And the reason is very simple. Often in the smaller relationships, you don’t have enough of a combined scale to be able to drive the kind of non-FTE pricing and value brace pricing that you can, when you do finance and accounting, with order management, with supply chain, and when you put all that together, our ability to drive real value is tremendous and we participate in that value creation.
Maggie Nolan: Thank you. And then on the margins, do you anticipate that this current dynamic with the short cycle work versus the longer term kind of cost optimization projects is going to have an impact on where gross margin or operating margin can come in over the next couple of quarters?
Mike Weiner: Well, there’s two separate dynamics that are going on associated with our gross margin. As you know, when we have these large deal ramp ups, particularly when we take onshore delivery and move it offshore, tends to have a dilutive effect on the business in the near-term and gets accretive from a gross margin perspective. With a countervailing view on that as well, is that our DataTech and AI gross margins, when we have slower revenue growth, disproportionately benefit us on a gross margin basis. So with that said, and our projections going into next year, with the recovery in DataTech and AI, I think they’d be relatively flat on a go forward basis with those two counter things going in different directions.
Maggie Nolan: Got it. Thank you. And congrats, Tiger and BK, on your announcements.
Tiger Tyagarajan: Thank you, Maggie.
Operator: Thank you. [Operator Instructions] And our next question comes from Ashwin Shirvaikar of Citi.
Ashwin Shirvaikar: Hey, guys. Tiger, congratulations on the long run, and it’s been a pleasure working with you. And BK, congratulations, very well deserved and look forward to working with you.
BK Kalra: Thank you, Ashwin.
Ashwin Shirvaikar: Yes. I guess the question I have is, as you look at Data-Tech-AI and Digital Ops, right, the Digital Ops business should still, I would imagine, even without sort of a budget flush and without things like that, should still be sequentially growing most quarters, right? And so that would imply kind of Data-Tech-AI can shrinks to the 475, 480 kind of range for December. So when I kind of think of the carry forward from that, the – I just want to try to get better color on the less – not quite double-digit kind of comment. Is that more of a mid-single digit type of comment? Better or worse? What kind of visibility do you have by line? Any thoughts there?
Tiger Tyagarajan: Mike, go ahead.
Mike Weiner: Let me kick off. Yes. There’s two things to really unpack there. So your sequential observation, third quarter into fourth quarter regarding Digital Operations is 100% correct both on a notional dollar basis and our year-over-year percentage basis, also off of a tough fourth quarter comp from that perspective. So correct by definition, our Data-Tech-AI business will be weak going into the fourth quarter. Okay. So with that said and the full ramp up that I’m going to build on some of the other comments we said earlier, with the full ramp up of the Digital Operations business that we have on the large deals we’ve won through the year, that’ll provide a nice base for next year, right? Now if you then think about our digital – our Data-Tech and AI business with some of the drivers that we’re talking about, particularly that regarding generative AI, right, and being able to utilize some of those budgeted numbers that are out there, particularly, again with the data engineering solutions that we’re offering, we think that’s going to help propel our Data-Tech and AI business.
So at the end of the day, logic would dictate that next year will be somewhere between our full year 2023 guidance, but less than our initial double-digit view that we had then. So we’ll have to ultimately see where it goes. We’ll provide additional information about that in early February. But the obvious other thing that we have to think about, the variable out there that’s creating a little less visibility than a normal is the macroeconomic environment. Does it remain stable? Does it improve? Does it deteriorate, right?
Tiger Tyagarajan: The one other thing that I would add, Ashwin – the one other thing that I would add to what Mike said, Ashwin, on Digital Operations, is that going into the third quarter actually probably even finishing off the second quarter going into the third quarter, the big discussion that we all had was confidence in the ramp of the wins that we’d had as we go through quarter three and quarter four. And one of the most pleasing aspects of our business is that ramp has exactly delivered what we had expected on Digital Operations. So even in this environment, we are really confident, not just with your comment that it’s a natural thing to come through, but even the risk associated with those types of ramps hasn’t played out at all. So it’s actually really, really solid.
Ashwin Shirvaikar: Right. And that’s sort of where I was going to go next is with regards to the expectations that you had. Just to confirm, you’re not necessarily seeing delays with regards to sort of rebadging type deals. What types of deals and decision making are you seeing delays with? I mean, I know the broad classification is short cycle discretionary, but if you can be more granular with regards to what you’re seeing by vertical, by geography, any details there would be helpful?
Tiger Tyagarajan: Yes. I’ll take the easy ones because I guess the whole industry would be seeing this. And you would agree with that because you probably see more of it as you talk to the peer group technology project work, where teams are allocated, let’s say to financial services firms, banks. And as those projects get completed, the question of what’s the next project comes up? And if the leaders in the firm decide that actually we don’t want to spend any more money on the next set of projects, so instead of spending X billion dollars, we’ll spend X divided by two, that means that those projects, new projects don’t come in to utilize the same set of people who built the expertise, who built the domain, et cetera.
It’s a really tough decision for that bank to take because the moment that happens, we move those teams into great projects with other people. Those people don’t sit idle, but everyone in banking, a number of people in retail, consumer goods and in manufacturing are clearly taking those decisions, have been taking those decisions. That’s one example. Another would be in the front end, improvement of marketing experience, improvement of digital marketing, some of those are coming under the radar and under the lens of is this really needed? And is the payback immediate? Those are the two questions that get asked, particularly as you get to the end of the year, budget flushing, not available, et cetera. So those are two examples. I’ll give you examples where we are not seeing that at all.
Supply chain is a great example where we are not seeing any degradation of I need to improve my supply chain, I need to get a diversification of my supply chain driven by all macro factors. Another one would be get my data ready for gen AI. Two examples where we are not seeing any degradation.
