Good morning, everyone. Welcome to the Oppenheimer 26th Annual Technology, Internet & Communications Conference. Very pleased to welcome Insight Enterprises, with the CFO, Glynis Bryan, doing the presentation this morning. You know, we would prefer, if you have any questions, that we can ask those throughout the presentation. On the bottom of your screen, you can type those, and I'll ask on your behalf. We'll also take additional questions at the end. Without that, any further delay on my part, I'll turn it over to Glynis to do the presentation, but again, feel free to submit questions throughout. Thank you so much for joining. Thanks, Charles, thanks for the invitation to join you again this year. We appreciate it very much, welcome everyone to the Insight presentation. I'm gonna start out with our disclosure statement, which you can just take as having been read. I'm gonna jump right into slide 3, thanks, I have somebody helping me with the slides. Which talks about why Insight. In October of 2022, we had an Investor Day at Nasdaq, we talked about our strategy to become the leading solutions integrator. It's a new category. We think it's a category of one today, it's offering our clients a differentiated value proposition that drives business outcomes. What does that mean? It's a combination of hardware, software, and services, combined with Insight IP, that we use in terms of solving complex business challenges for our clients. We evaluate our success in terms of the business outcome that our clients get and the pretty much cost efficiencies or revenue growth that we drive for our customers. We have global capability, and we're supported by a management team with a clear strategic vision that we've communicated to all of our teammates, and everybody is focused on the prize, which is to become the leading solutions integrator. Over the past several years, we've had above-market growth, very profitable above-market growth. We've expanded gross margins even more so this year, despite the slowdown in the economy. Part of the reason for our success is that we have cloud, digital, AI capability that we combine with our core services delivery organization to deliver those business outcomes I just spoke about. We actually use automation technology and IP that our technical talent develops in order to help businesses scale efficiently, and we're using that same IP that we use with our clients to help us internally with regard to how our business scales as well. We've increased our cash generation capability. We have strong cash flow generation. I think at the end of the second quarter, we had, on a year-to-date basis, $188 million in cash flow from operations. We've done share repurchases in terms of returning capital to our shareholders. In 2023, through June, we have repurchased the equivalent of $217 million shares of our, shares of our stock, and we have $200 million remaining under our current authorization from the board. We have significant capacity to support our organic investments in the business, as well as M&A. M&A is not included in the targets that we shared with investors in October last year, it is a critical part of our strategy in terms of accelerating our profitable growth. Next slide. Our strategy, as I talked about, is to become the leading solutions integrator. Let me start by telling you what we're not. A solutions integrator is not a systems integrator. If you think about the Accenture of the world, they are focused on very large projects. Usually, they have clients that are... where they can generate $100 million+ of revenue on an annual basis. Insight does not play in that category. They're also very much focused on systems without necessarily the solution that they could bring to the table around hardware and software, plus those services that would actually drive a solution. Insight does not do ERP implementations, modifications, et cetera. We don't do that. We're no longer a reseller. We started out life as a reseller, and we've evolved over the last couple of years, several years, and through acquisitions, and we're no longer a reseller like Connection. The other thing that we really take offense to is when people call us a distributor. We are not a distributor. The distributors, the TD SYNNEX, Ingram Micro, Arrow, et cetera, they are partners of Insight. We leverage their capability when we need it. They may have product more readily available than actually a, one of the OEMs. We leverage them in those instances, but we go direct to the client, and distributors typically go through a middleman like an Insight, so we're not a distributor. We have four critical pillars of our client, of our, of our strategy. The first is captivate clients. That means delighting our clients, doing a project well, executing it flawlessly, so that we earn the right to do more for that client, and that is how we build our business. We start out with a small project for a client, maybe a proof of concept. We establish the value that the project will create, and from there, we actually then earn the right to do more, and we get repeat business on that basis. We're focused on selling solutions, and we have talked about the sales transformation that we started in 2021, refined it through 2022, and launched it in 2023 with our sales force. It actually is driving more profitable sales. We have a profitability initiative layered on top of that, that helps our sales guys better define what is the best price to sell this product at, one, and also what is the value that we're