ADP's Usman 'Oz' Khan on How Big Companies Use Investment to Enhance Product Lines

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co.uk slash podcast to get started today Welcome to PeopleTech, the podcast of WorkforceAI.news. I'm Mark Pfeffer.

And my guest today is Usman Khan, who often goes by the name Oz. He's the Senior Vice President at ADP Ventures, and they're the corporate venture and incubation organization at ADP. And not surprisingly, they focus their work on products related to work in the workplace. I'm going to ask him to explain what all of that means But let me start by saying, Usman, Oz, welcome It's great to meet you Thank you, Mark Great to be here and great to sit down with you So let me start with, tell me about ADP Ventures And I guess the question I've got is, you know, what's the point?

Why does a company like ADP get involved with investing in new companies incubating companies and all that? That's a great question. And it would be remiss if I said that, I don't think about that myself, I wouldn't say every day, but probably at least once every week in terms of, hey, what is the value that we're bringing to this, you know, awesome, large, you know, market leading company with a 75-year legacy? And I think there's a short answer and there's a long answer.

I think the short answer is that organizations need to play to find the next thing that is going to drive value, to discover. And functions like ours are there primarily for that, is to basically give them creativity, to give them market reach, insights, and a view into what's coming next. And so that is the short answer. I think the long answer can go into a number of different directions, right?

Like I think you want to follow that methodology of having a very, very strong core that generates revenue, value, profit. But then you want to invest in making bets. And some of those bets are going to be very large, outsized, well-proven ones. And some of those are going to be slightly riskier bets that might be smaller in nature and they're more probes to experiment and augment what you're doing.

And so that's where typically corporate venture organizations live. Oftentimes they tend to be monotone. You either have a product lab or you have a corporate venture fund. I think the interesting thing with ADP Ventures is that we have both.

We started out with the incubation lab and we've been doing product incubation and venture building for almost a decade now. We were told by Global Corporate Venturing that we one of the most successful ones in the Fortune 500 not because we lasted this long but because it hasn been a series of science experiments We built some very very large sustainable businesses that generate over nine figures in annual recurring revenue for ADP So, you know, this method of like starting with an idea, testing it, seeing if it works, if it works, scaling it into a business and then graduating into ADP.

And then the second motion, which we started two years ago, actually almost three years ago now, is we started a corporate venture investing fund and a partnerships function. And so the intention there is not just to invest in early stage companies in HR tech, but also partner with them. Partner with them at a deep and meaningful level where we actually co-build solutions together. And so when you think about both of those motions coming along and really focusing it on the future boundaries of where your products live today, it starts to create a lot of paths and optionality for ADP.

And that's like the fun part of what we do, right? And so, yeah, that's the long answer. So I'll give you a short one and a long one. It's interesting, though.

But I'm wondering, like, what's your process? How do you identify the companies or the ideas you want to invest in? So our process has evolved over time, but I think the core DNA of it is we typically tend to have an ideation and analysis cycle. Sometimes it just happens several times a year.

Sometimes it happens, you know, maybe once or twice a year in conjunction with product organizations and business units at ADP do their strategic planning. And that's where we look at what the largest fringe opportunities for ADP might be that existing core teams don't have bandwidth for, right? And so you look at those, you stack rank those, you look at market signals, you want to have a team of professionals that know the space, that know the industry, that are able to do the analysis and just also use a lot of judgment to figure out what ideas are the most valuable.

And then you make some hard decisions on which ones to go after, right? From a venture studio standpoint, those decisions, they tend to be less frequent in nature because you only have so much bandwidth that you can leverage your engineers for. On the venture investing side, it's actually a much more bigger aperture, if you will, because there's a lot of companies. There's a lot of really smart people out there building really cool companies.

And I think figuring out which ones are the right ones for you, which ones are the right cultural fit for your organization, how to stack rent them and how to like that. That's like a continuous cycle. So we're always like taking this notion of what might be important for the organization and just marrying it with a ton of market insights, its reach and just sitting through it. I think it's just like, you know, exercising.

It's one of those things that you have to build muscles for by doing over time and maybe learning a couple of hard lessons. But you have to turn it into like a real motion that your organization does. Otherwise, it just becomes like a series of one-off experiments that, you know, people don't do well with, and that's the end of it. Right, right.

And you're looking for, you know, operations or products that can contribute to ADP overall. I mean, you've got a pretty wide suite of products and platforms. And so I guess it fair to say that you know you looking you know for projects that can strengthen what you got or start you in a new direction if there a new technology around Yeah, absolutely. I think there's a couple of dimensions.

One is scalability, right? When I say scalability, scalability to our customer base is very important, right? Can you bring this to our million-plus clients? Obviously not all of them because, you know, we have different divisions that have different product suites.

