Technology Business Research, Inc.Managing Strategic Alliances & Ecosystem Partners: How Top Alliance and Enabling Technology Practice Teams Use TBR Data
In this episode of “TBR Talks,” TBR Senior Vice President, Sales & Marketing, Dan Demers interviews show host Patrick Heffernan on how the globe’s top global systems integrators, ISVs, hyperscalers and OEMs use TBR’s proprietary data and analysis to make validated and data-backed decisions.
From strategy planning based on partners’ annualized revenue or headcount growth to allocation of training budgets and schedules to align engineering resources, TBR’s unique data and analysis within the ecosystem give leaders a meaningful and independent set of data to make partnership investment decisions.
Episode highlights:
• Understanding TBR’s data view of the market
• Case studies: IT outsourcing and applications outsourcing, staffing and headcount, perception of partnership alignment
• Age of AI and agentic AI: Pricing and staffing changes
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TBR Talks is produced by Technology Business Research, Inc.
Edited by Haley Demers
Music by Burty Sounds via Pixabay
Art by Amanda Hamilton Sy
Managing Strategic Alliances & Ecosystem Partners: How Top Alliance and Enabling Technology Practice Teams Use TBR Data
TBR Talks Host Patrick Heffernan: Welcome to TBR Talks: Decoding Strategies and Ecosystems of the Globe’s Top Tech Firms. Where we talk business model disruption in the broad technology ecosystem from management consultancies to systems integrators, hyperscalers to independent software vendors, telecom operators to network and infrastructure vendors, and chip manufacturers to value-added resellers. We’ll be answering some of the key intelligence questions we’ve heard from executives and business unit leaders among the leading professional IT services and telecom vendors.
I’m Patrick Heffernan, Principal Analyst, and today we’ll be sharing the audio of a recent TBR Insights Live webinar session where Dan Demers, Senior Vice President, interviews me about a TBR case study in managing strategic alliances and ecosystem partnerships. If you’d like to view the visuals from this presentation as you listen along, you can do that through the link in the show notes.
Introducing the alliance and ecosystem use case
Dan Demers, Senior Vice President: Appreciate the chance to present some of the ways that we work with clients. This is a little bit of a different webinar, I know a lot of times Patrick, who’s sitting beside me today, Patrick and the team of analysts will present on topics, emerging, disruptive events. Today, we’re going to click into a case study. And this is a case study that we’ve seen evolve over the last seven, maybe ten years, and get more and more refined as each year has gone by. I’ve had the pleasure of sitting in a lot of these meetings. So, today we’re going to flip the script a little bit, I know, Patrick, you often will be leading these webinars with some of your colleagues. I seldom participate, so this is kind of fun for me.
Patrick: Yeah, these are always fun. So welcome. Welcome to the party.
Dan: I’m glad to be here. So, today’s agenda, as the title suggests, we’re going to be looking at how do global systems integrators and their enabling technology vendor partners, how do they go-to-market? How do they partner? How do they staff? How do they ultimately drive revenue? And hopefully, I’m sure for all of those parties concerned, continue to renew, a sticky relationship with digital transformations, AI integrations, modernizations, the whole panoply of the services that they provide. So, we’re looking at the- specifically in TBR’s research and our data, and how our clients over the years have come to use our validated and independent data, such as our IT outsourcing, applications outsourcing, consulting and systems integration revenue breakouts inside your team, the professional services team’s, research. Looking at critical data on headcount and credentialing and certification of that staff, and how are the SIs moving the pieces on the chessboard when it comes to people and how they’re training those people? And what does that then mean for their enabling technology partners? And lastly, as a part of this conversation to frame it out, we’ll be looking at objective data, how our clients have come to use that to guide critical decisions on how to staff, how to manage, how to enable, how to train, and how to fund these alliance groups. And then within those alliance groups, specific alliance teams as they pertain to different members of the Global Systems Integrator class.