creating for a client when we actually create solutions, so that we can help them more appropriately price the solution to the client or the product that's embedded in the solution, as the case may be. The other key pillar is deliver differentiation. This is all around the IP that we have, the technical talent that we have. We have over 5,500 technical resources. About 2,000 of those are focused around digital AI, cloud enablement, the aspects of data analytics that are very much of the moment today. Before GenAI was there, we actually did many large data and AI projects for our clients. GenAI, AI for us, is an extension of what we have been doing over many years for our clients already. The last element of our pillar is champion our culture. We actually believe we've been very successful because of the culture that we have here at Insight, the engagement of our teammates that's demonstrated through our NPS surveys that we do, as well as the awards that we have won across the globe for best place to work in the US, in different countries within the US, as well as in most recently in Australia and in Hong Kong. With that, I'm gonna move on to our track record of innovation and M&A, and why this strategy has led us to where we're at today. I'm not gonna go all the way back in time when we were a reseller. I'm gonna probably start in 2015. In 2015... I'm gonna go back. I'm sorry, I lied. In 2012, in 2011, we bought a company called Ensynch. Ensynch was actually a services company, a pure-play services company. It was the first services company that Insight bought. It was small. It was here in Phoenix, and from that, we actually learned two things. We learned that when you buy a services company, keeping the talent is critical. The talent in a pure services company is a little bit different from the talent that we have in our core business, so Ensynch was a good first acquisition for us. They were local. We knew the owners, one of whom is still here and is actually leading our services business today, Stan Lequin. What we learned there is that we need to keep them separate initially. We need to maybe not integrate them. We integrated from a systems and finance perspective, but not necessarily from a front-end sales perspective, and then over time, a two-year period, we actually have integrated them. We followed that up with Ignia in Australia in 2015, getting our capability for our APAC operation in terms of what they, they needed to run their business. That actually has been a very successful acquisition for us. Moving on, in the US, we bought Datalink and then Cardinal, in 2017 and 2018. Datalink was a deep data center solutions provider, I would say, services provider. They usually wrapped services around the product that they sold. They were definitely more of an on-prem data center, and combined with the cloud capability that Insight had, it was a good marriage for us in terms of being able to then assess with our clients what they have on-prem, the workloads on-prem, which workloads could move to the cloud on a more cost-effective basis, and actually give them a roadmap over, you know, probably a three-to-five-year period, it doesn't actually happen immediately, that enables them to determine and move selected workloads to the cloud and reconfigure their on-prem data center. Most of our legacy enterprise and corporate clients are not going 100% to the cloud. They have an existing data center. They're consolidating that, maybe going down to one with a backup. In general, they will keep on-prem data center infrastructure, but move certain workloads to the cloud to maximize efficiency and then upgrade the existing data center so that they can take advantage of the digital and technical tools that are out there today. We bought PCM in 2019. That actually was doubling down on the small... not the small, we would say the commercial side of the business. Think about 250 seats to 1,500 seats. That actually is the backbone of Insight in, in the commercial side, and then we have the corporate and enterprise space, where we probably have about 68% of our business is in that commercial enterprise space. PCM significantly expanded, almost doubled the capacity that we had in the commercial 250 to about 1,500 seat size clients. Fenix was a very small acquisition we did in France around the Azure Stack. Then in 2022, we acquired Hanu, which gave us a presence in India and an academy concept that we could leverage to actually grow a base in India and be able to be more cost-effective and competitive with our overall labor charge-out rates for select projects in the US. I'm gonna move on now from there. I talked a little bit before about our technical talent and our industry-recognized experts. This is a map of our distribution across the globe. You can see anything that's highlighted in fuchsia or key color is Insight delivered, and anything that's in purple, partner delivered, anything that's gray, we don't play there. Part of what we've learned over the years is that when you're recruiting digital talent, technical, data AI experts, data analytics experts, data scientists, they like to work for companies where they feel they have a home, where there are other people like them already in the organization. We found that the best recruiting engine that we have is actually referrals from our existing teammates, and we've been very successful with retaining teammates from the acquisitions that we've acquired. Many of them are leaders across various aspects of our services business today. As