How AI Is Revolutionizing Cost Efficiency and Customer Experience in Telecom

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The History of AI in Telecom

AI has been utilized in the telecom industry since the early 2010s, primarily in helping communication service providers (CSPs) reduce costs. AI began in telecom with predictive solutions that leveraged structured data. Common use cases have included anomaly detection (from a cybersecurity, fraud and network performance perspective) as well as chatbots for basic customer care tasks.

 

Employing predictive AI to optimize energy consumption has become a more common use case following geopolitical events and the impact of the COVID-19 pandemic, particularly as CSPs have become more focused on reducing costs. CSPs are also under pressure in certain markets to align with environmental, social and governance (ESG) agendas, and AI has emerged as a technology that can help CSPs reduce their carbon footprint.

 

The next stage of AI evolution pertains to generative AI (GenAI), which leverages unstructured data and opens up a broader range of use cases for CSPs.
 

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TBR Insights Live: GenAI Impact on Telecom Industry

GenAI Promises Better Customer Outcomes and Cost Reduction of Up to 80%

TBR’s latest telecom research indicates customer care, which includes contact centers, will be profoundly transformed by AI. Though traditional AI has been utilized in customer care for many years (e.g., chatbots and interactive voice response), GenAI will take customer care to an advanced state.

 

TBR estimates that GenAI could reduce the costs of running contact centers by up to 80%, and this is an area telecom operators are keenly interested in as they remain focused on cutting expenses across their businesses.

 

GenAI can also optimize the customer experience, essentially creating a super agent that is able to handle more complex tasks and lead the customer to better outcomes, thereby reducing churn and potentially driving upselling and cross-selling opportunities.

CSPs Will Expect Vendors to Share Cost Savings Realized From the Use of AI

When vendors are able to bring true AI capabilities and solutions to CSPs, the CSPs will find value in a variety of use cases such as AI-based applications for network maintenance or optimization, which will increase the efficiency of network operations.

 

Vendors will also benefit from cost efficiencies gained from AI, but TBR’s research indicates that CSPs will expect vendors to pass along some of the cost savings from the use of AI, such as costs freed up from a reduction in human resources.

 

Automation, analytics, AI and machine learning technologies will all prove critical to helping vendors improve margins during the 5G era and beyond. Examples include portions of Nokia’s AVA (Analytics, Virtualization and Automation) portfolio and Ericsson’s Operations Engine.

Most CSPs Will Remain Technology Consumers, Not Technology Producers of AI, Limiting Their Ability to Generate New Revenue in This Area

The 2 Primary Ways CSPs Will Derive Revenue-related Outcomes from the Use of AI

Leveraging GenAI to cross-sell and upsell existing subscribers may provide optimal revenue capture on a per-subscriber basis, while on the revenue protection side, CSPs will likely use GenAI to improve churn by better addressing customer pain points and root causes leading to the decision to switch operators.

 

The primary location where GenAI technology will be incorporated is the CSP’s contact center and potentially during the digital sales journey, such as interaction with a GenAI-enabled chatbot in the CSP’s digital storefront.

Most CSPs Are Expected to Rely on the Vendor Community and Hyperscalers for AI Innovations

CSPs will rely on vendors (including hyperscalers) to provide, and in many cases support and manage, AI solutions in their operations. For example, traditional network solution providers like Nokia and Ericsson as well as disruptive network solution providers would bring AI innovations as it pertains to the RAN and core to CSPs, in many cases incorporating AI innovations into software and processes.

 

Meanwhile, hyperscalers would likely be the de facto foundational large language model and other types of AI model providers, on which CSPs would leverage for their telco-specific use cases, such as in the areas of network operations, contact center and customer journey.

GenAI Shift from Hype to Reality Begins: How the Telecom Industry Will Be Impacted

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The Coming GenAI Telco Impact

Reality is starting to set in regarding Generative AI (GenAI). Though GenAI (and traditional AI) is expected to have a broad, transformational impact across the telecom industry, the technology is still immature and there is currently a big gap between hype and commercialization of GenAI for communication service providers (CSPs).
 
In the below TBR Insights Live video, Principal Analyst Chris Antlitz deep dives into the current state of GenAI adoption in the telecom industry.
 
Chris also discusses how AI models will be leveraged for the telecom industry, including which models have staying power, and what kind of use cases and business outcomes the industry can expect from AI and GenAI.
 

 

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TBR’s Telecom AI Market Landscape covers how communication service providers (CSPs) and vendors that supply CSPs are adopting AI (both “traditional” AI and generative AI [GenAI]) in their internal operations and in their products and services. This telecom industry-centric report covers AI use cases, adoption trends, business outcomes, and AI-related offerings as well as AI-related partnerships and M&A in the global telecom ecosystem. We also provide commentary about how AI is likely to evolve the telecom industry.
 
The report covers key companies that enable AI for the telecom industry as well as leading CSPs that are adopting AI as part of their digital transformations.
 
To access the research and dataset, sign up for your TBR Insight Center™ free trial today!

Next-generation AI PCs: What It May Mean for the Next Refresh Cycle

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How Will AI PCs Impact Future Profitability of Windows PC OEMs?

After seven consecutive quarters of contraction, PC revenue among TBR’s benchmarked devices vendors returned to growth in 1Q24, expanding at an estimated 2.6% year-to-year. The long-awaited rebound in the market centers on PCs purchased during the pandemic reaching the end of their useful lives as well as increasing macroeconomic confidence on the part of commercial organizations.
 
However, PC OEMs across the industry are bullish on the opportunity presented by on-device AI, believing that the advent of the AI PC will drive an accelerated generational refresh cycle in an otherwise commoditized PC market. As such, OEMs are investing heavily in the development and sale of AI PCs based on the most cutting-edge processors from companies such as Intel, AMD and Qualcomm.
 
In this TBR Insights Live video below, Senior Analyst Ben Carbonneau and Research Analyst Alek Maxfield discuss key findings from TBR’s most recent Devices Benchmark, such as what year-to-year PC revenue growth means for refresh cycles and how AI PCs will impact future profitability of Windows PC OEMs.
 
Additionally, the pair will share what TBR is seeing from PC OEMs and silicon providers and their expectations for Intel, ADM and Qualcomm’s fight for share in the emerging Copilot+ PC category.
 

 

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TBR’s Devices Benchmark tracks the performance of nine leading devices vendors across five segments: PC, PC services, smartphone, tablet and smart device. The report includes overviews of quarterly performance and industry trends within each segment, as well as more detailed analysis of vendors’ quarterly revenue, profitability and business strategies at both a corporate and product category level.
 
Acer, Amazon, Apple, Asus, Dell Technologies, HP Inc., Lenovo, Microsoft and Samsung are covered in the available data spreadsheet.
 
To access the research and dataset, sign up for your TBR Insight Center™ free trial today!

