Quantum Corporation (QMCO) Earnings Call Transcript & Summary

Welcome to our 2022 Quantum Investor Day. My name is Brian Cabrera, and I'm the Chief Administrative Officer here at Quantum Corporation. Our presentation today contains forward-looking statements about the company's plans, strategies, and prospects, including capital structure and go-to-market strategies. We will also describe the company's future operating results, financial position. These forward-looking statements are based on information available to the company as of the date of this presentation and are based on management's current views and assumptions. These forward-looking statements involve a number of known and unknown risks that could cause actual results to differ materially from those anticipated. Welcome to our 2022 Quantum Investor Day. My name is Brian Cabrera, and I'm the Chief Administrative Officer here at Quantum Corporation. Our presentation today contains forward-looking statements about the company's plans, strategies, and prospects, including capital structure and go-to-market strategies, which will describe the company's future operating results, financial position. These forward-looking statements are based on information available to the company as of the date of this presentation and are based on management's current views and assumptions. These forward-looking statements involve a number of known and unknown risks that could cause actual results to differ materially from those anticipated. Such risks include changes in market demand and competition we face, market acceptance of new products, and the continued impact of the COVID-19 pandemic on the company's business, including on its supply chain. Information concerning other risks that could cause results to differ materially from our expectations is contained in the Risk Factors section of the company's annual report on Form 10-K and quarterly report on Form 10-Q filed with the SEC on June 8 and November 2, 2022, respectively. The company undertakes no obligation to update forward-looking statements to events or circumstances after the date they were made. In this presentation, the company will be discussing non-GAAP measures of adjusted operating expense, adjusted EBITDA and adjusted EPS, which are calculated from results based on GAAP. These non-GAAP financial measures are provided to enhance your overall understanding of the company's current financial performance and prospects for the future and are not comprehensive of the company's financial results. Such measures should not be viewed as a substitute for the company's financial statements prepared in accordance with GAAP. You can find a reconciliation of these metrics to the reported GAAP results in the reconciliation tables provided in the appendices to this presentation. A reconciliation of the non-GAAP measures to corresponding GAAP metrics on a forward-looking basis is not available due to high variability and low visibility with respect to the charges, which are excluded from these non-GAAP calculations. Now I'd like to turn our presentation over to our President and CEO, Jamie Lerner. Jamie?

Hello, and welcome. I'm Jamie Lerner, Chairman and CEO of Quantum. Today, we're going to be talking about a very large dislocation, very large change that's happening in our society in and around unstructured data. The world is producing more unstructured data than it ever has. 90% of the world's data is now unstructured. And this represents a massive opportunity for Quantum to build an end-to-end architecture to manage this data. But before we start, we probably should talk about what is unstructured data. And maybe it's best to talk about what it isn't. When we first started storing data using computers and technology, we predominantly stored numbers and letters and words. So think about it as columns and rows of data, columns of numbers, columns of names, addresses, phone numbers, very structured information. The information that we're talking about unstructured is very different. Think of it as hours of video surveillance data. Think of it as x-ray images, medical images, radar, LiDAR, CAT scans, movies and television. That data is massive. It is complicated and it's very hard to manage. And that's the opportunity that we're talking about today. I'll be speaking about our strategy and the underpinning investment thesis that we're taking on as a company. We'll also be inviting IDC to speak today to talk about the trends that are happening in our industry and the trends that are happening in the markets in general. We'll also be hearing from Brian Pawlowski, our Chief Development Officer. He's going to be speaking to the products and the product market fit of how our products are addressing this in a very unique way, a very defendable way, and we'll also be hearing from John Hurley. John will talk to our sales strategy and how we're going to market. And lastly, Mike Dodson is going to bring all this together into a 5-year performance statement. What makes unstructured data so fascinating is that today, most of the products and services around us are actually built with unstructured data. You could think of unstructured data as the raw material for the products you use today. When you watch a movie, maybe 30 years ago, that movie was actually made with film or with video tape. Today, films, television, they're really just a big piece of data. When you go and receive health care, your body is studied through medical images, which are data, X-ray, MRI. And when a drug is administered, while that drug is made out of chemicals, it was actually designed and tested and built through data, through the analytics of data, through the studying of data, really almost everything around us is a result of data. Even the cars we drive -- yes, they're made out of metal and rubber and electrical components, but they're really built with data, the music you listen to, the way the car drives, the way that it navigates itself the way that it provides safety features. They're driven by radar, LiDAR, interaction with the Internet and other forms of data. Really everything around us is built with unstructured data. And that's why we're so excited about this opportunity because the companies that manage their unstructured data, unlock value from that unstructured data better than their competitors are most likely to win. And those are the companies that we want to work with. So when we think about the size of this market, IDC has helped us size this market at roughly $15.7 billion by 2025, and it's growing at over 11%. So it's a large market. It's growing very quickly. And we believe we have very unique technology and a very unique strategy. It's going to be very hard for our competitors to follow us, copy us and duplicate the things that we're doing. Now $15.7 billion market, that's really large, but it's actually made up of a series of end markets that Quantum has years of experience serving. So that would be movies, television, sports, an area that we've worked in for over 20 years were often recognized as the leader in post-production storage infrastructure. We also have a long legacy in surveillance and physical security. This would probably be the largest end market for unstructured data. Cybersecurity and backup protecting this information, not just protecting it from data loss but protecting it from cyber criminals. There's also very large end markets in archiving, which is work that we've been doing with the world's largest hyperscalers to archive this data for years decades and even centuries. Very large end market in medical imagery, life sciences, think about genomic sequencing, X-rays, MRI imagery, LiDAR imagery of the planet, photography of the planet, just very large image archives. In addition, a new and emerging market is autonomous testing of technology. Think about testing of semiconductors testing of industrial equipment, and that testing generates millions or hundreds of millions of log files of test files and these files need to be studied, analyzed and archived. We also have been working with a lot of new use cases around advanced AI and machine learning, autonomous vehicles, autonomous airplanes, autonomous industrial equipment like autonomous mining equipment, autonomous forklifts and delivery vehicles. And ultimately, all of this leads to a huge amount of generation and sprawl of files that need to be managed. 4 years ago, we had this as a vision, but we really lacked a lot of the components and technologies for an end-to-end architecture to manage this kind of data. So we set about building new technologies and acquiring technologies to fill in this end-to-end architecture. One of the first things we did is we wanted to build a brand-new platform on the latest high-speed technology called NVMe flash storage. So we built a product called the F-Series. It was probably the first thing we had developed ourselves in quite a few years. And if you fast forward to today, it's one of our top-selling products, and it holds the SPEC SFS world records for 3 very important unstructured data performance criteria. We added to that an acquisition called ActiveScale. It's an acquisition of an object store, very modern storage and it sits in the midrange. So our F-Series, while it's the world's fastest, you may know about our tape products that are probably the slowest and cheapest and active scale sits in the middle. So we have high-speed storage, mid-range storage and cheap and deep long-term archive. Now one of the things we wanted to do is begin to build metadata. Now what metadata is, it's data about data. So if we have a file that tells us, well, it's not just a file, it's a file of surveillance information at this location. This is what's happening in the video. This is who's in it. This is what they're doing. These are the events that happen in that video and when that occurs. That's all metadata. So we acquired a company called Atavium that had a deep metadata repository that we've now folded into our core products. We also acquired CatDV that gave us a catalog. So if you have files all around the world, some on the Internet, some in the cloud, some at different locations, some of different tiers, we have a catalog of all those files that can help you search them, find them, manage them, move them. We also, during this period, started working with several of the world's largest data users. The largest cloud companies in the world, who have the biggest archives of unstructured data. And we started working with them on new advanced ways through both software and hardware to store and preserve this data very economically in a very green and environmentally friendly way, but store that data for centuries. And fast forward to today, we've become the #1 vendor in that space. We started adding components both internally as well as through acquisition to do a very advanced video surveillance, something that we hadn't been so good at. Maybe 4 years ago, we were new to that. But through the acquisitions of both Pivot3 and EnCloudEn, we now have over 1,500 customers today and some of the most advanced facilities in the world where we're doing video surveillance. We've also introduced cold storage technologies that are software defined for allowing not just hyperscalers to do massive archives, but allowing our enterprise customers to do that as well. And we've been adding a lot more AI enrichment and introducing AI and machine learning modules across our storage platforms. Now you bring all that together, we actually now have the most advanced end-to-end architecture for managing unstructured data. So let me pull it all together and walk you through what that looks like. Unstructured data is somewhat different than structured data in that it moves. It's modified. It's really part of a data factory. And so that data begins its life very fast. It is coming off a surveillance camera, coming off a satellite, coming off a medical piece of equipment, and it needs to be studied analyzed, modified very quickly. And so it starts on the red side of the slide or the last end of this architecture. But as it is worked on and as it becomes more of a finished good, it slows down. It moves to midrange and ultimately into archival storage. Now during that lifetime, the data requires a catalog and a workflow system. So almost all unstructured data is part of a factory and all factories are a workflow, a series of processes and steps that go from one to the next. And we have a workflow system that sits above all of our products that allows you to find data, sift through that data and move that data to the appropriate platforms, getting approvals along the way for each step. Underneath our architecture, we have an AI-driven operations platform called Cloud-Based Analytics that lets you monitor the health of our systems, the activity of the systems to make sure the environment is healthy, and being operated in a way that is optimal. Quantum has been serving customers in the unstructured data space for over 40 years. We have an incredible installed base of customers that range from the world household names in media and entertainment, the world's biggest television companies, movie companies, sports franchises as well as some of the most critical video surveillance environments in government facilities, critical facilities, casinos, transportation facilities, airports, and also, we've been serving government branches from civilian defense in both the U.S. and with countries around the world. And this installed base is so critical to us because this is really where our strategy begins. We're approaching our installed base, asking if they've been happy with the product they bought from us. They may have bought a tape product. They may have bought a backup product, a moviemaking product. And we're asking our customers if they trust us to go end-to-end. And by end-to-end, we want to do their creative workflows. We want to do their archival. We want to do their video surveillance. We want to help them with AI and machine learning, would they really go end-to-end with us? And overwhelmingly, our customers are saying, yes, they'd like to do that. And so to talk more about this, I'd like to introduce IDC, Natalya and Ashish, who are going to go into this market opportunity and the trends that are happening in our industry in more depth.

