In a recent NelsonHall blog, we looked at the key themes and investments being made across digital workplace services. The overarching themes were employee experience, AI-enabled digital support services, sustainability, and digital re-skilling (read more here). For this blog, we spoke to NTT DATA’s digital workplace leadership team to understand its key focus and strategic roadmap investments over the next 12 months.

The new NTT DATA Group is a much-enlarged firm with ~$30bn in revenues and 195k employees. The group comprises NTT DATA Japan, with ~$12bn in revenues, and NTT DATA Inc., the $18bn international business with integrated application, infrastructure, and network capabilities (read more here).

NTT DATA’s digital workplace services innovation is focused on four key investment areas:

• Generative Workplace: utilizing GenAI to provide personalized digital support services
• Experiential Workplace: using XLAs to support total experience
• Sustainable Workplace: includes sustainable device as a service (SDaaS)
• Smart Workplace: facilitating productive and safe workplaces with IoT-based services.

Utilizing GenAI to provide personalized digital support services

NTT DATA is investing in GenAI across all its digital workplace towers, including employee experience enablement through conversational AI. This provides the ability to mimic agent behavior and translate language in real-time. IT Service Desk use cases include incident creation/resolution, approvals and updates, request fulfillment, knowledge management, ticket details and self-service, access management, and password reset. The agent can also deliver other self-service and administrative tasks across other industry use cases including retail, financial and banking (FSI), airline and travel and more. NTT DATA has a single delivery team for GenAI in its high-performance delivery centers and consulting & advisory services and sales at a local level through its Glocal model approach. Below are examples of deployments.

NTT DATA deployed a conversational AI chatbot in partnership with kore.ai for a multinational food processing company with 150k employees. It further integrated specific LLMs, resulting in ~40% call deflection.

NTT DATA is also engaged in multiple Microsoft Copilot workshops, providing advisory and consulting services, readiness and deployment, organizational change management (OCM), and Copilot extensibility. Typical engagements include Microsoft 365 Copilot calling and meetings workshop, Copilot proof of value with NTT DATA Cloud Voice (Modern Work and Copilot Engagement Program), and Copilot Studio/Sales workshop. NTT DATA also offers a 3-week Copilot advisory workshop to assess Copilot readiness across all workloads, discover use cases, and ensure data governance and implementation roadmap and Copilot for Azure PoCs.

For a Spanish telco with 15m customers, NTT DATA provided consulting and advisory services supporting a 300-license pilot for Microsoft 365 Copilot. This included training in the transversal use cases of M365 Copilot and additional use case identification, including document summarization and creation, agent assist, outage and remediation notification, knowledge management, etc. In the pilot, 76% of users saw increased productivity, and 70% had a positive experience. The client is now entering a second phase, extending the licenses to 1k. A key factor in the adoption was NTT DATA’s change management approach to drive mindset change and generate interest in the pilot groups.

NTT DATA will continue embedding GenAI across its digital workplace offerings, leveraging IP LLMs and AI-powered Copilot for engineers and use cases supporting client experience and expert advisory. Using smaller LLMs and proprietary data to solve vertical or business-specific problems will increase moving forward. NTT DATA’s investments in OCM and Microsoft Copilot consulting services are also key as organizations seek to drive AI technology adoption. In particular, organization change management (OCM) and AI with OCM will play a key role in helping clients adopt GenAI technologies by driving a greater focus on personalization to expedite adoption, and we expect to see POCs and pilots moving strongly into production over the next 12 months. There will also be more emphasis on proactive experience centers supported by SRE teams that look at every aspect of experience and monitor users in real time as they engage across services.

Utilizing XLAs to support total experience

NTT DATA has developed Experience-as-a-Service (EXPaaS) with the aim of providing its clients with a total experience using persona-aligned services and XLA delivery supported by its experience management office (XMO) and dedicated DEX squads.

EXPaaS for EX focuses on operational, people, and technology experiences and combines them with CX assurance, services management, and analytics to enable total experience. NTT DATA aims to identify issues that impact UX and respond quickly to prevent issues, using its DEM platform to increase observability and visibility. It collects multiple telemetry info from devices, apps, networks, etc., in real-time, which it runs through its XMO and digital analytics fabric to derive insights and improve EX.  

NTT DATA uses its 5A framework to implement EXPaaS and enable XLA standardization. It starts with the initial Ask phase to understand the key stakeholders, the environment, the client’s experience aspirations, and what part of the scope is influenced by NTT DATA, the clients, or its partners. The next phases are Analyzing, Assessing, Acting, and Attuning and providing continuous monitoring and improvement of experience indicators through its dedicated XMO.

For a global airline client, NTT DATA implemented EXPaaS with its 5A framework and persona-based XLA dashboards, measuring multiple metrics parallel to SLAs. It utilized its DEM platform, OCM, and modern device management to support 30k devices. The client achieved an improved overall EX score of 9.5/10, using XLA-delivery and persona alignment, and reduced ~35% of service desk contacts through proactive automation.

NTT DATA’s focus on EXPaaS to drive its XLA approach along with its dedicated XMO capability are key, and we expect the company to continue to ramp its SREs in support of its SRE/agile POD-led approach to bridge the gap between operations and deployment.

In addition, NTT DATA’s Workplace Orchestration platform delivers consolidated client experiences across the workplace. For example, its digital twin capability built on Power BI looks to expedite the employee onboarding process from 4 weeks to less than a week, with accelerated Day 1 onboarding being a major element in the overall employee experience.

Infusing ESG into its Digital Workplace Services offerings

NTT DATA focuses on persona-aligned VDIs, rightsizing devices based on personas, and increasing remote technical support with AR/VR and digital humans to reduce carbon footprint. This also includes accessible devices, kiosks, inclusive meeting rooms, and remote device wipe services. A key offering is Sustainable Device as a Service (SDaaS), available per device per month or per user per month, with devices and peripherals aligned to the employee persona.

NTT DATA deployed this capability for a global biotech company with 54k devices, identifying opportunities for remote support and field dispatch avoidance. It also provided smart refresh by persona supported by 1E and Nexthink on a needs-only basis through a phased approach. It provided automated provisioning through Autopilot and streamlined the catalog to ensure the correct configuration for the user, for example, moving them to a VDI platform if more suited to the persona. The client achieved an ~85% increase in device provisioning time.

Adoption of NTT DATA’s Sustainable Device as a Service (SDaaS) is likely to increase in importance in support of clients’ ESG and sustainability goals.

Another key capability includes eSIM, which integrates personal and corporate telephony on one device with a single number for Teams and mobile phones.

In partnership with HP, NTT DATA offers re-manufacturing and refurbished device allocation at the end of three years, providing users with the same out-of-the-box experience. This approach will resonate with clients as they seek to lower their carbon footprint and sustainably extend the device lifecycle.

NTT DATA also helps clients optimize office space and improve energy efficiency using Workplace Orchestration platform employee intranet.

Providing smart workplaces

NTT DATA provides managed private 5G, SD-WAN, SPEKTRA platform for networks, IoT, and edge computing, infusing this into digital workplace services to create a smart workplace. This also includes its Private 5G Device as a Service, with a fully configurable device selection aligned to the user’s persona and a choice of lease versus buy. Industry use case examples include manufacturing (industry 4.0 and autonomous factories), healthcare (providing clinicians with access to patient data on any device), and automotive (providing visibility of the global supply chain). NTT DATA will increasingly invest in further industry use cases in support of its P5G Device as a Service offering.  

For a global construction and utility client, NTT DATA utilized Workplace Orchestration platform, conversational AI, and employee intranet to develop a mobile app to streamline physical bookings, corporate service access, and communications for employees and external collaborators. It also enables the optimization and management of common spaces and occupancy visualization. The client achieved several outcomes, including increased energy efficiency, reduced environmental footprint, and improved worker productivity.   

Virtusa recently briefed NelsonHall about how it conducts GenAI testing. With the emergence of LLMs, Virtusa has seen a rising interest in understanding how to validate them. However, testing LLMs is not easy, as traditional testing approaches are not relevant to LLMs. It requires reinventing software testing and looking beyond the output of a transaction.

Non-Deterministic LLMs Challenge How Testing Is Conducted

Welcome to the world of leading-edge technology and complexity! LLM testing is not easy and differs from testing other AI models: LLMs are non-deterministic (i.e., for the same input, they may provide different responses); other AI models, such as ML, provide the same output for the same input.

