the firm.

On top of that, what we've then done is build a program called Catalyst.

Catalyst is essentially us hiring AI engineers onto HG's balance sheet, using HG's money and then loaning out those AI engineers into our portfolio.

Companies that are either struggling to get the talent or need to scale the talent or frankly, you know, need an impetus and a push.

And so we got 100 catalyst engineers on our balance sheet that we're loaning out to our portfolio.

It was 80 a quarter ago.

It'll be 120 plus in a quarter or so's time.

We think that's a major kind of contribution to us being able to kind of push this agentic product within the portfolio that we talked about before.

Yeah, super interesting.

Let's talk about the operating model.

HG has been building out its value creation function for years.

Talent, finance, tech, data and AI legal, esg.

How many people is that and what does it actually cost to run?

Yeah, so that's the team I just referred to.

That's like 80.

It's probably more than 80 people now.

That is catalyst.

Okay, well, no, so two separate things.

So internal portfolio support team is the 80 people value creation group.

And that's been 60, 70, 80 people and growing for the last kind of like four or five years.

It's been going for more than a decade.

Right.

The crucial bit about that team is when most people in private equity talk about A value creation team.

They're generally talking about maybe a few kind of operators, maybe a few senior people, and then usually consultants.

And we frankly operate as a similar model.

If you go back maybe kind of eight, nine, 10 years, we shifted about eight, nine years ago to a model where essentially our team replicates the functional areas of, of a software company.

So we have a group that looks at software, go to market, and all the people employed in that group come out of selling in the software market.

We have three or four pricing and packaging specialists who come out of doing that in software industry.

We've got four or five people now in our cyber group who do nothing but cyber security.

And they come out of being CISOs, chief information security officers in software businesses.

We've got 20 plus AI people.

They come out of initially analytics and machine learning and now product development within software businesses, et cetera, et cetera, across finance, across talent.

So that's the portfolio support group that we've had for a long period of time.

Catalyst is essentially a new program in the last two, three years to develop very specifically engineering capability that our portfolio couldn't or find it difficult to develop themselves.

Got it.

And with that step change from the traditional operating partner model, what made you decide to build that internally rather than rely on external advisors or consultants as other firms do?

Because we think we're better doing it.

Fair enough.

We don't own it, we just, we want to own it.

It's so core and central to like how we help our portfolio teams create value, how our portfolio moves forward and thinks first that it's like a core part of our DNA.

That's not something we can outsource.

It's not something where we want to be reliant completely on other people.

We also use a whole bunch of specialist consulting firms as well as close partners.

So there's an extended network of probably about another four or five hundred people, including another kind of 30, 40 people in AI in Central Eastern Europe, including functional specialists in other areas.

So we do use consulting firms, but they're an adjunct and a resource that our portfolio team use.

They're not a replacement for that core portfolio team.

Got it, Got it.

And I guess back on the value creation team, how do you measure their success?

Is it in EBITDA improvement, revenue growth, NPS scores, and what does good look like?

Can you put numbers on the best outcomes?

So revenue growth, which translates into kind of EBITDA ultimately and ultimately then translates into us delivering capital back to our clients at premium values.

Pre is focusing exclusively on software.

And then you go back to the examples I quoted of selling G, treasury, selling intellerad.

Why did we get Premia?

We got Premia because they developed leading products in a new market, AI market that is partially catalyzed.

Not totally because of course the management team did great jobs as well.

But that's partially catalyzed by Catalyst and by our portfolio team pushing those agendas.

12, 18, 24 Months ago, those products didn't get developed in a month.

They got developed because people were thinking about this 18, 24 months ago.

We think that puts us as number one in AI globally in terms of PE firms.

We can't see any other PE firms that have actually generated billion dollar exits because of AI products that they built.

So we think there's a pretty direct link between what our portfolio team does, the products that get launched, and then the end value that our clients have already seen in cash.

Yeah.

As a fundraising advisor, I love that your first instinct is to answer that question.