Hello. My name is Ashish Nadkarni, I'm Group Vice President and General Manager of IDC's Enterprise Infrastructure Research practice. Today, we will be talking about unstructured data market trends, the workloads that are driving its growth and what it means for the future of digital infrastructure. Now I'd like to turn it over to my colleague, Natalya Yezhkova, who will go into details on these trends and how they align to Quantum's business strategy and portfolio.

Hello. My name is Natalya Yezhkova. I'm Research Vice President at IDC Infrastructure team. And for the past almost 20 years, I cover storage infrastructure. And in recent years, I also cover infrastructure for enterprise workloads. Today, we are going to talk about the current state of the storage industry, which is tightly related to the all -- everything digital in our life and a big element of this industry is unstructured data. So if you think about our life today, it's becoming more and more digital, whether we consume services, whether we buy our products, whether we acquire new knowledge, whether we interact with each other, everything in our life one way or another touches upon digital services. Likewise, business is function in a very similar way. And though business strategies in the internal operations in the interaction with our customers and building customer experience, they rely on digital technologies and on the backbone of these technologies, the IT infrastructure. The 3 major pillars of IT infrastructure includes autonomous separations, cloud technologies and ubiquitous consumption, which ensures that this infrastructure can be accessed from anywhere and can be managed and consumed in a consistent way. Cloud Technologies here refer not at where the technology is deployed, but at functionality at how the infrastructure is being managed, whether it's located in public cloud or at the Edge or in the corporate data center. In fact, if we look at today's organizations, they have multiple cloud technologies, multiple cloud strategies related to use of public cloud, related to the use of a private cloud. But what is important, the use of cloud also came with the use of cloud came realization that IT world became balanced. And cloud, whether it's public or private, is not uniformly solve all the problems that the organization face. And what we start seeing in the past several years is departure from cloud-only or cloud-first strategies to cloud also and best fit strategies, which allow organizations to build more efficient, more effective IT organizations. And essentially, it is hybrid IT. So looking at some results from a recent survey, our Cloud Pulse, which is done across multiple countries. 50% of applications, which organizations currently have is still deployed on premises. And actually, this ratio isn't -- is expected to stay fairly stable in the next couple of years. So this is the balance we are talking about, 50% of applications are still running on-premises. And other applications are running in other environments. It's not only public cloud. It can be hosted cloud, it can be colocation facility, there are like multiple choices that organizations have now. And what is remarkable, some of the emerging workloads, which are now driving a good chunk of the demand for IT infrastructure like here, I highlight AI life cycle, which is workload associated mostly with AI training, text and media analytics and structured database, they expect to grow across both dedicated and shared cloud environments. And this rate of growth are now accounting in double digits from the perspective of storage capacity, which is shipped to support these workloads. And what is also important for this particular presentation, 84% of data in these fast growing workloads are unstructured, along with a couple of other workloads, which I wanted to mention, current applications and digital services, while they are not growing as fast as the other 3 workloads I mentioned, they are also one of the largest workloads, which organizations use and we will be able to use and evolve in the future. Along [indiscernible] workload I emphasize is artificial intelligence. So here on this slide, you see only a part of the AI ecosystem. So it's just AI life cycle workloads, which are focused on AI training. But if we also include AI inferencing, that's one of the largest and fastest-growing workloads across multiple areas of business and IT infrastructure. And a successful implementations related to artificial intelligence include file systems. And like in particular, parallel scale-out file systems. So that's becoming -- this one single workload becoming one of the major drivers of demand for file storage. And also looking at this more unstructured workloads and workload associated with data protection with archiving, whether it's unstructured workloads or structured workloads. These are growing areas of business, which also provide more demand or generate more demand for integrated file and option-based strategies for organizations. In the forecast, which we published last year and which we will be updating later this year, we show that the overall market for file and object based storage including hardware and software is expected to grow at 9.9% compound annual growth rate between year 2020 and year 2025. And by 2025, it will reach $44 billion in spending. The workload evolution, part of which I showed on the previous slide, also impacts how the file and object market is changing. In the past, majority of file was object-based scale-up storage. Now this is the smallest segment of this market is not growing. In fact, it is declining at a 1% CAGR. Most of the growth and the size of the workload is of the file and object-based storage market is on the scale-out architecture site. And the 70%, actually more than 70% -- almost 80% of file-based storage is deployed in dedicated environments. And about 30% of object-based storage is deployed in dedicated environments. And this includes non-cloud like more traditional deployments as well as dedicated cloud or like another word from private cloud, whether it's on-premises or off-premises. So for organizations for vendors, who deliver products on the market, the way how they deliver is becoming as important as functionality of the product itself. And here, like speaking about Quantum. Quantum has a great portfolio of products. And in recent years, it made a number of acquisitions, which enhanced this portfolio of offerings, which targets unstructured data across multiple areas, across multiple domains from video surveillance, media entertainment, active on cold data, data protection, analytics, this becoming a very comprehensive portfolio to sort this type of data. But also how the data is deal or how the products are delivered. Appliances products, subscription-based products, integration with public cloud services, availability of these solutions on as-a-service consumption. That also kind of completes the picture, which positions Quantum would grow in the next several years. Thank you.