well as leveraging, leveraging those same teammates in terms of referrals that we get from them as we're thinking about expanding the technical talent pool that we have. We also have a pretty robust university recruiting program as well in terms of new people coming in. I think overall, we, we have the ability to bring in seasoned experts, as well as an engine underneath to bring in new emerging talent, as well as our India base that now, is expanding on that, academy concept through, partnering with universities in and around the various key cities so that we can expand our talent pool as well in India. When you think about our areas of expertise on the next slide, we are well positioned to help companies, drive business outcomes. We think of our expertise in six key areas. I'm gonna go through all the modern ones on the, on the left-hand side: modern workplace, modern apps, and modern infrastructure. What makes them modern? What makes them modern is the underlying technology, products-- sorry, hardware and software, as well as services that we provide to our clients as we help them be more collaborative within their existing organizations. Think about modern workplace as being, as you are engaging with your client-- with your co- your teammates, how do you provide flexibility? Big word today in this, you know, hybrid environment that we all work in. A secure workplace, 'cause security is embedded in all of these areas of expertise. We embed security in those areas of expertise. Modern apps is, once again, what I talked about regarding the data center with regard to expanding in the data center. Modern infrastructure is combined with the data center in terms of how we can help clients make a determination about on-prem versus in the cloud, whether it's Azure, AWS, GCP, we're agnostic there. Clearly, we're a Microsoft shop, so Microsoft is one of the key drivers, and it makes sense since most of the clients in our portfolio are Microsoft clients as well too, so it's a natural default there. Intelligent edge is up and coming. I wouldn't say that we have a lot of revenue in this area right now, but as you think about all the data that's out there and what we can now do with data, whether it's using generative AI or traditional AI, there's, there's some data that needs to not be in the cloud, but be close to where the actual decision is being made. That data, think about an electric car, probably needs to sit in the car. That data center, that, that device needs to sit in the car to actually make those split-second decisions that are required. Millisecond decisions, really, as opposed to having the latencies associated with going back and forth to the cloud. The edge is a growing area. It's a combination also of hardware, software, and services that are required to make an effective decision with regard to: Should I go directly to the cloud? Should I put a device on the edge? This is gonna become even more important as we think about generative AI. Generative AI requires good data to start off with, but it also requires, the ability... It requires more bandwidth, it requires more storage capacity, more compute capacity. The choice that companies will have to make is, where am I gonna actually leverage that compute capacity? On-prem, at the intelligent edge, also on-prem, or through one of the hyperscalers that are out there today. Data and AI, we've been doing this for several years now. Started out with the BlueMetal acquisition earlier on, and then we followed up with Cardinal through that process, as well as Ignia. It gives us that base, and we've expanded from that base that we acquired over a couple of years and built that out now with talent that we have. We have 90 patents pending, 90-plus patents pending, and it's all related to IP that our teammates have developed as they're working with clients in terms of putting different software/platform pieces together in a different way to deliver a different business outcome for our clients, and that we can leverage across other clients in terms of helping them get to a faster delivery around certain options. Of course, cybersecurity is independent, but it, it's woven through all of these applications in terms of what we, what we need to do. We also have three key services: managed services, consulting services, and professional and lifecycle services. Think about starting with a consulting engagement, potentially about how do you consolidate your data center. You have multiple data centers, how do you consolidate to one or two? What is the backup process? Which workloads do you move off-prem? How do you manage them when they're when you move them to the cloud? How do you manage the efficiency of that cloud move? Then think of that consulting engagement evolving into a managed services to manage that data center, the hybrid data center that you now have over a period of time. Usually, it's a three-year contract. Then the hardware lifecycle services are related to some of the hardware products that we have and the software products that we have in terms of how we integrate them, in terms of a device that we may deploy across the country for a large accounting firm, such that it's plug-in-ready for teammates, and if the teammate leaves it at the security operation in the airport, as they're going through security, we wipe it clean and send them a new one to wherever their final destination may be. At the end of the life of that device, we take it away, we wipe it, we dispose of it, and we give them a new one. It's kind