Maxar Technologies Inc.

Good day, and thank you for standing by, and welcome to the Maxwell Technologies second quarter conference call. At this time, all participants are in a listen-only mode. After the speaker's presentation, there will be a question and answer session. To ask a question during the session, you will need to press star one on the telephone keypad. And please be advised that today's conference is being recorded. If you require any further assistance, please press star zero. I would now like to hand the conference over to your speaker today, Mr. Jason Gursky. Sir, please go ahead.

Great.

Good afternoon and thanks, operator. Welcome to Maxar's second quarter 2021 earnings conference call. I'm joined today by the company's chief executive officer, Dan Jablonski, and its chief financial officer, Bix Porter. Both will make some opening remarks, after which we're going to open up the line for your questions. We're shooting to wrap up the call in about an hour. Before we get started, I'd like to refer listeners to the accompanying slides for today's presentation, which can be found on the company's website at maxart.com. Once there, please turn to slide two, where I'd like to remind you that part of today's discussion, including responses to various questions, may contain certain forward-looking statements, which represent the company's estimates, future plans, objectives, and expected performance at today's date. These statements are based on current assumptions that the company believes are reasonable but are subject to a wide range of uncertainties and risks that could lead actual results to differ materially from the forward-looking information. You're referred to the advisory regarding forward-looking statements contained in our quarterly earnings releases, earnings call slide decks, and the company's most recent MD&A section found in our Form 10-Q under the company's EDGAR profile at sec.gov or on the company's website at maxr.com. And with that, I'll hand the discussion over to Dan. Dan, go ahead. Thanks, Jason. Good afternoon, everyone. This afternoon, I'm going to cover the key highlights from the quarter and provide an update on the progress we're making on our 2021 priorities, including where we are with the Legion program, our next-generation satellite constellation. I'll also spend time providing some context on the company's artificial intelligence and machine learning capabilities as they apply to Earth intelligence and how we're using them to drive growth. Please turn to slide three of the accompanying presentation. We generated 16% year-over-year revenue growth in the quarter, excluding the effect of a non-cash EV deferred. Of note, Earth intelligence grew 14% year-over-year, despite the fact that we're currently capacity constrained ahead of Allegiant launches. Growth here was driven by sales of 3D products to commercial and government customers, as well as solid performance and services to the U.S. government. Importantly, we also saw 150 basis points of adjusted EBITDA margin expansion, excluding EBITDA deferred, driven by improved execution and space infrastructure. We recently signed our first Legion capacity sale during the quarter with an international government customer as part of a large multi-year renewal. This follows the four contracts we announced last quarter to upgrade customer ground infrastructure to be Legion ready. We're making steady progress with our business development efforts ahead of the Constellation launch. Next, we also received our 11th renewal of the Enhanced View Program with NRO for the period starting September 1st of this year. As a reminder, we've been a trusted partner of the U.S. government for nearly 20 years, delivering commercial capabilities with superior quality, cost, security, and reliability on the current EV program and its predecessors. We're proud to support the U.S. government mission and look forward to continuing to work with the NRO as they increasingly adopt commercial imagery. We continue to perform well on this program, a track record we believe sets us up nicely for the upcoming EOCL competition, which is the electro-optical commercial layer, the successor program to EnhanceView. As we discussed during our recent investor webcasts, the NRO issued a draft RFP in June for the upcoming EOCL program, and we understand they expect to make award decisions by the end of the calendar year. Please turn to slide four for a review of the progress we're making on our 2021 priorities. We remain focused on providing high-quality Earth intelligence, which means driving Booking's growth, including for capacity on Worldview Legion, growing 3D capabilities, and extending the Enhanced View program. We're also continuing to make good progress on our AI, ML, and platform capabilities, and I'll discuss those more in a bit. Key recent wins included awards from the U.S. government to assist with geospatial production and persistent change monitoring, and another related to space domain awareness. In the international government vertical, as I mentioned a minute ago, we signed a large renewal that includes leaching capacity, as well as a contract with the Australian government for both 3D and imagery data. And finally, I'm excited to announce that we signed a multi-year, multi-million dollar licensing agreement with a large social media company for imagery-based maps, demonstrating our continued traction across all customer verticals. From an execution perspective, it was a good quarter, with the team generating solid book-to-ship activity and adjusted EBITDA margin performance. Even while we enjoy strong backlog as we perform on multi-year contracts, we continue to find good vectors for growth with existing and new customers. I'm pleased with the ability of the team to drive bookings and revenue in the same period, and this quarter was a good example. Moving to Worldview Legion. We have decided to delay the launch from the fourth quarter of 2021 into next year. This isn't a decision made lightly. There are two key drivers since the last update. First, while Honeywell has delivered the reaction wheel sets for the first