So, speaking of clients, who uses our research? This is a slide that our marketing team has put together. Going into our user data and our subscription contract data, without getting into names, many of our customers prefer that we not mention them. But it’s safe to say that the vast majority of our customers are the very companies that we cover. Our historic use cases have always been in competitive and market intelligence, and again, starting ten years ago and moving through, really, the last four years, we’ve seen the incidence of usage, the conversations that we have, really start to shift towards those alliance and ecosystem leaders and the staff within those organizations as they strive to get a validated outside-in view on the ecosystem. So, 10 of the top 10 SIs, three of the top three big hyperscalers, virtually all of the major OEMs, the federal systems integrators, really the largest names, the most recognized partners and really the leaders in each of their core areas are represented by our customer base. So, the talk that we’re going to have today is really centered on whether it’s me sitting in listening to you and your team, Patrick, talk to clients, or our sales team receiving questions from our users, and we pass them on to you, or to Allan Krans and his team in the Cloud and Software group, Angela Lambert and her team in our Infrastructure group, really across the board, this use case has really organically grown from our users tapping into your expertise, your team’s data, and your colleagues’ analysis.
Patrick: Yeah, one thing I would add, Dan, is that when I started here over 12 years ago, my focus was entirely on those GSIs and those management consultancies, and that’s who I talked to all the time. Now I spend less than half my time talking to them because I’m instead talking to their alliance partners. So, it’s those hyperscalers, it’s the OEMs, it’s everybody else in the ecosystem that’s coming to us and saying, what’s really happening with the GSIs, what’s really happening with the management consultancies? And honestly, it’s a lot more fun for me that it’s now the ecosystem, not just one set of vendors.
83% of enterprise technology spend
Dan: So that’s us. I always like to look at this picture and think of the time that we spend on the road together. I often will refer to Patrick as my winsome travel companion. Together, we’ve traveled the world, we’ve met with leaders. And it’s interesting, as you were just talking about how half of the time you’re talking about other folks. One of our last trips to the UK, you shared that you were spending more time talking about microprocessors, silicon, and chips than you’d ever in your entire career.
Patrick: Yeah.
Dan: And we weren’t even really meeting with those folks. We were talking to your classic peer group, the systems integrators.
Patrick: Right. I was all fired up about liquid cooling at the time. So, it’s funny how that happens.
I do want to just frame out a little bit of this discussion today and from my perspective of where a lot of this is coming from. The most important number, perhaps in this whole entire session, but certainly on this slide, is that 83%. And that is that 83% of enterprise technology spend is going to multi-vendor engagements. What’s interesting about that is we also know that the win rates for IT services companies and their tech alliance partners are significantly higher when they partner with at least one partner, but even higher when they partner in a multi-party engagement. So, we know that this is exactly the thing that has changed so much and so dramatically over the last, say, five, six years within the ecosystem that we’re looking at is the reliance of the GSIs and the consultancies on their technology partners. And so, they have to have, in order to take advantage of that, in order to reach that 83% win rate, or in order to capture that 83% of the enterprise technology spend, they have to have really well-developed, constantly refined, leadership-driven alliance strategies. It’s an absolute imperative right now.
Dan: Again, it’s going to remind me of, I think, our first trip together, we went to Texas, visiting with some of the SIs and their experience centers. And they were avowed agnostic when it came to their technology partners. And I remember debriefing afterwards with you and members of your team and then progressively going across the world and visiting with other SIs and other hyperscalers. And that seems to have been a- there’s a change there. That vendor agnosticism is no longer something that they lead with.
Patrick: It’s totally dead. And I’m happy to see it go, because I think it was always kind of a bit of a fiction anyway. So, we can do a whole webinar on why that was a fiction, but all right.
Dan: So why are we talking about this? As you just pointed to, that 83% number has only grown in the time that I’ve been here since 2016/2017. More and more of the spend is flowing through this ecosystem. I think I’m going to quote you and tell me if I got it wrong, but, maybe 3 years ago, you finally said it is the end of end-to-end solutions.
Patrick: Amen.
Dan: There is no single entity that can deliver every aspect of a full modernization or digital transformation engagement, from the management consulting through the support and deploy of the hardware and managing the workloads on the cloud. It’s an entire ecosystem of partners. More and more of them are declaring their partnerships. They’re working deeper and more, engineering-wise, more intimately together, commercially, more intimately together. So, we look at our research, and we see clearly our clients using our strategy analysis for their strategy planning. We see their engineering headcount being driven by the revenue and the trailing 12-month trend lines that we see from our revenue in our services category. We see marketing staff, marketing budget, a lot of our research gets pulled into marketing enablement. Obviously, the sales and pre-sales staff and the credentialing, the vital critical time that gets spent. All of these core use cases are tied back to some of the data that we produce. And we’re seeing, it’s not that gone are the days of the Accenture lead at ISV-X telling us, “you can’t tell me anything about Accenture I don’t already know.” Sure, you talk to Accenture every day more than our Accenture expert, perhaps. But you don’t know what Atos is doing, or Wipro is doing, or CGI is doing or any of the other 20, 30+ SIs that you’re competing against. And ultimately, that gets down to their quarterly business reviews and how well they’re doing on a revenue basis. And we’ll show today how we’re going to connect some of our service line revenue that your team produces and how many clients are using that to literally benchmark team performance against specific SIs. So, it’s really very, very strategic and tactical all at the same time.