Hybrid, Proximity and Ecosystems Are Elevating the Importance of Colocation

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A Multitude of Secular Trends Are Reinforcing Colocation’s Value Proposition

Market trends over the past few years have made several things clear about the IT strategy of most enterprise customers, all of which reinforce the value proposition offered by colocation providers:

  • Hybrid environments will persist — Whether due to existing legacy investments, divisional or regional nuances, or acquisition and divestiture activity, heterogeneity will remain in most IT environments. At one point, the benefits of public cloud made organizations consider a homogeneous, fully cloud-based IT delivery strategy, but those visions have faded for most. The challenge — and goal — is to embrace the hybrid heterogeneous approach and find the best way to integrate, manage and optimize services across these diverse sets of delivery methods and assets. Colocation data centers play a critical role for customers, offering a hybrid approach to facilities and in the interconnection of cloud and on-premises services.
  • Location and proximity matter — The importance of delivery locations is driven by not only the hybrid nature of the environment but also the latency requirements of many workloads. Edge workloads are the clearest example, but there are other cases where latency is critical or where regulations determine the location of data.
  • Investment costs and opportunity costs are important — While organizations are still looking to control and minimize IT costs where possible, there has been a shift toward selective investment. This started when IT became one of the few levers companies could control as they shifted their business models to adapt to changes wrought by the COVID-19 pandemic. Most recently, the onset of generative AI (GenAI) convinced organizations that IT could be a competitive advantage as well, prompting investment in new solutions and technologies to keep pace with the market and key competitors. In this way, organizations are still closely controlling investment costs in new solutions but also can be swayed to spend due to the fear of lost opportunities. Colocation provides an emerging value proposition with GenAI and AI workloads, offering prebuilt facilities and interconnection services without requiring large retrofits or new capital expenditures.
  • Ecosystems equal innovation — Though hyperscalers have become the center of the IT ecosystem over the past decade, the network of infrastructure providers, ISVs, systems integrators (SIs), colocation providers, consultancies and managed services providers remains intact. With the hybrid approach that most customers are embracing, combined with the digital transformations being deployed and then amplified by the onset of new AI and GenAI technology, numerous vendors are part of most enterprise IT solutions. The orchestration of those multiple vendors is critical and most often handled by a trusted SI partner.

Colocation Is a Relied-upon Option for the Vast Majority of Enterprises

According to TBR’s 2Q24 Infrastructure Strategy Customer Research, a significant portion of enterprises report colocation as some part of their overall IT delivery strategy. Most have less than 25% of their workloads deployed in colocation facilities, which is a reflection of the two predominant delivery strategies: their own centralized data centers and cloud-based environments. Colocation is even more of a consideration for new workloads, however, as 72% of surveyed respondents expect to deploy between 25% and 50% of net-new workloads using colocation providers.
 
We believe this trend is due to two factors. First, enterprises are reluctant to build their own data center facilities for workloads that perform best outside the cloud or that have location and latency requirements. Most organizations want to reduce their data center capacity at this point, not add to it at. Second, for many new workloads, data center requirements are more challenging to provide. With the need for increased density, more power requirements and unique GPU-based AI services, a modern data center is required. The challenges of technology, facilities and staffing highlight the value of a ready-to-use colocation facility.

Digital Realty and Equinix Stand Out in a Tightly Packed Colocation Market

Recent trends around hybrid deployment models, latency-sensitive workloads, data residency and AI-reliant solutions have highlighted the sometimes-overlooked benefits of colocation providers. Especially for large enterprise customers, the scale of colocation facilities, strength of alliances and ability to invest in supporting new technologies make a difference in the value of their services. TBR research shows Digital Realty and Equinix are head and shoulders above the rest of their peers in terms of the ability to meet enterprise requirements. From a purely data center location perspective, Digital Realty is the market leader worldwide, with 309 data centers, including those from unconsolidated joint ventures, effective 1Q24.

 

The current revenue perspective is one component when it comes to colocation spending, but enterprises also want to know their solution providers will be able to scale as demands grow. Especially after the supply constraints over the last couple of years and the ongoing shortage of key components for next-gen workloads like GenAI, customers are not always secure in their ability to access resources on a timely basis. While the supply of colocation capacity remains tight, investing now to guarantee expanded capacity is another differentiator. Here again there are advantages to scale, as Digital Realty actually outpaced all covered vendors in level of capital expenditures in 2023. This commitment to current investment is a signal to customers that they can continue to grow with Digital Realty moving forward.

Digital Realty Is Well Positioned to Address Hyperscaler Demand, Both Financially and in its Go-to-market Approach

Though adamant about vying for mindshare among both enterprises and hyperscalers, Digital Realty has always been better known for its play in wholesale colocation. Over the past several quarters, Digital Realty has employed an aggressive joint venture strategy, allying with private equity firms to build multibillion-dollar hyperscale data centers in both Tier 1 and Tier 2 markets. As such, much of Digital Realty’s financial makeup and recent performance have stemmed from this customer base, with over 80% of annualized base rent from new leases in the >1MW category (effective 1Q24). The retail colocation market will undoubtedly continue to grow, led by robust demand for hybrid deployments and cloud adjacency for reasons highlighted earlier in this piece.
 
But many sources continue to suggest a rampant demand surge in the wholesale market as hyperscalers rush to satisfy their own customers’ AI and GenAI deployments. There are several ways Digital Realty is addressing this demand. Some are financial, including the ability to recycle capital by selling off nonscalable, single-tenant facilities to reinvest in strategic markets and maintaining a conservative capital structure; for context, Digital Realty owns nearly all of its facilities, in stark contrast to competitor Equinix, which is still leasing roughly 40% of its data centers. But the other aspect is Digital Realty’s go-to-market approach and how the vendor is nurturing relationships with the hyperscalers and their own partner ecosystems.

Digital Realty and Oracle Have a Strong Customer-partner Relationship: Other Hyperscalers Should Take Note

Digital Realty has always had a strong relationship with Oracle, which is now Digital Realty’s third-largest customer, deploying in 38 locations and spending $170 million in annualized recurring revenue (ARR). It is hard to dispute Oracle’s success pivoting from a traditional software incumbent and SaaS provider to an IaaS challenger with OCI (Oracle Cloud Infrastructure), which is on track to become Oracle’s largest cloud business in the coming years. Digital Realty astutely took notice of OCI’s role in the market, not to mention Oracle’s tight relationship with NVIDIA, which supplied Oracle with GPUs early in the AI wave.
 
Recent developments like connecting to Oracle’s EU Sovereign Cloud and offering NVIDIA-based OCI instances in its high-traffic Northern Virginia data center only reinforce Digital Realty’s role in powering OCI’s expansion. It is one of the reasons Oracle can not only boast more rapid footprint expansion over peers but also deliver on the “distributed cloud” message that nearly all hyperscalers are eager to convey. For perspective, Oracle holds only a single-digit share percentage in the IaaS market, but Oracle’s ability to leverage Digital Realty to expand ahead of peers is notable and something that other hyperscalers that are adamant about building their own data centers should recognize as they fight to capture net-new AI workloads.