The non-deterministic nature of LLMs raises several challenges for testing/QE. The broad principle of functional testing is to validate that a specific transaction on a web application or website provides the intended result, e.g., ordering a good on a website and validating that payment has been processed and completed. However, with GenAI, the output is dynamic and can only be broadly defined. For example, testing a generated response to a question, summary, or picture under a traditional approach is not working, as there is no right or wrong answer. Also, several answers can be correct.

As part of its efforts to deal with this complexity, Virtusa has organized its capabilities under the Helio Assure Framework, which covers LLM data, prompts, models, and output.

Data Complexity

Data validation is a starting point for any LLM project. Virtusa offers traditional data validation services, such as checks around data integrity, consistency, and schema/models.

Virtusa also conducts statistical assessments specific to data used for training AI models; for example:

• Data outliers, i.e., identifying data that deviates from the rest of the dataset
• Data skewness review, e.g., detecting a data distribution asymmetry. Several statistical models indeed require normally distributed data.

Beyond data and distribution validation, both well-understood activities, Virtusa emphasizes two approaches:

• Data bias detection
• Unstructured data validation (going through semantic search, grammatic search, and context evaluation).

Of these two, data bias detection is the most difficult, mainly because bias identification varies across cultures and contexts and is challenging to automate. Virtusa continues to work on data bias detection.

Prompt Validation

For prompt validation, Virtusa relies on several approaches, including bias checks, toxicity analysis (e.g., obscenity, threats), and conciseness assessments (e.g., redundant word identification, readability). Virtusa highlights that prompt templatization, through a shared repository of standard prompts, also mitigates security threats.

Virtusa also uses adversarial attacks to identify PII and security breaches. Adversarial attack is the equivalent of pen-testing in security, initially developed in ML. The approach is technical and rapidly evolving as LLM vendors finetune their LLMs to protect them from hackers. Nevertheless, it includes methods such as prompt injection and direct attacks/jailbreaks.

LLM Accuracy Evaluation

For evaluating AI models such as LLMs, which is particularly challenging, Virtusa relies on a model accuracy benchmarking approach, creating first a baseline model. The baseline is an LLM whose training is augmented by a vector database/RAG approach relying on 100% reliable data (‘ground truth data’). It will evaluate the accuracy of LLMs vs. this baseline model.

The Roadmap is Creative Content Validation and LLMOps

Virtusa has worked on GenAI creative output/content validation, looking at three elements: content toxicity, its flow (e.g., readability, complexity, and legibility), and IP infringement (e.g., plagiarism or trademark infringement). Virtusa uses computer vision to identify content patterns present in an image or a video, classifying them into themes (clarity and coherence vs. the intent, blur detection, and sometimes assessing the relevancy of the images/video vs. its objectives. We think the relevancy of this offering for social media, education, marketing, and content moderation is enormous.

We think that GenAI is the next cloud computing and will have significant adoption: enterprises are still enthusiastic about what GenAI can bring, though recognizing they need to pay much closer attention to costs, IP violation, data bias, and toxicity. Governance and FinOps, to keep cost and usage under control, are becoming increasing priorities. GenAI vendors and other stakeholders are eager to move from T&M to a usage-based consumption model and want to monetize their investments.

NelsonHall recently attended T-Systems’ Digital X 24 event in Cologne, the flagship event of its parent company, Deutsche Telekom. T-Systems provided an overview of its key portfolio focus areas across the cloud, including sovereignty, digital solutions, AI, including GenAI, and its array of strategic ecosystem partners.

T-Systems' headcount is ~26k, with Q2 2024 revenues up 2.3% y/y at €981m. Key target industries include automotive, manufacturing, public sector, health, public transport, retail and logistics, and financial services. T-Systems’ business units are comprised of advisory (Detecon), digital solutions, cloud services, and security in support of planning, building, and running.  It supports ~1k clients across these industries with major strategic delivery hubs in Germany, Spain, Hungary, Slovakia, and India.  It also has local business units across multiple countries, including North America, Mexico, Brazil, and the Nordics. T-Systems also has eight SOCs globally defending against 36m attacks per day.

While discretionary spending has been impacted across Europe, the cloud is still viewed as a critical enabler for digital transformation, and we expect budgets to improve further between Q4 2024 and Q1 2025.

In this blog, we look at some of the key focus areas and investments for T-Systems across cloud, AI, and workplace services, including:

• Cloud and mainframe transformation services
• Enhancing Sovereign Cloud capabilities
• Digital solutions, including AI and GenAI.

Supporting clients’ cloud transformation initiatives

T-Systems utilizes its Detecon consulting capability as the tip of the spear to engage clients in design thinking consulting-led engagements to understand client cloud maturity and business requirements.  It provides a Cloud Readiness Assessment, which runs alongside assessing the client’s business challenges and goals. It then provides a proposed application-led transformation solution outlining the target systems within a multi-cloud environment; and then supports migration through its Cloud Professional Services unit, enabling the client to leverage the potential of various cloud providers.  

This includes not just lifting and shifting but enabling applications to run in containers, making them scalable, and covering the entire 7R (e.g., rearchitecting, refactoring, etc.), enabling clients to take full advantage of the cloud. T-Systems also focuses on FinOps, full-stack monitoring and observability, and DevSecOps. This approach will resonate with clients as they increasingly seek to reduce the complexity of their hybrid multi-cloud environments, reduce costs in response to current macroeconomic conditions, and drive better predictability through full-stack monitoring. 

T-Systems provides a holistic portfolio of multi-cloud services with horizontal-based offerings, making these modular to combine industrial services for the vertical-specific needs of clients through its application-centric, ecosystem-driven, and multi-cloud platform approach, including security and sustainability. T-Systems’ key private cloud offering (with VMware) enables clients to bring IT systems together on one platform.  Its managed private cloud bridges the gap between legacy and on-premises systems and public and private clouds. Its future cloud infrastructure is offered in an as-a-service model, providing a highly secure private cloud environment with the look and feel of the public cloud. Clients can use it as a hybrid cloud in their own or in T-Systems’ twin-core data centers.

T-Systems offers managed services in support of AWS, Azure, and Google Cloud. As part of managed services, it integrates into the client’s DevOps, for example, taking part in daily sprints to understand the client’s environment and quickly fix potential issues through an SRE-led approach to cloud operations. We expect this approach will resonate with clients as they increasingly seek to improve the predictability in their IT environments through a co-innovation and co-collaboration approach with vendors.

T-Systems’ zFuture offering also supports clients who need to maintain and modernize their mainframes with next-generation IT infrastructure, hardware, and platform optimization. It provides consulting and advisory services through a mainframe migration to public, private, or hybrid cloud environments. T-Systems also uses GenAI, including automated code generation and translation with GitHub Copilot, with translation from COBOL to Java to modernize the application. It further utilizes GenAI tools to understand source code in legacy mainframe environments. This approach enables clients to expedite legacy transformation and improve the overall developer experience through GenAI tools.

Aiming to become DACH region’s #1 sovereign cloud leader

T-Systems Sovereign Cloud powered by Google Cloud, provides full compliance with German regulators while retaining the public cloud functionality of a hyperscaler. It also offers T-Systems’ Open Telekom Cloud, which is based on OpenStack as a plug-and-play solution offering private cloud security and providing IaaS from the public cloud with two dedicated data centers in Germany and one in the Netherlands. T-Systems is also developing capability with AWS when AWS’ European Sovereign Cloud is launched in Germany in 2025. Also, through open-source collaboration services, it enables GDPR compliance in a Microsoft public cloud through its Cloud Privacy Service and offers managed security for a fixed monthly fee.  

We expect further traction across Sovereign Cloud as clients increasingly focus on regulatory compliance, especially from clients across the DACH and Europe region. In addition, we expect to see more leverage of this capability across digital workplace services for clients operating in highly regulated environments.

Increasing emphasis on AI within its digital solutions unit

T-Systems’ digital solutions unit drives multiple AI, GenAI capabilities, and POCs across the organization. This includes conversational AI and virtual avatars with numerous industry use cases across public, utilities, HR/IT, health, and financial services. Example use cases include information system municipalities, utility appointments, HR bot, pharma information, and the ability to take out simple insurance. It aims to improve the employee experience with agent assist and CX through ease of engagement. It also has multiple GenAI POCs running with AWS across its primary industries, including predictive maintenance in manufacturing, passenger tracking in public transport, and fraud detection for telcos.  

Across AI, client outcomes include creating an automated quality assurance process for a German automotive client using AI to enable zero outages and significantly reduce errors. Another example is a faster MTTR through AIOps, which resulted in a 15-20% cut in operational costs. We expect T-Systems to continue to ramp its capabilities across AI and GenAI and in supporting skillsets, where it currently has ~1.6k dedicated AI specialists and IT architects, 700 scrum masters, and 300 agile coaches.