Understanding TBR’s data view of the market
Patrick: Yeah, so let’s get deep into the numbers here, at least just to show you the way that we look at the world, because I think it’s important if you’re not super familiar with TBR to understand.
You’re looking at our signature graphic. We take hard numbers, we put them into our taxonomy so we can compare companies in a meaningful way. The apples to apples is a cliche, I think about it more like it’s a fruit salad, you know, and you get a lot of different fruits, but you got to cut them up and put them all in the salad. And you only get to understand them as they are meaningful to each other. So then we show the most important metrics; revenue, revenue growth, and operating margin. Often we present directly to the GSI’s technology partners, again, like AWS, Nvidia, Microsoft, SAP. We typically stay right here. We just walk through all the analysis and all the insights that this singular graphic can provide. And I wanted to show two things to sort of reinforce this. First, we’re analyzing and presenting meaningful data, proprietary and meaningful. It’s a rigorous process. It’s our taxonomy. And second, this approach underpins all of our research. So, when we talk about ecosystem relationships and metrics, and performance in a little bit, we’re coming at that with the same kind of rigor.
And I’ll share a quick example that just happened today. Our lead analyst who covers Deloitte, which is a privately held company, so they don’t produce quarterly earnings. They’ve recently- he recently published his estimates for the firm’s revenue and headcount. Again, Deloitte is privately held. He estimated global revenue, global revenue at $70.1 billion, and they’ve reported at $70.5 billion. He estimated global headcount at 474,000, and they reported at 470,000. So, being that close, which is for a Big Four firm, that’s essentially dead on accurate, that reassures us that our data is solid. So, that’s where we’re coming from.
Also want to show this, which is the ecosystem view that we take. And what you’re seeing here, speaking of proprietary data and contextual analysis, what you see here are the relationships between 3 GSIs, and yes, we’re considering Deloitte a GSI in this case, and one of their hyperscaler partners. We’re estimating the revenues, the growth, the staffing, and then critically, we think critically and we hear critically, what percentage of the GSI’s total revenue is tied to that hyperscaler partner? That’s the data and the context that helps understand the strategy behind it all, the go-to-market opportunities, the when, whether, how others in the ecosystem can or honestly should partner. So, this ecosystem research has become enormously important to us and to our clients.
Case study: IT outsourcing and applications outsourcing
So now we’ll sort of begin the case study part of this and we’ll dive into the agenda fully here. So, I’m going to show a couple slides real quickly. And these are the, again, bubble charts. This is the latest bubble chart on IT outsourcing. So here, take a quick look and a close look at where Infosys is on this chart. And then on this next chart, we’re looking at applications outsourcing. And here I would say take a look at HCLTech. A little hard to see, they’re to the right and up, but just barely, but they’re an important company. And I’ll explain exactly why in just a moment.
Here we have the trends that we’re seeing across these two areas, IT outsourcing and applications outsourcing. So, what do these trends mean? You can read them. What do they mean for the rest of the ecosystem? Well, you’ll see there’s a slight decline overall, at least in IT outsourcing. And that’s just not, that wasn’t true for Infosys. As I called out, and as we saw, Infosys grew over 5% in part because Infosys has been successful in integrating its AI platform and accelerating that time to value for clients. And that helps maintain client stickiness, which is necessary to secure their incumbent position in a market where there’s just constantly consolidation. And I want to say, Dan, at the very beginning, you mentioned the desire by GSIs and their technology partners for that client stickiness, true and not true at the same time. And a little bit later, I’ll explain why that’s not true. But it’s really important to understand. And when we look at IT outsourcing, how it’s client stickiness that really determines who is doing well and who isn’t. And again, I’ll come to why and how the hyperscalers and other technology players play in that.