SIs and Consultancies Pull It All Together at Scale for Enterprises

For IT services companies and consultancies, two needs mentioned above — orchestration and scale — illustrate how the colocation piece of the enterprise IT ecosystem can provide competitive opportunities.

Orchestration Is Critical and Most Often Handled by a Trusted SI Partner

Companies like Deloitte, Accenture and Infosys have the most complete view of an enterprise’s IT environment, positioning them best to coordinate vendors that provide disparate technologies. Most consultancies and SIs stay in well-defined swim lanes, delivering their added value while facilitating cloud, software and even hardware solutions from an enterprise’s suppliers. In TBR’s research, the market-leading consultancies and SIs use their industry knowledge, influence and reach within a client as the basis for orchestrating a full spectrum of technology providers, calibrated specifically to an enterprise’s IT needs.
 
As described above, colocation continues to be a pressing need, creating an opening for IT services companies and consultancies that have traditionally shied away from alliances that are too far removed from their core competencies. Just as alliances have formed around cloud computing and enterprise software, with IT services companies and consultancies delivering value through innovation, cost containment and managed services, partnerships with colocation specialists could add a compelling component to an IT services company’s orchestration value proposition. Consultancies’ and SIs’ business models depend on retaining clients and expanding footprint within clients. If colocation can become another differentiating factor and improve enterprise clients’ overall IT environments, SIs and consultancies will willingly seek partnerships.

Enterprises Want to Know That Their Solution Providers Can Scale as Demands Grow

If client retention remains critical to SIs’ and consultancies’ business models, scale increasingly marks the difference between average performance and market-leading results. No SI or consultancy can out-scale the largest players, but TBR’s research shows that companies that manage their alliances well can leverage their ecosystem for scale unattainable on their own. In short, no other company can be Accenture, but an SI or consultancy can replicate Accenture’s reach with the combined forces of a well-oiled tech and services ecosystem.
 
Colocation providers already play within the technology ecosystem but have not traditionally been considered a means for consultancies and SIs to increase scale. As AI and GenAI increase compute power demands and enterprises turn to their consultancies and ask, “How can I take advantage of all this new technology without exploding my IT budget?” and “How can I take this GenAI-enabled solution from pilot to my entire enterprise,” colocation can become a critical component.

The SI and Consulting Tech Evolution: From ERP to Cloud to GenAI to Colocation

In TBR’s view, SIs and consultancies will never become adept at selling those components of the technology ecosystem that are the furthest from their core competencies, but the market leaders have become exceptional at managing and expanding their ecosystems. TBR’s research around the relationships between the largest cloud providers and the largest SIs demonstrates how much revenue can be driven through alliances. As SIs and consultancies mature their partnering practices, colocation will become another element orchestrated by the likes of Deloitte, Accenture and Infosys. Quite possibly some smaller SIs and consultancies will use colocation as a critical component to scaling themselves into competitive positions against those larger players. As GenAI drives new demands — on compute power, budgets and expertise — TBR will closely watch these relationships between SIs and colocation providers.

Databricks Pivots Around Data Intelligence to Address GenAI Use Cases

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Just like it did with the data lakehouse five years ago, Databricks is establishing another paradigm with data intelligence, which has the data lakehouse architecture at its core but is infused with generative AI (GenAI). Data intelligence was a key theme throughout Databricks Data & AI Summit and signals Databricks’ intentions to further democratize AI and ultimately help every company become an AI company.

A Brief Databricks Backstory

Founded by the creators of Apache Spark, Databricks is known as a trailblazer for launching new concepts in the world of data, such as Delta Lake, the open table format with over 1 billion yearly downloads, and the “lakehouse” architecture, which reflects Databricks’ effort to combine the best of what the data lake and data warehouse offer. Launched in 2020, the lakehouse architecture can handle both structured and unstructured data, and addresses the data engineer and business analyst personas in a single platform.

 

Delta Lake and Unity Catalog, which governs the unstructured data stored in these Delta tables, serve as the basis for the lakehouse architecture and are part of Databricks’ longtime strategy of simplifying the data estate and, by default, AI. But with the advent of GenAI, which is causing the amount of unstructured data to proliferate, Databricks has spearheaded yet another market paradigm, pushing the company beyond its core areas of data ingestion and governance into data intelligence.

 

At the heart of data intelligence is the lakehouse architecture and also Mosaic AI, the rebranded result of last year’s MosaicML acquisition that equipped Databricks with the tools to help customers train, build and fine-tune large language models (LLMs). These also happen to be the same technologies Databricks used to build its own open-source LLM ― DBRX ― sending a compelling message to customers that they, too, can build their own models and use the Mosaic AI capabilities to contextualize that data and tailor it to their business, thus achieving true data intelligence.

What Is Data Intelligence?

Databricks’ executives and product managers largely communicated the definition of data intelligence through demonstrations. One of the more compelling demos showed how Mosaic AI can be used to create an agent that will build a social media campaign, including an image and caption for that campaign, to boost sales.

 

The demo depicted how a user can use transaction data as a tool to supplement a base model, such as Meta’s Llama 3. This demo was key to highlighting one of Databricks’ product announcements, the Shutterstock ImageAI model, which is built on Databricks in partnership with Shutterstock and marks Databricks’ foray into the multimodal model space.

 

The exercise created an image for the fictional social media campaign that included a company’s bestselling product — chosen through transaction data — and a catchy slogan. But to convey the contrast between data intelligence and general intelligence, the demonstrator removed the “intelligence” ― all the data-enabled tools that exist in Unity Catalog ― and generated the image again. This time, the image did not include the bestselling product and was accompanied by a much more generic logan.

 

This demo reinforced the importance of contextualized data in GenAI and the role of Unity Catalog, which helps govern the data being used, and Mosaic AI, which allows developers to use enterprise data as tools for creating agents (e.g., customer support bots).

 

Data intelligence is about not only the context behind the data but also making that context a reality for the enterprise. For instance, in the above scenario, the demonstrator was able to put the image and slogan into Slack and share it with the marketing team through a single prompt. In this example, it is clear how a customer with Databricks skills could use GenAI in their business.

Databricks’ Acquisition of Tabular Is a Blow to Snowflake and a Surefire Way to Stay Relevant in the Microsoft Ecosystem

As a company born on the values of openness and reducing lock-in, Databricks pioneered Delta Lake to ensure any engine can access the data sitting in a data lake. Delta Lake remains the most widely adopted lakehouse format today, handling over 90% of the data processed in Databricks, and is supported by other companies, as 66% of contributions to the open-source software come from outside Databricks.

 

But over the past few years, we have seen Apache Iceberg gain traction as a notable alternative, garnering significant investment from data cloud platforms, including Snowflake. When Databricks announced its acquisition of Tabular ― created by the founders of Apache Iceberg ― days before the Data & AI Summit, it signified a strategic shift that will help Databricks target a new set of prospects who are all in on Iceberg, including many digital natives.

