In February 2022 TBR spoke with Logicalis Group Chief Operating Officer Michael Chanter and Chief Technology Officer Toby Alock for an update on the company’s strategy as well as an overview of the company’s new Global Services Organization (GSO), including its solutions portfolio and road map. The conversation, which contained specific details on strategy, was a continuation of the journey Logicalis embarked on nearly two years ago when it appointed Bob Bailkoski as CEO.  

In TBR’s special report Know-your-tech strategy could be invaluable as Logicalis aims to disrupt peers in cloud managed services, we wrote, “Logicalis’ efforts to optimize its legacy operations while doubling down on key growth areas such as cloud will largely depend on the company’s ability to develop integrated scale to ensure standardized service delivery.” The launch of Logicalis’ GSO highlighted these efforts and marked a new stage in the company’s ability to deploy practical solutions that build a foundation of trust with partners, employees and clients.  

Transforming into a modern managed services provider  

Logicalis Group’s executives understand the need to develop an ever-evolving strategy that allows the company to stay abreast of market trends. Pivoting from historically employing a regional focus to now building outcome-based solutions that are global in nature paves the way for Logicalis to build scale. Ensuring internal organizational silos are removed will be key, as clients expect vendors to deliver services locally through globally integrated operations.  

At the same time, Logicalis realizes the importance of nurturing local relationships, ensuring its consultants and professional services organization continue to operate as close to the customer as possible. Developing a “modern managed services organization,” as Chanter describes the company’s transformation, is not an easy task, especially when executed at scale.  

Accounting for the permeation of automation to drive efficiency and fine-tuning operations and business models to facilitate cloud-enabled sales, service delivery and support are among the key pillars of GSO. Continuing to provide existing clients with support also enables GSO to secure foundational revenues and maintain relevance, as often clients take time to move to the next phase of their digital transformation (DT) programs.  

When TBR asked about the change management that typically comes with such evolution, especially due to the increased use of automation in service delivery, Chanter provided a strong use case for how the company is handling it. Starting with the appointment of an executive dedicated to overseeing transformation, the main focus then has been teaching staff how to be agile while also considering new compensation models in connection with cloud-enabled service delivery.  

Providing support to external clients has been enabled by a three-part framework: Align, Transform, Scale. Logicalis first assesses where clients are in their DT journey compared to their desired outcome. The company then maps out the kind of support it can provide at different points in the journey, relying on its professional services organization to feed regional market nuances. With sales teams trained and certified before going to market, Logicalis also tries to align and close the feedback loop with staff at the Centers of Excellence (CoEs), which are typically responsible for the development and management of global solutions.  

As Logicalis Group aims to increase its share of the managed services market, we believe the company will continue to work toward striking the right balance between developing automation-enabled services P&L and achieving integrated scale. Previously, TBR wrote, “Logicalis has begun to identify areas across geos, industry verticals and horizontal areas that can support its goal of expanding share of highly profitable ‘as a Service’ managed service sales, which currently garner about 25% of its global revenues. … As Logicalis works out the details around managing its partner ecosystem, Bailkoski and [Chief Customer Experience and Service Transformation Officer Vincent] DeLuca are also increasing the company’s investments in internal portfolio offerings that will not simply standardize global service delivery but also pave the way for an innovative approach to engaging with clients. Launched in June, we believe Logicalis’ AI-enabled Digital Service Platform (DSP) will be the center node of Logicalis’ solutions and services ecosystem, similar to how iTunes has helped Apple (Nasdaq: AAPL) build a community of die-hard brand followers.”  

Logicalis is on the right path to achieving its managed services goals, but like many of its peers, it needs to partner better and differently than it has in the past, especially as buyer expectations around managing partner ecosystems also evolve. Meanwhile, expanding its global footprint, similar to opening an engineering center in Portugal to house about 200 employees in support of the Agile, Transform, Scale framework, will continue to bolster Logicalis’ resource bench for building and delivering solutions at scale as clients seek support around migrating and transforming operations. Chanter noted that the new Portugal facility will “help transform clients quickly and help Logicalis transform.” TBR notes this dual-track approach has proved successful for other IT services vendors undergoing their own digital transformations.  