I'm Brian Pawlowski, the Chief Development Officer at Quantum. Our tagline is your differences in your data, and I'm going to talk about how our difference is in our software. There are 3 key things I want you to take away from this presentation. First, current approaches to storage are failing in the face of the explosion of unstructured data; second, the only way to tackle this problem is through a comprehensive end-to-end approach from data creation to archiving; and third, at Quantum, we are making use of state-of-the-art AI from driving insights from data for customers to driving the management and movement of the data itself in our end-to-end architecture. Let's look at the emerging challenges facing IT leaders around the explosive growth and use of unstructured data. Unstructured data are those things we store in files and objects. High-resolution von images, complex medical data, genome sequencing, the input to machine learning models, captured scientific data about the natural world such as maps of oil and gas fields and the simulation of reality. The next era of data brings with it just a huge amount of unsolved challenges. The data is exponentially larger than anything that's come before and growing. We're talking about trillions of files, exabytes of capacity. And the challenges are compounded because this data does not stay in one place, but moves throughout its life cycle and is highly mobile from the edge to the archive. Additionally, it's going to be used for decades, not just archived or preserved for decades, but used for decades. Organizations will need to access this data online through standard file and object methods. This presents a whole new challenge in terms of how to think about the accessibility of long-lived data. Lastly, unstructured data is the least understood compared to the traditional methods of storing data like a database. The sources and formats of unstructured data are continually evolving. Deep meaning and context is only derived from the intersection of disparate data types and sources. Our customers know they have millions or billions of files and objects, but they don't know exactly what's inside of those files and how to really use it. And this is a huge unsolved problem for the foreseeable future. So how are you putting together both the storage and data enrichment architecture for the next era of data. At Quantum, we believe it requires a completely different storage architecture and advanced data services designed from the ground up to be cloud native. A scale-out solution based on containerized microservice implementation. The need here is to deliver a seamless hybrid workflow experience from on-premise to the cloud, regardless of where customers choose to deploy their applications. Building on our experience to date, delivering an end-to-end data-driven storage architecture. We find that we are using AI in 2 ways. First and foremost, to help customers judge the importance of their data and enhance the insights they can get from their data. We turned this enriched metadata tagging and cataloging. Second, we use from an AIOps perspective, that is using artificial intelligence for IT operations to automate and streamline operational workflows. AIOps is the next step that allows customers to ensure that they are using their money wisely that their data is automatically located properly to provide required performance at the lowest possible cost at any given time. Automated AIOps is the only feasible approach looking at scale of unstructured data today. The age of manual data management and movement by the loan system administrator is long behind us. Of course, it is critical to provide a comprehensive end-to-end cyberattack resilient infrastructure solution. External criminal threats resulting in data loss have overshadowed traditional worries of inadvertent data loss in the enterprise storage. Those problems are solved with well-known approaches today. Today's companies and products are built with data. And I want to talk more about what it looks like for these unstructured data workflows. When I visualize an end-to-end approach to large unstructured data management, it looks a lot like a factory. We start with raw materials. You have a lot of unstructured data being generated by some type of edge device, satellites, cameras, DNA sequencers, autonomous vehicle instrumentation. The data then goes through a space that we call work in process. This is where the raw data is transformed in some type of finished product. And then lastly, are the finished goods, where data is deployed and also preserved for reuse, often for many years or decades. During the work in process phase, there are some capabilities that really matter. Performance is often the first thing that comes to mind; second, the ability to easily connect to the data and collaborate from anywhere is critical; and third, this is really the stage where we first start to use AI data enrichment to derive more value from the data. When it comes to long-term data archiving, there's a different set of capabilities required. The capabilities needed are the ability to store data at the very lowest media cost possible. The solution needs to be sustainable and green that is power and data center real estate cost efficient, and it must operate reliably at exabyte scale for years. One additional behavior of unstructured data that complicates this factory model, is that data is mobile across the entire factory and data does not only move in one direction. Take for example, moviemaking. The raw materials are shot. Video is captured. It's turned into a finished product through editing and special effects additions to create your favorite movie or TV show. Then it's stored for long-term retention. But our customers in media entertainment want to then bring back finished goods to do new takes on existing high-value material and produce extended addition releases, adding new material in commentaries or more frequently today, up raising of old content for new high-definition markets. Film making is about one example. The data factory model is really applicable to many of the largest unstructured data applications that are driving all this growth. As you can see, the concept of data factory is a big challenge that Quantum is solving for our customers today, building on our experience, delivering an end-to-end data-driven storage architecture. So what have we learned so far delivering an end-to-end architecture to our customers? First, the future of high-performance primary storage is software-defined flash. Flash-based storage is where all the high-performance workloads are moving to over the next decade; second, for long-term data archiving, the future is really about software-defined disk and tape. Tape still provides the lowest cost way to store data for years, providing unrivaled density and zero-cost power draw for dormant data. But the use of tape has evolved dramatically from its previous position as a simple backup solution, where you put things you thought you never had to access again. Tape today is effectively replacing large capacity, slow spending disk storage as the nearline storage solution of choice where data is dynamically and continuously accessed. Today, spinning disk use cases are increasingly being displaced by high-performance flash for critical primary data applications as shown on the left side of the diagram, while tape is the nearline storage media of choice as shown on the right. Is spinning disk dead now. Spinning disk is still a cost-effective solution for very specific sequential and streaming data applications like video post production, where our StorNext product remains unbeatable from a price performance perspective. So let's drill into the right side of the diagram, software-defined disk and tape. This is an area where Quantum has been rapidly innovating. We are the acknowledged leader in providing software-defined tape to the hyperscalers for their new object-based nearline storage applications, the so-called Glacier Class storage. It's been an amazing growth business for us. In the past year, we have sprung from that work to release an enterprise data center product called ActiveScale Cold storage, which brings the technology we've developed in partnership with the large hyperscalers to a broad range of Fortune 5000 customers. ActiveScale Cold storage delivers the industry's first on-premise deep archived tier, a long-term S3 object based cost-effective and highly durable exabyte scale storage solution. This solution allows our customers to effectively address the same challenges that many of the hyperscale customers face in delivering cost-effective long-term preservation and reuse of massive amounts of unstructured data. Because of this work, we were named the leader in object archiving for this product in a recent GigaOm Sonar report, and we're growing wins with the solution with our large on-premise customer deployments. Now let's talk about the future of primary storage. The future of high-performance storage is software-defined flash. We have an amazing track record already with cutting-edge flash technologies, such as low latency NVMe fabric. We introduced our first software-based flash storage solution, the F-Series 2000 and in 2019 and won Product of the Year at the NAB show and several other awards, and we've had great product adoption by our comers. This product is currently used with our StorNext file system and high-end video postproduction use cases. We recently introduced the next generation of the F-Series product, providing twice formats at the same price point. Early next year, we'll be introducing the F4000 series that integrates the entire StorNext stack into a single NVMe flash box. Now while that's amazing for StorNext, we know that realistically, StorNext only addresses about 5% to 8% of the total scale-out unstructured data market. It's very good for high-end post production, it's very good for select video and image workloads, but there's a much broader market out there where StorNext doesn't fit the needs of many emerging use cases, such as modern data lakes, high-resolution imaging in health care and life sciences, advanced software development, deep data analytics and advanced business intelligence and more and more AI and machine learning approaches are being applied across all of the industries we serve. The new storage platform road map focuses on an all-flash scale-out and object-storage platform designed to address the challenge and opportunity of a huge unstructured data market. In many ways, this next-generation platform completes our end-to-end story when it comes to storage infrastructure. The next-generation storage platform brings together the best of Quantum innovation where everything is software-enabled by providing for the storage and management of files and objects at massive scale using a ratio encoding to provide cost-effective data representation when ensuring high availability, containerization techniques as cloud-native microservices enable the hybrid world, and we use advanced data reduction to reduce the cost of flash ownership. Enriched metadata is used to drive user insights and enable autonomous data movement across the factory, all the while setting a new bar for ease of use for an all-flash storage platform. So that's what the next era of data looks like. For data storage, it requires an end-to-end architecture that is uniquely Quantum with software-defined tape for long-term data archiving and software-defined flash for the high-performance workloads. Quantum brings this together to manage data across that entire data factory life cycle. AI tagging and advanced metadata management allow us to both add value to existing or for the user and drive policy-based data management to minimize the cost of storing data over its dynamic life cycle. So the next era of data, it's not just about storing the data. It's about enriching it and making it available where it's needed, when it is needed. So I want to bring back to 3 points to remember through this talk and remind you that, first, we believe the current approaches of storage are failing in the face of the explosion of unstructured data; second, at Quantum, we believe the only way to tackle this problem is through a focused end-to-end architecture spanning from data creation to long-term archiving and providing for mobility throughout the data life cycle; and third, at every point in the data factory, we are making use of state-of-the-art AI from driving deep business insights for data customer use to driving the data management and movement of the data itself between stages and the data of the factory. I want to now turn it over to Dave Clack, our General Manager of our CatDV business unit, to show you the ways that Quantum is enriching data today using cutting edge AI.