With performance returns to investors and risk.

Dpi.

DPI is king.

That's great, Nick.

We've trained you well.

Our clients definitely have clients.

Definitely.

You listen to your clients.

That's key.

Is there a category of intervention that moves the needle more than anything else?

If you had to pick one function, say talent, finance, tech, AI.

Where's the clearest return on investment?

Product.

Investment.

Product.

So product investment, we think it's like a really simple equation.

I'm going to make a very bold statement here, but most of private equity is an extractive industry.

They basically take an existing business with an existing set of products and they extract more value from it.

That sounds great.

Sales go up.

There's a crude way of doing that.

So the most extractive is I've got a sticky business with sticky products.

I whack prices up, have more than inflation.

That's pretty crude.

That's like the guys who are still doing cost cutting a lot do that as well.

Right.

The more sophisticated version is I'm actually really good at understanding territory, planning, commission planning, sales, incentivization or I'm really good at thinking about how I expand into other geographies or into other adjacencies and I actually expand the market for my business which is actually pretty creative and actually less extractive.

But even that is essentially take an existing product set and taking more value out of it over time.

Correct.

The only true way to build long term compounding businesses that are growing at well above the market is essentially to launch new products.

Product innovation that your customers desire, that customers are willing to kind of pay a fair price for and you're going to extract a fair price, not a user's price for.

And so that's really where all of our orientation has been.

It's not an accident that that's kind of how engineers would think because most of us are engineers.

And so for 15 plus years we've really orientated most of our thought process kind of business we back and our value creation process as to kind of how do we kind of keep customers having new products.

It's a classic.

If I had my phone with me, I've left it outside, I'd hold it up and go like if this wasn't an iPhone 16 or 17, it was an iPhone X, you wouldn't be buying it.

You don't want the one that's seven years old, you like having the three lens camera, et cetera.

So it's all about, you know, not radical change but being able to consistently put good new products into the marketplace that your customers want.

Makes a lot of sense.

That's where we want to take.

And of course AI directly fits into that.

So the answer in current day terms will be AI.

But actually 10 or 15 years ago the answer was build great SaaS product, don't have legacy crappy on prem products and don't be satisfied with that.

If you buy a business with that you have to have a plan to convert it to SaaS.

But actually ideally don't buy an old business like that, go and buy a modern new business.

So we've been practicing this for 15 to 20 years.

Amazing.

The stackpretees idea.

Stackpretees, I think that's your word actually.

That was quite a small.

Is that a Reed invention?

We'll take credit if you're going to give it the ability to apply pattern recognition from owning say visma, Iris team system and access across the same cluster.

Is that something you can actually systematize or is it more of an art?

No, I think it's systemizable.

I think it's kind of like something you can learn from and apply and people can apply consistently across all parts of the business.

And it actually works both ways.

So it's not just taking the bigger businesses that are more mature and taking some of the things they're doing and passing them down.

We definitely do that because Visma's got 4,500 engineers.

There's a lot we can learn about the literally hundreds of AI projects that Visma are running at scale.

And we can apply that further down our portfolio in Genesis and Mercury.

But of course it's also the other way, which is businesses in Mercury are fast moving.

One or two products, usually highly innovative, usually got great founders because that's what we look for, really innovating on product and customer.

And so we can take ideas that we're seeing there at a smaller scale, maybe operating quite fast like a speedboat, and think about how they apply up the chain as well.

So it's a kind of two way flow of ideas kind of information.

And we spend an enormous amount of time and effort trying to look across the entire 60 companies.

We spend a lot of time getting them together.

So we run CEO forums, CFO forums, CTO forums, CISO forums for every function, as well as having kind of conferences three, four times a year for everybody in the store, C suite, and trying to get people to not just kind of communicate through us and us show the businesses what everybody else is doing, but actually building really good links.

We don't expect every one of our 60 CEOs to be in constant contact with the other 59.