of like a cradle-to-grave scenario that we have. Maybe to illustrate a little bit about generative AI, very, very early stages, just a couple projects that we're working on. This is not to say that we're generating and monetizing GenAI today. We're talking to clients. We have a couple proof of concepts that we're doing with different clients. Several clients have asked us to help them with the governance structure around data and AI. I think as we think about data and AI, there are a couple of things I want to leave you with. One, if you're going to use your data, it has to be good data. It has to be validated. It has to be the data that is the source of truth in your organization. Many companies don't necessarily have that data estate managed well. Part of what we need to sometimes do for clients in advance, and that we did this for clients before generative AI, was actually help them manage their data estate. I think that MDM, Master Data Management, is what, what we call it or what the industry calls it. Part of that is ensuring that when you actually then apply Gen AI to your data, the answer that you get is actually meaningful and will drive the business outcome that you need, as opposed to a flawed answer, because garbage in is actually garbage out. A couple early, early stage Gen AI initiatives that we're working on with clients is synthesizing information to help with faster and better hiring decisions. Think about a recruiting firm that wants to pull in data across a variety of sources, not just LinkedIn, as an example, but a variety of sources, so that they can look across job postings, look at the candidate pool, determine what the salient characteristics are that they need to fill a specific job, and actually, do an evaluation across multiple clients, potential candidates. Do an evaluation across potential candidates and make a determination about which candidate should they move forward to their client. Or in the case of Insight, our recruiters are looking at this and using this and determining which, which candidate is the best candidate and which one should we move forward. We have a tool that we use, it's called Lens for Generative AI. We used to have Lens for AI before. It was a tool, IP, in Insight IP, developed by one of our key technical engineers, and now we have expanded that and leveraged the broader capability that Gen AI brings to the table. We're using that. One, it actually helps us very quickly knit together different pieces of information across the spectrum. Gen AI does that for us as well. And then create this platform that can support this ongoing evaluation of candidates and matching between candidates and job profiles more efficiently and effectively, like, really incredibly quickly. The other thing that we're looking at is a conversational agent, kind of taking chatbots to a whole different level by generating more free-flow dialogue and conversation that you can then knit together to create a more optimal solution for the client at the end. One of the efficiencies of Gen AI is it does, it does work that you can do yourself over a period of hours, days, months. It does it amazingly quickly. You need to understand how to ask the questions. You need to have the right database. You need to be able to pull in data from multiple sources. The beauty of, of Gen AI is that you can use video, you can use chatbots, you can use pictures, you can use image, words. It's across the entire spectrum. You pull all of that information into one place and get to a quicker, more effective solution, depending on whether you have the right data at the end of the day. I'm going to move on now and just give you a little bit of an example about a large hospital client, and this is not a Gen AI example. This is just an example of what we do. It's traditional AI with large language learning that actually helps knit together for multiple data points. In this particular example, it's a healthcare service provider, and they wanted to look at treatment for patients with high blood pressure. They were looking at something that had 800 patient data points. For each patient, they had 800 different data points, and they were trying to pinpoint what is, what is the best course of treatment for each patient based on the specifics of their data points, and have a much more targeted treatment for hypertension, not in general, but very much specific to each individual client, and be able to do that at scale and to be able to do it quickly and effectively. I would say that this solution for a large hospital chain that we worked with them on, leverages ongoing machine learning. As you get more information in the portfolio, as you test and learn, it gets incorporated into the tool that we've, we've built and provided to them, and they can refine and predict more, more prescriptively what is the best solution in terms of treatment care for the clients on a go-forward basis. Pretty impactful in terms of hypertension care going forward in their hospital chain across the country, so they can leverage this in many different places and improve patient quality of life as it relates to high blood pressure. I'm going to move on quickly and just summarize our Q2 earnings. In Q2, as we said, we, we were, we didn't have the results that we had expected in Q2. Let me put it that way. We had revenue growth revenue decline of 14%. The good news in the quarter, as it relates to the strategy that we have on a go-forward basis, is the following: Our gross margin expanded 240 basis points. Our