Secondly, on applications outsourcing. So, HCLTech, as I mentioned, they use their AI platform, it’s called AI Force. We’ve done a couple of reports specifically on AI Force, because I think it’s something worth calling out and looking at. But they have used that to win more deals and like Infosys get stickier with their clients. And we’re, again, we’re cognizant that client retention is an IT services- it is the IT services company’s most important metric. And being embedded in a client ends up being a superpower for any one of these GSIs and these consultancies. So, it’s not surprising then to us that the companies that are succeeding in ITO and applications outsourcing are prioritizing this aspect of this engagement. And a caution on that, and this is what I mentioned before, client retention is the holy grail for IT services companies, but not for the technology ecosystem partners. Client retention doesn’t mean the same thing to a hyperscaler or to an ISV as it does to IT services vendors. And understanding that point is really critical. Understanding why those differences exist and how to bridge them is important too. Dan, I know you have some thoughts on this slide as well.
Dan: The slides that you’re showing with the bubble charts and the data, what I wanted to call out here was how I see members of your team when clients peel back the underlying data tables that our clients have access to through their subscription. They’re seeing vendor by vendor from this bubble chart and the others, vendor by vendor, revenue, operating margin, headcount, and in some of your reports, even nation state where headcount is located. And the key point here, I think, for the partners of the SIs, they’re able to look at that data and compare and contrast it against one vendor to the next, one country to the next, growth in headcount, growth in revenue, or decline in headcount. Because the question we get time and time again is: TBR, who should we partner with? And so, it’s finding the right match between the Tier II ISV and their widget, their value proposition. Does it align to which service line, which SI has the right engineering talent and is themselves focusing and investing in that? So, the data tells this incredible story with these visuals at the senior level when we’re sitting in a boardroom. But then there are the folks three layers deep in an organization who have to answer up their food chain. Who should we- tell me, give me the data, why we should partner with HCL versus TCS. All of those questions are very hard to answer from a data-driven sense because this data is not available anywhere else. And a lot of it is gut-driven, relationship-driven. “Well, our CEO plays golf with their CEO.” Okay, wonderful. But is it the right marriage? Is it the right combination of technology solution and SI skill set and staff?
So, all of these wonderful visuals have really deep, boring Excel spreadsheets underneath them. I don’t- I’m an English major, so I say boring. I apologize. I’m not a quant. Quants love our Excel files and our data files because you can go so deep and compare with such nuance that you’re able to tease out the exact right company to partner with. And you can always phone a friend. We often will have Boz Hristov, a member of your team, come in and talk a lot about the companies he covers, or Elitsa, or Kevin, or any one of our analysts to really help those technology partners who want to find the right SI.
Patrick: I’ll add one other thing, because you throw up a bubble chart and it’s hard for us not to keep talking. But if you’ve got the right eyes and you’re not old like me, you can see that this actually says 2Q25. There’s two things that are really important about that as we’re sitting here in the beginning of 4Q. One, this is data that comes from the companies that we then put in our own taxonomy, like I said before, in order to compare apples to apples. So, this data is the most recent data because it’s the most recent data that’s been released that we’ve been able to transform. But really importantly, we do it every single quarter. So, Dan, to your point about how this is used three levels down below the C-suite, it’s because those people every single quarter need to have a reliable, relentless source of data coming to them.
Dan: Yup.
Patrick: So, I think that is super important. And the other thing is, yes, we just published this. The report itself, the benchmark itself, has projections going into this quarter, into next year, into two years, and in some cases into five years. So, we’re not just presenting a backwards-looking view, we’re using the backwards-looking view and the hard data and the hard estimates to go ahead and look at- seeing what’s coming next.
Case study: Staffing and headcount
All right, with that, we got a little bit sidetracked here because I had to talk about that. But now we’re going to talk about another aspect of this, like looking at what we can see from the peers in terms of strengths and weaknesses. So here, this comes from our Global Delivery Benchmark, and the lesson here is- so just by way of explanation, our Global Delivery Benchmark comes out twice a year. It’s all about where the people are. Dan mentioned the country by country look at headcount, that’s exactly where you’ll find this data. But we do it for a smaller subset of companies than the larger IT Services Benchmark, and that’s for a lot of different reasons, but what we’re trying to do is really understand, since services is a people business, you can understand how the business is doing by looking at where the bodies are, how much change is happening in terms of the way that IT services companies staff. And the lesson here on this chart is really clear. When revenue growth disconnects from headcount growth, the labor arbitrage model that is the backbone of outsourcing and IT services broadly is, if it’s not broken, at least it’s under some threat. And I realize that you can see on the far right, things seem to be coming back together. I don’t think we’re predicting that that’s going to last. And so only the deep pocketed and the well-managed and well-led IT services companies will continue to thrive.