But if they can kind of find two or three or four people either in the same sector or same geography that they want to pick the phone up to, to kind of bounce ideas around.

You know, being a CEO can be a lonely business.

Having two or three people in the network that you feel you can call have got similar type of business to you that you can learn from or pass thoughts back to, we think it's just a super powerful kind of network effect.

Yeah, absolutely.

Well, the stack clearly gives HG something unusual.

You can follow the company up the EV curve across fund generations.

Can you walk us through what that looks like in practice?

I mean, is that a competitive advantage?

Does it create conflicts?

Maybe a bit of both.

And how that's managed,.

I mean, simply from our point of view, we invest in funds that are linked to size of business.

Obviously there's Mercury, Genesis, Saturn, Mercury, small businesses, Genesis mid market, Saturn kind of upper mid market.

And the way we orientate from a fund point of view is really driven by what we think our clients want.

So we think our clients like to understand this is a smaller cap fund, mid cap fund, larger cap fund, etc.

LPs.

Yeah, investors.

And for them having a dedicated team for each of those funds where we can go.

So we think that's helpful from a client point of view.

When you go into the market, actually what management teams care about is do you understand my business?

And that's not just about size, it's often about segment or cluster.

You know, I'm in accounting for small businesses or I'm in healthcare software, you know, for radiologists, etc.

And so the way we actually orientate our business from a point of view of the end market is the teams within each of those funds.

So Mercury, Genesis and Saturn will all have healthcare experts because we want to be in healthcare software and those healthcare experts exist across each fund.

They work together in that cluster.

So basically we can have people at the mercury level who'll be raising really interesting ideas that they're seeing Even at like 1 or 2 or 3 million of arrows, small businesses and saying this is relevant not just to kind of Mercury sized businesses, but it could be a product opportunity for Saturn sized businesses.

It could be an acquisition for Mercury or Genesis or Saturn.

So they're kind of constantly raising things across that stack.

Conversely, people at Saturn may have links into some of the very biggest strategic acquirers.

Sure.

GE Healthcare, for example.

That's super useful whether we're selling a business for a Saturn or Genesis or Mercury.

So we find having people operate our investment executives operate across that kind of like sector is most effective.

And being able to kind of COVID everything in the waterfront from very small businesses to very large businesses has been a big advantage for us over time.

Yeah, super powerful new development at hg.

You've recently hired a secondaries team to explore that market.

That would be a different posture.

You'd be a minority investor relying on another GP's control and governance.

For a firm that's always been a control buyer.

What would have to change in the way you think about investing to make that successful?

I think our main posture is as a control buyer.

Historically we've been a majority in most of our deals, but we have actually done about a dozen deals investments where we've been a minority and that's been a minority either alongside another GP or it's been a minority alongside a founder.

And so we're pretty relaxed about having either a minority or a majority.

What we're driven by is the quality of the counterparty and a consistency of alignment between us and that counterparty.

So we don't mind it all being a minority as long as we're open and aligned with the other kind of majority.

I think for a secondary product, clearly we're very, very, very clear that we will be a minority and somebody else is leading that deal.

And it's super important that that's clear for the management team.

It's super important that's clear for the other GP as well.

They want that to be the case.

I think we've got good examples in our existing portfolio where we've been fortunate to come into deals where somebody else led it.

And we've been, I think, very respectful and very open with our LPs about the fact that this is somebody else's great deal and we've just been super fortunate to come in on the back of it.

So IFS is a great example.

We're delighted to be partnered with EQT in that business.

But let's be clear, EQT were the really smart guys who got into it before we did.

Right.

So we've just been fortunate to become part of that journey and we're very appreciative to EQT for, and our management team for bringing us in.

So I think we'll adopt exactly that stance.

We're very clear about our position.

It's not a surprise we know exactly what that is.

And then we have to act like a kind of minority, respectful party for the majority owner.

What we will do, I think, is offer something that a general secondary investor can't offer, which is deep expertise and understanding of the company, probably because we're going to back companies we've known for a while and we've respected in markets that we've operated in for decades and we respect the cluster strategy and software.