two satellites, the hardware from Raytheon is coming to us later than anticipated. The Maxar team has been in El Segundo this week for pre-shipping reviews, and the first instrument is in transit to our facilities. The Raytheon teams have been working hard, and the second instrument should arrive in September, followed by the other four this fall. However, we had expected both of the first two instruments to reach us in July, and this has had a negative impact on schedule. Second, the return to work in California post a loosening of COVID restrictions on June 15th, while very positive, for a variety of reasons, has not led to the achievement of the schedule we anticipated with our integration, testing, and software teams. And of course, we're now all watching the Delta variant closely. We appreciate all that the teams have accomplished under challenging circumstances. COVID has been a difficult operating environment for both our suppliers and us, and it's clearly had an impact on the program. Given the hardware delays and remaining work streams, which include software, integration, integrated systems, and environmental testing, and launch phase operations, and the importance of this program for both our customers and Maxar's long-term objectives, it's important to get the launch right, and this requires a little more time. While we continue to look for ways to reliably accelerate production and test, we now expect a launch timeframe between March and June next year for the first launch. We are continuing our progress with the other four spacecraft. Remember, this is a six-satellite constellation. We've historically said that the second launch would be three to six months after the first. We intend to get them up as soon as possible. How quickly they launch after the first will depend on how much we can overlap the remaining work, including hardware deliveries, software, and testing schedules. To address the remaining work on the program, we've taken a number of actions. One, we've assigned overall program responsibility to Chris Johnson, who joined MaxRMA and brings significant program expertise to the company. Two, we assembled a mission assurance and red team to review and assess the program and remaining work streams. They provided important insight, which we've incorporated into the revised schedule discussed today. And three, we've added additional internal and external software engineering resources. We're driving forward diligently with a focus on maximizing the value of this program for both our shareholders and customers. With respect to our largest customer, the draft RFP for the EOCL program I mentioned earlier contemplates a 10-year program, which aligns with the 10-year-plus design life of the Legion Constellation. This is a good fit. We continue to expect that our current on-orbit assets that provide service to the U.S. government, now as well as the Legion Constellation, are tailored to meet the current and future needs of the U.S., Turning now to space infrastructure, where we're committed to delivering the best possible solutions and systems for our customers, and from a business standpoint, have been focused on establishing a foundation for future growth. On the power propulsion element for NASA, we completed preliminary design reviews and were awarded additional change orders. We were also awarded study contracts for national security classified work as we continue to look to shape new programs and further diversify the business. Importantly, we're beginning to demonstrate our competitive positioning for national security work, having recently been down selected from eight competitors to five on a program. That field will continue to narrow, but it's a positive sign that we've made it through this gate, and now we need to drive for a win on the program. We've also continued to execute. We launched Sirius XM8 in the quarter, successfully conducted commissioning ops, and turned the keys over to the customer last week. Last week, we also launched R1-V2 for Emberpel, and I'm pleased to report that we've been awarded Sirius XM9, Sirius' next geocommunication satellite. From an investment standpoint, we continue to work on new satellite and constellation designs, including modular spacecraft and proliferated constellations, as we look to serve commercial, civil, and classified programs with highly engineered and affordable solutions. Reflected in the financial results, we had a solid quarter as adjusted EBITDA margins continued their improvement, reflecting better performance and healthier program mix. Finally, on financial flexibility, we're continuing to drive strong financial results in the business and see our way to significant cash generation in the quarters and years ahead, both of which should drive debt and leverage levels lower. So, overall, pretty good financial performance in the quarter and some good bookings momentum across both segments and across our addressable verticals. Let me be clear, though. I'm not pleased with the additional legion delays. That said, the methodical work we're doing on the program are the right steps. We're building a generational constellation that is going to drive growth, profits, and cash flows for the next 10 years, and we want to be confident that we've got it right. Before I hand the call over to Biggs, I'd like to shift the discussion about another exciting portion of the business. Over the past two quarters, I've done deeper dives on some of the innovative technology we've been developing and deploying in Earth Intelligence to support the U.S. government by reducing sensor-to-shooters timelines on the battlefield and in space infrastructure to support both government and commercial missions. Today, I'd like to pivot back to Earth Intelligence to talk a little bit about our AI and ML capabilities and how we're increasingly using them to drive growth. And the timing of this is pretty good, given the amount of discussion in the marketplace about this technology and the various capabilities that exist out there. We've been at this for quite some time, and we benefit from having the best commercially available Earth