So, if you think back to the very first bubble chart that I showed, the average, average growth was 2.5%. And that’s just not sustainable for IT services companies. It’s not sustainable for the industry, period. So, we’re looking to see what will accelerate revenue growth. And what we can see from this chart right here is it’s not going to be from adding bodies. And this is looking at Deloitte from the perspective of their hyperscaler relationships. The number that gets the most amount of attention here, of course, is $2.4 billion with Microsoft, which is a company that Deloitte, in fact, audits. So, we get the question a lot, how is it possible that Deloitte actually does that kind of business with a company that they audit? And if you’re familiar with why that’s complicated, great. If you don’t, it’s really simple. It goes back to Enron, to be honest, is where it all comes from. The bottom line is this; Deloitte is exceptionally good at managing their partners. They’re exceptionally good at finding ways to go to- sorry, I was going to say go to market, they didn’t go to market with Microsoft. They’re exceptionally good at finding ways to align their sales interests and their hyperscaler sales interests. They’re very good at aligning leadership. They’re very- they’re probably the best at, the most exceptional at ensuring that each partner knows what the other is bringing to the table. So, Microsoft actually pays for training for Deloitte professionals. So, if you’re in the consulting business, the only time you’re making money is when you’re at a client site, but you’re not always at a client site. And for that downtime, you need to find something to do. And Microsoft has stepped up and said, if you have a deloitte.com e-mail address, you can get training from Microsoft. So how do they do $2.4 billion a year and growing in Microsoft related revenue? It’s because they’re partnering in a different way, I would argue, in a much smarter way than many of their peers and the other IT services companies.
But all of that said, look at the other number that’s on there under Microsoft, and that’s 18.8% of Deloitte’s total trailing 12-month cloud revenue. So, despite this $2.4 billion number being as large as it is compared to where you think it should be, which some would say maybe 0, it’s only actually, it’s actually less than 20% of the total cloud revenue that Deloitte is doing. So, this is an example. All of this is a way of me showing that we dive into these numbers. All of this data on here is all proprietary, this is not reported. We have our own taxonomy and we have our own way of coming up with what these numbers mean. And we show these numbers to Microsoft, AWS, Google, and we show these numbers to Deloitte all the time to get that kind of feedback that we’re going in the right direction.
Dan: If I can just piggyback here as we transition to the headcount slide. So, this is a glimpse of our Cloud Hyperscaler Ecosystem report, which is just one ecosystem report among a portfolio that includes coverage of the technology partners in the cloud space, so the big three that you see here. Then we’re looking at the front office solutions, your typical standard Adobes and Salesforces. And we’re looking at the back office, we’re looking at Workday, we’re looking at SAP, ServiceNow, that cohort. In some reports, we’re even looking at Oracle. And we’re really diving into this exact same kind of framework.
Question that’s coming in, I can see this one comes up all the time, is it’s echoing on the methodology question, right? So broadly speaking, this, if you think back to all of those bubble charts that you were showing a moment ago, all of that underlying revenue and headcount data, that same kind of data is being tracked among our hyperscaler and ISV analysts, looking at all of those companies from their point of view. It’s the combination, it’s the, as I like to say, it’s the getting the chocolate on my peanut butter versus peanut butter on your chocolate, plus a bunch of primary research interviews. And the conversations that I’ve had the fortune of sitting in on, whether it’s the boardroom in Toronto of one of the Big Four eight years ago.
Patrick: Eight years ago, yeah.
Dan: To last month in San Francisco. These are the questions that we get asked all the time. How do you get this information? Can I trust this information? And then how often do you publish this data? So, the ecosystem reports are annual reports. The underlying revenue and margin and headcount data is typically coming out quarterly.
What makes partnerships work
Patrick: And I do want to just dive a little bit deeper for a second while we’re on the slide, because I think it’s a really important one. And I’m glad you brought up the SAP Ecosystem report, Oracle, Adobe, Salesforce, Workday, ServiceNow…
Dan: SAP, it’s the big ones.
Patrick: SAP, it’s all the big ones.
Dan: The money makers for the SIs.
Patrick: Right. And the question, Dan, like you said, the question that we get, that we got eight years ago, we’re still answering now is like, what makes these things work? And so, I want to touch on that real quickly here.