So I think we'll bring a level of understanding and ability to price transactions and ability to frankly underwrite the entirety of a transaction, even at scale that a lot of existing generalist secondary players can't do.

And then on top of that, we'll have a range of kind of value added services from our portfolio team of 80 plus people that we're willing to provide for those kind of new investments in the secondary fund.

But it's entirely up to the management team and entirely up to the prime sponsor.

Whether they want to take advantage of those or not.

They'll be there, but it'll be a pull model.

If they don't want to take any of it, no problem from our point of view.

If they want to Take all those services which can include things like we're one of the largest customers for some of the big LLM model providers.

That means we get rates with them and with large hosting companies that you can't possibly get as a smaller cap investor.

That's a very simple one.

We can offer at a better rates and therefore reduce cost for businesses.

Or it could be to the extent of being able to provide our catalyst team and some support in terms of AI thinking, engineering and a few things in between.

So we'll offer those people want to take them up, that's great.

If they don't, we completely understand as well.

Okay, well, you've very thoroughly answered my next question about why a GP would choose HG Co investor.

So thanks for that.

Over 25 years you built what looks like one of the deepest GP to LP networks in European private equity, if not global.

You've bought from these people, co invested with them, sold to them, competed with them.

What is that relationship currency actually worth?

We think, I mean it's almost like immeasurable in the sense of we think we can learn from a lot of people.

We're not a group that thinks we know everything by any means.

And so there's some incredibly smart people in other private equity firms.

They demonstrate it with returns that are similar to ours and very good returns.

They generate those returns in slightly different ways.

And so we've never had this kind of attitude of like it's our way of the highway, there's only one way of making money.

We think there are loads of ways of making good returns for clients and we happen to have one that works well for us and hopefully clients like that.

But we think there are plenty of other models that we can learn from.

So I'm not going to name firms, but there's like dozens of firms out there that we look at, we respect, we like working with because we can think, we can learn something and hopefully we can kind of reciprocate and it's a mutually beneficial relationship.

So we're not just taking from it, but we like working with other people provided we've got some of the basics sorted out.

So it's like fundamental that we don't want to be a single digit minority investor where somebody can't quite remember our name or our telephone number that's not of interest to us.

We don't want to be in series F, blah blah, blah.

We want to be a major kind of contributor on the cap table and we want to be somebody that is going to work in hand in glove with management and the other investors.

And then we need real clarity on alignment, on objectives.

And so again, the benefit of being around for 25, 30 plus years is you've seen these go wrong, you've seen when these things don't work.

And it's usually because people didn't have open, frank, hard conversations at the start.

And so, you know, we try and have adult conversations, you know, with counterparties that we think are similarly kind of mature and experienced about where the kind of misalignment could come about, how we're going to solve that, you know, those kind of things.

And so, you know, we found that as long as we do that and as long as we've got a counterparty that we built relationships with at multiple levels, typically over decades, these things can work kind of super well.

And they've worked very well with, as you say, you know, probably at least a dozen different firms.

So, you know, we like partnering, you know, when it's productive, when it works.

We obviously don't like the five way deal where four or five people have clubbed together and nobody's really sure who's got a seat at the table.

So we've never done those deals and we never will.

Okay, clear, what has driven that level of investor demand and did you expect to build it this quickly?

No, we didn't.

We were modest in our expectations, which I guess is a kind of character trait of ours.

We try and take things gradually.

So whenever we're going to do things, we always want them to be at decent scale, otherwise there's no point.

But we're very kind of disciplined and we're kind of very long term about it.

So for us, scale over 10 years is important.

Taking it really steady in the first two or three years and building and learning is also very important.

And so we set modest expectations and Martina and Katie and the whole team around them in wealth has done a fantastic job of significantly exceeding those expectations and actually getting frankly a kind of group of investors from family offices, individuals that have had a relationship with us in the past, maybe as chief executives or management team members, and made money that way, and also some particular kind of institutions, which by and large is probably a network of people that we knew before, but they weren't clients or they weren't consistently clients with us.

