Here. My name is Maggie Nolan. I'm the research analyst here at William Blair that covers IT services, including Endava. We are very happy to have with us here today the CEO, John Cotterell, and the CFO, Mark Thurston. I am required to inform you that for a complete list of research disclosures or potential conflicts of interest, please visit our website at williamblair.com. Endava is a next-generation technology services provider. We are going to have an overview from John, and then maybe a little time afterwards for me to ask a few questions. With that, I'll turn it over to you.
Great. Thanks, Maggie. I will flash up our disclaimer, but I'm not going to leave it up for you to read it. I'm sure it's available on our website somewhere. I'm going to talk a little bit around the shift that's going on in our marketplace and where Endava sits in that shift, and, you know, unpack a little bit of some of the changes we've been going through. The last 25 years, we've been one of the leading players in the digital transformation wave that was kicked off with the advent of the internet. There was the dot-com boom, and then there was a pause of about two or three years while everyone worked out what the real engineering was behind the internet. Out of that was birthed the digital transformation wave, which in Endava, we rode for about 20 years, from about 2003 to 2023.
2023, slightly before that, November 2022, along comes AI with ChatGPT waking everyone up to the possibilities. That has transformed our marketplace. We call it the digital shift. It is not that the market has completely changed, but everyone is looking at how AI is part of the solution that they are going to create and how you create more customer-friendly, better interactions, and so on by incorporating AI into what you do, but also using AI in the way in which you create software. You know, that is driving changes in the way in which we run our business. AI is obviously creating opportunities for new use cases, whether they be automation-based and so on, to help drive efficiencies with our clients.
Now, one of the big areas that's changed is the digital transformation wave that ran for about 20 years was all around building technology capabilities that were customer or client-facing, open channels up to those clients. Largely, we built them without going into the core legacy systems that exist within client base. It had boosters along the way. You had things like mobile came along, cloud, and so on. Each of those triggered a new level of channels, a new level of ways of executing on the business. You know, we did go into the core a little bit in terms of creating APIs and creating routes into the data that was there, but we didn't go deeply into the core. That was essentially the technology modus operandi that was established coming out of the dot-com boom that I was talking about earlier.
AI is going to be different. AI needs to get at the data and the processes that sit in your legacy systems. If someone phones up and you want AI to resolve a question about the bill that they have, AI needs to know how that bill got created, what it can do about the query that's coming through, and then actually take some action into those systems to change the bill or to make some credit or something, depending on the nature of the interaction. That does not happen unless you sort out the legacy systems. The other thing that's been going on over the last couple of years is that a lot of the engineering around AI has proved more complex than people expected. Things like hallucinations.
Actually, if you're a top brand, you're not going to implement an AI solution where every so often it completely hallucinates and gives your customer a load of rubbish. Now, that's largely being solved through things like agentic AI, but also regulatory requirements, getting regulators on board with the use of AI. Security has been an issue. I think the thing that surprises me is often people don't realize that quite often the business cases have not been standing up in the last, well, until about six months ago, because the cost of processing AI solutions has actually been so high that replacing people with AI has not necessarily stood up to scrutiny. That's changing. We're starting to see that easing through.
Now, at Endava, one of the approaches that we've taken is to bring the expertise that we have together over the digital transformation wave, which is all about how do you ideate new products and solutions and then scale through into building production systems without going through multiple organizations. You don't get a creative organization to envisage a product and then a strategy organization to envisage the go-to-market and then get an engineering organization to build it with all the friction that happens between them. You get one organization that can do the ideation and the creativity and drive it through into a scalable solution in the market. That actually works really well in an AI environment. A lot of AI-based solutions need that ideation to production capability and mindset. The other thing that is really key is actually investing in what we call automations.
The capabilities and in the way in which you use AI to create tools and automations that help you accelerate the transformation process. We picked up a business called Galaxy just over 12 months ago, and that brought a whole load of capabilities that are very relevant to core modernization. They had a tool set that they'd been working on for about 25 years, which was all about reading legacy code, the really ancient stuff that AI doesn't know because it's never been trained on. Then through reading that and actually creating a map of what the code is doing, we're able to feed that into AI-based solutions to back engineer an architecture map, an understanding of the business requirements, and so on. Now, this is actually the biggest issue when people are kicking off core modernization programs. They don't actually understand what their existing systems do.