Outlook

We expect T-Systems to continue to expand its AI capabilities, including GenAI, and across Agentic AI, and build up its LLM hub across Open Telekom Cloud through the OpenStack approach. In addition, LLM capabilities will be increased across key hyperscalers, such as AWS, Azure, and Google. It will also need to focus on OCM to drive the adoption of GenAI, including greater use of AI in OCM to drive personalization.  

It has an opportunity to leverage its mainframe experience and use of AI to drive legacy modernization for clients and support hybrid multi-cloud initiatives. Its focus on FinOps and full-stack monitoring and observability, DevSecOps, and its ability to tailor cloud services aligns with client needs. We anticipate T-Systems will expand its cloud privacy and sovereignty services across BFSI, the public sector (including education), and midsize enterprises.

In support of digital workplace services, we expect to see more expansion of its Microsoft 365 CoE capabilities and the provision of an SRE-led approach across workplace and cloud operations. In addition, its commitment to 100% full circularity for technology and devices by 2030 will align with client strategies as clients seek to expand their Evergreen services and meet ESG agendas.

T-Systems’ strategic partner ecosystem approach will resonate with clients as they increasingly seek to leverage their existing tooling investments, as will its vertical cloud capability to drive specific business outcomes. Finally, we expect T-Systems to increase its focus on AI specialists, platform SMEs, and business-value leads and build SRE CoEs supporting delivery locations.

NelsonHall recently attended Dreamforce, the annual Salesforce flagship event in San Francisco. Billed as the largest AI conference in the world, Dreamforce 2024 saw a marketing push like none other, even by Salesforce’s standards, towards Agentforce, its new platform for creating autonomous AI agents capable of analyzing data, making decisions, and taking action. Agents built on the Agentforce platform can, for example, be deployed to answer customer service inquiries, qualify sales leads, and optimize marketing campaigns.

From the keynote, speaking sessions, and our conversations with Salesforce experts, it was evident that Salesforce’s future is now spelled completely as Agentforce. So much so that the rare moments when Agentforce was not mentioned were when Mark Benioff took swipes at competitors and what he calls the DIY culture, where enterprises try to do AI on their own.

What is Agentforce and why Salesforce claims it is different

The difference between Agentforce agents and AI copilots, according to Salesforce, is the ability to go beyond generating content to act autonomously without the need for human supervision. For example, when most of today’s virtual assistants get a query, they scrounge through a data set and throw up a response in the form of a link or a next step to do. But an agent, according to Salesforce, will initiate a purchase instead of merely suggesting the ways to make a purchase.

This capability is enabled by Salesforce agents from Agentforce and custom-made agents that enterprises will be able to put together using the Agent Builder, a low-code tool available in the upcoming Agentforce October release. These agents are powered by the new Atlas reasoning engine, which, according to Salesforce, improves itself based on the outcomes from previous interactions and not necessarily human feedback. Salesforce pitches itself as having a unique advantage over open-source models, claiming a comprehensive customer view from its multiple clouds, and better data quality orchestrated through its Data cloud. This, according to Salesforce, results in fewer hallucinations.

Salesforce service providers respond

NelsonHall spoke with more than 15 service partners at the event. The general tone was one of guarded optimism. Most agree with the perception that Salesforce had catching up to do in the AI race but that now, true to style, Salesforce has pitched itself right into the centre of the AI world. Clients are impressed with early Agentforce examples like OpenTable, Wiley, Bombardier, Wyndham and Saks Avenue, where agents are used to offer customized service to a customer, suggesting and executing a purchase and any subsequent return or re-delivery without human intervention. The initial hesitancy expressed by clients is to be expected for a release of this scale and significance, given that clients continue to grapple with the perennial issue of tech debt and messy subscriptions to SaaS platforms. However, what Benioff and his execs did well was build a compelling case for Agentforce and showcase possibilities across industries which will play out positively as adoption grows in a few months from now.   

Vendors are keen to get their hands on the upcoming release while awaiting an improved understanding of the commercial promise of $2 per transaction. The next six to twelve months will see a flurry of building agents across horizontals and industries. Initial adoption is likely to be faster in industries like retail that deal with seasonal surges, and for use cases involving personalized customer service.

The agent lined road ahead

Salesforce states that Agentforce represents the third wave of AI, the first being the predictive wave back in 2016 with Einstein, and the second wave involving co-pilots. The fact that Salesforce claims to have rearchitected the entire Salesforce product portfolio, including applications like Tableau and Slack, is a strong indicator of intent and future direction.

Salesforce is not alone in the agent gold rush, even if it sits atop by the sheer scale of its ambition. Oracle has spoken about having ~50 agents inside its Fusion applications by next year, and ServiceNow before Dreamforce announced use cases for agents across ITSM and customer service. With others also moving in this direction, Agentic AI is set to become more mainstream and build on the success of GenAI.

At the Cognizant UK & Ireland analyst and adviser meet in London this week we were keen to get a closer understanding of three things:

1. How some of the changes introduced since the arrival of Ravi Kumar S as CEO are making a difference to the company
2. The factors underpinning this year’s revenue underperformance of Cognizant in the UK and Ireland, also any new go to market priorities for the region
3. Cognizant’s plans for leveraging the newly acquired Belcan.

Our takeaways in all three areas were encouraging and we came away with a positive outlook both for Cognizant in UK and Ireland and for its expanded ER&D business.

Cognizant in September 2024: refreshed management, more energized workforce, radically improved CSAT

Firstly, anyone who follows Cognizant will be aware that since his arrival in January 2023, Ravi Kumar S has brought in a wealth of new senior talent (including at the very top CFO Jatin Dalal, ex Wipro, and EVP and Global Head of Operations Rajesh Varrier, ex Infosys).

To give a few more examples:

• In terms of sector heads there are two new SVPs formerly at Infosys, Anurag Vardhan Sinha (Comms, Media & Tech) and Nageswar Cherukupalli, (Financial Services and Insurance). Also fresh from Infosys is Shweta Arora, now SVP, Global Head of Consulting
• Wipro, in addition to Jatin Dalal, has also lost Mohd Haque, now Cognizant’s Chief Commercial Officer, Americas. He also brings in extensive sector domain expertise and networks, this time in healthcare, a key sector for Cognizant.

It is almost customary for a new CEO to bring in execs that they have worked with or alongside before, particularly when joining a company that has faced well publicized challenges – this is not remarkable. But changing faces does not always work its magic. At Cognizant, there is a palpable sense of revived energy and of clarity about corporate strategic priorities.

One of Ravi Kumar’s stated priorities is for Cognizant to be “an employer of choice”: this does not sound particularly ambitious, but it does hint at challenges the company was facing, including around attrition, recruitment, employee morale, and also performance. Attrition has fallen at Cognizant – but so has it for its peers: this reflects the current labor market. One initiative launched last year, the “Blue bolt” internal grassroots “idea incubator” is likely to be having a positive impact on both employee involvement by delivery personnel and also client perceptions of Cognizant, thus a contributory factor to company achieving its highest ever Net Promoter Score, after a less successful period. We gather that NPS has increased in the last 2 years from 46 to 60, a huge improvement.

Increasing focus on Industry Solutions

Cognizant formerly had four “integrated” horizontal practices (Core Technologies and Insights, Enterprise Platform Services, Intuitive Operations & Automation, Software & Platform Engineering). In 2023, Cognizant set up its Industry Solutions Group as part of the company’s strategy to build further differentiation at the industry level. The ISG is essentially a sub-unit (led by EVP of Intuitive Operations & Automation) that houses industry technologists and specialists in vertical micro-segments with the remit to work with external partners in developing industry-specific products and services: an early example is Telco Assurance 360, built on ServiceNow.

Cognizant UK & Ireland: looking to new offerings in key sectors

After three years of decent growth (3-year CAGR of 12.2%, thanks primarily to the strong U.K. public sector), Cognizant UK&I has had a disappointing year so far in 2024, at least in terms of revenue performance. H1 revenues of $900m were down 5.4%, around 6.4% in CC). An 11.4% decline in the financial services sector (last year accounted for a third of UK&I revenues) accounts for most of the region’s underperformance: this can be attributed to falling discretionary spending, Cognizant having lost out on vendor consolidation at a major U.K. bank.

For some vendors, the U.K. continues to be a growth region in 2024 (we note TCS, 6.0% growth in its last quarter, Sopra Steria, 5.3% in H1 2004). Those vendors have invested heavily in the region and have some well-established and very large outsourcing arrangements. Although Cognizant has made a number of tuck-in acquisitions in recent years in the region (and Belcan has also brought in U.K. capabilities), we would argue that it has not done this: UK&I represents just 9% of global revenue (in comparison, the region accounts for around 17% of the global revenues for TCS and Sopra Steria) and most activity remains dependent on discretionary spend; Cognizant is not protected by sizeable outsourcing deals.

