AI, Cloud, and the Channel: A Conversation with Ingram Micro’s CEO

With AI reshaping the global technology channel, what role is Ingram Micro playing in addressing partner challenges and opportunities?

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Hosts Patrick Moorhead and Daniel Newman are joined by Ingram Micro's CEO, Paul Bay, for a conversation on how Ingram Micro’s platform-driven transformation and AI strategy are impacting the technology channel. The discussion covers the evolving role of global distributors, the launch of the Xvantage platform, closing partner skills gaps, and how Ingram Micro is balancing traditional offerings with new demands for AI and cloud solutions. 

Key Takeaways:

🔹Evolving Channel Leadership: Ingram Micro’s foundational role in technology distribution and its strategic shift towards a platform-centric approach, actively driving innovation for partners and vendors.

🔹The Power of Platform Transformation: Insights into the transformative impact of the Xvantage platform, redefining how value is delivered to partners and vendors and measured by key business and customer engagement metrics.

🔹Navigating Market Shifts: An examination of strategies for managing the intersection of traditional PC refresh cycles with the escalating demand for AI and cloud solutions, ensuring a balanced portfolio for a dynamic market.

🔹AI & Talent in the Channel: A look at how artificial intelligence is influencing both internal operations and external value propositions, alongside strategies for leveraging global reach to address critical talent and skills gaps across the channel.

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Learn more at Ingram Micro.

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Patrick Moorhead: Welcome to the Six Five podcast. I am Pat and that is Dan. I appreciate you guys tuning in today. You know, Daniel, I always talk about in this fast paced AI world, it does take a village, right. People need help. And companies are not only who are helping people, not only are taking advantage of this huge AI interest, but also they're using AI themselves to help their customers.

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Daniel Newman: Yeah, the terminology can evolve and change and it really depends from vendor to vendor, partner to partner. Sometimes the word ecosystem, sometimes the word is channel, sometimes the word is go to market, sometimes, you know, but what they really are saying is something that you sort of alluded to, Pat, is that it's never one. And so when you look at the complexity of what it actually takes, and it doesn't matter if it's the all in one big rack Nvidia NVL72 system or it's a whole distributed set of implementations across 20 locations, right. There's going to be partners, consultants, there's going to be integrators, there's going to be distributors and channels and value add all over the implementation. So there's a great topic and something I know at least you know, you and I care deeply about and we've invested heavily in building this practice.

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Patrick Moorhead: Yeah, for sure. And let's talk, talk to somebody who's at the forefront of that and that is Paul Bay, CEO of Ingram Micro. Paul, welcome to the show.

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Paul Bay: Thanks for having me. I'm looking forward to it.

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Daniel Newman: It is really good to have you here. Ingram Micro is a very, very large company and of course, you know, while you're in the billions and billions of dollars in revenue, sometimes when you're somewhere in between, the end customer, say the massive bank or pharma company that uses technology and the tech provider, you heard me say Nvidia or it could be Microsoft, there's these big companies in between, but not always do they get the same amount of publicity, even though they're so intimately involved in these, in these integrations? Give us a little bit of the just background and explanation of Ingram.

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Paul Bay: So yeah, a lot of times people say we're one of the largest companies that people haven't heard of. So we're 45 years old. We just went public in October of 2024, October 24th. So now we're back on the fortress. So we're a Fortune 100 company and as you mentioned, we're doing billions of dollars. We do nearly $50 billion in revenue and we sit right in the middle of that multi trillion dollar global technology ecosystem that you guys are discussing each and every day. We do business in nearly 60 countries and we have over 160,000 customers. What I'll just use because there's a lot of different names as you know for them, I'll call them solution providers. And as you know, these customers are really solving the technology challenges and providing those outcomes for those millions of end businesses that they're serving each and every day. And so through our customers, we're proud to say because of our reach, we can reach nearly 90% of the world's population. And you know what we're excited about? We're transforming into a platform company through our, what we call our AI driven digital experience platform that we call Xvantage.