 

The general availability of Databricks’ Delta Universal Format (UniForm), which helps unify tables from different formats, indicates the company’s intention to make Delta and Iceberg more interoperable and, over time, potentially reduce the nuances between both formats, though this may be a longer-term vision.

 

The Tabular acquisition in some ways also marginalizes Snowflake’s steps to become more relevant as a Microsoft Fabric partner. Available through Azure as a first-party native service, Databricks has always had a unique relationship with Microsoft, and Delta serves as the basis for Microsoft Fabric. But Microsoft’s recent announcement to support Iceberg tables with Snowflake in a push for more interoperability was notable, and now with Tabular, Databricks can ensure it remains competitive in the Microsoft Fabric ecosystem.

It Is All About Governance

First announced three years ago, Unity Catalog has emerged as one of Databricks’ more popular products, allowing customers to govern not just their tables but also their AI models, an increasingly important component in GenAI.

 

At the event, Databricks announced it will open source Unity Catalog, which we watched happen during the Day 2 keynote, when Unity Catalog was uploaded to GitHub. Despite Unity Catalog’s mounting success, this announcement is not surprising and only reinforces the company’s commitment to fostering the most open and interoperable data estate.

 

It is very early days, but open sourcing Unity Catalog could help drive adoption, especially as governance of GenAI technologies remains among the top adoption barriers.

Databricks SQL Is Gaining Momentum

It is no secret that Databricks and Snowflake have been moving into one another’s territories. Databricks, with its expertise in AI and machine learning (ML), has been progressing down the stack, trying to capture data warehouse workloads. Snowflake, with its expertise in data warehousing, is looking to get in on the AI opportunity and address the core Databricks audience of data scientists and engineers.

 

Snowflake’s early lead in the data warehouse and strong relationship with Amazon Web Services (AWS) could be making it more difficult for Databricks to attract workloads. Combined with the enormity of the market, there may never be a scenario in which Databricks becomes a “standard” in enterprise accounts for data warehousing. But Databricks’ messaging of “the best data warehouse is a lakehouse” certainly seems to be working.

 

Traditionally, customers have come to Databricks for jobs like Spark processing and ETL (Extract, Transform, Load), but customers are increasingly looking to Databricks for their data warehouse. These customers fall into two groups. In the first group, customers on legacy systems, such as Oracle, are fed up with the licensing and are looking to modernize. In the second group, existing cloud customers are looking for a self-contained environment with less lock-in, compared to vendors like Snowflake, or are seeking to avoid challenges with system management and scale after having worked with hyperscalers.

 

As highlighted by Databricks Co-founder and Chief Architect Reynold Xin, Databricks SQL is the company’s fastest-growing product, with over 7,000 customers, or roughly 60% of Databricks’ total customer base. During his keynote, Xin touted improved startup time with Databricks SQL Serverless to five seconds and automatic optimizations for BI workloads to be four times faster compared to two years ago. Provided Databricks can continue to enhance performance while pushing the boundaries on ease of use to better compete with Snowflake and other vendors in attracting less technical business personas, we expect this momentum will continue and will challenge competitors to raise the bar for their own systems.

Databricks Is Bringing an Added Layer of Value to the BI Stack

Databricks AI/BI is a new service available to all Databricks SQL customers that allows them to ask questions using natural language (Genie) and perform analytics (Dashboards). In a demo, we saw the two user interfaces (UIs) in action: BI offers common features like no-code drag and drop and cross-filtering, and AI includes the conversational experience where customers can ask questions about their data.

 

Databricks AI/BI may lack some of the complex features of incumbent BI tools, but ultimately these are not the goals of the offering. The true value is in the agents that can understand the question the business analyst is asking and hoping to visualize. Databricks’ approach exposes the challenges of bolting on generic LLMs to a BI tool. But the company is not interested in keeping this value confined to its own BI capabilities. Staying true to its culture of openness, Databricks announced at the event that it will open up its API to partners, ensuring PowerBI, Tableau and Google Looker customers can take advantage of data intelligence in these BI environments.

Conclusion

With its lakehouse architecture, which was founded on the principles of open-source software and reduced lock-in, Databricks is well positioned to help customers achieve data intelligence and deploy GenAI. The core lakehouse architecture will remain Databricks’ secret sauce, but acquisitions, including those of MosaicML and Tabular, are allowing Databricks to broaden the scope of its platform to tap into new customer bases and serve new use cases.

 

If Databricks can continue to lower the skills barrier for its technology and sell the partner ecosystem around its platform, the company will no doubt strengthen its hold on the data cloud market and make competitors, including the hyperscalers in certain instances, increasingly nervous.

Blending Industry Expertise with Cybersecurity Credibility: Insights From PwC’s EMEA Financial Services Team

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Compelling Cybersecurity Needs Meet PwC’s Capabilities

A July 1, 2024, briefing by PwC’s EMEA Financial Services (FS) team provided TBR with a closer look at PwC’s largest industry practice by revenue and the ways the firm has blended industry expertise with cybersecurity managed services experience and credibility. Julian Wakeham, UK EMEA Consulting Financial Services leader; Moritz Anders, Digital Identity lead, Cyber Security & Privacy, Germany; and Joshua Khosa, Service lead, Cyber Managed Services, Germany, steered the discussion for PwC.

 

Anders said FS clients’ three compelling cybersecurity needs — compliance, cost optimization and talent — shaped PwC’s approach to cybersecurity managed services and, in TBR’s view, will be consistent revenue drivers for PwC as those needs will be perpetual. The challenges around recruiting and retaining highly specialized cybersecurity experts, for example, remain outside the core functions of most enterprises, yet the cybersecurity risks continue evolving, necessitating that consultancies step into that role. A significant part of PwC’s value, therefore, comes from assembling and deploying experts in both cybersecurity and the underpinning enterprise technologies.

 

Critically, according to Anders, PwC has approached cybersecurity managed services not as an IT play, where it can simply throw technology and people at the problems, but as an ongoing business challenge best tackled through a highly automated architecture and a sustained focus on business outcomes.

 

Echoing the three compelling cybersecurity needs highlighted above, Anders and Khosa provided details about a use case with a Europe-based bank that delivered three clear business outcomes: “compliance and audit readiness, operational efficiency, and enhanced security,” with the last relying, in part, on PwC using its alliance partners to keep emerging technologies and updates flowing to the client.

 

In TBR’s view, the compliance and audit-readiness components reflect PwC’s legacy strengths and brand around governance, risk, and compliance, and the operational efficiency outcomes build on the firm’s decades-old emphasis on and experience with operations consulting. In short, PwC continues playing to its strengths.

 

At the end of the briefing, the PwC team was asked why this particular Europe-based bank chose PwC for a complicated, multiyear cybersecurity managed services engagement. Anders said PwC remained direct and humble throughout the selection process, informing the client, without marketing spin, what PwC could and could not do well.