Quantum's vision is to be the leader in video and unstructured data. Key to this vision is our capability in analytics, understanding and enriching the data on our customers' storage platforms. Quantum's analytics inform our customers' business decisions, how to store data cost effectively and safely while adding value to our business processes and workflows. CatDV and Quantum's implementation of AI and machine learning are important parts of our strategy. Bringing AI into the reach of all Quantum customers is transformational and the market is in its infancy. This kind of enrichment using cutting-edge AI and machine learning will shape our industry in the years to come. Quantum's AI implementations are extendable and include models that include language transcription, speech detect, for search and captioning, image, object and logo detection, not safe work content, people and celebrity detection, traffic flow and more. CatDV is the container for our data enrichment and AI results and provides a visual searchable index of the customers' content and the enriched metadata from AI processing. In addition to the third-party AI with Amazon, Microsoft and Google, Quantum is investing in its own AI and ML implementations with our partners at NVIDIA. NVIDIA's GPU technologies power the majority of the world's AI workloads and Quantum's AI services provide unmetered, flexible and trainable AI that can be learned on-premise in our customers' data centers or in the cloud. Here, we are showing some of the AI analytics unlocked with Quantum AI tooling. Common AI workload include video upscaling and quality improvement with using noise and artifacts and unlocking more value from the digitization of older content. Adding language translation to transcription in both written and spoken audio, even including lipsing opens new applications to existing content. Enriching content, with body positioning led shots of people sitting, standing, lying, dancing or fighting be tagged and searched. With CatDV and Quantum's AI enrichment tools, Quantum is bringing the power of AI to all of its storage platforms, current and future.