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Patrick Moorhead: Yeah, let's drill into that. We talked a little bit about Xvantage at the The Six Five Summit. It was great to have you guys there. But I want to talk about metrics. In the end, AI ideas are great. Putting stuff on a PowerPoint presentation and spreadsheet are one thing. But what are the core metrics that you're using to determine the degree of success of Xvantage?

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Paul Bay: There's a couple of things I think actually maybe if I can give you just a little bit of background on the journey we're going on with our, with our customers. So this transformation of our company to our customers comes in three phases. So the first one is really about removing friction and streamlining operations and driving operational efficiencies. The way I like to look at it is what's the cost to serve? So to answer your question, in this first phase we've done things which a lot of times there's inbound distribution and the relevancy and the value of distribution for a lot of years has been about the really kind of tactical and there's a lot of friction in this industry because on average we have six products or services, six different vendors that are made up of our average solution. We receive over a million emails a year with respect to, hey, place this order, put it into your system. And this is my order. It's email validation. And we've created technology where we actually take that email and make it touchless. It goes right into our system and confirms right back to a customer. Another one is what we call order status and tracking. Like we know in our personal lives, you know when stuff is going to arrive at the front door of your house or your office and order status and tracking our industry has been very challenging because of the complexity of Carriers and vendors and all the things that go along with that. And we've created some technology where actually now you can get on our platform and you can see the order and when it's going to arrive. And the reason why I bring that up is because we're making it more efficient in that cost to serve our customers to actually free up time to spend more time with those end businesses every day. So that's kind of the first phase and we look at that as how long are people coming onto the system? And we've got some great success that I shared in our Q2 earnings results with regard to how long people are on there, how many self service orders are up considerably quarter over quarter and year over year. The second phase is really around demand generation and for our customers it's how do we shorten the sales cycle for them. An example of this is we have what we call an integration sub. And you guys know this, there's so many different systems that are out there today. Our systems that our customers are using, their CRM systems or many different versions of it, their ERPs of how they're running their business and just other business applications that are running their operations. What we've done with our integration hub is ensure seamless connectivity into the Xvantage platform. Effectively we're meeting partners where they are on their digital journey. And so we're trying to provide a very consumer-like ease of doing business. And a lot of these integrations into these CRMs and ERP systems could take months, many, many months in IT technical resources. And now what used to take many months can actually happen in minutes. And then the last thing I'll just touch on is kind of the third phase that we'll get through with our customers is really unlocking value for our customers and our vendor partners. And it's about what I always talk about. The easy way is what a platform for me is, how do we take the supply and the demand and bring that together. So how do we take supply and demand more intelligently to use this data to help them further grow and enhance their profitability ultimately with their end businesses. So I look at this as profitable organic growth or say it another way, how do you use data and insights to drive the company and help our partners?

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Daniel Newman: Paul, you know you alluded to the fact that you were pretty much private until just about a year ago and now you're a public company. It's interesting, I was reviewing some of the metrics, and it looks like you had a really good performance. Performance beat on the numbers that people, the people that shareholders like to see beat and the analysts, of course. I also know some things in your numbers that probably aren't surprising to anyone that knows channels, but you definitely run on it on a thin margin. Like you have to run this business incredibly efficiently. 0.3% profit margin on billions and billions of revenue. I mentioned AI has become quite an a, an interesting tool for you to look at. You know, I, we've talked to a lot of CEOs, there's a lot of efficiency gains where it was the early sort of implementation use cases we've seen. And then of course, it's all about growing in productivity. Right. It's getting all the things you just talked about moving. But I'm super interested because you're, you're hitting numbers, but you're, you're always walking on that thin ice because margins are tight. You've got to execute almost perfectly. Where's AI sort of driving, you know, your ability to A, execute more with customers in the channel and then of course, B, are you putting it to work inside Ingram to maybe try to get that extra tenth or couple tenths of percentage of margins up in the business?