Creating a start point where you can see what the existing systems do gives you much greater assurance on putting together a transformation program to modernize those platforms and make them ready for AI. Here are some of the accelerators. I'm not going to go through all of them, but just to give you a feel that this is not just about smart people using publicly available tools to do work for clients. It's about the automations in the accelerators that go with those people that actually enables you to do something different to what other organizations can do out there. We've been investing in these that some are in the AI space, some in the modernization space, and some are in industry-specific areas. We've only called out one there, which is the payment space, but we have others sitting in other industry areas.
Now, when we IPOed, which is 2018, so just coming up to seven years ago, I realized last month I'd just done my 28th quarterly earnings call. The business was quite concentrated. Over the last seven years, there've been quite a bit of diversification going on. We were very heavily payments and financial services. The key there is actually not correct. The green is the payments and financial services on the left-hand side. Last quarter, you can see there's a lot more diversification in the industry split. Likewise, our geographic split has become more mixed. A lot of this through M&A, but also through a conscious effort to go win clients in industries and geographies outside of our focus. Quite a big shift in our regional presence. We were very, very concentrated in Central Europe.
Even the Western Europe element was the EU parts of Central Europe that we were in. That has diversified. We now have a footprint that enables us to deliver to clients globally in Asia-Pacific, as well as in Latin America and, of course, Central Europe where we started. The revenue side, it's been an interesting market that we're in at the moment. It's going through that transition from people focused on the digital transformation wave to actually how to incorporate AI into the solutions, the engineering challenge that has been associated with that. That's definitely creating a hiatus as we switch from the previous modus operandi to the new AI-enabled modus operandi, similar to the one that we went through in 2002, 2003 at the beginning of the digital transformation wave.
That has caused a flattening off in the business, initially a drop, and then a flattening off over the last 12 months. We are focused on developing what is quite a strong pipeline, much stronger than it was in the digital transformation wave that we went through of larger deals, which are significantly larger than we had in the digital transformation wave. Our current focus as a business is on getting those closed. As we close those, which means sorting all those engineering challenges, negotiating the macroeconomic environment that we're currently in, and the usual getting things signed off within client businesses, that is the route that we see from moving off this flat hiatus that we're in into getting back onto a growth path. We unpacked that quite a bit in the earnings call if anyone's got any questions on it later.
That's the quick walkthrough. In summary, AI is accelerating change in our business. There's a lot of need for innovation associated with that. This need for a digital core so that AI can get at the data and the processes that sit in the heart of your organization to have its full impact means big programs of change in order to make that happen. And then, you know, we have established over the last seven years a diversified portfolio in the business across industries, across geographies, and across the locations that we can deliver from. With that, I'm going to hand it over to do some Q&A. How long have we got?
Thank you. We've got about 15 minutes.
Great. Mark's here as well, so if you've got any financial questions.
A tremendous amount has changed in the business in the last year, and there's been a ton of focus on core modernization, larger deals. I'd like to spend a few minutes there. When you think about your go-to-market strategy in the context of these larger scale deals or these core modernization projects, what have you had to change in the business, and what's kind of come into focus for you as an organization?
The biggest change in the business has been, from an engineering point of view, making sure that we have the skills and capabilities for this new AI world. Right? Data we always had, but that's expanding. The AI skills in terms of how to use both generative AI, agentic AI, and large language models to create solutions for clients is a pretty skilled area.
Actually, over the last 12 months, we started off with the pods. I don't know if you remember us announcing that a little over 15 months ago. That created real centers of excellence around how to drive change using, well, AI was one of them, core modernization was another, and then rolling that out across the organization so that that becomes a more widely held skill as we scale with clients.
As you think about, you know, that pod concept and the appropriate staffing for teams, what is the blend that you're finding between, you know, team members and technology that's optimal for your clients and for your delivery? You know, what inning are we in and kind of getting to more of a steady state of where you think that blend could be in the future?