intelligence data in the market. Please turn to slide five. Before we get started, I thought it would be useful to level set and quickly outline what artificial intelligence and machine learning mean in the context of geospatial intelligence. As you're aware, our constellation assets generate vast amounts of the highest quality commercial data available every day, over 3.5 million square kilometers of the Earth's landmass from all over the globe. To make that data useful for intelligence and commercial applications, it helps to snap it all together to create a geo-referenced data set that provides a reliable foundation to conduct analysis. Comparability and compatibility of high-quality data sets are preconditions for AI and ML algorithms to run at speed and at scale. Feature extraction, change detection, and object identification are examples. Using artificial intelligence and machine learning techniques, we're applying algorithms to data to identify objects and detect change at a small fraction of the time it would take humans to do so. Importantly, we're doing this at scale with high levels of predictability and accuracy. This in turn starts a virtuous cycle where we can proliferate products and analyses to provide geospatial intelligence answers, which in turn drives more demand for the underlying high-quality data. Please turn to slide six. Foundational elements of our AI ML capabilities include analysis-ready data, or ARD, deep core, platform capabilities like Global AGD and SecureWatch, and cloud accessibility of industry-leading imagery data, which will be further enhanced with Worldview Legion. ARD is comprised of pre-processed time series stacks of imagery that are aligned, produced at a set standard, and geo-referenced for accuracy using our precision 3D registration software. Aligned image stacks from ARD provide increased usable content, more accurate feature extraction, faster processing, lower storage costs, and homogenized inputs for analytic workflows. Our precision 3D registration software also allows us to take other sources of data, whether or not geospatial, and lock them down in a highly accurate fashion in the same reference chips. This kind of data helps our customers save time and jump ahead to the next stage of their analytic workflow with a more accurate and AI ML-ready baseline. Organizations and government agencies are enabled to use machine learning and artificial intelligence to extract roads, parcels and buildings, as well as identify land use and vegetation at scale, or pick out and count objects like military vehicles or commercial automobiles. As you'll note, we get better results with higher quality data sets. It's also helpful that we can train the algorithms against our vast 20-plus year archive of the planet. Please turn to slide seven. DeepCore is a machine learning engine that is a cornerstone technology the company uses to perform its AI and ML projects. It evolved from Maxar's direct experience as an industry leader, developing automated computer vision techniques for commercial and national missions. Importantly, it has deployed more than 100 models to detect 130 plus object types using multiple machine learning models, frameworks, and networks against multiple satellite, airborne, drone, and terrestrial sources. and it's been used in commercial and government clouds, as well as bare metal and hybrid environments, scaling from a standalone machine to an infinitely scalable cluster. With DeepCore, users can leverage the services and experience of the Maxar team or mix and match training data, models, and visualization capabilities within DeepCore or other repositories and tools. Please turn to slide eight. We maintain a constellation of satellites that generates the most and the highest resolution, most accurate geospatial data in the market. We're adding to that with the Worldview Legion constellation, which will play an important role in our AI and ML capabilities. Slide 9 shows the power of ARD deep core and high-resolution data working together with a car counting use case. As noted, this type of work can be completed in seconds versus the hour-long timeframes needed using traditional methods. This is a huge breakthrough in the use of geospatial intelligence and is a key reason why we see robust demand signals from customers and continued growth. Slide 10 provides some details on our global EG and SecureWatch platforms. Slides 11 through 17 provide additional examples, including the use of algorithms to more effectively monitor real estate development, to build 3D models and base maps at scale, to automatically detect ships in the ocean, and to produce crowdsourced maps built on multiple mission sets. We've been working these kinds of customer needs for years and believe the continued investments we're making in our data generation capacity and AI and ML technologies will allow us to continue to drive revenue growth in the future. I'd like to end with slide 18, which is one I shared earlier this year. As I mentioned then, one of the key goals of the investments the U.S. government has been making in its AI, ML, and Joint All-Domain Command and Control efforts is to achieve an advantage on the battlefield by shortening the sensor-to-decision timeline from space, which is all about seeing, identifying, targeting, and prosecuting dynamic targets at scale and at distance. Ultimately, DoD is driving to combine broad area surveillance and automatic target recognition to support long-range precision fires at speeds required on future battlefields. We believe the breadth of our coverage and the quality and accuracy of our imagery, as well as our software processing capabilities, are key enablers. Hopefully, all this gives a better sense of how AI and ML fit into the overall Maxar story and the continued investments we're making. We believe our efforts position us well in the market versus competitors, and that we will drive sustained growth for the company with customers to increasingly unlock value out of geospatial data and intelligence. And with that, I'm going to turn the call over to Biggs for a deeper dive on quarterly performance. Biggs?