As the world awaits the scientific discoveries needed to bring quantum processors to commercial applicability, Atos’ BullSequana XH3000 allows for ecosystem participation within the compute platform itself and future-proofs any early buyer investments. In its Feb. 16 official announcement of the XH3000 supercomputer, for which TBR was provided pre-briefing access, Atos claims the product will have a six-year life cycle and that it is an open architecture capable of housing up to 38 blades. The blades can accommodate a mix of different XPU processors, with more under consideration and development.

The rapid rise in large data sets and evolving AI/machine learning (ML) algorithms have driven this global appetite for greater compute capacity — an appetite that many data scientists believe will only be sated once quantum computers reach commercial viability. Atos’ early lead in quantum simulators and alliances with various quantum systems vendors imply the company will be capable of pivoting its high-performance computing (HPC) offerings quickly to accommodate the addition of commercial-grade quantum processors when they arrive. Atos’ flexible hybrid supercomputing architecture will sell well in Europe for a variety of reasons and may enable Atos to gain share against notable HPC vendors in North America and Asia.

Data and AI require new compute platforms to address intractable problems

Atos correctly asserts the state of compute trails the size of the data sets that are available to run algorithms. Specifically, the world is running out of computational capacity to address the complex problems that can now be simulated and analyzed through increasing digitization.

Proof points offered in the Atos announcement included:

• Average HPC job durations grow as larger data sets will be applied against systems with as many as 10,000 nodes and 25,000 endpoints.
• Application refactoring and algorithm refinements can provide as much as a 22x speed improvement.
• Data centricity and edge processing grow in use case applicability, requiring greater hierarchical depth and more localized compute near the application.
• Hybrid Sim/AI Workflows for approximate computing are nearing reality. Atos offered the example of Alphafold 2 for protein folding prediction reaching over 90% accuracy, whereas classical methods currently achieve between 30% to 40% accuracy.
• Yet another industry prediction of reaching the physical limits of Moore’s law now that the industry is at 3nm technology.
• Extending the performance gains from classical computing while quantum discovery and commercialization advance will require greater innovation around multiple XPU architectures. These hybrid or heterogenous compute architectures need a new compute system structure, which Atos believes the XH3000 system provides.

The Atos Exascale strategy is a hybrid approach that serves many masters

Atos states the future of supercomputing will be hybrid. According to Atos, the future of supercomputing will involve a hybrid approach, consisting in the near term of a blend of classical CPU configurations and specialized processor architectures to address specific workload requirements. Presently, Atos collaborates with AMD (Nasdaq: AMD), Intel (Nasdaq: INTC), Nvidia (Nasdaq: NVDA), SiPearl and Graphcore, among others. Eurocentric chips based on ARM designs are also in the news and have been discussed by Atos.

Atos has addressed the need for future-proof flexibility in its designs by building the standard chassis of the BullSequana XH3000 to accommodate up to 38 compute/switch blades on one rack to be mixed and matched as workflows require from the different blades currently available and available in the future.

This hybrid architectural design approach serves many masters, such as those addressing:

• Sustainability: Different cooling and processing designs not only generate greater computational capacity but also, when coupled with the hybrid configurations and algorithm innovations, can lead to lower power consumption, and therefore lower carbon footprints.
• Sovereignty: Technonationalism is not going away, and Atos is a flagship European technology vendor. Former Atos CEO Thierry Breton is now the commissioner for internal market affairs within the European Union (EU) and has been tasked with managing many elements pertinent to digitization and “enhancing Europe’s technical sovereignty.” The EU has clearly stated its intentions to ensure there are European-controlled processors in market. Hybrid computing structures enable companies to select different processors to address the computational requirements amid the increased attention nation states place on compute access as a strategic national interest.
• Higher performance: The HPC market increasingly takes on the dynamics of emerging ecosystem business models and requires a physical compute stack that can accommodate the many tech stack variations the ecosystem can create to address the world’s compute and AI challenges. Atos claims it also has built the architecture to be resilient and adaptable for six years without forklift upgrades. This flexibility, Atos asserts, can accommodate new discoveries as the unknowns around deep learning, algorithm development and new processor developments in the classical and quantum computing realms come into view.