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Paul Bay: Yeah, it's a great question. So thanks for recognizing. We did have a good Q2. And so I always tell the team we got to continue to perform while we transform. And you mentioned, you know, kind of AI and we've used the buzzwords now, but we're really, what we're doing from a platform, platform standpoint is we're using AI to effectively do it's in our business to drive net new growth for our customers. So I'll give you a couple of examples of how we're doing this. But if you look at what we did, we think that architecture matters. So when we started this journey just three years ago, the first thing we did was we had to pull our information out of all of our ERPs over the almost 60 countries that we're in. So we're not ERP dependent, we're ERP agnostic because we pulled everything up into a data mesh, not a data lake. So we're using AI and machine learning automation, which is really the basis for a program that we call, and I talked about on the earnings call, it's called Intelligent Digital Assistant. We call it ida, the acronym, which helps our customers win more business and deploy more resources effectively. You called out, that was my first phase, which was around productivity. How are we freeing up time to go from inbound to outbound? But now it's about how do you take that next step. And IDA is really around that second phase, which is how we're using advanced AI and machine learning models to analyze data across. We take it and IDA has more than 50 attributes to help our customers identify and prioritize sales opportunities that are most aligned to them. Let me give you an example. So at the end user, because of all the data we have, we can see the end user information and these customer. I'm just gonna give you an example. The customer places an order or a quote with us. So they have a quote there. We can tell based off of that quote that the end user that they're servicing may have the propensity. I'll make it up that they'll procure within the next seven days. We're proactively reaching out to our customers to say this quote that you have in our system with this end user, because of the data we have and the way we've set up our AI and ML automation, we can tell you that in the next seven days they're going to purchase. Historically, we're going to make a purchasing decision. So what we're doing is, is helping move our sellers from being reactive inbound order takers along with ourselves to outbound, proactive outbound order makers. And that same again, it goes for the same. We've seen this with success with many of our customers that are saying, look, you know the end user better than we do and you're providing us real valuable information to help me grow. As an example, in Q2, our IDA alone, we brought in tens of thousands of opportunities to our partners that we were calling, doing outbound calls. And these were valued at hundreds of millions of dollars on a global basis, which was actually up nearly 50% sequentially. And we've done this for the past two quarters. So the point is, this isn't about basis points on margin, this is about adding more value. And how do we actually help go drive further value creation and value capture for our customers as they're out servicing the millions of end businesses each and every day.

Patrick Moorhead: Yeah. So Paul, my company, we evaluate generative AI architectures and platforms. I'm not just saying this because we're on this video right now, but. But you just outlined what you're doing is very sophisticated, meaning this idea of having multiple ERP systems, being able to have a common data mesh and to be able to activate and add value on top of that. So congrats on doing that. There's a lot of people talking about it. There's not a lot of people doing it because of the complexity of just how hard that is, I wanted to get into. I wouldn't call this a more tactical discussion. It's about managing the challenge of. On one hand, you have this giant Windows 10 to Windows 11 PC refresh and a little bit of AI PC mixed in with this gigantic opportunity out here with the data center. We talked about Blackwells, whether it's the H series Blackwells and everything in between. How do you manage these two? I would surely hope there'd be more profit with AI and cloud infrastructure as compared to PCs, which is, quite frankly, it's about velocity, it's about the different things you can add to that solution to be more value added. How do you balance those two things?