 

Among the strengths PwC brought to the table, according to Anders, was Europe-based talent at scale, in contrast to competitors, which relied on offshore resources. Wakeham noted PwC’s flexibility, focus on business problems (and not just selling technology solutions), PwC’s Industry Edge+ as a key enabler for business model reinvention, and the “deep trust” PwC’s clients have in the firm. 

Watch Now: TBR Vice President Dan Demers and TBR Principal Analyst Patrick M. Heffernan discuss trends expected to shape the market in 2024, including GenAI’s impact on ecosystem alliances and how clients use TBR’s research and analysis to add context to strategic questions and address challenges around alliance enablement

Business Model Reinvention, Ecosystem Strategy and Expansive Capabilities

Reflecting on the EMEA FS briefing and previous discussions with PwC across topics and capabilities as diverse as people advisory services, IoT and generative AI, TBR made a few observations. First, PwC’s focus on “business model reinvention” was mentioned at the beginning and end of the discussion, with Wakeham acknowledging that the firm did not create that term or idea but explaining that PwC’s own market research indicated the importance to CEOs of that strategic focus. TBR reported earlier this year on PwC’s ideas around business model reinvention and notes that while previous strategic shifts have taken time to gain traction across the PwC member firms, business model reinvention appears to have considerable momentum and heft.

 

Second, PwC’s alliances strategy appears to be evolving as both the competitive and ecosystem landscapes change, with increased expectations that technology partners will bring business to PwC. In contrast to the usual equivocation and lack of details around how ecosystem partners can play a role in PwC’s go-to-market strategy, the EMEA FS team provided both a direct answer to TBR’s question about whether partners bring PwC into client projects and an explanation for the underlying reasons why software vendors would introduce PwC into an engagement.

 

PwC maintains a vast array of technology partnerships across cybersecurity, enterprise platforms, cloud, IoT and more, necessitating a well-managed ecosystem effort and providing extensive opportunities to gain new clients and expanded opportunities within existing accounts. Continually refining the ecosystem playbook will be vital to PwC’s continued success.

 

Lastly, PwC’s EMEA FS team provided another example of the breadth of the firm’s capabilities, an element of PwC’s value proposition that can sometimes be forgotten when focusing too intently on one piece of the overall firm. For example, in cybersecurity managed services, PwC brings expertise and capabilities in cyber incident response, smart cyber defense, cybersecurity upskilling, identity and access management, and OT & IT security, to name a few.

 

TBR believes the extent of PwC’s capabilities and offerings, while not unique, can sometimes be lost on clients and ecosystem partners that are focused on the immediate services the firm is bringing to their engagement. If PwC remains focused on business model reinvention and continues evolving its ecosystem strategy, the breadth of the firm’s capabilities will become the underlying strength that sustains PwC’s success.

Competitive Benchmarking: A Strategic Guide

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What Is Competitive Benchmarking?

The IT market is a crowded space in which IT providers of all sizes compete for a share of the spending customers have budgeted for business and technology transformations and modernizations. Knowing where an IT vendor stands against peers in the market and understanding what competitors provide and how successful they are in terms of financial performance are key levers that IT vendors use to build business growth strategies. Competitive benchmarking uses qualitative and quantitative data to rank IT vendors against their peers. Understanding current IT vendor positioning is key to setting a strategy to outperform peers.

 

Competitive benchmarking is a tool that TBR has been providing to leading IT vendors for nearly 20 years. The tool dives deep into multiple metrics in areas such as revenue, revenue growth and profitability; productivity and resources; operations and investments; and business segments, industry verticals and geographies to construct a meaningful picture of the IT vendor landscape.

 

While ranking IT vendors across multiple metrics is the first important step, the most essential analysis is understanding why certain vendors are taking leading positions in specific metrics and business segments. Data-driven ranking, combined with a thorough analysis of what IT vendors are offering, what their strategies are and where they are investing for growth, helps vendors understand why their peers are being placed in leading or lagging positions.
 

Click the video below to discover the fundamentals of competitive intelligence and learn how it can benefit your business strategy

Understanding the Competitive Benchmarking Process

The process of competitive benchmarking begins with collecting data across multiple vendors, ranking the vendors and analyzing their positioning. A very important aspect of competitive benchmarking is establishing common metric definitions and taxonomies that drive the benchmarking process and provide an apples-to-apples comparison across vendors included in the report.

 

The extensive and thorough collection of financial and nonfinancial information is the foundation for competitive benchmarking. The addition of expert knowledge and impartial opinions by TBR’s analysts about each vendor rounds out the competitive benchmarking process.

 

For example, TBR’s IT Services Vendor Benchmark is a quarterly research program that covers 31 leading vendors in the IT services segment and analyzes their go-to-market strategies and investments, alliances and acquisitions, resource management practices, and financial performance. The IT Services Vendor Benchmark is one of our largest benchmarks and also one of our oldest, having been publishing since 2002. The report includes 15 metrics across three strategic areas (financial, go-to-market and resource management), along with analysis of three main revenue segments (consulting & systems integration, outsourcing, and support & maintenance) and three geographies (the Americas, Asia Pacific, and Europe, the Middle East and Africa [EMEA]).

Benefits of Competitive Benchmarking

Competitive benchmarking enables IT vendors to understand in which areas they outperform or lag their peers. Understanding the ranking of peers helps vendors close gaps in areas such as portfolios, resources, alliance partnerships and acquisitions. Vendors can also identify opportunities for expansion utilizing areas of existing strength in segments, geographies and industries.

Steps to Performing Competitive Benchmarking Analysis

Effective competitive benchmarking begins by carefully selecting a topic area for the report. The topic can be broad, such as IT services, telecommunications services and software, or a deep dive into a specific business segment such as management consulting, cloud, analytics and AI, or sustainability services. The next step is selecting the vendors to cover in the benchmark. Typically, vendors of similar sizes and business models make the most suitable candidates for benchmark reports. Collecting and analyzing data and categorizing and ranking vendors through visual representations enable analysts to identify leaders and laggards and provide expert opinions around vendor positioning.

Determining Success

Using peers’ performance across metrics, business segments and geographies tracked in competitive benchmark reports enables IT vendors to determine the success of their business strategies. IT vendors can understand how successful they are against specific peers and peer groups, depending on the data cuts and analysis, which can be categorized by service area, specific geography, vendor size and/or vendor business model, among other business facets. Competitive benchmarking also provides aggregate views of trends for the entire group of IT vendors covered in the reports. This helps IT vendors understand historic market growth trends and outlooks and identify areas of improvement for future financial results.

Possible Pitfalls

Competitive benchmarking reports typically include a set number of IT providers determined by specific criteria based on the topic of the report. While competitive benchmarking includes a directional view of overall trends and vendor positioning in each report, it does not represent an all-inclusive global market view of the topic covered in the report. Lack of data availability and accuracy can be a challenge when trying to develop comprehensive competitive benchmark reports. Including too many metrics and too many companies can overcomplicate the analysis and provide inaccurate vendor landscape trends. Additionally, overemphasizing data while not utilizing qualitative analysis tied to the data and specific vendors’ business models might create inaccurate benchmark positionings.