Hi. My name is John Hurley, I'm the Chief Revenue Officer at Quantum. I want to follow up on some of the things you heard recently from Jamie and from BP, really around 3 areas: the market opportunity that Quantum is going after today, the sales transformation that I've been working on for the last year, and then how am I going to do that in a very profitable way, because in the market we're in today, I've got to be much more efficient in how our sales organization operates. So let me start with when I came here about a year ago, the sales organization was very point product focused. So you had folks in the organization that were either selling media entertainment products, they're selling backup products or they were selling into the hyperscale space. We needed to evolve. The messaging that we've been working on for the last year is really about how do we stitch together the technologies that we have from an ingest perspective to deep archive products. And then how do we have a conversation with our customers about what more could Quantum be doing with you as we talk to you about some of your biggest business challenges. So we've been working on that for last year, and we're in a really good space right now about how we're doing that. In the last 6 to 9 months, I've been really focused on putting a layer on top of our media entertainment and other groups that we have out there and starting to hire folks that can focus into the enterprise market place. As you've heard from both BP and Jamie, there's a lot of other opportunities we start to think about next-generation scale-out flash systems. So we need to have the right people in here that can have that conversation. So the profile that we've been working through is coming from folks in the marketplace that today sell in an end-to-end fashion. And so we're bringing them into the organization, and we'll continue to cross-pollinate those throughout our organization. We're also going to be selling in the primary storage space, and so I'm hiring a lot of folks in that area as well and have a tremendous success getting those folks to come into quantum. As we evolve over the next several years, the big part that we need to do is really talk to our customers, not so much about technology, but really about what they're trying to solve. A lot of customers today in a market are either trying to develop new revenue sources. But when we look in some of these other markets, they're trying to save money. They're trying to save cost. They're trying to save energy savings. Whatever that may be, there's a critical business problem, and we need to be able to understand that and apply our end-to-end message to how we can solve that problem. The other part is we committed and we're continuing to move along on this process of moving customers to subscription, but also how do we serve them in a managed services way. So in partnership with Ross Fujii, who runs our customer success organization, we're going to continue to work on our as-a-service offerings into our customers so they can acquire technology the way they want to acquire and that it help them much more expediently move forward the business. I mentioned at the beginning that I need to do this in an efficient way. So I'm not going to be out there doubling the size of my sales organization, but what we are going to do is try to go deeper and wider with our larger accounts. So I've asked all my sales leaders across the globe to take their account teams, talk about the top 10 to 15 customers each of these reps would have. And then how do we build longer, broader conversations with them? How do we go and sell into different market spaces within those organizations? Have account plans to talk about the end-to-end message and how we can help their customers. And we do believe that over time, as our new technology starts to emerge, the amount of opportunity that we'll open up inside those customers, especially these large enterprise accounts, the ASPs or the average selling price and those accounts will actually go up, and we'll start to see 2 to 3x the ARR that we're looking for as a recurring offer. So really deep and wide understanding business problems at the top layer. The middle tier, which again, if you remember, we have about 10,000 customers out there today. Many of those customers are going to be served by our partner community. So call it mid market, call it mid-tier, we're going to continue to do that. So where the customer is at the top end of the pyramid are going to be Quantum directly led by partner fulfilled. We're going to continue to do this partnership models that we have out there through our Channel 2.0 model, and we'll start to see scale and expand with the channel partners that are out there today as they transform with us to be able to sell more in an end-to-end fashion to the channel partner. The bottom tier is our lower cost model, which is really coming out of the inside sales organization. And there's 3 areas there that are very specific to me. One is our services business. So how do we do service and renewals, how do we then go and do more volume, small, medium business outbound calling type of thing. And at the end is, as we've continued to transform our customers into a more subscription format, how are they actually adopting the technology? Is there more opportunities inside the organizations to take advantage of these subscriptions. And then as we get to the end of that model, how do we renew, so we continue to move that through that layer model on land, expand, adopt or renew. So this is the way we're going to tier out our sales organization. We're not looking to add more. We're just having our conversation with end-to-end, which we do believe will bring up the level of ASPs. You're probably asking are customers adopting this new model? Are they listening? And I think it's pretty simple. When you talk to a customer today and you ask them just a question. Do you like doing business with Quantum? Are we serving you the right way? Do we sort of support you when you have issues? For the most part, we have a lot of customers out there that enjoy using our technology and have used it for many, many years. So here's an example of our professional basketball team. We started in a very straight forward use case, StorNext, selling video management within their organization. Well, they have a stadium. So we started talking to them about how do they handle video surveillance. We actually -- you trust us with your video of the sports team, which you entrust with us your video surveillance environment. Of course, they said, we'd love to hear more about it. We talk to them about our Pivot3 technology. And if you look at where we've gone, we've taken a $200,000 onetime point product sale and we turned into $1.5 million sale around StorNext, video surveillance and then deep archive. Very important technology for us, but again, it showed the level of expansion when we have a broader end-to-end conversation. Let me give you another example. In the Federal government, again, a single use case, where we did a backup technology to tape, then we started asking the customer in the last year. What else are you challenged with. And you can imagine there's a lot of video surveillance opportunities out there in the federal government. But not only are they looking at the video that they have in the space around video surveillance, but how do they search upon that? How do they manage it, how they long-term archive it and they got very interested in our object store. So now you see a customer that would do backup and tape solutions with us in about $600,000. Now this customer is over $3.5 million, but over $1 million of that is recurring. So we made that transition with this customer by having an outcome-based conversation with them about what they challenge with and how can our end-to-end conversation and solutions really benefit them. Let me close with this. This is the opportunity that I talked about at the beginning about where we're going as a company and how the sales organization is aligning. So when you think about the sales motion, we're going from single point products, single points of pain to a more end-to-end conversation about what's the customer trying to do. We're moving from single areas, media entertainment, backup and hyperscaler as an example, and we're adding on to that a much broader enterprise focus, so that we can open up those opportunities in the TAM space that we have with those large enterprise customers. Compensation, the previous compensation was good for its time. But as I think about how we get the sales organization to really partner together and work from a specialist perspective and cross-sell, I changed the compensation pattern this year to a much more growth-oriented plan to cross sell, actually benefits the account managers to more work together selling the entire portfolio. The deal size, you can see we're -- we've taken several customer examples that I just used, and you saw the size of that change. So we do believe that over the next 5 years, we'll take deal values from $75,000, well over $200,000, with a much more higher subscription recurring rate coming along with those deals. The results. We'll take a high $370-some million business. And over the next 5 years, grew well over $650 million to $670 million. And we feel that progress is really right in front of us because I think what you heard from Jamie, I think what you heard from BP and now what we're doing from a selling organization is, we're more than prepared to take advantage of this opportunity. I want to thank you for your time today. Now I'd like to introduce Mike Dodson our Chief Financial Officer.