So, what are Cognizant’s priorities for UK&I? Nearly two years ago, we noted the following:

• Continued focus on the U.K. public sector (central government, defense, and health)
• Reigniting the BFS sector across banking, targeting large deals and security and market infrastructures, also government regulators, and fintech
• Scaling up consulting sub-vertical expertise.

This broadly remains the case today. The sectorial priorities are still BFSI (specific areas of banking, also of insurance), public sector (back-office operations), also Comms Media & Tech (e.g., field operations, order processing, digital content marketing). We note a stronger focus now on outsourcing opportunities, including areas of BPS. Cognizant does not have a significant presence in the U.K. for BPS and thus will be positioning as a challenger. There are some obvious areas of both public and private sector BPS which present potential opportunities for Cognizant in which to look to compete.

Belcan – third acquisition in ER&D means end-to-end ER&D service capabilities

Cognizant has been investing since 2001 in boosting its ER&D capabilities. That of Belcan, recently completed, follows the company’s earlier acquisitions of:

• Mobica (March 2023), an IoT software engineering services provider headquartered in Manchester. Mobica brought in nearly 900 employees across Europe and the U.S., including around 550 in Poland, a significant expansion of Cognizant’s nearshore delivery capabilities in Eastern Europe (where we felt it had lagged its peers)
• ESG Mobility (June 2021), a Munich-based engineering R&D provider for connected, autonomous and electric vehicles, brought in around 1,000 employees, in Germany, U.S., and China.

In total, we estimate Cognizant has invested $1.75bn in these three acquisitions, including $1.29bn for Belcan (the company’s largest acquisition since that of Trizetto). The rationale for beefing up ER&D capabilities is clear; our interest is how Cognizant intends to leverage Belcan (which is slightly margin dilutive, we note also it counts Boeing as a major client, although its overall revenues are growing).

Belcan has around 6,500 employees globally and gets around 85% of its revenues from the U.S. Its revenue mix is approximately 45% product engineering, 34% systems & software (model-based engineering, embedded software), 21% manufacturing and supply chain. A blend that dovetails nicely with those of Mobica and ESG Mobility: in terms of its portfolio, Cognizant can now claim to having end-to-end capabilities and scale (around 10,000 employees) in ER&D. An immediate priority will be integrating the three companies, presumably under the Belcan brand.

Belcan brings to Cognizant a presence in the aerospace sector: as well as there being continuing high demand for engineering talent in this sector, there are opportunities to bring in IT services capabilities from Cognizant to clients such as Airbus. Belcan also has some activity in the defense sector: we would not be surprised to see Cognizant look to leverage this to set up a federal sector business in the U.S. We see also potential opportunities for Cognizant to introduce Belcan to some of its automotive sector clients in Europe.

Renewed sense of confidence

It is less than 21 months since Ravi Kumar started as CEO. This blog does not aim to be comprehensive: it does not, for example, look at progress in major initiatives such as the corporate push to land large outsourcing deals (where the company has seen success in North America) but we note a renewed sense of confidence at Cognizant and in the UK&I market and we look to see some new developments over the next year or so.

(see also Cognizant Aims for Major Uplift in Bluebolt Grassroots Innovation Program in 2024 - NelsonHall (nelson-hall.com)

Hitachi Digital Services recently held an Advisor & Analyst event in London. The company is rolling out its communication plan to increase client and industry awareness. It goes to market, selectively, with the larger Hitachi Group in the U.S. and U.K., targeting a few industries.

So, who is Hitachi Digital Services? The mid-sized IT and ER&D services vendor spearheads Hitachi Digital’s international business with a NelsonHall estimated headcount of around 6,000. Its sister companies include GlobalLogic (product engineering services) and Hitachi Vantara (enterprise storage). In Japan, Hitachi Digital has DSS, a significant business, with ¥ 2.6bn (USD $19bn) in revenues (we assume this includes some hardware and software).

Hitachi: an ERP Background

The company’s sectoral background, reflecting its Hitachi Group ownership, is asset-intensive industries, with offerings ranging from enterprise application services and software development to data, analytics, AI/GenAI, and ER&D services. It tends to target the mid-market. i.e., companies with revenues of $2bn to $3bn, though it also has some large enterprise clients, such as the North American operations of a tier-one Japanese automotive OEM.

Hitachi Digital Services’ initial core offering was ERP services (Oracle and SAP), adding Salesforce, ServiceNow, and Workday to its portfolio over time. We estimate enterprise application services today account for around one-third of its global revenues.

The company’s Hitachi Group heritage is also shown in its ER&D services activities, spanning product engineering services (e.g., embedded software, command & control systems) and Industry 4.0/IoT. Hitachi Digital Services takes a Hitachi Group-wide approach to Industry 4.0 (‘Industrial IoT’), with Hitachi Group providing industrial automation and manufacturing software (e.g., a Flexware MES product popular among Japanese automotive OEMs). The company has a Factory Lighthouse with a greenfield factory set for Hitachi Rail in Maryland. With Hitachi Group having ~800 manufacturing plants, HDS’ potential activity in this area is immense.

Expansion to Software Development, Data & AI, BFSI

Outside those two offerings, Hitachi Digital Services is also active in software development (‘Cloud ’Engineering’), data & analytics, and application maintenance & support (Managed Services). The company emphasizes its Hitachi Application Reliability Center (HARC) methodology, which it has deployed in three delivery centers (Hyderabad, Dallas, and Tokyo). HARC provides best practices across processes, people, and tools and promotes a combined software development and support team approach. HDS highlighted several times the importance of SRE and FinOps in its HARC methodology.

Hitachi Digital Services has expanded from Hitachi’s asset-intensive industries to asset-light sectors such as BFSI, where the company has several specialized niches, helping, for instance, a closed books reinsurer deploy data processing and analytics. The client wanted to formalize its expertise to help it scale the business through M&As but is impacted by having its business logic and expertise residing in Excel spreadsheets and the heads of employees.

As you would expect, Hitachi Digital Services is investing in GenAI, which is part of Hitachi Group’s investments there. Internally, the company has deployed several GenAI use cases, e.g., converting Fortran code to Python, taking a reverse engineering approach. Externally, Hitachi Digital Services focuses on sector-specific GenAI use cases, such as generating user manuals for automotive OEMs and designing predictive models (based on a combination of ML and LLMs).

Another offering that Hitachi Digital Services promotes is sustainability around carbon emissions and the circular economy (the three Rs of the lifecycle: reuse, refurbish/repurpose, recycle). HDS has consulting capabilities (with an expertise center in Lisbon) and several IPs. The IPs go beyond carbon emissions accountability and include identifying the scope three emissions of a supplier or a product. HDS highlights that depending on the vertical, clients have different sustainability needs. Manufacturing is about the supply chain and product traceability. Financial services, telecom, and data center/colocation vendors focus on data center emissions. The hospitality, retail, and real estate industries favor building energy management.

The Priority Is Client Recognition in U.S. and U.K.

A primary objective of Hitachi Digital Services is to expand its client recognition in the U.S. and U.K., its two largest markets. The company believes it can continue its current momentum (double-digit revenue growth in a slowing market) by rolling out its capabilities with existing clients in its core markets, keeping its vertical and service portfolio approach. HDS favors the creation of technical accelerators and, selectively, software products (e.g., sustainability). GenAI continues to be a priority.

NelsonHall expects further collaboration with the larger Hitachi Group, primarily for GTM. Accelerators and products are also an essential element of Hitachi Digital Services’ growth strategy, with the larger Hitachi Group spending ~$5bn annually on R&D, of which Hitachi Digital Services is a ‘significant recipient. Expect the company to do more of the same to accelerate its growth with Hitachi Group funding innovation.

Tech Mahindra (TechM) recently briefed NelsonHall on TechM AppGinieZ, its GenAI solution for software engineering and SDLC.

Recent times have seen all major IT services providers release GenAI-powered solutions, targeting two broad scenarios: those that help developers build, test, and support applications more efficiently and those that enable capabilities like virtual assistants to help clients improve or even transform business processes.

Identifying GenAI opportunities internally

TechM’s AppGinieZ GenAI solution falls into the first category. AppGinieZ assists TechM’s teams in application services, including development, QE/testing, and support. AppGinieZ and other investments in AI/GenAI are a part of TechM’s strategic initiative, ‘Scale at Speed,’ where TechM promises clients accelerated delivery. This gives AppGinieZ senior management’s sponsorship and investment focus.