services business grew, services GP grew, cloud GP grew. Those are two tenants with regard to how we will achieve our, our ambition to become the leading solutions integrator. Our cash flow improved dramatically, and our earnings... we're down 8%. Net sales down 14%, gross profit down 1%, earnings down 8% overall. A little bit disappointing for us. We would have preferred if we were flat at the earnings line. However, I think the elements of our cycle, our of our strategy remain strong throughout this time frame, time period, and we had EBITDA margin of 5.9%, the highest, one of the highest, a record for us actually in that year. Our gross margin was 18.4%, up 240 basis points, also a record for us. I would just remind you that typically, Q2 is our highest margin quarter. It's a little bit the Microsoft effect in terms of their year-end. Being in Q2, and usually a higher volume of software and cloud services that drive that gross margin. What we said in our guidance, what we said on the call, was that we would anticipate that at the end of the year, we're gonna end 2023 with margins, gross, gross margin in the range of 17+%, which would be a record for us in any given year. I'm gonna move on now and just talk about the full year outlook. We said that our gross profit was gonna grow in the low to mid-single digit range. That's down from what we said in Q2. I'll tell you the reason for that decline. The reason for that decline is that hardware is not performing as well as we had expected. We knew hardware was gonna be down. We're not, we were not blind. We knew hardware was gonna be down. Hardware was just down 24% for us in Q2. We had expected that hardware would be down in Q2, but not at 24%. Hardware being down 24% was actually offset at the GP line in terms of getting to that 1% growth by growth in infrastructure, as well as cloud and services growth. We started these profitability and pricing initiatives in the back half of 2022, and those are actually helping us drive more profitable in deals, in terms of each deal that we sell, such that we were able to minimize the effect of the, that 24% decline in device revenue. We changed our guidance on adjusted EPS to be $9.40-$9.60. That reflects our view that the economy, as it exists today, is probably gonna continue through the second half. We don't see that there's gonna be a significant uptick in the second half that would drive us back to the $9.90-$10.10 that we had originally envisioned. Interest expense down slightly. Our effective tax rate is 26%, and our capital expenditures down slightly to $45 million-$50 million versus our prior guidance of $55 million-$60 million, primarily related to the fact that we are just evaluating, pulling back on some of our own expenditures as our clients are doing, and making a determination about what are the key priorities for this year versus what we can push into next year. With that, I'm gonna go on to our, the KPIs that we shared with you, with our investors in October of 2022. On the right-hand side, the 2027 CAGR KPIs. We said we're gonna get adjusted EBITDA margin of 6.5%-7%. Adjusted ROIC greater than 25%. Core services growth somewhere in the 16%-20% range. Cloud GP growth, likewise, in the 16%-20% range, diluted EPS growth over a 5-year period, in the 19%-22% range. Adjusted free cash flow as a percentage of adjusted net earnings greater than 90%. Over the trailing twelve months, our adjusted EBITDA margin has increased to 5%. In Q2, it was 5.9%. Adjusted ROIC is 15.6%, still increasing to get to that 25% mark. Core services growth was, trailing twelve months was 13%. EPS cloud growth was sorry, cloud growth was 23%, and our diluted EPS was 12%. Adjusted free cash flow, as I said, was a strong thing for us at a 224%. I think we're well on the way to achieving the objectives that we had laid out with regard to our strategy. It was never gonna be a straight linear journey, but nothing that we've seen today would say that we need to change strategy, change course. We're well on the way in terms of our, our expectations about how our strategy is gonna play out in this economy, as well as over the remaining four years that we have to get to 2027. I'm gonna move on now and talk a little bit about key drivers of our strategy. Part of it is around sales growth that is above market. It requires core services and the cloud to grow at a faster rate than product. Product being hardware and on-prem software. Core services, services delivered by Insight or managed by Insight and cloud will grow at a higher rate, almost double the rate of product growth. That's a key driver of the margin expansion that we talk about, as well as our portfolio and pricing initiatives, and the way that we're incenting and compensating our sales force on a go-forward basis, which drives them to more profitable business. In a reboot. Then we have the continuous operational improvements around operating leverage. I think we talked in our conference call just recently about growing our SG&A at a slower pace than our GP growth. We ourselves are leveraging process automation and technology to help us be more efficient so that we can scale without adding additional resources as we grow. We're leveraging the tools that are out there around digital and big data to better help us target specifically with the sales force, how it is they can sell and follow up and have some predictive analytics around what products your client bought, XYZ. Likely, they're maybe doing something, check this out with your client, see whether