Thank you, John. And welcome to the Analyst Day. I'm Mike Dodson, and I'm the CFO. What you've heard so far is that we have a significant market opportunity in front of us. We've got the technology, the products to address that market opportunity, and we've got a sales strategy to take advantage of that opportunity. And what I'd like to share with you today is the business plan that pulls everything together. It's not rocket science. When you look at revenue growth, you look at gross margin growth, you look at OpEx discipline that drives a strong operating leverage, which will lead to a strong EBITDA growth and cash generation. So I would first like to on the next slide here, go over our financial goals. And this year, we've split these between midterm and long term. So the midterm, which is 2024 to 2025, we're looking at getting to a revenue level of $510 million, which is a 12% CAGR. And included in that total revenue is recurring revenue at 44%, which has a CAGR of 24%, and that's twice as much as the overall revenue growth. Now with revenue at that level and recurring revenue at that mix level, that would drive a gross margin of 39% to 45%. That would drive OpEx to 32% to 30% of revenue and generate EBITDA of $30 million to $75 million. And then when we look at the long-term model for fiscal year 2026 and fiscal year 2027, we would look to reach a revenue level of $670 million in total, and that would represent a 14% CAGR. And the recurring revenue would be 55%, and that's 27% CAGR for recurring revenue. And with revenue at that level and that mix of recurring revenue, the gross margin, we would expect to be 50% to 52%; OpEx, 27% to 26%; and EBITDA generation of $150 million to $180 million. So if we go to the next slide, I'd like to talk about our revenue and our revenue growth. And one difference from our model last year, and one thing that we learned from a year of doing subscription revenue contracts with our customers, is that our customers really want to buy our hardware with our software. So last year, we had assumed for the primary storage business that we were going to go to a pure software model eventually. And our customers would buy their hardware from -- we were agnostic to who they bought it from. What we've discovered is because our customers really want to buy our hardware from us, we've kept that in our financial model. So you can see the onetime hardware revenue -- in last year's model, that was declining. And in this year's model, it's slightly increasing, and you can see the target CAGR of 7%. So that is one difference from last year's model. And one distinction to understand is really we believe that lowers our execution risk on our long-term model that to keep the revenue in -- the hardware revenue in our model. So when you look at the recurring revenue, the recurring revenue is important. It's really our growth driver. And the growth in this recurring revenue really represents our software subscription model. And what's key about that and the growth of that is if you look at a level leaving fiscal year 2023, although it's rather small because we've just got 1 year behind us. By the time we get to 2027, we believe that's going to grow 15x. So that's really a very strong growth and very important to our business to be successful and understand that's really in our primary storage business is where that growth is. So when you look at the total revenue, the target is 13% CAGR, and it gets us up to $670 million. But you can see the growth is really driven by the recurring revenue, a little bit of growth from the hardware but that is how we think of our revenue and our long-term model. So on this next slide, what I'd like to talk about is how do we get the operating leverage. Yes, we can increase our revenue but operating leverage will come from higher gross margins and more disciplined or continued discipline on the OpEx side. So as it relates to the gross margin percentage, there's really 2 driving factors that allow us to get to the 52% by 2027. The first is our mix in revenue. We're going to see a significant growth in our primary storage business, and that typically has higher margins. And when we look at what we're leaving fiscal 2023, the level that we're leaving that year, including the support revenue and the subscription revenue, we look at what it is in FY 2027, we're growing that business 3x. So that's really a key part of the gross margin story because that's helping our mix and it's driving those margins higher. And also included in that revenue is our subscription revenue that we've talked about. So that's also important to accelerate that revenue, which will help our margins. So those are the 2 key drivers to get to 52% by 2027. And then when we look at our operating expenses and our discipline over that, we showed last quarter, we got to our target on OpEx 2 quarters early. So we've shown a good level of discipline to keep those expenses in line and to reduce those. So we've demonstrated that we can look at our operating expenses, we can do things better. We can do things with less. And we would continue that discipline through the long-term model time. But also, as John had mentioned, his sales strategy is really going to be more efficient. When he is selling end-to-end solutions and they're selling to large enterprises our average deal size should be bigger. And it's just -- it's a more efficient sales model. So we would expect to see leverage there as well. But those factors will combine that we believe we can get to 26% operating expense as a percentage of revenue by 2027. So if you go to the next slide, what this strong operating leverage means is we are generating significant EBITDA and significant cash flow. So when you have higher gross margins, less operating expenses as a percentage of revenue, you're growing your revenue overall. You can see the power in our operating model and the strong operating leverage that we have. Now when we get to this point and we're generating cash and we have a much strong balance sheet, first, we want to put this cash on our balance sheet, and we want to have that strength. But it also gives us -- affords us a little bit of flexibility. I think the first thing that we would look at knowing that we've got this flexibility is to refinance or pay down our debt. Now we've demonstrated over the last few years, we have been paying down our debt. We've been refinancing for lower interest rates. So that's always been a focus and would continue to be a focus for us. But also with a stronger balance sheet, you can look at organic investments to support your growth. You can look at inorganic opportunities. But as again, we've demonstrated over the last few years, the inorganic opportunities, it would have to fit our strategy. It would have to fit our financial model, and we've been very conservative in those efforts. So we would continue with that philosophy going forward. And then finally, we want to return value to the shareholders. So it's plans like a share repurchase. I know that's years in advance, but that's how we think about allocating our capital as we move forward. and as we are successful on our financial goals. And one last thing that I would say is related to the cash flows, we've talked about the operations and what gets thrown off the operations. We're not a capital-intensive business. So you think of other uses of cash, you think of CapEx I mean historically, our CapEx has been 1% to 2%, and we would expect of revenue. We'd expect about that level. Also, we've got debt service -- it runs at 5% of the balance. So that's $3 million to $4 million a year. So those are really the only 2 key areas outside of our operations that would be using cash -- so that's not significant, but you should take that into consideration when you think of our long-term model. So in conclusion, on our journey, I get to the last slide, what I'd like to share with everyone are the key metrics of our targets for 2027. That's revenue of $670 million. That's recurring revenue of 55%. That's a gross margin of 52%. And adjusted EBITDA of $180 million. So with that, that concludes our prepared remarks. Thank you for joining us on our Analyst Day here today, and I'd like to open it up for questions.

Thank you for attending Analyst Day. We're now going to move to the Q&A. I -- what we're going to have on our panel today Jamie, Mike, VP and John, who you've already heard from. We've also arranged to have Ross Fujii, our customer -- Chief Customer Success Officer, Natasha Beckley, our Chief Marketing Officer; and Eric Isom, our VP of Supply Chain and Operations. [Operator Instructions] Let me start. I see a few here already. Let me start with just kind of a little bit of amalgamation. Jamie, I wonder if you could talk a little bit about the approach that you took this year in terms of the modeling and how you categorize this year versus last year in terms of this presentation?