For now, TechM has taken a measured approach with AppGinieZ. It has been built by TechM’s ADMSNXT COE (application development and maintenance services), focusing first on the SDLC stages that provide opportunities for automation and then expanding into other use cases depending on client interest and GenAI’s evolving capabilities.   

Broadly, TechM AppGinieZ has two sets of capabilities.

• GenAI: generates text and code from different inputs like text, code, image, etc.
• Predictive AI: analyses data to perform activities like defect triage, risk-based testing, and log analysis.

TechM AppGinieZ supports the following use cases in the software development lifecycle, with code snippet generation, log analysis, and unit test generation seeing higher adoption.

• Requirements refinement: generates or refines stories based on requirements artifacts, simple text
• Code snippets: generates code snippets from text and image prompts
• Code documentation and commenting: generates comments for multiple languages and synopsis of the code functionality in text
• Unit tests: generates unit tests for the input code
• Log analysis: reviews logs and generates reports in multiple formats
• Code conversion: converts code from one language to another, like Java to Python
• YAML: generates YAML code for automation tools like Ansible.

To date, TechM has trained around 25,000 employees in AI pair programming. It claims that in some DevOps implementations using TechM AppGinieZ there was a 25% effort saving. NelsonHall believes the effort and cost savings will be more determinable and subject to further improvement once working with GenAI becomes institutionalized. Initial engagements also require more effort towards training, familiarisation, oversight, and human-led reviews, which, with time, will get faster for all vendors with a GenAI play.

Client case study

TechM highlights a North American client success story. Taking the traditional Three Amigo concept of business, development, and testing perspectives in Agile development further, TechM added AppGinieZ as a GenAI assistant, which it claims helped delivery teams perform story reviews and rewrites faster and efficiently generate test cases from refined stories. Encouraged by the engagement's success, the client and TechM have jointly filed for a patent for the solution.

QE/testing activities have been early adopters across the STLC lifecycle in implementing automation and AI, and now GenAI. TechM AppGinieZ is used in QE across: 

• Test strategy creation: converts requirement documents/user stories to a test strategy
• User story refinement: takes rough user stories from Jira and other sources and generates detailed user stories
• Test automation: generates test scripts from test cases
• Test data generation: generates synthetic test data in multiple formats
• Test case generation: generates scenarios and test cases based on inputs like requirement documents/user stories and images.

Test cases and script generation are currently the most popular QE use cases. In early deployments, TechM claims savings of 20-30% in the end-to-end test life cycle when using AppGinieZ. 

Overall, TechM feels that AppGinieZ and AI-driven development will have a positive and meaningful impact on margins in the future.

The road ahead

TechM showed us a demo of TechM AppGinieZ in action across QE and ADMS use cases. Based on the scenario, it can be connected to LLMs such as Gemini, OpenAI, Llama, and others. Its ability to be integrated with an increasing number of tools gives it flexibility and more acceptance into existing client landscapes.

Constant oversight and reviews are necessary when using GenAI, as the output can only be as good as the data quality and LLMs involved. This necessitates the infusion of client-specific rules to create a contextual layer to improve the accuracy of the response generated.

NelsonHall believes that the TechM AppGinieZ roadmap is pragmatic and will see the addition of more predictive AI, compatibility with more LLMs, and increased granularity of use cases across the SDLC.

We recently talked with TCS about its ERP on Cloud offering. The SAP ecosystem has been going through intense change, with the planned end of SAP ECC support from December 31, 2027, and transformation with S/4HANA and recent Clean Core SAP initiatives. The change is driving accelerated ERP adoption, as demonstrated by SAP’s increasing revenue growth driven by SaaS applications. To accommodate this increased pace of change, TCS recently amended its ERP on Cloud offering.

TCS has positioned ERP on Cloud at the intersection of SAP cloud infrastructure and application services with bundled services. The offering is firmly focused on the cloud infrastructure with, for instance, migration of SAP ECC to the cloud targeting hosting modernization. ERP on Cloud also comprises the provisioning of development and test environments, as well as monitoring. It also bridges with application services and S/4HANA systems integration/transformation services. While the focus is on SAP opportunities, TCS also offers related services for other ERP and custom application production environments.

TCS’ ERP on Cloud offering is part of TCS’ Products and Platforms. While TCS’ IP investment is known for its software product portfolio, it also hosts offerings such as ERP on Cloud, i.e., bundled application and cloud infrastructure services, targeting large enterprises and the mid-market.

TCS’ immediate priority for ERP on Cloud is to scale the offering. The growth opportunity is significant, fueled by the end of ECC support and the S/4HANA transformation. The growth is also necessary to help TCS continue bringing automation across its various ERP on Cloud offerings and lowering costs.

Four Specialized Offerings

TCS’s flagship offering is around SAP migration to the cloud. With this offering, the company offers a lift-and-shift migration. The offering is technical, targeting the migration of databases and OS. Common client scenarios for this offering include organizations facing middleware that is no longer supported by their respective ISVs. The company highlights the IP’s scalability and that it can accommodate any middleware. TCS provides the necessary middleware refresh, minimizing client investment while benefiting from cloud hosting and hyperscaler innovation.

TCS started its ERP on Cloud journey with environment provisioning, whether for SAP PoCs, development and testing, specific usages such as document archival, or even large production environments. TCS has worked on accelerating instances deployment on the cloud and has pre-installed cloud templates to provision SAP Basis. With the rise of FinOps, TCS promotes a right-sizing approach to control spending while reaping the benefits of public cloud.

Complementing its lift-and-shift migration to the cloud offering, TCS offers greenfield S/4HANA transformation. The company provides pre-configured templates with ~120 standard processes to accelerate the deployment. Most processes support back-office functions (e.g., order to cash, procure to pay). They also address several industry-specific templates for processes in discrete manufacturing sectors (e.g., plan to produce, quality management, maintenance management). TCS has also localized these templates for several countries, including U.S., U.K., India, UAE, China, and Indonesia. TCS estimates that this offering helps to reduce implementation, targeting 16 weeks of deployment time. For this offering, TCS is an SAP-Qualified Partner-Packaged Solutions, targeting the mid-market with its pre-configured templates.

TCS also provides SAP environment monitoring and management. The company has its TCS Enterprise Manager IP for multi-cloud application and cloud infrastructure monitoring, also integrating with ITSM tools (e.g., ServiceNow). TCS is investing significantly in automation with AI, deploying SAP updates automatically, and conducting production data and ITSM pattern analysis. TCS Enterprise Manager is ERP on Cloud’s fastest-growing offering. Client demand is SAP-centric, but expanding to other ERP platforms and custom applications, filling an application monitoring market gap.

The Road Ahead

Naturally, TCS is looking for additional productivity gains and automation to reduce costs further; accordingly, it is investing in automation and has grouped its IP and automation efforts under the ERP Enablers category. An example of a recent investment includes a library of IaC configuration files to provision cloud instances. Another example is a data migration and source and target validation tool dealing with a heterogeneous set of now unsupported databases.

Geographic expansion is also a priority. The current SAP momentum should help. Organizations are accelerating their transition, whether lift-and-shift or transformation. They require a standard and industrialized service to mitigate risk in the context of tight budgets. TCS’ emphasis on innovation and service repeatability should help.

NelsonHall recently completed an in-depth analysis of advanced digital workplace services, in which we spoke to multiple leading IT services vendors and their clients. This blog looks at some of the key themes from this research, the investments vendors need to make to meet client demand, and how the market will evolve over the next 12-18 months.

The four overarching themes from this study were:

• Applying a human-centric approach with employee experience at the center
• Enhancing digital support through AI
• Increasing focus on sustainability
• Ramping digital re-skilling and up-skilling.

Employee experience at the center

Clients continue to utilize digital workplace services as an enabler for hybrid workplace transformation and to improve the overall employee experience. There is a greater focus on hyper-personalization through a consulting-led approach. This includes the implementation of DEX and DEM platforms to measure the experience by persona, including device and sentiment analysis. There is also more commitment to total experience (TX), a combination of employee and customer experience. Over the next 12 months, the focus on proactive experience centers will increase, supported by SRE teams looking at every aspect of experience and real-time monitoring of users as they engage across services.