Future Trends in B2B Competitive Benchmarking

The future of competitive benchmarking will be driven by progress in technology. Analyst firms that develop competitive benchmarks will increasingly use big data analytics, AI and machine learning solutions to gain deeper insights from datasets, improve their ability to identify and predict trends, and speed up the benchmarking process and make it more efficient.

 

Technologies will also help analyst firms change the cadence of their benchmarking process by utilizing systems that enable tracking and comparison of companies in real time. Data visualization tools will also help benchmark developers improve the quality of their reports and increase the value of their insights.

 

Additionally, an increased emphasis on customer experience and satisfaction will push analysts to customize benchmark reports to address customers’ preferences and specific business needs, thus increasing the value of competitive benchmarks. As long as competitive markets exist, competitive benchmarking will be used by leaders to stay ahead of laggards.

Conclusion: Achieving Success Through Benchmarking Strategies

Competitive benchmarking is an essential tool for IT vendors aiming to navigate and thrive in a crowded market. By leveraging both qualitative and quantitative data, vendors can assess their positioning against peers, identify strengths and weaknesses, and develop strategies for growth and improvement.

 

TBR’s comprehensive benchmarking process, which includes data collection, ranking, and expert analysis, offers valuable insights into market dynamics and vendor performance. As technology advances, the future of competitive benchmarking will be shaped by innovations in big data, AI, and real-time analytics, further enhancing its efficacy and relevance. Ultimately, competitive benchmarking empowers IT vendors to make informed decisions, capitalize on opportunities, and maintain a competitive edge in the ever-evolving IT landscape.

 

For an in-depth, personalized look at TBR’s competitive benchmarking tools, schedule your Insight Center™ private demo today!

SoftwareOne Strategy Brings Speed, Ease, Flexibility and Low Cost to SAP Clients in DACH Region

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SoftwareOne’s Strategy for SAP Clients in DACH

In a June 2024 discussion with SoftwareOne’s DACH (Germany, Austria and Switzerland) leadership, TBR came away with three observations on what might make SoftwareOne a potentially unique player in the SAP ecosystem. At a minimum, SoftwareOne in DACH appears to be taking a different approach to the market opportunities created by the confusion around RISE with SAP, GROW with SAP, migrations to S/4HANA, and the 2027 deadline for the end of ECC support. From the presentation by and discussion with SoftwareOne’s Stephan Timme, president DACH; Vincenzo Boesch, sales leader for SAP Services; and Oliver Berchtold, service director DACH, TBR noted that:

 

  • SoftwareOne remains focused on customers’ current SAP environments and helping those customers get to S/4HANA and to the cloud. SoftwareOne is decidedly not focused on business processes. TBR believes that distinction, while subtle, matters because almost every other IT services company and consultancy in the SAP ecosystem of SoftwareOne’s scale and larger starts with identifying business problems and processes that need to be fixed and then declaring, “Hey, look at that, SAP RISE is a perfect solution to fixing these problems!” SoftwareOne does not dance around the business issues but instead gets straight to what it excels at: solving the SAP challenges of licensing, migrating and maintaining.
  • SoftwareOne recognizes SAP customers have been struggling with the confusion and costs around S/4HANA and RISE, along with all the other changes wrought by the end of support for ECC coming at the same time as the rise of generative AI (GenAI). During the SoftwareOne analyst event that TBR attended in Austin, Texas, in April, PF Grillet, SoftwareOne’s global SAP leader, told us there has “never been a more complex time for decision-making around SAP.” SoftwareOne’s answer to the confusion is a value proposition rooted in four promises: fast, easy, agile/flexible and cost-effective. TBR would summarize that value proposition and SoftwareOne DACH’s overall approach to clients in one word: And TBR suspects DACH clients value pragmatism.
  • When TBR noted the absence in SoftwareOne’s presentation of the SAP catchphrase “clean core,” Vincenzo Boesch explained that for him and his colleagues, SoftwareOne’s readiness services provided a comprehensive approach to what SAP calls clean core, emphasizing the need to prepare for migration, migrate only what is needed, and then maintain the benefits of a clean core throughout the transition and ongoing functioning of SAP within the client’s environment. SoftwareOne aims to remove complexity and streamline a customer’s environment, modernize and prepare customers for innovation, and then adopt an iterative transformation approach, more focused and agile, to continue the move to full clean core over the time frame best suited to the customer’s needs and capabilities. SoftwareOne recognizes few customers will have the means and the appetite to do it all in one go. In short, SoftwareOne is honest about the challenges, does only what is necessary and sets the client up for sustained success.

 

On the last point, TBR believes this approach to clean core likely fits the needs of small and midsize businesses with less complex IT environments. In follow-on discussions with TBR, SoftwareOne explained that the company is not targeting all customers but rather focusing on those customers that have limited need for business transformation, already have efficient business processes, and are driven to modernize their ERP and remove the mainly technological limitations of ECC. With enterprise clients migrating complex and highly customized SAP instances, SoftwareOne’s focus purely on SAP runs the risk of discounting business process change management cost and potentially pushes complex and problematic processes into the future, setting clients up for aggravation, not success. Failure seems unlikely given SoftwareOne’s overall track record of success with SAP. A more likely outcome for SoftwareOne would be selling additional consulting services related to complex migrations.

Stepping Back to Look at the Bigger SAP Picture

Just as there has “never been a more complex time for decision making around SAP,” as Grillet said in April, there also has never been a better time for a services firm to take a pragmatic approach to helping small to midsize businesses migrate to S/4HANA. As of 4Q23, GROW with SAP had amassed only 700 customers, which pales in comparison to the estimated 24,000 customers on ECC, 14,600 on S/4HANA and 8,800 in S/4HANA Cloud. Furthermore, GROW’s install base skews toward new logos, suggesting many legacy SMB customers have been comparatively slow to adopt the offering.
 
SAP will look to change this trend, primarily through its ecosystem, which will present opportunities for partners focusing on the SMB segment. The partners that succeed will recognize the oversized impact that cost and complexity have on SMBs, which are more likely to be resource-constrained in technical staff relative to larger enterprises. These customers are more apt to pursue the simplest path to the cloud possible, aligning closely with how SoftwareOne is positioning its services.
 
The contrast between SoftwareOne’s pragmatic approach and the strategies of much of the rest of SAP’s services ecosystem is becoming more stark. While RISE and GROW still hold S/4HANA migration at their core, SAP has become vocal about the offerings’ ability to drive multiproduct sales motions. In 1Q24, SAP released new add-on packages for RISE that bundle line-of-business (LOB) suites in finance and supply chain, and the company will look to partners to lead the charge in their adoption.
 
Yet, cross-selling initiatives risk adding to the complexity of an already challenging migration and implementation process. In the coming years, efforts to encourage business AI adoption will add to the noise for customers simply looking to bring their ERP deployments to the cloud. Many customers, especially SMBs, will appreciate a service provider whose value proposition is a fast, easy, agile/flexible and cost-effective migration. This will be a key differentiator for SoftwareOne as the vendor positions as a services provider capable of cutting through the noise and guiding customers toward the path of least resistance.