It's actually opened up an aperture on a new set of relationships which have become more meaningful for us.

And we think that'll actually possibly extend across other aspects of our business.

You know, people that are in a wealth product as investors could well end up becoming kind of clients in the institutional side over time.

If they're a family office or they may be a source of investment origination flow, they could be people that we want to bring onto our boards.

So actually we're finding it can multifaceted.

That's great.

As you explore the secondaries market now too, how do you ensure that adding products doesn't dilute investment quality or create conflicts across the platform?

And how do you manage the different needs of say private investors via HG wealth versus stack investors?

Yeah, it's a really good question and a complex question that we're very conscious of and we spend a lot of time trying to think about how we avoid conflicts and how we basically make sure that we're fair to every one of our investors onto the quality problem.

I think that's just in our DNA to be honest with you.

So our DNA is all about trying to be the premium return source.

So being somebody that is differentiated from the larger completely kind of over everything cult asset names in our industry, we have to differentiate ourselves with returns, the quality of those returns from some of the biggest names in the industry.

Otherwise y comb to get hg.

So it's the kind of Ferrari, Porsche, Hermes type strategy.

That's how we think about our business and where it's positioned in its marketplace.

So that central lens has to be about investment strategy, investment quality that runs through absolutely everything we do.

So we are never going to launch a fund or a product that we don't think we can get to be absolute premium and amongst the best in the world at simple as that.

So for example, we don't do credit, generic credit at scale.

And the rationale, we've looked at that many, many times our rationale for not having that is that we don't think we could be differentiated.

We don't think we can be clearly number one at doing that.

We do think in areas like secondaries, taking a long period of time, a decade, we think we can build a business that will be absolute premium on a global scale.

At scale.

Yeah.

Makes sense on wealth.

When you look at say Blackstone and KKR and what they've built in wealth management aum in the, I guess hundreds of billions from retail to semi institutional capital.

Is that where HG wants to be in 10 years?

Say no.

Okay.

I think a we're pragmatists and realists as well as, you know, ambitious and I think it would be highly, highly unlikely we could do that even if we wanted to do it.

They have a brand And a scale and a bunch of other things that kind of come from history that, let's be realistic, we don't have.

Could we put an enormous amount of effort into trying to do that?

Possibly.

I don't think that's really where our business needs to be or wants to be.

So we think wealth will be an important part of the mix in terms of funds flow to us.

As I say, it's important to us for the other ancillary reasons we talked about as well.

We don't have a particular kind of target in mind.

Will it scale from where it is?

Yeah, we believe it will.

Will it probably be kind of like somewhere in the kind of 20% plus of our business, which it kind of somewhat already is.

If you put all the different aspects together, that will probably be the case.

Yeah.

But are we going to have the scale that a Blackstone or kind of KKR has?

Highly, highly unlikely.

Okay.

Is this business genuinely scalable?

Are you approaching a ceiling?

So we're not so far, and I don't so far see a reason why it shouldn't continue to scale at a reasonable rate.

Is it going to grow at like 20, 30% a year?

Definitely not.

We never planned for that.

But is it the kind of business that because of end markets growing, can grow at, you know, a few multiples of gdp, maybe kind of like double digit plus, we think grow at that kind of rate and we can manage and sustain that kind of growth.

So we're not trying to triple, quadruple, quintuple the size of our business, but we do want a growth business that's going to grow at roughly those double digit rates because that creates both more opportunities for our clients, more opportunities for our internal teams, and it means we can frankly can back more great businesses.

So we think it can continue to grow at those kind of rates.

And if you actually look within the kind of software and tech and AI universe, because that end market is growing, so both the number of companies and the revenues within those companies are growing at multiples of GDP, typically kind of minimum 7 to 10%.

Because we're in a growth market.