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Paul Bay: Yeah, it's a great question because as you know, and you've been in this industry for a long time, we saw kind of the chipset shortage when we went through some of the server and networking business a few years ago. We had Covid before that, and now we're sitting right in the middle of this kind of refresh that's going on from a systems perspective. But let me talk about how that kind of comes together. As I mentioned, the six different products and services and what we call the flywheel effect, and how we're using this to drive growth in new ways and not just around one category. So we're combining the solution. So the ultimate goal of what we've done is we're providing a single pane of glass. So what we're doing, having this conversation today, whether it's your computer, whether it's your phone, you know, your mobile phone, desktop, your mo book, your, you know, mobile device, anything that you basically run your business on. For our customers, we're giving our customers the benefit of selling, supporting and managing more complete solutions versus just a single transaction. Yeah, which is what this industry used to be. I need to get something from point A to point B. It's hardware, it's complexity. And we like to talk about how we've invested in front of the future. We spent more than $600 million on our cloud platform more than a dozen years ago over the last dozen years. And really that was the foundation for Xvantage, because you're bringing together the single pane of glass that you're able to have where you have hardware, as I mentioned, software, cloud and services, all in one transaction. And when you look at consumption and as a service is a different outcome and deployment of how you manage that than a physical good. So our goal is to generate this flywheel effect of growth, which it hasn't been done yet. You know, people always talk about Ingram as you're going to this, this platform and, and what you're doing is most companies that start as a platform company, these, these new platform companies are starting from scratch. We're taking a 45 billion profitable, or excuse me, a 45 year old, 50 billion dollar, nearly $50 billion company. And we're transforming it. We're not starting from scratch. The challenge is we have a very successful company that we've been doing business for 45 years. But effectively what happens is we have the largest network of customers, 161,000 customers, we have 1500 vendors. So we have two of the three things that can reach 90% of the world's population. The challenge of what we didn't have and this industry quite frankly doesn't have is the technology that brings that ecosystem together more efficiently and intelligently. So we're transforming this company. We have the supply, our vendors, a huge vendor solution portfolio, our great customers that choose us each and every day to give us nearly $50 billion. And now we're providing the technology to bring that together. And what we've done over the last four years is we built this proprietary real time data mesh as we've talked about a little bit. And it's not just a data lake. So a lot of people are using buzzwords in the industry. And our data mesh provides the data value and it can do it at scale and it's about providing data at the time that we're able to take. It's not just the unstructured data in a repository, it's truly providing the ability to bring together that single glass experience. So we're pretty excited about where we are and things that we used to take. Literally this journey where we're seeing some of this intelligent automation. I just gave you the IDA example. Many of the things we're doing, I gave you the integration example. Things that used to take months and days, we're taking out of those B2B trans, this fragmented B2B transaction of business we're in and we're handling it in minutes and seconds. So we're pretty excited about that as we go through these three phases. Sorry about that. The lights went out on me. And so that's kind of what we're doing around how we're helping enable our customers.

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Patrick Moorhead: That's great.

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Daniel Newman: You want to flash them on? We can pause a second.

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Daniel Newman: Just to keep you lighted. That's really fascinating as a leader of a business that's going through a transformation. I love your platform story. Again, it's a careful predicament for many of us that have service intensive or channel intensive businesses to sort of use the word people, you know, want to challenge. Is it a buzzword? It sounds like it's not. And we're, you know, the same thing. It's, you know, it's like an analyst business used to be very every person was your scale. Now it's like knowledge can be scaled with data and with insights and with wisdom piled on to AI as a, as a platform. And it can be delivered in new ways. And it sounds like that's really your mission is to figure out how to deliver the services that people really care about in a new way while taking advantage of all that infrastructure that You've built over 45 years. And I want to, you know, congratulate you. I honestly learned a lot just listening to you because you're a. We appreciate it.

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Paul Bay: Sorry to interrupt you, but I love the fact that I appreciate we're getting into a little bit of the differentiation because part of the challenge we have is that everybody can use it. We played buzzword bingo at the beginning, right? You hit on all the kinds of things that are going on in the industry, but all things aren't like the words that are there. But really what's happening below the surface is where we think the real opportunity is because we put the customer, our solution providers in the middle of everything we do or how we're building out. What are the challenges they have? Today it's about OPEX efficiency, how do we free up time then how do we really go drive more demand and shorten those sales cycles for our industry? And it's challenging when you have, you know, as much scale as we have, but the opportunity we have is pretty exciting.