We expect to see a greater focus on experience performance indicators (XPIs) supporting XLAs to measure experience outcomes. Vendor examples include:

• DXC Technology provides managed service experience and deploys XPIs in client engagements. Through its Experience Cube, DXC mixes experience, technology, and operational data, feeding this into reporting and analytics to understand perception and sentiment
• Compucom is also evolving XPIs into XLAs, working jointly with clients on business outcomes
• Infosys has developed a Key Experience Indicator (KEI) framework to help clients define XLAs through a five-step process over 15 weeks
• Unisys has also developed an experience governance board (XGB) with clients to manage the lifecycle of XLAs and, as the XLAs plateau over time, uses the XGB to focus on the next XLAs in line with business imperatives.

Enhancing digital support services through AI

The most significant impact on digital workplace services in the next 12 months will be AI and predominantly GenAI. Vendors are running multiple POCs with clients across Copilot for Microsoft 365 to augment service desk agent capability, create knowledge base articles, and identify gaps in KB articles. It also enables agents to focus on experience as opposed to tasks; in addition, providing expert connect capabilities in the field for problem management with AI-enabled root cause analysis and assisted insights with GenAI responses.

Examples include:

• Cognizant recently purchased 25k M365 Copilot seats for its employees with plans to deploy it to 1m users within their global 2000 clients across 11 industries
• TCS has launched TCS WisdomNext, a platform that integrates multiple GenAI services into a single interface to expedite adoption at scale
• Kyndryl recently partnered with NVIDIA on GenAI, integrating NVIDIA with its Kyndry Bridge platform to enhance AI and automation capabilities in support of digital workplace services.

We expect vendors to utilize smaller LLMs, using proprietary data to solve vertical or industry-specific problems. Vendors need to focus on organization change management (OCM), which will play a key role in driving the adoption of GenAI technologies and using AI with OCM to drive a greater focus on persona preferences. There will be a greater focus on AIOps and ML for intelligent event management and trigger automation to auto-remediate and fix issues and drive real-time insights and recommendations across the workplace.

Supporting clients’ ESG and sustainability goals

Vendors are deploying IP and third-party tools to support clients’ ESG and sustainability strategies through Evergreen devices and PCs as a service. ESG management and reporting with analysis through hyperscalers (e.g., ServiceNow) providing custom ESG analytics and dashboards. Vendor examples include:

• Infosys, which provides infrastructure in carbon-neutral regions, services, and resources with a low carbon footprint
• NTT DATA also offers open API integration into cloud carbon footprint data from hyperscalers
• TCS takes a two-pillar approach to sustainability, including Greening of IT (reducing IT's carbon emission and footprint across infra, platform, data, and apps) and Greening by IT (solutions to decrease emissions and resource consumption while allowing for growth)
• Atos is also contracting on decarbonization-level agreements.

Over the next 12-18 months, vendors need to increase the use of green apps and gamification to allow employees to measure and reduce their carbon footprint across the hybrid workplace.

Digital re-skilling continues at pace

We continue to see traction in digital re-skilling initiatives and hyperscaler certifications supporting digital workplace services. New skill sets are emerging, including machine coaches developing algorithms for AIOps and automation, AI architects supporting GenAI, and experience and innovation leads. Vendors are developing specific power programs to enable freshers to become full-stack engineers and up-skill industry-specific skill sets through domain SMEs, dedicated automation, and experience CoEs.

Vendors need to expedite resources building automation, GenAI use cases, and AI leads by client account. This includes developing industry and business-specific LLMs, both IP and open source. They must also enable a real-time data insights-driven approach supported by site reliability engineers (SRE) approving machine recommendations.

Outlook

The most significant impact over the next 12-18 months will be AI, with multiple GenAI POCs running across Copilot for Microsoft 365, for example, to augment agent capability, improve KB articles and conversational AI in the field, and GitHub Copilot to improve developer experience and drive legacy modernization. Also, there will be greater leverage of hyperscaler AI capabilities across ServiceNow, Amazon Q, Google Gemini, and Open Source LLMs. However, OCM will play a key role in driving the adoption of these technologies, with greater use of AI in OCM to drive personalization.

Vendors must focus on an experience management office (XMO) approach to drive and measure total experience across client organizations. Digital re-skilling will continue focusing on AI specialists, platform SMEs, and business value specialists. This includes building SRE CoEs in support of delivery locations.

Sustainability and ESG will be key drivers over the next few years, with clients utilizing Evergreen services, including DaaS, to manage device lifecycle, PCaaS, and circular computing. There will also be more focus on employee empowerment through gamification and green apps, and greater use of cloud to reduce carbon footprint and SMEs providing infrastructure in carbon-neutral regions. We expect vendors to increase their GTM and joint IP with hyperscalers and key ecosystem partners to support hybrid workplace transformation in the next 12-18 months.

We recently spoke with Datamatics about its $17m acquisition of Dextara, which was announced on April 1st.

Datamatics is a Mumbai-headquartered IT services and BPS provider with revenues of INR 1,550 Crore ($187m) for FY24, which ended March 31. It has three lines of business:

• Digital Technologies (IT services: 39% of revenues)
• Digital Operations (primarily F&A, plus intelligent process automation: 45% of revenues)
• Digital Experiences (CX, research & analytics: 16% of revenues).

The company generates 54% of its revenues from the U.S., primarily the SMB segment, and 24% from India. It has 300 clients globally, with the top 5 accounting for 23% of total revenue, the top 10 contributing 35%, and the top 20 over 50%.

Details of the Deal

Datamatics has expanded its capabilities with a series of acquisitions, including those of TechJini (mobile and web app development, 2017) and RJ Globus Solutions (voice-based BPS, 2018). Now, with the acquisition of Dextara Digital, a Salesforce Summit (Platinum) Consulting and ISV partner, Datamatics is boosting its fledgling Digital Technologies business (0.5% growth in FY24, declining by 12.4% y/y in Q4). Key drivers for Datamatics acquiring Dextara included:

• Expanding its Salesforce capabilities and improving the Digital Technologies business performance
• Augmenting its existing leadership with Dextara’s experienced management team.

Datamatics highlights that 25% of its clients are Salesforce users, an opportunity that it could not effectively target before the Dextara acquisition. In a previous effort to address this gap in its portfolio, Datamatics formed a JV with Cloud Route in 2022 with a view to start building a Salesforce services practice. These capabilities are now consolidated with Dextara, which is now the face of Datamatics Salesforce and leads any GTM initiatives. Datamatics and Dextara combined have around 150 certified Salesforce resources (130 in India and 20 onsite in the U.S.), serving around 80 clients.

Along with the Salesforce capabilities, Dextara brings to Datamatics an experienced management team led by the founder, Sreekanth Lapala. Prior to starting Dextara in 2020, Lapala managed around 25,000 resources as the global delivery head at Virtusa. This experience in building and leading large sales and delivery organizations that Lapala and his management team bring will help Datamatics beyond Salesforce as it aims to re-energize its technologies business and compete for bigger deals.

Dextara has an existing client base of around 50 American SMBs in the manufacturing, healthcare, professional services, high-tech, and BFSI sectors. Its core capabilities include CPQ, CLM, LWC, and Integrations, along with Einstein Analytics. It has developed two AppExchange-listed applications:

• Dextara CPQ, a customizable solution that clients can tailor to specific processes and industries. Features include product-attributed-based pricing. It was launched in FY24 and has two clients

• DXHealth+, a patient management product that targets small and medium elective healthcare providers whose services, like cosmetic surgery, are typically not covered by insurance. The product has 12 clients.

A Growth Engine for Datamatics

The existing Salesforce users among Datamatics’ clients are prospects for cross- and up-sell opportunities across Salesforce services, products, and Dextara’s IP. More importantly, the improved scale now makes Datamatics eligible for larger Salesforce deals (greater than $5m) and also positions it to convert some of its existing sales pipeline.

Datamatics has been busy on this front. It claims to have already introduced most of its clients to Dextara for consideration in Salesforce engagements. NelsonHall expects more account mining and cross-selling to Datamatics clients and an evolution of Dextara’s existing client profile to the larger Datamatics client base.

The Datamatics sales engine will also leverage Sreekanth’s leadership team’s delivery and sales experience to help manage large deal pursuits.

Datamatics has guided revenue growth of 7-8% for FY25, of which around 3-4% is organic and 4% (~$7m) from Dextara. Given this is the same as Dextara’s revenues last year, this is a conservative estimate: Datamatics looks to be factoring in time for the integration and client outreach completion over the next few months.   

Expect to see some investments in both Salesforce products and services. NelsonHall anticipates a particular focus on Salesforce Einstein and copilots in line with Datamatics’ corporate positioning as an AI-first service provider.  

Wipro recently briefed NelsonHall on its GenAI investments for quality engineering, discussing the creation of use cases and sharing the thinking behind some of its decision-making.