When I talked about what Deloitte does with Microsoft and alignment, alignment of sales organizations, alignment at a leadership level is a given. You’re not going to have a successful alliance relationship and you’re not going to do well unless you have that, so, that’s a given. It’s alignment at the sales level and alignment is never going to be, and I even hate using the word alignment, it’s probably more complimentary because take a McKinsey or a BCG or an EY, they do not have salespeople, but Microsoft does. So, organizationally they’re structured very differently. So, you’re not going to align, but you need to know what each other’s incentives are. You need to understand how each organization is set up. You also need knowledge management. I got to this with speaking about Deloitte and what they do with Microsoft. Again, you have to make sure that not only do you know what you do, but you know what your partners do, that you can articulate what the value is that your partners bring to the table. And that’s the most important part there. And that’s, do your partners actually sell you? When you are not in the room, is your partner saying, I think you should be going with you. If your partner isn’t advocating for you when you’re not in the room, you don’t have the kind of alliance, the relationship that you need. How do you get there? You got to invest, you got to measure, you got to analyze, you got to repeat, and then sometimes you actually need to stop doing what you’re doing and find another partner. And on that cheerful note, Dan.
Dan: Well, this is, I think this is just a specific example. So, we were working with a client and inside the Insight Center portal, which is our client user interface, we’re launching a data visualization tool. So, clients can actually go in on their own. They can either pull the data file and drop it into Tableau or Excel or whatever they want to use. But in our portal, you can actually dive in. So, this is looking at AWS practices among Infosys, TCS, and Wipro in the Americas and their headcount in the Americas. So, this is available across all of the hyperscaler research. You’re able to look at headcount across all of our ecosystem research. And this is that critical piece that when the technology enabling partners downstream, you know, they don’t want to be considered downstream of the SI, but that’s how the SI views it, right?
And we also look at the ecosystem from the hyperscaler marketplace. We can do a webinar on that next month. It’s a completely different ecosystem and a totally different set of dynamics. But in the SI ecosystem, it’s headcount, it’s people, and where those people are, especially now in this age of data and AI sovereignty, getting this data for Europe is absolutely critical, and we have it.
Patrick: Yeah. And we’re going to, at the very end, we’re going to talk about artificial intelligence, because you could be sitting there thinking like, talking about where the people are doesn’t matter in an agentic AI age. I mean, we’re all going to be replaced by robots, but we’ll get to that at the very end of this. I promise we will talk about agentic AI. We have to.
Case study: Perception of partnership alignment
All right, so this last part here, talking about the staffing, the marketing budgets and all that. What you’re looking at here on the right is a survey from our Voice of the Partner, and that is Voice of the Partner, the annual report. It gets back to what I was saying earlier about how alliances actually work. And maybe I’ll give you a good example of that while we’re in here. And I think Fujitsu is on this chart here. We heard an example once of Fujitsu partnering very closely with ServiceNow at a particular client. And to their credit, both ServiceNow and Fujitsu were very direct about what they were doing and what was working so well. And part of it was that ServiceNow was measuring their success at this client the way they always measure success, which was based on net new contract value. And they were looking at it quarterly. They even admitted at times they were looking at that monthly. How many people are they adding to the ServiceNow platform? How many people are they monetizing? And they were compensating their salespeople 100% based on net-new contract value.
Fujitsu on the other side is looking at the relationship with the client as a whole. What more can we bring this client? How do we retain this client to get back to that idea? They were not looking necessarily year to year, yes, they were looking year to year, but they were definitely 100% not looking at it quarter to quarter or either monthly. So how is it that you can get two sales organizations and two completely different companies aligned and working together and showing the client such a strong partnership, it was because they actually understood where they’re coming from. So, the Fujitsu people understood why the ServiceNow people were looking at quarterly or monthly metrics and the ServiceNow people understood, okay, this is about a relationship for them. So that’s the kind of thing we just wanted to pull out on this particular slide and just understand that that’s how those alliance partnerships can evolve. And having that alignment is just enormously important. Dan.