And the executive team and the Board thought about our 5-year model, we had a couple of themes in mind, Clearly, we've been impacted by supply chain issues by the pandemic and now certain macroeconomic headwinds. And so overall, we wanted the model to be conservative and most importantly, achievable. So we wanted to make sure that our opportunity was vastly larger than what our needs were or our goals were. The other thing we thought about was lowering the execution risk. We've been transforming Quantum for a number of years. But clearly, if we can achieve our goals with a less aggressive transformation, it allows us to lower the risk portfolio for everyone. And finally, we wanted there to be a significant amount of considerable amount of unmodeled upside, where there were multiple opportunities for us to exceed the plan and exploit further opportunity. So maybe I should hand over to Mike. Mike can describe some of the changes that we made this year over last year to make the model more conservative, to make it a lower execution risk and less of a long jump to achieve our goals.

So when we look at our model this year versus last year, the first thing to highlight is the gross margins and when you think about execution risk, right? We had -- we were -- had a model that was leaving the last year at -- in the low 60s. And this year, this model is leaving in the low 50s. And that lower margin really reflects the new approach that we've got hardware in there. We listen to our customers. We understand we're going to have hardware in our model. And what that's done is it's increased our revenue, right? We've got instead of hardware revenue decreasing, it's increasing, albeit at a 7% CAGR. But I think it helps bolster the company. It creates EBITDA and it really reduces the execution risk. When you think of we were expecting to take all of our primary storage business eventually to a software subscription model. So that revenue -- the hardware revenue is coming down. And the other thing that takes the execution risk out as it relates to this area. And as John has described, is we're going end-to-end. So we're not selling products, right? We're going end-to-end. What that means is we're talking to fewer customers, and we have a larger deal size. So that's another key factor that helps reduce our execution risk. And then finally, what I would say is the ARR and the number of customers. That same factor means where we had in the range of 12,000 customers, generating what we expected $200 million of ARR in the model last year. We have about the same level, $200 million ARR this year, but it's 7,000 customers in that neighborhood. So we're dealing with a much lower customer level, which we also would believe would reduce our execution risk.

Another couple of questions are along the lines of -- last year, we talked about 500 subscription customers -- questions around sort of the subscription services and software and where do we see that going and the learnings from last year? Maybe, Jamie, you could start and just give us your perspective there.

Yes. I mean, we -- certainly, our goal was to transform as much as possible into a software company. And our customers agreed that they were making their purchasing decisions based on software features, software capabilities and the overall value of our software versus our competitors. But they also told us that they expected when they do purchase to, in most cases, have the hardware and software together as an end-to-end solution and as a single point of contact for support. Some of our most sophisticated customers, they want to buy their own hardware, stitch it together manage that. But the majority of our customers have come to us and said, while we're buying your software, we want the convenience of it fully integrated. So we still have a very aggressive growth rate in our software subscription business, but I think a large percentage of our customers will want the convenience of the integrated hardware and the support of that together. So that's really the big difference between this year's model and last year's model. And I thought BP, maybe you could talk a little bit about -- what we're seeing in the market, just for infrastructure companies in general, most infrastructure companies like us are leading with software, -- but when you look at the switching market, the storage market, routing markets, everyone's focused on software-defined architectures, but I think most customers are still expecting to have the hardware and software packages together for convenience. But BP, maybe you could expand upon what you're seeing from your peers in the industry?

Thank you, Jamie. No, I think you summarized it well. The primary drivers around the integration of software and hardware from a customer's perspective is simplifying the life cycle of deploying a given product from buy-through service and upgrades later on, they prefer to deal with a single part of contact, especially around the service aspects of it. And when looking at an end-to-end architecture, I think they're seeing the value of having a single point of contact for the data life cycle through different parts of what we're calling now the data factory, right? When -- and this is no different than a lot of the infrastructure providers today, especially in the storage space. But what I think when people want to understand is that the differentiation is around the software. They're seeing industry standard platforms as the hardware underlayment and looking at the company's visibility to be able to perhaps offer different partnerships on hardware platforms. But more importantly, having the software being the key component of the innovation, they're looking when they think of software-defined, I think, on-premise integrated platforms, but software in the cloud and having a uniform kind of experience in a hybrid environment. And so from their perspective, software defined, I think, to them means flexibility and around where they essentially use technology, and that's achieved through the software approach. So I think software to them is more about an experience from cloud to on-prem in a hybrid experience and being able to fluidly move back and forth between them, perhaps for different use cases and different collaboration models and still have one partner to do that with. So I hope that helps.

Yes. And maybe, Mike, you could just follow up a little bit in terms of the revenue, the recurring revenue piece that I think touches on this as well. if you would, some questions about where we are in terms of the software piece.

I'm a slow learner. When you look at the recurring revenue, the 2 biggest pieces are our support revenue from our historical hardware sales and now the subscription revenue. The growth in that number really is the subscription revenue, as we've discussed. Underlying that is the support revenue, which stays over this period. It goes up a little bit, it comes down a little bit, but it's holding its own. And what's allowing it to hold its own is we're continuing to sell hardware. So that's new in the model this year, where in the past, this was also declining because we weren't selling that support revenue into the hardware -- with the hardware. So it is helping with the higher hardware numbers in our model currently, it helps offset what we've always talked about is the golden glide. The older systems come off support and that puts pressure, that's a headwind, but we're continuing to sell hardware. So we're continuing to add to our support revenue as well. So over this period, it stays plus or minus flat. So that's kind of how you should think of the recurring revenue.

Thank you. Let me switch gears a little bit to supply chain. A few questions, and I think it's perfect that we've got Eric here, who runs this for us. Eric, maybe you could just walk us through a little bit what you're seeing? We've told -- we've talked to folks about the fact that we're seeing improvements in supply chain. From your perspective, could you talk a little bit about any of the challenges you're seeing, particularly with respect to IBM and other supply chain elements?

Improvement in the supply chain overall in the last quarter, we're seeing much more linear builds this quarter because our supply chain issues are mostly resolved. We still have spot issues here and there. But for the most part, we're able to now take the team and refocus on cost reductions and optimizing the supply chain and then also just setting up the supply chain for our future products and making sure that we are able to effectively support a appliance model as we go forward with high-quality, simple supply chain solutions. And so we're really turning the corner there and focused on the future.

John, some questions for you and Jamie, just around the sort of sales process, what you're seeing in terms of enterprise customer engagements? Where does this discussion usually start? What are the areas that they're most interested in terms of the portfolio? And are there areas that they're asking us to add to our portfolio?