Wipro’s GenAI investments for QE are part of the company’s ai360 program, a $1bn investment that includes activities in developing use cases, training, and GTM. The launch of its QET GenAI Platform is part of this initiative.

It has identified ‘quick win’ use cases, including:

• Automated requirement analysis, test scenarios, case and script generation from user stories
• Test design recommendations
• Synthetic test data generation
• Knowledge management
• Data transformation and validation.

Like its peers, Wipro highlights the benefits of standard prompts, e.g., LLM’s output accuracy, lesser output variability, and capturing the client’s application and testing context. Wipro has created libraries of standard prompts, classified by role (UX designer, developer, tester, architect, BA, and application support) across the software development lifecycle.

RAG and Prompt Engineering

Beyond prompt engineering, Wipro wants to improve the accuracy of the LLMs. Rather than fine-tuning LLMs (through training the models on additional training data sets), it has chosen the retrieval-augmented generation (RAG) approach, which essentially relies on creating vector databases of the client’s testing artifacts. With the RAG approach, Wipro believes it takes a more relevant method to include the specific context of the client’s applications. To that extent, the company has created a tool that goes through various document formats (e.g., .doc, .pdf, .ppt) and creates a data set in a vector database.

For several use cases (e.g., test script generation, test data), Wipro wants to be LLM-agnostic and will connect with GenAI COTS (e.g., ChatGPT 3 and 4 and Azure OpenAI). It supports most test execution tools and languages (e.g., Selenium, Eggplant, Appium, and Playwright).

Looking to the future

The company is developing several GenAI use cases targeting specific tasks. Examples of these include locating an error in a Selenium script or writing a VB macro to migrate data from ALM to JIRA. Wipro is building a repository of use cases covering testing activities, taking a bottom-up approach.

There is a clear focus on helping clients beyond the interest stage and consulting engagements to PoCs and deployment. To facilitate client adoption, Wipro is looking to make its GenAI services enterprise-grade with assured data privacy and security. Options offered by the company include hosting on the client’s premises or its own.

Investments in GenAI will continue to be a priority in the foreseeable future. The company recently invested in data transformation and validation. Wipro plans to bring further depth to its user story analysis; it is exploring how to make user stories more standard and consistent within an enterprise. Current writers of user stories tend to have their own style. Wipro believes that GenAI can bring some standardization while increasing overall user story quality. The company also wants to go into more depth regarding automated root cause analysis beyond traditional defect classification.

Bringing an enterprise-grade service

Beyond LLM use case depth and standardization, Wipro believes that it will differentiate its value proposition by offering an enterprise-grade service. The company highlights it has taken several steps in this direction.

Wipro provides access to LLMs through its ai360. ai360 wants to ‘guardrail’ LLMs and systematically monitors and controls LLM usage. It ensures:

• The right usage, for instance, taking a persona-based approach and providing access to the right model
• Cost control, in a FinOps approach
• Reporting for corporate and regulatory compliance purposes.

Wipro has also worked on decreasing the time to create test scripts from an initial 15 minutes to one minute, relying on proprietary Python test script libraries.

The company highlights it has also progressed well in LLM output consistency. It finds the LLM output/responses to English language prompts can be unreliable. To overcome the challenge, Wipro created a library of UML models for specific processes (e.g., completing an online purchase transaction). It will update the UML libraries for each client and subsequently create test cases and scripts. With this approach, the company believes it can also increase test coverage.

Wipro points out that clients hesitate to move from demos and PoCs to deployment. The company believes its enterprise-grade approach will help organizations make the move and will continue to invest in it.

Cognizant has a long history of continuous improvement and innovation. However, its grassroots delivery teams were reticent in taking minor innovations to clients, so it underperformed in idea and innovation generation and ran beneath the radar, with clients typically unaware of innovations being undertaken.

However, in 2023, following the arrival of its new CEO, the company took the decision to focus on service improvement at scale, with its innovation program rebranded as Bluebolt and relaunched on April 21, 2023.

Cognizant believes its Bluebolt innovation program is already leading to greater levels of grassroots innovation activity, greater client recognition of innovation being carried out in their accounts, and increased associate engagement.

Indeed, the company’s ten key priorities in its 2024 Bluebolt roadmap include increasing client visibility, planning innovation days with client-impacting themes, increasing the pace and quality of ideas generated, and launching its innovation-as-a-service offering in conjunction with Cognizant Consulting.

Using Bluebolt Platform & Enabling Ecosystem to Ensure Scalability

Cognizant has developed a proprietary platform and enabling ecosystem to manage innovation processes, metrics, and documentation to ensure that innovation can be handled in a standardized and reliable manner at scale across its organization. The enabling ecosystem includes:

• Cognizant’s proprietary Bluebolt platform, that orchestrates the processes associated with innovation and manages innovation from ideation to impact
• Learning modules
• Governance, to ensure that what is reported is authentic and repeatable
• Consulting, working with the consulting team to offer this capability as a service to the market and to drive success within client accounts
• Bluebolt Garage, using bench capacity to develop MVPs and reusable assets that can be used across the company
• Recognition programs, rewarding people monthly, quarterly, and annually.

In addition, Cognizant has recently launched its generative AI-enabled innovation assistant, which assists associates in identifying frequent problems and exploring solutions. Its library includes all Cognizant’s innovations undertaken in the past five years, abstracting the details and removing client attribution. It has been used by ~10,000 associates so far and is now being enhanced to address RFP responses.

Using Innovation Days to Boost Joint Ideation

Cognizant classifies the types of innovation from its Bluebolt program into:

• Incremental, where the company improves on the quality, efficiency, or effectiveness within an existing client project
• Adjacencies, where Cognizant innovates on something complementary to the work already being done, possibly resulting in a separate order for this work
• Transformative, leveraging emerging technologies to create new solutions and offerings.

An example of a recent incremental solution was shortening the KYC process for a banking client; an example of an adjacency innovation is applying analytics to produce harvest timing recommendation, germination and yield prediction models for a biotechnology client; and an example of a transformative innovation is implementing digital chassis car-to-cloud services for a semiconductor client.

Hackathons and ideathons are key mechanisms in boosting these innovations. In 2023, Cognizant carried out 41 hackathons and 18 ideations involving clients, and 70 and 87, respectively, involving solely Cognizant associates.

In addition, Cognizant is increasingly using innovation days to generate immersive innovation experiences for clients. These joint ideation sessions can include client-centric, domain-specific product-aligned themes; account priorities to accelerate performance, e.g., by showcasing all Cognizant platforms and enablers; and global themes and challenges, including sustainability.

Within sustainability, the major themes are net zero pathways, sustainability and ESG reporting, sustainable product development and circular economy, sustainable manufacturing and operations, and sustainable supply chains. These sustainability themes have 235 sub-themes and 200 specific prompts that can be used with clients and prospects.

Achieving Client Satisfaction Uptick with Innovations & Improvements Following Bluebolt Introduction

Cognizant is experiencing an uptick in client satisfaction as a result of Bluebolt. Satisfaction with innovations and improvements delivered by associates has increased over the past 12 months from 4.18 to 4.36.

In the 12 months following its launch, the Bluebolt program has achieved:

• 130k ideas generated
• 23k ideas implemented, with a number of these funded by clients as an adjacency
• 220k associates trained on Bluebolt.

Of the 130k ideas generated, ~5% are transformative, ~35% are adjacent, and ~60% are incremental. 8,927 of the 23k ideas implemented impacted client value streams and 321 were directly funded by clients. Elsewhere, clients may be willing to co-invest using the innovation funds typically incorporated within Cognizant’s larger contracts.

Cognizant is now targeting a major increase in impact from its Bluebolt initiative in 2024. It achieved 104k ideas generated by December 2023 and was initially targeting 200k ideas generated in 2024. This target has recently been reset to 500k. In addition, its 2024 targets include:

• 20% growth in impact measures
• 250+ Bluebolt garage projects leading to MVPs
• 500+ client-facing cases that can be published for wider internal use
• Filing a patent application for the Bluebolt Central platform.

To increase the chances of achieving these targets and ensure that innovation is firmly embedded in the company, these goals have been included in the bonus plans of ~900 senior delivery leaders.

Further pressure is placed on account teams, and greater visibility of innovation within client accounts is being achieved by client Bluebolt journey summaries being provided to the CEO before his client meetings. These show the key innovation statistics, including the numbers of ideas generated and implemented, the top ideas generated by the ideathon, and client feedback.

The impact measures used include:

• Revenues for clients
• Revenues for Cognizant (from client-funded adjacent initiatives)
• Hard cost savings for clients
• Hard cost savings for Cognizant.