It's not like we're trying to take more and more share.

Exactly.

Frankly, with what we talked about in AI, we think there's a whole bunch of generalists, software tourists that are going to get out of the market because they see it as scary, they don't know what to do, et cetera.

And so if you look at a growing market in terms of the types of business we talked about and you look at a competitive set that probably was increasing all the time, but probably half of that competitor set were not specialists and therefore frankly going to start questioning their judgment.

We think actually the dynamics of who's going to gain more share, who can do some more investments is probably going to favor us and some of the other specialists that we operate against globally.

Yeah, I can see that you have an exponentially exploding tam.

And what's the effect of AI for those businesses that do launch successful AI products?

It's a TAM expanding business because AI is essentially going to enable what was a software business only to start to kind of eat into and take some of what were services or people based revenues.

So for those business that are successful in AI, whereas before your TAM was X, which is, let's say an average business spends about 5 or 6% of its revenues or its opex on software, it spends probably 60, 70% of its revenues on people.

AI is going to enable you to expand that kind of software share from 6% to.

You tell me.

We don't know, do we?

5% More, 10% more, 20% more.

If it's 5 or 10 or 20% more, you know, that's a doubling or tripling, a quadrupling of the TAM available for what our SaaS businesses.

That's interesting.

Yeah.

The opportunities are boundless, it would seem.

And you won't have to sacrifice performance.

Right.

If you can continue to be selective.

Yeah.

What we do agree is that scale generally means performance is likely to come towards the mean.

And so again, even within our larger cap businesses, what we have is almost a barbell approach as we call it, which is about 20, 25% of the capital in a large cap Saturn fund is put into very big businesses, 10 billion plus businesses, which we think are absolutely exceptional.

But we're talking about two or three of those in a fund, less than one a year in a fund.

And we think we can find one business a year at that scale that is truly exceptional and defies these kind of like reversion to the mean norms.

The other 70, 75% of Saturn and all of Genesis and all of Mercury is going into mid market deals, deals at a billion EV or below.

And those businesses are typically 100, 200 million of revenue.

These are not enormous businesses on a global scale.

They're still mid market businesses and they can scale at 15%, 20% per annum.

Yeah.

If you look at our total portfolio, 60 businesses, somewhere between 190 and 200 billion of enterprise value dollars and that business in total is growing Revenues at more than double digit organically over the last four or five years on average.

And it's growing profits at more than 15% organically.

So these are growth businesses.

And that growth, think about the fundamentals is that growth that drives performance.

This is not leverage, it's not multiples and those kind of things.

It's the underlying growth of profits.

Basically.

Before we leave platform and sort of firm management, I just want to circle back on one of the things that's been central to the the institutional quality of the firm's leadership and succession.

HG recently transitioned this co CEO role from Matt Brockman and Justin Von Simpson to Steve Batchelor and J.B. bryant, two people who between them have spent over 35 years at the firm.

What made that transition feel like the right moment and how did you think about continuity versus renewal?

Yeah, so for us, our core raison d', etre, for me, for Matthew, Justin, for Steve Jobe and many of our partners for kind of being in business is we want to be investors, we want to be making premium returns.

That's why we started doing this.

That's why we still love doing it.

We love getting out there with entrepreneurs and building businesses.

So to be honest with you, none of us really want to do management.

I, I quoted at LP the other day.

But essentially that's not, you know, management is not really in most of our DNA.

Right.

We do it because of course we have a business of 400 plus people and of course we have to manage it.

But we almost see it as an obligation that one or two partners have to take on at some point in their career because we obviously need leadership.

But it's almost a kind of like servant type leader role.

It's serving your time.

We're doing this because we're serving our time.

We're doing this because the organization needs it.

And so people take that on for a period of time.

Typically it's been about eight years.

I did it for 10, Matthew did it for eight or nine.

Steve and JB will probably do it for kind of like anywhere between 5 and 10 years as well.