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Daniel Newman: Well, I'll tell you, just, you know, Pat and I rarely talk about our own books. Wink. We love talking about our own books. We can, but like, we literally, you know, just went through a transformation of looking at how evaluations are done by analysts and we basically said they're too long, they're too slow, they're too full of friction, they're backwards looking. And the point is like with AI, with, you know, autonomy with information and data, can you make them forward looking and can you make them dynamic in real time and with AI? So what I'm saying is you take an old business that's really beat up and something most people don't like doing, and you say, how do we make this business great to do business with again and make it really valuable. And it sounds like that's really been your mission. And this obviously always, Paul leaves people in the in as it was part of the equation, the human side. You have a lot of large companies, lots of people, and of course, AI. We've talked a little bit about it. It's creating excitement for those that have really embraced it and have used it to scale. It's created some consternation and fear for people that say, oh my gosh, this AI can work faster than me and can do my job. What am I going to do next? And then of course, you've got all kinds of areas you're expanding into beyond AI. You've got cloud, you've got cyber, you know, not just, you know, moving PCs and servers. I mean, how do you sort of think about how you address talent, how you give people that growth incentive and how you create a culture that makes Ingram the kind of place people want to work and of course, staying on the cutting edge and driving that profitability.

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Paul Bay: Yeah, it's probably the hardest thing. I would say culture and mindset have been the biggest challenge because as I mentioned, we've been a successful company for, you know, 40 plus years when we started this journey. And so we like to say in the human aspect, relationships still matter in this business. I've been around this business at Ingram for 25, been around this industry for 30, and I have some of my best friends over those many years of creating relationships. So relationships matter and that human element matters too. So we're not trying to just automate everything and take all the human touch out of it. What I'm trying to do is make sure that we make it as efficient as possible and how do we free up people to go have more proactive conversations. We like to say at Inger Micro, the skills we have today are not the skills we want tomorrow, but the people we have today are the people we want tomorrow. And so it's on us as leaders in the organization to how do we go through that change management and make sure we say, here's where we are today, here's where we're going. This is what our expectations will be of you as we go on this journey and how do we help them through that? So it's been one of the single biggest things that we continue to focus on. And then when you put that at scale, because everything we do now is global, because our global data mesh is everything. So it's all out of the erp. So what we're doing in the US is the same capabilities and opportunity we have in the UK or in Brazil or one or the other in India, all around the world. And so you get different cultures mixed into that, too, and you get the differences a little bit about how those markets and how you service those markets. So the human element is probably where I spend a fair amount of my time on how we're going from where we are to where we want to go, and how we make sure we're helping our team members get to where we're trying to go.

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Daniel Newman: Yeah, well, Paul, this was great. It was really interesting. And the. The data mesh is one of the big takeaways, not just a data lake. And by the way, that's a really important thing for people to discern in this era. We spent, by the way, 20 years sort of saying if you just get your data in order, big data, you'll be ready for what comes next. And amazingly, most companies, many that you probably served in 20 years of big data, never got their data in a position where it was ready. So doing it with massive data like you have at Ingram, to be able to deliver value is no small task. So congratulations on that.

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Paul Bay: Hey, I appreciate the fact that you acknowledge that, too, because that's really what it's about. And people are going to talk about and use the buzzwords, but we spent a year literally getting the data right and hiring the right talent from outside the industry or outside of our company and bringing that together. And at the end of the day, AI is only as good as the data. And so if you don't have the right data, it doesn't matter. You're going to be, you know, dressing that up to something that's completely different or running reports and calling it AI. So, you know, it's a journey we're on. We're proud of where we are. We're kind of in those first couple of phases. As I mentioned, when we get to phase three, we'll be super excited. And I hopefully, as we continue the journey, I'd love to. To continue to have this conversation with the two of you.

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Daniel Newman: We will absolutely. Both Pat and I will tell you, even with our smaller data problems, it's a great challenge to try to make it really usable and accessible. And so I want to learn more, we'll spend more time and in fact, if I'm not mistaken, I'm going to have the chance to spend some time with you at the Ingram One event. So I definitely want to call that out. Myself and Tiffany Bova, our head of research, will be joining me and can't wait to be there. But it's so great to have you here on this 65 episode, Paul. Hopefully you'll become a regular. We've got so many great guests. Love to make you one of those that spends time with Pat and I more frequently. And for everyone out there, we appreciate you tuning in. Such a great story here, so much to learn from a great company like ingram that over 45 years has created a $50 billion business delivering it and so many more technologies. Now, to all of you, subscribe, be part of our community. Stay with us. But for this episode, I got to say goodbye. See you all later.

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