Hyperscaler-built networks will look very different from traditional networks

Hyperscalers are building end-to-end networks that embody all the attributes and characteristics coveted by communication service providers (CSPs) as part of their digital transformations. The most significant differences are in the software stack and the access layer, where new technologies enable hyperscalers to build dense mesh networks in unlicensed and/or shared spectrum bands and build out low Earth orbit (LEO) satellite overlays for access and backhaul. Mesh networks will likely be used to provide low-cost, wireless-fiber-like connectivity in urban and suburban environments, while satellites will primarily be leveraged to provide connectivity to rural and remote environments.

Hyperscalers are starting from scratch, completely reimagining how networks should be built and operated. Their clouds, numerous network-related experiments over the past decade, plus the raft of new network-related technologies on the road map will enable hyperscalers to build asset-light, automated networks at a fraction of the cost of traditional networks.

Hyperscaler networks will cost a fraction of traditional networks

TBR estimates hyperscaler networks cost 50% to 80% less to build than traditional networks (excludes the cost of spectrum, which would make the cost differential even more pronounced because hyperscalers will primarily leverage unlicensed and shared spectrum, which is free to use). Most of the cost savings stems from innovations, such as mesh networking, carrier aggregation, LEO satellites and integrated access-backhaul, that enable significantly less wired infrastructure to be deployed in the access layer for backhaul and last-mile connection purposes.

For example, Meta’s Terragraph mesh access point can autonomously hop signals through multiple other access points before sending the data through the nearest available backhaul conduit. In the traditional architecture, some form of backhaul would need to connect to each access point to backhaul the traffic. Mesh signals could also be backhauled through LEO satellites, further limiting the need to deploy wired infrastructure in the access layer, which is one of the most significant costs of traditional networks.

Another key area of cost savings stems from cutting out certain aspects of the traditional value chain. By open-sourcing some innovations, such as hardware designs, hyperscalers can foster a vibrant ecosystem of ODMs to manufacture white boxes to compose the physical network. The white-boxing of ICT hardware can lead to cost savings of up to 50% compared to proprietary, purpose-built appliances.

Hyperscaler disruption portends structural changes to the telecom industry through this decade

The technological and business model disruption hyperscalers are bringing into the telecom industry portends significant challenges for incumbent vendors and CSPs. TBR sees the scope of disruption becoming acute in the second half of this decade, likely prompting waves of M&A that will reshape the global landscape. CSPs will engage in M&A to stay relevant and financially sound, while incumbent vendors scramble to evolve as their primary business model (selling proprietary hardware and/or software and attached services) is increasingly marginalized and eventually becomes obsolete as hyperscaler innovations spread through the industry.

Hyperscalers do not want to become telecom operators; they want to leverage networks to obtain data and drive their other digital businesses

Hyperscalers are in the data business; providing network connectivity is a means to that end

Hyperscalers are building large-scale networks to drive forward and support their big-picture strategies, which revolve around building out their respective metaverses and supporting a wide range of new digital business models that will be enabled by new technologies such as 5G, edge computing and AI.

To that end, hyperscalers have a vested interest in ensuring the entire world is blanketed with high-speed, unencumbered, intelligent, low-cost connectivity. The economic justification to build the network is driven by the need for hyperscalers to gather and process new types of data to drive these new digital business initiatives. TBR notes that this business case is completely different from CSPs’ business case, which monetizes the network access rather than the data that comes over the network. The hyperscaler model emphasizes giving away low-cost or free connectivity and monetizing the data that comes through the network. The hyperscaler model is far more valuable than the traditional connectivity model and will likely ultimately become the predominant business model for connectivity.

CSPs sit on vast data lakes and have for many years. These data lakes contain valuable information about subscribers, endpoint devices, real-time location and tracking, and other metrics that are of critical importance for some of the digital business ideas hyperscalers want to commercialize, such as drone package delivery and autonomous vehicles. Owning more of the physical network infrastructure and the core software stack puts hyperscalers in a prime position to capture and monetize this data.