these products will also be helpful. Oh, by the way, maybe there's a solution that we can help them with in terms of determining what the business outcome is they're trying to drive. I think those are the key pieces there. With that, I will just summarize with our alloc- our capital allocation philosophy. We invest to accelerate above-market growth. That, that's one of the key kind of internal drivers. On an organic basis, we do that through organic investments that we make in our sales force, increasing the breadth of the solutions talent that we have, in our technical talent, and ability to leverage and scale that technical talent. We're also investing internally in automation to make us more efficient in the long run. Other big part of our strategy that is not included in any of our metrics today would be M&A, and we have three criteria that we use: cultural fit, strategic fit, and financial. The cultural fit says they have to kind of live what we call the Insight values. The strategic fit says they have to fit into the portfolio, either because they're increasing our capability in a specific area, or our expertise in a specific area or geography. Then there's scale as well, ultimately, with regard to when these scale acquisitions come to the market, we don't control the timing. We evaluate that, take a look at them, and make a determination about whether it would be good for us to roll into our portfolio and consolidate. On a financial basis, we have our discount rate is 300 basis points above our cost of capital. We look to be EPS, positive EPS, accretive in the first full year following acquisitions, and we expect to be 300 basis points or more above our WACC in, in the, the third year following acquisitions. As you've seen, we've been increasing our returns to shareholders. We did $217 million of share repurchases, as I mentioned earlier. We have increased cash flow generation. We're gonna be leveraging that cash flow generation through a combination of M&A, as well as returning capital to our shareholders. From a debt perspective, currently, we are at a leverage ratio. That's not really how our debt facility works, but we're at a leverage ratio of 1, and absent acquisitions, that's kind of sort of where we would be. We would be sub one, if we didn't do any M&A because the business continues to generate cash, and eventually, we would pay off the debt that we have outstanding. We have the ability, one, to fund future M&A, two, to fund share repurchases, and three, to invest in our business on a go-forward basis. We have a $1.8 billion ABL facility, and we have $1.5 billion available as of the end of 2023. With that, I will open it up for any questions that we may have. You know, Charles, if you asked any questions, I couldn't see. Very good. Thank you so much, Glynis, and I think you did a terrific job getting through everything. I just had one question that came through, which you did address, your, your view of the macro environment for hardware and it being down a little bit more maybe than expected. Is there anything that was, you know, concentrated in the way that, that came through? Or, you know, do you believe any of that was kind of pulled forward? Then maybe any thoughts on just kind of volume versus pricing? Is pricing a component, maybe it's not as strong as it could have been? Just curious your thoughts on that. ion. So I would say that in the macro environment, hardware, we said, was down 24%, but within hardware, devices were down even more than that. That says that it was offset by infrastructure. Going into Q2, actually going into 2023, we talked about having a record infrastructure backlog. Think about networking and server storage backlog that was going to... It's because of the supply chain issues that we had in 2021, 2022. So some of the product that we're getting now in the infrastructure space has been ordered, like, over a year ago. So the supply chains are improving. We're starting to see that product flow through, and we had the benefit of that in Q1 and in Q2, and we're gonna see the benefit of that in Q3, and maybe a little bit into Q4, before the backlog for infrastructure normalizes. The backlog for devices normalized earlier last year, and we had said that we thought hardware would be down this year. The reality is that hardware is down much more so than we had envisioned. We have a lot of large enterprise clients, and hardware and large enterprise clients is the, is the asset that they can sweat when they wanna conserve capital. We're seeing a lot of that ultimately. Our view is that we're almost at the bottom of the heart of the device decline, and that we should start seeing some improvement in devices, maybe not in Q3 so much, but in Q4. For Insight, since we have this heavy enterprise corporate mix, we would anticipate that we would get the benefit of, of enterprise refreshes starting in the second half of 2024. I say that only because historically, enterprise refreshes from a device perspective, happen later. The SMB market adopts it earlier, but the enterprise clients tend to adopt later, going through their IT departments as they make their own assessments, et cetera. Windows 11 will drive some, some refresh in the second half of next year, we believe. Perfect. Well, we'll give you 2 minutes here, Glynis. I just wanted to thank you and the Insight team for joining us today and everyone for dialing in on the line as well. Look forward to seeing everybody again soon, and thanks again. Thanks, Charles. Appreciate it. Thank you.