Dan: The broader picture, though, because it’s the commercial alignment, but then this report on the perception between and among how are the SIs viewing the OEMs, how are the ISVs viewing the SIs, how are the hyperscalers viewing all of- it’s a four-dimensional look from the Big Four partners in that transformation and modernization alliance, what do they need from each other? What do they want from each other? We’re going in and actually asking them what they think of some of these partners. And I’ve been in conversations where the SVP of global alliances saw how well she was doing, and they wanted to push that out to the world because they had tried so hard for so long to change how they were seen, and it was finally showing up. So, having this annualized benchmark on perception between and among peers and partners really does tie back to, how well are we aligned? How do we monetize? How are we commercializing? How are we supporting with engineering talent? All of those questions, this series of questions in this report is 80 pages long, just chock full of all of these benchmark standards and metrics on how they’re partnering.
It really is, for me, it brings it back again to that boardroom in Toronto, because I was always amazed at how partners at these Big Four firms would come to us and say, “well, what do our partners say about us when you guys are talking to them? Because I’m sure you’re talking to them, aren’t you, Patrick?” And vice versa. It really is, they want to work well together. There are many cases fundamentally built differently, but they still have to collaborate, build, and monetize and hopefully retain. I bet the ServiceNow sales guy really would like that contract to get renewed next year too.
Patrick: That’s absolutely true. Yep. And the other thing about this report is that this Voice of the Partner is we complement this survey that you see one of the results up here with in-depth interviews with alliance directors and above at a range of companies in the GSIs and consultancies. So, the Accenture’s and the McKinsey’s of the world and the Infosys’s and the Cognizant’s. And then we talked to alliance directors at hyperscalers and ISVs. And then we talked to alliance directors at OEMs. And I think one thing that we’ve learned in this is that when we have those in-depth conversations, to then be able to go to our clients and say, you know, this is what we heard from an OEM. I’ll take an OEM as a really good example. This is what we heard from an OEM. They’re trying to understand how can we get PwC to sell more boxes. And the answer is you can’t. You can’t get PwC to sell more boxes. But that is the opening for how they actually do build a better alliance relationship. How do they actually find the right people within each organization. So, this research has been enormously fun to do. I do see there’s a question in here that no one was very dissatisfied. Well, I mean, it was a survey, you take what you get. I mean, I imagine everyone has their sort of horror story out there of something that went very, very wrong with a particular partner. That’s how you fail at client retention, is having something go very wrong.
Age of AI and agentic AI: Pricing and staffing changes
All right, one more thing I want to share here before we wrap up. And that is, this is agentic AI, AI in general. We can’t talk about- we can’t talk at all these days without talking about this, in part because of the fundamental change that AI and agentic AI is going to have in the ecosystem that we look at. And again, I’m coming from a very consulting and IT services perspective on this. So, and yes, I’m borrowing this from something that I saw this summer. So, it’s, what is it, imitation is the sincerest form of flattery. This isn’t even imitation, it’s outright theft. Anyway, so, what you see on the left, that is Fifth Avenue, New York City, 1900 Easter Sunday. There are no cars. 13 years later, it’s all cars. Same exact spot, Fifth Avenue, New York City in 1913 Easter Sunday. And that is what AI feels like right now. It’s everywhere. But when you zoom out, and I don’t have the other half to this slide, which is the data on the number of cars sold in the US, but in 1913, it was 1,190. Twenty-seven years later, it was only 23,000. Twenty years after that, by 1950, it hadn’t even doubled by then. And then 30 years after that, it shot from 40,000 to 122,000. So, the adoption curve took a long time for all kinds of reasons that we all can get into in terms of the history. But if you were on Fifth Avenue in 1913 in New York City on Easter Sunday, you would think the world had changed completely. And it had for New York City, but not for the rest of the world certainly, not even for the rest of America. That’s where we are right now with AI. In some places, AI has changed the world, but in most of the rest of the world, we are barely entering the AI era.
We were just out in San Francisco, and every billboard, literally billboard, which kind of stunned me that the physical hard- it cannot be more hard copy than a billboard, was all about AI. Every single billboard was about AI, the Waymo’s were everywhere. There was the sense there that AI had taken over the world, and yet you step out of that bubble and you realize a lot of us are still back in 1900 on Fifth Avenue with the horses and buggies, not the cars.
Dan: It was absolutely shocking. And you step back into the real world or here in the comfy environs of New England, and people are still getting soft-serve ice cream and playing putt-putt golf. They’re tucking their kids in at night, and the robots haven’t quite arrived.
Patrick: Not yet.
Dan: Not yet.