When you say blend, people and technology, you're talking about AI agents?
People working alongside AI agents from your perspective delivering to your clients?
Yeah. Using agentic AI alongside what our developers are doing is pretty much everyone. It isn't quite everyone. I'll come back to that in a moment. Generally, it would be everyone across Endava using that every day in what they do. You're getting the higher productivity. You're getting the capabilities that you bring to the daily coding activity. It isn't quite everyone because not all of our clients allow us to use AI, surprisingly. Two and a half years down the road from ChatGPT, some clients are still nervous about it, which we respect, of course.
The area that is really interesting is how you can use agentic AI in particular, and some of the LLM providers are starting to launch these to get much, much more significant acceleration and productivity out of what you do. Essentially being able to brief agents with requirements and then be the human in the loop around checking the relevance and the capability of the code that's coming through and then iterating and sharpening what you're doing. It is going to massively change agile delivery because agile delivery was all about how you do iteration through sprints. You will be able to take a much bigger leap forward, maybe 60% or 70%, using an agentic solution and then use an agile type process to sharpen it up rather than doing it from scratch. We're modeling out how those methods of delivery are changing.
What inning do you think we're in? I mean, how far along in that process of changing how you deliver do you think you've come?
In terms of understanding the art of the possible, we're quite a long way. In terms of people adopting it, less than 5% of the real sharp end using agentic solutions. The world at large, I would say 0%. It's hardly started on it. When you think about, you know, delivering with this new technology, what's the importance of Endava as an organization developing proprietary technology or IP versus, you know, your intentions to partner with some of the others that are out there doing that? I took you through some of the accelerators, which is the IP that we're developing.
That is all around the IP of how we do our job and how we make our people more effective so that essentially the service we're offering to clients is not just know-how, but it's also the augmented capability that comes with the accelerators so that they know they're not just getting a bundle of smart people who can architect clever solutions or whatever. They're actually getting those same smart people, but also with tools and capabilities that help them understand their existing estate and the challenges of moving to the future state, which, frankly, is what everyone has been asking of services businesses for the last 30 years. Actually, AI gives us the capability of putting that in place.
Mark, maybe you could comment on, you know, large deals in terms of their composition of the revenue mix, how important they are today and on a go-forward versus, you know, what maybe revenue was comprised of mainly five or so years ago.
They're quite different. I mean, we've always been through a sort of ideation to production phase, which is starting small with, let's call it discovery work, and then teams scale up. You could have, you know, a few hundred people actually working for a client. There would be a slow, sometimes, you know, rapid scaling, and then you would be at scale. The way things were contracted is when they got to a certain size, you would then put in place a master service agreement around minimum commit.
It was just making sure that, you know, the client got value as we were producing the source scale product for them. It helped us in terms of visibility of, you know, that delivery. The way the bigger deals are working is they tend to have a different sort of construct. They can either take the shape of, we've got existing people doing something, and we will give it to you, Endava, to modernize enterprise-wise. You would get revenue stream sizable almost from the get-go as you're providing that service back to the client. You get the efficiencies, and then you get the improvement in terms of the velocity at which you deliver over a period of time. They will have that sort of dynamic.
Some may have similarities with the existing sort of MSA structure where it is build something which is large over a longer period of time, and it will bring in ancillary work. It is the nature of the sort of step change of it that is very different. I think if I can sort of phrase it in a sort of a non-big deal framework, we basically had very good cadence and visibility about how the projects would move through or the opportunities would move through the pipeline. You could use weightings, et cetera, and you would know about the velocity at which they would move to enable you to sort of predict. We're finding at the moment with the larger deals, the timing or predicting when they will happen is very difficult. I think it is a sort of mixture of uncertainty, macro uncertainty.
I think it's about the technology. You know, what is a technology solution going to look like? I think it's our sort of experience with these larger engagements and the binary nature of them that has made it sort of problematic. I think going forward, and certainly in terms of guiding, we'll adopt a more conservative methodology to it, for want of a better word, until we see that cadence or that understanding of the rate at which deals move through the pipeline becomes more predictable.