TBR notes that this strategy is already in use in the telecom industry in various places in the world. For example, Reliance Jio and Rakuten are using this strategy in India and Japan, respectively. In both cases, connectivity is given away for free or at a significantly lower cost compared to rival offers, and the data generated by the connections indirectly feeds and monetizes each company’s respective digital businesses, such as advertising, financial services and e-commerce. There is significant evidence suggesting that Alphabet, Amazon, Apple, Meta Platforms and Microsoft all have strategies that are similar but of a far greater magnitude.

Hyperscalers already own and operate the largest networks in the world; the next build-out phase is the mobile core, far edge and access domains

Over two-thirds of global internet traffic traverses hyperscaler-owned network infrastructure at some point in the data’s journey. The vast majority of that traffic travels over hyperscalers’ backbone networks, which primarily comprise optical transmission systems (submarine and terrestrial long-haul optical cables), content delivery networks, and cloud (including central, regional and metro) data centers.

The domains of the network where hyperscalers have yet to dominate at scale are the mobile core, far edge and access layers, but there is mounting evidence to suggest this is changing, thanks to technological advancement and regulatory breakthroughs (e.g., the democratization of spectrum).

TBR’s Hyperscaler Digital Ecosystem Market Landscape focuses on the five primary hyperscalers in the Western world that TBR believes will own the largest, most comprehensive end-to-end digital ecosystems in the digital era. Specifically, the five hyperscalers covered in this report are Microsoft, Alphabet, Meta Platforms, Amazon and Apple. Collectively, TBR refers to these five hyperscalers under the acronym MAMAA. TBR covers the totality of the largest hyperscalers’ businesses, with an emphasis on how they are disrupting the ICT sector. Gain access to this full report, as well as our entire Telecom research, with a 60-day free trial of TBR Insight Center™.

Applications serve as the vessel for cloud’s business value 

Value, in the form of agility, innovation and efficiency, is now the driving force behind customers’ cloud investments. Applications, in the form of SaaS, are the purest vessel for customers to implement and achieve the value they so desperately want in order to improve their businesses. It is for that reason that TBR published our first Cloud and Software Applications Benchmark, tracking the nuances of the applications space from a workload and subworkload perspective.

Customers’ growing reliance on SaaS solutions is shown in the market growth of the 10 vendors covered in the inaugural report — their aggregate revenue increased by 26.4% year-to-year in 3Q21, a rate that has accelerated over the past year. Business Applications workloads, which include ERP solutions, was the fastest-growing segment, with aggregate revenue for the 10 vendors covered increasing by 28.5% year-to-year during 3Q21. The drivers of this expansion are threefold: conversion of existing customers to cloud; the integration of solutions through hybrid deployments; and revenue driven by the ecosystems that are critical to the innovation and go-to-market strategy for SaaS solutions.  

Providers from all backgrounds now look to existing customers as their first growth option 

For both traditional software providers and companies that were born on the cloud, customers with existing traditional software installations have become one of the main drivers of SaaS growth. Traditional software providers did not always see the market this way. In fact, SaaS was a threat to their existing license and maintenance businesses for quite some time. After years of customers voting with their dollars and selecting SaaS-delivered solutions over the traditional license and maintenance delivery model, nearly all applications vendors currently see their existing bases as the first opportunity for growth.

In some ways, this transition has played out on a workload-by-workload basis. Sales and marketing applications, led by CRM, are on the periphery of most enterprise applications suites and were the earliest to see a shift to SaaS over traditional software purchasing. Salesforce (NYSE: CRM) led this trend, converting many existing customers from traditional leading providers like SAP (NYSE: SAP) and Oracle (NYSE: ORCL). The dynamics in CRM served as a warning shot for many traditional providers. Even the most reluctant SaaS providers, like Oracle, are now focused on offering cloud solutions to their existing customers before their competitors can.