Minding the Minefields Before Stepping in Them

During the early days of robotic process automation, some IT services companies and consultancies advised clients to automate their processes before evaluating the efficacies and benefits, betting that automating even less-than-optimal processes would generate cost savings. Predictably, that bet did not always pay off.
 
Two considerations for SoftwareOne: First, the company should ensure that its message and what it delivers reinforces the pragmatism of speed, flexibility and value. In other words, promote this really well to ensure SoftwareOne’s approach and value proposition stand out in a large and noisy market. Second, in TBR’s view, while Boesch and his colleagues presented a compelling value proposition for SoftwareOne’s DACH clients, this approach will not necessarily apply to the customers that need a broader business process transformation.
 
For more than a decade, many consultancies and IT services companies have been stressing a business-first and technology-second mindset, but TBR believes SoftwareOne’s approach will appeal to clients – maybe especially in but certainly also outside of DACH – that are similarly focused on pragmatic, technology-first outcomes.

Is India the Right Growth Market for Global Consultancies?

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Are All of the Largest Consultancies Right That India Is a Growth Market for Them?

If India’s economic growth story continues apace and global management consultancies continue investing in India-based talent to serve India-based clients, what strategic distinctions between the firms can we expect and what are the firms’ prospects of making India a top-tier market for consulting services? In short, if India is on track to become the third largest economy, will it also be the third largest revenue source for the Big Four, Accenture, IBM and Capgemini, or only for the firms that act first and implement the optimal strategies?

 

First, here is a quick review of recent India-centric announcements and developments, and TBR’s analysis of the Big Four firms and some of the management consulting peers:

 

  • While Accenture largely relies on India as the company’s largest offshore delivery hub, the company is also investing for future locally sourced growth, as evidenced by the announced opening of a generative AI (GenAI) studio in the country. Additionally, deal wins, such as with Union Bank of India to design and develop a data lake platform supporting the bank’s data strategy architecture and analytics-enabled reporting capabilities, will arm Accenture with strong use cases as it elevates its GenAI value proposition. Accenture also announced plans to open GenAI studios in China, Japan and Australia, highlighting the company’s culture and willingness to take on risk, which both remain consistent regardless of clients’ subdued discretionary spend.
  • Deloitte continues to diversify its regional opportunities in an effort to build a beachhead in emerging markets including India. Deloitte India released the Digital Public Infrastructure playbook for nations, which we believe will help it drive tech-enabled strategy discussions with India-based state governments as well as other countries in the APAC region as they embark on citizen-centered digital programs.
  • IBM is expanding its innovation and research capabilities in India to strengthen relationships with clients and startups and support digital transformation in the country. In November IBM opened a new IBM Consulting Client Innovation Center (CIC) in Gandhinagar, India. IBM is expanding in emerging Tier 3 cities across India to benefit from access to talent, such as graduate hires, and strengthen its ecosystem. IBM Consulting’s CIC will emphasize expanding asset-led IT services activities around GenAI, hybrid cloud and cybersecurity. IBM Consulting will use security engineering professionals to build cybersecurity platforms and accelerators to automate threat management and improve regulatory compliance.
  • TBR continues to believe KPMG sees India as both a global delivery hub and a market that can help the firm bolster its overall performance over the next decade. We recognize that KPMG is far from reaching its optimal staffing pyramid to support both sets of opportunities, but recent investments suggest the firm is taking the necessary steps to fill the gaps. For example, KPMG announced the expansion of its global delivery center in Kolkata, India. KPMG India also partnered with Lineaje Inc. to jointly pursue supply chain security management opportunities with local clients seeking support for third-party risk management programs.
  • In February Capgemini’s chief technology and innovation officer in India, Nisheeth Srivastava, shared that the company is gearing up for a hiring spree in India for FY25 (ending March 31, 2025) due to an expected surge in domestic business. The ramp-up in hiring aligns with positive industry trends following a challenging FY24 within the IT sector. Srivastava stressed the importance of upskilling in areas such as data, machine learning and AI because of the disparity between industry hiring needs and technical education in India. Srivastava also highlighted the potential for GenAI to expand the workforce through coding-based learning opportunities. Demand for skills such as user experience and interface, data science and cybersecurity is expected to rise in India as vendors increase hiring to meet the market’s need for an evolving skill set within the country.
  • In TBR’s view, EY’s India strategy appears to include amplifying the firm’s India-centric thought leadership through nongovernmental organizations and/or industry groups, such as the Organisation of Pharmaceutical Producers of India. Not surprisingly, much of EY India’s thought leadership has focused on GenAI, with a highlight on the private equity, healthcare and global capability centers sectors.
  • TBR discussed PwC India’s recent analyst event in Gurgaon in a special report, PwC touts India as strategic growth hub, investing in the country’s tech and talent for long-term gains. According to the firm, PwC has seen 30% year-to-year revenue growth in India, driven by India-based clients across a wide spectrum of services. India-based clients look to PwC for integrated solutions in a variety of areas, including supply chain management, human capital management and operations consulting. In addition, clients in the country have matured since 2019 and are more adept at evaluating and buying consulting services.

Strengthening physical presence across India remains a core piece of the consultancies’ strategies to position closely with clients. Through their various collaboration centers, the consultancies bring GenAI expertise, enhanced delivery, increased innovation efforts and expanded portfolio offerings to local clients and partners. Planting themselves in front of clients will validate or negate the consultancies’ strategies of how to effectively connect with and generate new revenues across the region.
 

Curious About the Performance of Global Systems Integrators in 2023 and early 2024? Check Out the Below TBR Insights Live Session for Insights into the World of Hardware-centric, Legacy GSIs and What Lies Ahead for These Vendors

 

If the Largest Consultancies Follow the Same Basic Industry Strategy in India, Will They Aall Succeed?

PwC India has focused on five industries — financial services, healthcare and pharma, manufacturing, infrastructure, and retail — which, not coincidentally, are the same industries the Indian government has determined to be strategic for the country’s sustained growth. Looking over the recent developments, the rest of the Big Four, along with Accenture, IBM and Capgemini, are pursuing similar strategies, with all of them potentially over-indexing on a handful of industries and markets.

 

Discussions during the PwC India event led TBR to ponder the questions posed earlier in this report. In addition, we wonder if price pressures; compelled cooperation among consultancies, IT services companies and technology vendors; and consolidation within these select industries lead consultancies to develop highly specialized talent who become the undisputed go-to for that particular domain or industry? Will PwC or any peers focus on subverticals and carve out a niche? Or will these consultancies cast as wide a net as possible for opportunities in these select industries, creating opportunity for talent mobility (the nice way of saying “poaching”), salary spikes and subsequent margin pressures? This is, admittedly, only one element of these consultancies’ strategies, but given the similarities across GenAI hubs and innovation centers and upskilling local talent, this could be an avenue for one or two of these competitors to separate from the pack.