And then they'll hand the bat on that allows us to then promise them that they can come back to what they love doing, which is investing.

And that's exactly what I've done.

Intend to be probably till they stick me in a box.

Matthew is still full time, a cio.

Justin is still full time as one of our most senior highly performing investors.

So that's the bit we love, that's the bit we want to do.

But you have to do some management at some point in time and we unfortunately have to pick a couple of people to do that.

So I'm sorry to Steve and JB that they've got it, but they'll get back to the job they really love later on.

They're doing a great job.

It also of course by having this kind of serial kind of rollover of management, it gives you a chance to refresh, it gives you a chance to get new ideas through the business.

You know, some people could be great as a CEO for 30, 40, 50 years.

Certainly that wasn't me.

I don't think Matthew and Justin think it was them.

You know, eight to 10 years is a period where you brought most of your good ideas to the table.

And actually getting some fresh ideas on the table is really good for the business and healthy, we think.

Yeah.

Makes a load of sense maybe switching to career learnings.

Nick, you've had a long and super interesting career.

You've seen multiple technologies cycles, the dot com crash, the rise of sas, the post Covid software boom, the current AI inflection.

What have you learned about making long term bets in an industry that changes faster than any other?

I think, you know, one thing is just to have a kind of philosophy of, you know, you never know everything.

A philosophy which is about kind of continuous improvement.

And so probably the kind of number one underlying trait is a belief that we're always going to have things we can improve.

And whether it's talking to clients or talking to people like yourself, or talking to management teams, if you kind of like close this a little bit and open these a little bit, people will tell you in a nice way things that you could improve your business.

And if you're open to that, it creates multiple things.

A it gives you some pretty simple problems that are maybe a 2% or a 1% or a 3% improvement, you do two or three of those every year, you improve by three or four or 5% every year.

So I think that's kind of one of the underlying traits, which means there's always things to kind of learn and improve on.

It also creates this culture where everybody from clients to kind of external parties to internal people at the most junior level are encouraged to bring problems up because you get a kind of history of being pretty good at solving problems.

So we're not afraid of people bringing problems up because we've got a really good history of proving we can solve them.

And it encourages open thought, open speech, etc.

As you get bigger, you have to keep repeating that.

You have to keep instilling it in people.

It doesn't become any easier to encourage people that.

That's true, but we have to kind of try and live that as closely as we possibly can.

So I think that's probably like one of the number one learnings is that by applying that philosophy consistently, the problems that you raise are, of course, are very different.

So different problems you've learned from along the way.

But I think it's that kind of underlying philosophy that has kind of helped.

Yeah, that certainly speaks to culture.

Right.

And mindset.

And I'm hearing a lot about constant improvement and self awareness and humility.

And I think those are aspects of the HG culture that I've seen.

Yeah, we in lots of different ways, some quite sophisticated kind of like measurement of traits and personality and those kind of things.

Some just very basic kind of human openness.

And so what do I do?

Like beat myself up about it?

That didn't really work.

You know, kind of like pretend I am a good manager.

That would be like, not very satisfying for me and probably very dissatisfying for most of the people I'm working with or say, actually, I've got a great couple of partners in Matthew and Justin, and they're really good at doing this and let's let them do what they're good at and I'll go off and hopefully do what I'm okay at, which is trying to think about some strategic expansion into SAT and other things.

So being very open with each other about, you're strong at X, I'm strong at Y.

Why don't we just be open about that?

Then we can work together and we'll be super effective.

I know that sounds like really basic mother and apple pie kind of stuff, but it's just kind of.

That works for us.

It's worked all the way through our careers.

That's great.

What's the investment decision in your career that kept you awake the most, and what did you ultimately learn from it?

To be absolutely honest with you, I've been super fortunate that I don't really have many things that keep me awake.

I'm just, like, not one of those people.

I sleep really, really well.

I'm comfortable with the fact that, like, we're in a risk business and sometimes those risks, you know, don't go right, and you have to kind of live with that and then go and kind of fix it, basically.