But can you bring it to a broad swath of your client base and actually have it either be a value creator or a real differentiator? And I think the win-win there is you, when it's an internal build, you know, it's like you've organically built something that is intrinsically valuable to ADP. and then, you know, like ADP Marketplace, which we incubated back in the day, is a very large and scaled business, which is very core to how we do, you know, how we go to market. Buy ADP for your core needs and then you'll buy, you know, marketplace partners to extend the reach of ADP.

And so that can create a ton of value and you wouldn't have, you know, the Work Personnel team, for example, come up with ADP Marketplace. But to your question, I think that's what brings reach that's what brings scale. And then when it comes to the venture investing side, I think it's like, you know, you have to think about what problems our customers have that our products would like to deliver but don't have the bandwidth to deliver. And so that's where investing and partnering deeply can add a ton of value.

And I'll give you an example there. We invested in a company called Naya. Naya is a, I'll describe them as a benefit system of action, right? So they connect with carriers, They connect with brokers and they connect with HRS systems such as ourselves.

And they sit on top of all this benefits data and help employees make better selections on their benefits plans. And they also have very strong capabilities on how to make claims. And now they've added an AI layer on top of that. NIA is installed currently with reach extending to millions of client employees at ADP.

And when you think about the size and scale of that impact, to millions of people making their annual enrollment decisions, that comes out of a small team such as ourselves. Those are things to be, you know, really happy and proud about. Because like that, that's like, you know, you can be the tiny little crowbar that moves a massive boulder, right? It's got to be tough vetting some of these ideas.

I mean, first, you know, for how many projects do you consider before you actually get involved with one? But on the path to making that decision, how do you make sure that they're doing something that's real, that's not just sort of talk? And I'm thinking particularly of AI, you know, because my mother would have an AI product if she could. Everybody does it.

You've got to figure out which ones really work. So can you talk about that a little bit? Yeah. I think on the venture investing side, we talk to hundreds of companies before we do a deal.

I think if I look at the pipeline and the consideration side and how it distills down, and a lot of it, like I said, it's about having extremely strong people that know how to distill, but also you can't do it by yourself. I think you have to rely on the brain trust and the intellectual capital of very experienced, very competent, very sharp leaders at ADP that know their domains and know their spaces and capitalizing their time at the right point in the decision cycle to basically narrow it all on the things that you want And so we have a very very well thought out process in terms of how you get from like you know one company in a list of probably 20 on a particular project to getting it down.

This is the one and it does take time. And so companies that work with us, they know they have to invest time with ADP. And they also, we tell them like, this might not be a thing. You might fall out of the process.

And then addressing that AI point that you just made, that rigor actually helps weed out whether the AI capabilities are real, they're generally real. Like, look, if you've raised $20 to $50 million out of the valley, you probably had some very smart investors do diligence on you, look at your product, talk to your customers, see how real you are. But the question is, for a company like ADP, we're always trying to look for who the best for our use cases is. And so then you have to get into stack ranking.

So it goes far beyond, like, is it real, but more into how you stack rank it. And that really goes back down to the referenceability of their customers, the real value that their solution develops, the defensible moat around their product because everybody can build POCs and lightweight products very, very quickly. But I think what people forget in HR tech is that most companies should remember they're in the business of compliance, right? I think a crazy recruiting thing that's been going on for the better part of a decade as far as like, you know, mentor-backed companies go.

Like several have raised so much money. Yeah, there's a ton of value for recruiters, for sure. And it's one of the most critical functions that you have because getting the right people in the right seats is life or death for a chief people officer. But if you do it wrong, there are several compliance things that you can break and you can end up in a lot of trouble with a lot of authorities.

The same thing goes on payroll. The same thing goes on benefits. And so for us, AI takes on an entirely new dimension where we have to be very comfortable with the compliance angle for a lot of these products. Because why do you buy ADP?

You buy ADP because, A, we have the best products. But you buy ADP because of that assuredness that there has been a ton of thought put into how compliant the product is. It's going to keep you out of trouble from errors that might lead to employee complaints to things that might cause. Don't want to get into the myriad of issues that can come from the legal side of it, but you can get into a lot of trouble, right?

And so for the AI to be real there, there has to be so much proprietary build done around those AI guardrails to make it not hallucinate, to make sure that it picks up the real rules around what you can do and can't do. That's the lens that you have to take to testing these companies and testing those solutions. Because quite frankly, building a lightweight GPT wrapper is not hard. It's not hard at all.

Oz, thanks very much for joining me today I hope you'll come back This is actually really interesting And I think a lot of people care About what you guys are up to So thank you And to everybody who's watching and listening Thank you This has been People Tech The podcast of WorkforceAI.news I'm Mark Pfeffer Thank you.