Patrick: They’re very, very, very much coming for all of us. And I think it’s going to mean, we can open it up to some more questions, but I think it’s going to mean for the IT services companies and the consultancies, and their broader ecosystem, there’s, I think, two things, Dan, that I think just to wrap it up from my perspective. As we look ahead for the next five years, let me back up, as we look ahead for the next three years, I think there’s going to be two really profound changes at the IT services companies and the consultancies that will have an impact, an effect on their relationship with the hyperscalers and the ISVs and the OEMs. And that is, first of all, pricing is going to change. We’ve been talking about it since AI, since ChatGPT got popular. AI forces transparency, and transparency means there’s going to be a change in the way that the pricing is done. We’re going to see the traditional times and material model fade, not fade away completely, and we’ve got different bets within this office, you know, what the percentage is going to be over time. But basically the way that IT services and consulting engagements are priced is going to change. That’s number one. And so, all right, and I’ll come back to what that means in a second.
Number two is staffing is going to change. You’re going to have full-time digital employees, digital full-time employees, whatever you want to call them. You’re going to have agentic agents doing a lot of the work of an IT services company, less so a consultancy, so there will be probably fewer people doing more work, or at least fewer people delivering more value to the enterprise customer. So, what does that mean for a hyperscaler or an ISV or an OEM? It means that their go-to-market, their sales alignment, even their leadership alignment, is going to have to recognize that the companies that they’ve been working with, the Accenture’s of the world, are changing and are going to change dramatically over the next three years. So, if they are aligned and understand where they’re going, and they can say strategically, these are the bets that we’re placing, then they’re going to be able to walk side by side with them and continue to grow. If they don’t understand, if an SAP doesn’t understand what’s happening, at an Accenture, at a Deloitte or an EY, if they don’t understand the strategic bets that those companies are making right now, then an SAP is going to be lost. They’re going to miss opportunities. They’re not going to be able to change alongside the IT services companies and the consultancies as they change. That is my soapbox that I just built and I’m very happy to be standing on top of.
Dan: Well, it reminds me again, to go back to some of the meetings that we’ve had and clients that we’ve been able to serve, as AI came out hard and really began to disrupt the services model, we immediately got questions and it looks like we can get to that question next. The core questions around pricing, if enterprise is now seeing fewer people in the engagement and the bill continues to climb year after year after year, we’ve been able to go out and look at the market and interview ITDMs and ask them, what is the perception of delivery of value? What is it that they’re willing to spend and pay? I mean, these are the core questions that we’ve been able to answer using the research, a lot of which we’ve shown today. And a lot of it is getting commission and going out and doing that kind of work.
Final thoughts
But one of the questions was, how do we see more of this? So, I believe there’s the link in the bottom of the portal here for the webinar. We’re happy to extend trial access to the entire array of data and analysis on our Insight Center portal. So, go ahead and pop in that request through the portal. One of the folks in my sales organization will be happy to reach out and set up a seat or two for your organization.
I think that about sums it up. Patrick, thank you. I appreciate the chance to come in and kind of be the host. It’s a little bit of an inversion for you, but it’s been fun. I love having the chance to chat. Look for us, we’re going to be hitting the road, probably going to London in a little bit, maybe going to Seattle, going down to Texas, we’ve got a trip to Chicago. Where are we not going?
Patrick: I think we need to go back to Toronto because in a lot of ways those meetings eight years ago sort of got the ball rolling on how the ecosystem was changing for all these guys. And most importantly, like they didn’t know, like they didn’t understand. They were sitting there, and by they, I mean the consultancies and the IT services companies, were looking out at their tech partners and saying, we know what they do. Like we see the technology, we can implement the technology, but what are they actually doing? What’s their business model? What’s their strategy? Which ones of these do we bet on?
Dan: Well, thank you, Patrick. This has been fun.
Patrick: Awesome.
Dan: So, thanks folks for joining us. Again, this has been Dan Demers on behalf of Patrick Heffernan, we appreciate you spending 45 minutes with us. Look forward to helping you. Feel free to reach out. Have a great day.
Patrick: Next week, I’ll be speaking with Chris Antlitz and Allan Krans for a retrospective on their 2025 predictions.
Don’t forget to send us your key intelligence questions on business strategy, ecosystems, and management consulting through the form in the show notes below. Visit tbri.com to learn how we help tech companies, large and small, answer these questions with the research, data, and analysis that my guests bring to this conversation every week.
Once again, I’m your host, Patrick Heffernan, Principal Analyst at TBR. Thanks for joining us and see you next week.
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