Yes. Brian, thanks. No, I think the progress is really good right now. I think they're -- as we've made some changes. So look, you think about me, I've been here a little over a year now, call it, 14 months. I've made some changes to my leadership team in some key areas. One was in North America. We had to make a change, I believe, is the right change, because we needed to bring in a leader that had shown experience in selling in an end-to-end architecture model and being able to do that. We've also done the same in our federal business. And I don't think there is any change as I looked at the questions that were put out, I'm not seeing any adoption change in federal specifically. I think it's really just branching into areas that we weren't really focused on. So if you think about our federal business, it's -- what BP talked about is very much something that they're very needed in. They need that technology. They need to understand more about it. I use one of those examples in my presentation. But I also think that we have to do a much better job as we engage with the system integrators: Boeing, Lockheed, General Dynamics of the world. We really weren't spending as much time here, I think we could have. And we're -- you're going to see us spend a lot more time there. We're starting to see the pipeline change a bit on, but more in our federal space. So I do believe you'll see that business come around. I also don't believe that the North American business, as we start to branch into this more enterprise conversation, we've trained all the sales teams, the sales organization understands that have changed the compensation model, so that now as teams need a specialist to come in as they uncover maybe a media entertainment individually spends a lot of time there, finds a backup opportunity, finds a video surveillance opportunity. They know exactly where to go and to bring those specialists in. And that made the compensation in such a way that allows them to feel comfortable having multiple folks come into those opportunities. So we're starting to see specialists engage a lot better in those conversations. So I feel good about where the teams are starting to engage around the world. And again, we're starting to see a lot more connected opportunities as we ask the customer for more areas where maybe our solutions, they weren't aware of it. Now the other piece is we're actually seeing customers more. So as we engage in a virtual conversation like we're doing today, we're seeing more of our teams getting on site and the customer is really happy to see us. They're like, wow, we really love hearing more about what's going on at Quantum, we weren't aware of some of those things. So one of the things that we're really focused on heavily right now is as we see customers make that transition with us. Obviously, I'm working with Natasha on our marketing side to make sure that we have those references and we can start to be a lot more about that. I don't know, Natasha, if you want to mention a little bit about some of the work that we're trying to do there.

I think staying tightly aligned with the sales team, as John was saying, getting on site and in front of customers, we've really sort of broadened our reach. Anybody that watches Quantum [indiscernible] done a series of Quantum Elevate events and just really getting our end-to-end message out in front of our partner community and a broader partner community, more opportunities to be in front of customers. We're looking at a broader set of events, so that we can start reaching the CIO and IT leadership beyond some of the more niche or boutique event, we've been at in the past. So just really getting that end-to-end message out there. I think one of the some parts of big embarked as we've worked on this message is we've been able to talk with a lot of partners and customers and really understand how to adapt to talk about data and customer problems as we talk end-to-end versus this is our latest storage product for M&A or for backup. So just think tightly partnered with sales on all of that.

Yes. And look, it's the marketing air cover we need. So the work that Natasha and I do is as we see those customers come about -- and we know that it's very replicatable, not just in North America, but around the globe. We're obviously looking for those opportunities to be much more public about what we're doing. And so that will help us lead into the enterprise conversation. So thanks. I can answer any more questions. Brian, or if there's a couple more down here, I'm happy to do as well.

Okay. I'm just looking through here and make sure I think I captured most of them here and. Yes. I think I'm just reading through making sure we've kind of captured most of those.

Brian, if you don't mind. I'm just looking at the one down here. I think there was a question that was specific around the enterprise customer engagement, like where does it start I think the interesting thing for us right now is I mentioned again in my presentation, we have well over 10,000 customers that have bought something from Quantum. And if you look at the data that we have out there, some of these are the biggest Fortune 500 customers in the globe. And so we're going back and we're having that conversation about what did they buy from Quantum, were they happy with it? And as we start to talk about the different pieces of that infrastructure. BP also mentioned that a lot of customers moved a lot of their data, in some cases, the cloud, but are now due to ransomware, now doing the data protection opportunities, we actually have with ActiveScale Cold storage, a much different conversation that we can have with our enterprise customers about how do they want to see their data protected, what are they doing in their security architecture, where do our pieces of our technology fit in? And we're getting a lot of reception and the message is really resonating, which is now opening up net new opportunity. So I can't say it starts one way or the other, but just in a traditional IT conversation, we would go talk to the VP of IT. We will talk to the storage director. Eventually, we would want to go talk to the CIO. But I think specifically in that use case, where we start talking about data protection and ransomware, I can talk to a CFO. I can talk to a Chief Information Security Officer. I can talk to the CIO is primarily about what are they doing in their data plans. So -- it -- I can't tell you pointed out in one specific area, but we're just going right back into our installed base on those point product sales and we're just having a much broader conversation. And the examples that I used earlier are those same conversations and how they've expanded in a much more end-to-end fashion.

Thank you, John. Mike, I see one more here in terms of just gross margins. Can you touch on that and give a sense of where we are in terms of the trends there and the mix?

When you look at our model, the trends really are gradual over this period. Where we are today is we're under the influence of a mix that's very heavily weighted towards the hyperscalers, which is our lower-margin products. So when you look forward, really, it's the mix as we improve our mix, that's really going to drive the gross margins. And that mix is, as we've described, growing the primary storage business, moving to the subscription revenue, as that gets traction, that will improve our margins. But we're still, I would say, for the next 2, 3 quarters we're heavily influenced by the mix that includes the hyperscalers, but then we'll grow out of that. But it will be gradual. It's not quick.

Okay. Thank you. Seeing no other questions here. I'm going to turn it back over to Jamie for some closing remarks. Anything, Jamie, you'd like to finish us with.

And thanks, everyone, for joining us on our Analyst Day today. I think we've outlined a very large opportunity in and around unstructured data. But more importantly, we've been working with this type of data for going on 20 years. And I really think the last 4 years, we've really built out that core competency into a full end-to-end portfolio. And we're seeing that traction of that strategy of this portfolio in the market, we've made the changes. We've made the business model changes. We've restructured our debt, where we carry drastically less -- significantly less debt than we used to, which given today's economy and what's happening with interest rates, I think, positions us much better. And most importantly, the supply chain issues that we've been wrestling with for the last 18 months, seem to be diminishing greatly, still some pocket issues, but I think most of our supply chain woes are behind us. So we're really in a pretty phenomenal position to start to grow the company to start to exploit this opportunity. So I want to thank our current investors, who've been with us, some of you for many years. I also want to thank all the Quantum employees from around the world, who really put a huge amount of energy, enthusiasm and motion into our strategy. I've just never seen a team of people this small produce this much results in this little time. It's really inspiring and just want to call the Quantum employees for that. I'd like to thank everyone for joining, and we look forward to seeing you on our next earnings call. Thank you, everyone.

Thank you, everyone. Bye. Thank you.