 

One final caution or caveat: Transforming India from low-cost delivery factory to a high-value engineering hub is appealing — to the Indian government, to the talent hired into these jobs and to the firms charging Indian companies for higher-value services. But the short-to mid-term outlook will remain aspirational for a bevy of reasons related to India’s systemic and persistent economic challenges. In TBR’s view, as much as global firms continue to pour resources into India to serve the local market, the predominant investment motivation will likely remain the labor arbitrage, lower-cost advantage India continues to provide. For a deeper look on this, see the recent TBR special report, HCLT leads revenue growth among India-centric IT services vendors amid market uncertainties.

SoftwareOne: Gritty, Determined, Local

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SoftwareOne’s leadership hosted about 20 analysts for presentations, client briefings and breakouts dedicated to specific SoftwareOne solutions and services. In addition to attending the formal program, TBR analysts met one-on-one with select SoftwareOne leads. The following reflects both summit presentations and TBR’s ongoing research of and discussions with SoftwareOne.

Simplify access to technology

In the year since TBR attended SoftwareOne’s inaugural analyst event in Milwaukee, the company has refined its value proposition and further established its place in the market, in large part by expanding its IT services capabilities and revenues.

 

During his event opening presentation, Duffy outlined five client priorities that SoftwareOne intends to tackle, all of which echoed the company’s value proposition:

  1. Simplify access to technology
  2. Maximize ROI on technology spend
  3. Enhance workforce productivity
  4. Accelerate cloud adoption
  5. Fast-track results in the AI and generative AI (GenAI) era

 

The first two priorities align with TBR’s Voice of the Customer research, which shows that IT services and consulting buyers want to get more from their IT investments and expect new technologies, in particular GenAI, will be complementary, compatible and immediately additive in relation to existing technologies.

 

Overall, in TBR’s view, SoftwareOne has captured the current market vibe and positioned itself well to continue its transformation from a VAR, primarily involved in cloud and software resale, to a truly full-service IT company.

SoftwareOne: “We can predict when they are going to do what”

During the opening presentation, Duffy said that SoftwareOne understands when a client bought their various IT components, how much they paid, how happy they are with IT performance, and when their licenses are up for renewal. In short: “What do clients own and how do they build things?”

 

That insight, combined with SoftwareOne’s overall approach, allows the company to look at the market through a “customer’s lens” and not through SoftwareOne’s own delineations of its offerings. In TBR’s view, this distinction — which starts with a recognition of how customers think — often becomes clouded by organizational constraints and sales demands within many IT services companies and consultancies. Starting with the client’s business challenges in mind is relatively easy; gaining intimate knowledge of their IT environment and spend is not.

 

Schlotter, in his presentation, noted that SoftwareOne can “predict when [clients] are going to do what,” because the company has tracked patterns — including software renewals, adoptions, and wholesale changes — across its vast client base. Thomson deepened that point by saying that for SoftwareOne, “IT portfolio management is our value proposition.” Importantly, SoftwareOne sees self-funding innovation as the flywheel that takes the company’s understanding of a customer’s IT environment, including opportunities to optimize that environment, and turns it into new value.

 

Through initial software cost takeout, ongoing IT asset management (ITAM) services and a focus on licensing expenses, SoftwareOne helps CIOs free up capital to reinvest in technology modernization. As Thomson noted, “Licensing costs were last year’s problem,” so SoftwareOne leads with the value that will come through enhanced technology but always makes explicit that funding will come through savings around licensing. In TBR’s view, this is SoftwareOne’s defining strategic advantage. Full stop.

 

One last point on SoftwareOne’s thinking about the market and the company’s place in it: During her breakout presentation, Burke emphasized the continuing need to recognize regional differences at client facilities and managing, selling and delivering to all clients in a local manner. The technology, by its own nature, may be region-agnostic, but clients are, by their own nature, local. SoftwareOne, therefore, embraces a be-local, stay-local culture. One can see the echo of intimate knowledge of a client’s IT environment in being enmeshed in a local environment.

Sustained growth is an alliance play

Berry, a recent addition to SoftwareOne, explained the company’s new approach to running partnerships “like a business.” While potentially overly transactional, Berry framed SoftwareOne’s approach as being “proactive with a set of prioritized [strategic partners]” whereby SoftwareOne would invest in joint solutions and joint go-to-market support, while “continuing to support clients gaining access to many software vendors.”

 

To evangelize within SoftwareOne, alliance partner managers would be the face of that partner while also externally educating the partner on SoftwareOne’s value proposition and capabilities. According to Berry, the alliance partner managers would maintain strategic relationships while also operating “as a business” and supporting and influencing sales efforts.

 

Recognizing that SoftwareOne’s client base differs from those of the giant IT services companies and global consultancies, Schlotter said that while the majority of customers have already made a commitment to one cloud or another, the corporate (not enterprise) market has less mature cloud environments and remains open to “re-migration” advice — i.e., move to another cloud — from SoftwareOne.

 

In TBR’s view, having the capability to serve those chance encounters with a willing cloud-hopper should not distract from the overwhelming reality that most corporate and enterprise clients have already made some kind of commitment to a cloud provider.

 

On specific alliances, Berry and Schlotter noted Microsoft’s importance to SoftwareOne’s revenues and long-term strategy, including the short-term opportunities around Copilot. In Schlotter’s view, “Copilot is a door-opener because now the CIO needs to talk to us.” From the hyperscalers’ perspective, according to Schlotter, among SoftwareOne’s values is the company’s ability to make hyperscalers’ value even “stickier” at a client.

 

In TBR’s view, no single nonfinancial metric has been more passionately sought by consultancies, IT services companies and hyperscalers than client retention.

 

During informal discussions and a breakout session with Grillet, two points struck TBR as particularly relevant to SoftwareOne’s partners in the SAP space. First, out of SoftwareOne’s 400 SAP specialists, only 32 reside in the Americas, providing an opening for SoftwareOne’s partners to bring opportunities and greater scale. Second, Grillet noted that around half of SoftwareOne’s new SAP leads come from the company’s own ITAM business, demonstrating — to SAP — a clear differentiation for SoftwareOne. One final note: TBR has reported previously on SoftwareOne’s SAP practice and continues to view the company’s strategy as exceptionally well-suited to SoftwareOne’s capabilities and market position.

Not every superhero wears a cape

TBR’s event perspectives typically include extensive recapping of companies’ client stories, product demonstrations and performance metrics, but we left those elements out of this report. During the event, SoftwareOne provided numerous client stories, extensive details about its capabilities and numbers to support its growth, but we wanted to emphasize that SoftwareOne represents a different kind of competitive threat and partnering opportunity, independent of the usual evaluation metrics. Intimate knowledge of a client’s IT environment, to include licensing challenges and opportunities as well as usage and costs, provides a superpower potentially significant to technology partners and threatening to competitors, especially as we move into a better analyzed and more transparent GenAI era. Forewarned is forearmed, as they say.