The shift in strategy is well timed for traditional providers, as cloud demand in the Business Applications segment is beginning to accelerate. As shown in Figure 1, Business Applications has the lowest cloud revenue mix for the vendors included in TBR’s Cloud and Software Applications Benchmark, making it the largest opportunity for traditional customer conversion.  

A deal would indicate revenue potential, but the evolving competitive and technology landscapes raise questions

On Dec. 20, 2021, Oracle (NYSE: ORCL) announced plans to acquire Cerner (Nasdaq: CERN), a front-runner in the healthcare IT (HCIT) industry, for $28.3 billion. The announcement comes as COVID-19 continues to strain global healthcare systems, driving up demand for digitized workflows and processes that can help improve efficiency, enhance service quality and reduce costs. The announcement also comes as Oracle faces a turning point: After six consecutive quarters of corporate year-to-year revenue gains, net-new buyers, not just those inside the Oracle ecosystem, are showing interest in the company’s feature-rich suite of back-office applications and second-generation cloud infrastructure.

As such, by drawing on some of the successes of its previous acquisitions, including Peoplesoft and NetSuite, Oracle hopes to use Cerner, whose business has similarly been on an upward trajectory, to enter a new phase of growth that is more on par with the 30%-plus growth rates recorded by competitors Amazon Web Services (AWS) (Nasdaq: AMZN), Microsoft (Nasdaq: MSFT), and Google Cloud (Nasdaq: GOOGL). Should the deal close, this growth could stem from multiple areas, including onboarding electronic medical record (EMR) and electronic health record (EHR) workloads to Oracle Cloud Infrastructure (OCI), and using AI services like Oracle Assistant to kickstart conversations with the clinical, operational and financial branches of healthcare in a land-and-expand approach.

Despite the growth potential, investors appear skeptical, with Oracle’s stock price falling 5% on the day of the announcement, largely due to concerns around the company’s cash standing and ability to position Cerner as a more notable alternative to Epic and other competing HCIT firms. In some ways, this skepticism stems from Oracle’s lack of comparative experience in the industry cloud space and, perhaps to a larger extent, investors see the acquisition as another one of Oracle’s attempts to buy revenue, similar to the company’s failed TikTok deal and subsequent fallout.

Regardless, Oracle’s biggest challenges stem from the evolving technology landscape that is actively favoring not only the cloud but also open, hybrid multicloud delivery methods. Oracle plans to use Cerner to bolster its cloud position, but given the company’s later-to-market standing and perception for locking customers in, it is unclear the extent to which Cerner will actively support Oracle’s cloud vision. Furthermore, competitors, including those with deeper pockets and arguably more open partner ecosystems, only add to this skepticism.

Cerner would be the largest buyout in Oracle history, but valuation is reasonable

After the announcement, sticker shock was inevitable, as the deal came at a price tag in line with some of the largest acquisitions in software history, including Microsoft’s purchase of LinkedIn and IBM’s purchase of Red Hat. However, based on Cerner’s 2020 and projected 2021 financial results, Oracle valued the deal at roughly 5x Cerner’s annual revenue, a level that is typical in industry acquisitions, especially those that include firms with more transactional business models. COVID-19’s halt on upfront spending impacted Cerner’s license business and overall revenue growth in 2020, but the company has quickly bounced back in 2021 and is expected to meet its annual revenue guidance of 5% year-to-year growth.

A key part of Cerner’s strategy has been accelerating organic top-line growth through platform modernization and emphasizing SaaS-like delivery methods. This approach aligns with Oracle’s strategy, which similarly emphasizes revenue growth through annuity-based cloud services. Another priority for Oracle is gaining share through OCI, which will be a difficult feat given the highly saturated nature of the IaaS market. Oracle will help Cerner overcome challenges entering global markets, especially in an unpredictable industry like healthcare, to meet its growth objectives.

Although Cerner management boasts leading market share in many markets outside the U.S., in the U.S. EHR space, the company currently sits at about 25% market share and is losing out to Epic, which is nearing an estimated 30% market share. As such, Cerner’s, and Oracle’s, biggest opportunities could come internationally. Oracle will play a key role in helping Cerner, which currently derives 89% of its revenue from domestic customers, expand its international presence.