And because I've had quite a long career, I've made lots and lots of mistakes, and I've had lots of things that I've been able to fix and a few that I haven't, you know, but overall, it's been okay.

You know, the risk rewards been okay, and the level of volatility has been better than the industry average.

And so, you know, things have.

Things have worked out all right.

So I'm very fortunate in that kind of sense.

I would say if I picked a couple of highlights, you know, back in, like, very early in my career, kind of like 91, 92, 93 of the first four or five investments I made, I blew up two entirely, like, zeros, what they call donuts.

Private equity world.

They were fairly small, less than a million dollars of investment, and I essentially got ripped off by management teams that knew I was naive, knew I didn't understand their business well, and took advantage of me being young and stupid.

And number one, I found that a real affront.

I mean, in a way that deeply didn't hurt.

It just made me very angry.

I. I won't tell you what I planned to do.

My wife persuaded me not to do the things that I planned to do.

But what I did decide was, like, this is entirely my own fault.

Yeah, they took advantage of me, but really that's my fault for being stupid and naive, and I'm not going to be stupid and naive about those things in future.

So both the businesses had large amounts of stock and work in progress, and EBITDA was essentially fictional, and cash flow was way below ebitda.

Because essentially they were inflating stock values and work in progress values, et cetera.

And I was naive enough not to be able to understand the difference between EBITDA and cash flow.

What was I going to do about it was a key question because I've got to change some kind of behavior.

I sat down and concluded, what's the chance that I can become really good in different industries valuing stock and work in progress?

Because that's what it boiled down to.

How do you value stock and work in progress?

And there's very, very little probability that I could be good at being an expert in valuing stock and work in progress in a multiple of different industries.

So I just concluded, don't do investments in multiple different industries.

Pick one, software tech.

And number two, don't invest in business that have stock and work in progress.

That's why you have subscription software where you get paid annually in advance.

And I just decided it's the Warren Buffett circle of competence.

I couldn't understand certain things.

I didn't think I was capable of understanding certain things.

So I just admitted my frailties and said, I just won't do that.

There's enough of a market that doesn't have those characteristics, I'll go do something else instead.

And I've kind of applied that similar thought process to most of the kind of key decisions.

You know, first of all, this is Jim Collins goods, great stuff, you know, admit what's wrong, get to the absolute baseline of like what's wrong and confront the brutal facts.

The brutal facts were I'd got ripped off and it was my fault.

Number two, was I capable of changing that?

No.

In that case, so that's a brutal fact as well, you know, and then three, what are you gonna do about it?

And once you've got to that kind of base level of like raw granite concrete foundations, you can usually build from there and find some something you can do.

But too many people in life basically spend their time bullshitting themselves and don't get down to the brutal facts of like, it was me, it's my fault, what I've done wrong.

And I've applied similar kind of philosophies kind of like all the way along through hd and we're still learning by still making a few mistakes.

And we'll be applying those same philosophies in the next few years, I'm sure.

Well, that's Great.

Nick, maybe just to bring this to a close, would love your thoughts on 25 years from now.

What do you hope HG is remembered for?

Number one, great risk adjusted returns for clients.

That's all that matters.

That's our business.

Number two, doing that in a way that is basically building some really successful businesses with great entrepreneurs that actually kind of like ours as a kind of partner.

And number three, extending that to kind of wider network.

There's no reason at all why we can't do that alongside other GPs, other friends that we've known for 20, 25 years and be a good counterparty.

So essentially being a business that treats everybody, investors, CEOs and entrepreneurs, other counterparties with a huge amount of respect and therefore we have a good time, they have a good time working with us, we have a good time working with them and the things are going to mutual win win.

That's what I like.

Super successful at scale.

Good stuff.

Well Nick, this has been an absolute pleasure.

Really appreciate your time and you're sharing some great insights for our audience.

So thank you very much.

Not at all.

It's been great.

Enjoyed it.

Thank you, thank you.

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