Maybe elaborate on that for, you know, what you just discussed on the last quarter. How did you factor it into the guidance for the rest of this year? Maybe give us kind of what's still remaining out there that you need to go get to achieve the guidance that you've laid out.
Most of our pullback, well, partially it was FX. It was big deals. There are no big deals. To be frank, if they were going to hit in the quarter, they would not have had a big impact. We are basically forecasting, guiding the non-big deal revenue. We have very little at the top of the guide pipeline. That is known opportunities converting with the existing sort of clients, like 1%. Typically when we have gone into a quarter, it has been about 5%. At the bottom of the guide, none of the pipeline converts. Then you are starting to actually eat into the contracted and committed. What that means is clients are starting to either, you know, give you notice about ramp down. We think it is a very de-risk figure that we are giving.
You know, when you think about growth drivers kind of beyond the next quarter, what are some of the end markets that you think play well into this theme of core modernization where you may see good traction for the business over kind of a one or two-year time period?
I mean, the biggest one for us is the banking and capital market space. There are huge opportunities there. We're already seeing traction. The BCM space grew, was it 40%? Yeah, probably. Over the last 12 months to Q3. You're already starting to see the pickup coming through there. That's a huge one for us. We're also seeing opportunities in the mobility space. Automotive has got traction. Healthcare, there's actually a good foundation of core modernization deals out of the Galaxy business. That was their core arena that they operated in.
We're actually finding opportunities to scale that because obviously Endava is a larger organization than Galaxy was, and it's opening up doors with those clients. There will be others that open up, but those are the ones where we're seeing most traction right now.
That's kind of a long-term lens on it. You mentioned mobility and automotive, but that was actually maybe one of the more difficult areas in the past quarter. What do you think would be the tipping point where, you know, some of those customers may feel comfortable spending again or thinking about engaging in larger scale projects?
I mean, we've got the conversations going. It's one of the areas that automotive is one of the areas that has been most hit by the tariff challenges.
That is where we have seen people take a step back and go, actually, we have got to go and sort out our supply chain before we can really double down on some of these technology change drivers that we have. We are seeing that as a three- to six-month thing rather than them stopping for two to three years. I think there are so many drivers in the automotive space that mean these guys need to get on with things. Obviously, that tariff impact on them has been absolutely enormous.
How do you think about that in the context of staffing and utilization and trying to achieve your margin goals that you have laid out? Obviously, on a multi-year basis, we would expect margins to kind of climb back up to where they have been historically.
I think we're, I think at a low point in terms of our gross margin. I think we've got our utilization is in a sensible place. It's about 72%. Venture's in a sensible place as well. The larger deals will be using more, leaning more heavily on the accelerators, using the agentic tooling. I think the profile in terms of the headcount will start to decouple as we move more towards a, you know, a commercial construct, which is around outcome-based. That allows us to capture more of the margin than we would have under a T&M, you know, basis. I anticipate we're at a low point in terms of our gross margin. I think we can expand it. I think it will expand more quickly as growth comes back.
I think the trajectory in terms of the mix of the business more towards outcome-based will facilitate in that.
Very good. We have time for one more. You know, your heritage was often viewed to be within the payments industry. There's been a lot going on in that industry and a lot going on with some of your larger clients in that industry as well. You've talked in past kind of analyst days about the value proposition, expanding those capabilities into other end markets as well. Is that still something that you think is a growth driver for the business, or are you more indexing and investing in core modernization for banking and capital markets, for instance? Are you thinking about that payments opportunity?
Both of those are true as in the core modernization.
But also, you know, there's a lot of payments progress happening in the banking industry, for instance. A lot of the investment that we're seeing is flipping from the payment processors, the acquirers, across to the large banks. If we do payments work for a large bank, we call it banking because they're banks. If you look at the payments world, putting aside the payment processors as a category, we are actually seeing that turn and actually seeing an uptick in payments work that we're doing across industries. It is working better for us as a horizontal than as a vertical right now.
All right. That is all the time that we have. We do have a breakout session where we invite all of you to come and ask your Q&A directly to management as well.
That's going to be in Burnham B upstairs, and that will start in the next 10 minutes. Thank you.
This presentation has now finished. Please check back shortly for the archive.