Bluebolt garage projects typically involve 8-10 associates for an 8-week period. So far, 133 ideas have been evaluated and shortlisted, 70 garage projects are in progress, and 13 MVPs have been produced.

NTT DATA held its first EMEA Latin America (EMEAL) Analyst Day last week since the merger of NTT DATA and NTT Ltd. announced in June 2022. The event provided some perspective on the new structure of the firm, its capabilities, and its short-term priorities.

The new NTT DATA Group is a much-enlarged firm with $31bn in revenues and around 150,000 employees. The group comprises two standalone companies:

• NTT DATA Japan, with $13bn in revenues
• NTT DATA Inc., the $18bn international business, co-owned by NTT DATA (55%) and Japan's NTT (45%). The unusual ownership structure reflects NTT Ltd's former ownership by NTT and a business model difference between the two entities.

It is possible that, in time, the two companies will eventually be integrated into one global organization.

NTT DATA Inc. has started its integration first at the geographic cluster level (U.S., EMEAL, and APAC outside of Japan). Historically, NTT DATA looked more like a federation of companies loosely aligned with several integrated practices (such as SAP services). The new geographic cluster structure will help the firm integrate businesses in EMEAL, while preserving its onshore and consulting heritage.

An Application, Infrastructure, and Network Integrated Firm

The 2002 merger with NTT Ltd. expanded NTT DATA Inc.'s capabilities to include data center colocation, network, connectivity, and IT infrastructure. Most of the NTT Ltd. portfolio is services. It also includes a significant network product reselling business.

NTT DATA Inc. has kept the data center colocation business independent, highlighting its CAPEX-heavy business model. The company claims to be the third-largest data center/colocation provider, with 80 data centers. Potential synergies with the rest of NTT DATA Inc. are limited, although there may be occasional joint GTM for server and computing projects.

The integration has focused on connectivity and network services capabilities, along with those in IT services. The aim is to sell integrated IT services, network services, and connectivity, something that few competitors have achieved, through a business (and consulting-led) approach rather than emphasizing connectivity and technology only. An example is private 5G, which the company sells under an Industry 4.0 approach to automotive OEMs rather than through a more technical 5G equipment resale and integration approach.

Priorities: Innovation and Assets

Priorities for the next two years highlighted at the event include innovation and the Asset-Based Business (ABB) initiative.

NTT DATA Group has aligned its innovation efforts across the three geographic clusters. NTT DATA Group's Innovation Headquarters is driving this initiative, prioritizing its R&D spending across:

• Mainstream services (70% of spending)
• Growth (20%)
• Emerging (10%).

GenAI is a priority, with NTT DATA Group using its parent company's investment in its own LLM, Tsuzumi. The company is actively deploying GenAI and Tsuzumi across the SDLC. Here, we noted in conversations an acknowledgment that GenAI's gains are likely to be 10-15% in the mid-term, well down from optimistic claims in the industry of 30-50%. Automating the full SDLC with GenAI will require a long-term investment in addressing gaps.

With its Asset-Based Business (ABB) initiative, NTT DATA Inc. has identified products, solutions, and accelerators built by local and vertical units. It wants to bring a structured approach to its assets, identifying and assessing them, prioritizing and allocating investments, and accelerating its growth through commercial focus and cross-selling into accounts through Inc.'s account managers.

ABB's ambitions go beyond monetizing software assets. The unit wants to structure its portfolio, where possible, into a suite of modules and products under the Syntphony umbrella brand rather than standalone products. Beyond sales (mostly subscriptions), NTT DATA Inc. wants to use ABB's portfolio to differentiate its services. The company targets project sales rather than standalone product sales. NelsonHall estimates ABB accounts for around 6% of NTT Data Inc.'s total revenues (including software and services). ABB has bold growth ambitions to account for over 10% of revenues eventually.

Getting the Word Out

Getting the word out is also a priority. NTT DATA Inc. remains a quiet giant whose capabilities are not yet well-known. For instance, the company has a much bigger scale in its global delivery network than expected, with around 66,000 employees in India and another 16,000 or so based in nearshore locations, including Czechia, Romania, South Africa, and the Philippines. An immediate priority is standardizing tools and processes across centers to harmonize its delivery.

The integration journey is ongoing. In EMEAL, the company has selected its innovation portfolio priorities: GenAI, sustainability, and ABB. NTT DATA Inc. has a very broad portfolio, including SAP and Salesforce services, data & analytics, application cloud migration, and its much-enlarged IT infrastructure and network services.

We expect NTT DATA Inc. to continue to review its portfolio regarding investment and GTM priorities.

Topline growth is a stronger priority than margin expansion: NTT DATA Inc. considers itself the growth unit of the NTT DATA Group.

NelsonHall recently talked with Eviden, Atos’ consulting and application services business, about its QE practice, Digital Assurance.

Digital Assurance has 5k quality engineers, 65% offshore, reflecting a high leverage in North America (due to its Syntel heritage) counterbalanced by Atos’ large European public sector client base. The practice has aligned its service portfolio around high-growth offerings such as testing applications for digital projects, migration to the cloud, testing Salesforce migration projects from Classic to Lightning Experience, and SAP.

Beyond these technologies, Digital Assurance has focused on AI, initially traditional AI with ~45 pilots underway, and then around GenAI in 2023-24.

AI/GenAI as priorities

Eviden currently has five primary GenAI use cases relevant to testing being deployed on its GenAI QE Platform:

• Test strategy generation
• Ambiguity assessment and scoring
• Test case creation
• Test data
• Test script automation.

One of the demos we attended was ambiguity assessment and scoring, where Eviden evaluates the quality of a user story/requirement. Other demos such as automated test case and test script generation provide several insights regarding the current art of the possible.

GenAI quick wins

GenAI provides quick wins that do not require significant ML model training.

An example is assessing the quality of user stories. Commercial LLMs will work out of the box and can be used as-is without further training. But LLMs only work if the input data (user stories in this example) follow best practices, e.g., are detailed enough and have clear acceptance criteria. If those fail, the LLM will reject the user stories.

Prompt engineering rather than data finetuning

Eviden is finding that the pretraining provided by the hyperscalers is good enough for most use cases, and is not currently contemplating conducting clients’ data training.

Eviden sees a need for structured prompt engineering, i.e., providing the LLM model with the right instructions. It is building repositories of standard/proven prompts. In addition, Eviden will adapt the prompts to the specificities of each application, e.g., table structures and user story patterns. Digital Assurance estimates that adapting prompts to the client’s applications will only last a few weeks. This approach is time-sensitive and provides quick wins, for instance, around automated test script generation.

Combining traditional AI and GenAI

Eviden is combining GenAI with more established impact analysis AI models (e.g., predicting the impact of code change/epics on test cases) and is conducting GenAI processing once it has done so with predictive AI model investments. The ecosystem approach goes beyond other AI models, and Eviden points out that it is deploying container-based delivery to execute GenAI models independently to shorten time-to-process.

The beginning of the GenAI journey for QE

This is just the start of the GenAI journey for Eviden’s Digital Assurance practice. The company is deploying early GenAI use cases and deriving its first best practices. Eviden also points out that human intervention is still required to assess GenAI’s output until GenAI reaches maturity. Even with GenAI, the testing industry is far from autonomous testing or even hyper-automation.

Eviden is working on other GenAI initiatives, including around Salesforce and SAP applications. For instance, Digital Assurance has used GenAI in SAP to generate a repository of ~250 T-codes (SAP transactions) with relevant test scenarios and cases.

Eviden is also exploring migrating to open-source tools away from SAP-recommended COTS for their regression testing needs. The migration goes beyond changing text execution tools and migrating test scripts. This is not the first time we have seen interest in moving away from commercial tools, but historically this has not materialized in massive migration projects. GenAI will ease the process.

During the summer of 2023, we met with Mohammed Sijelmassi, Sopra Steria’s CTO and Digital Transformation Office head and discussed how Sopra Steria was deploying internally and helping clients externally with GenAI and LLMs. Earlier this month, we met with Mr. Sijelmassi again to assess Sopra Steria’s progress on its transformation, its work with clients, and use cases.

Use Cases: Knowledge Management & Reverse Engineering Remain the Priority

Sopra Steria currently has two use case priorities: conversational agent/knowledge management to complement self-service portals and bring a higher quality of chatbots, and reverse engineering for creating documentation out of existing applications: documentation generation is time-consuming and is a popular candidate for GenAI.

Code generation is next. Sopra Steria finds that code migration between object-based languages and Java version migration (e.g., to JDK 17 LTS) works fine: the challenge is to increase code quality, create concise code, and reuse software components (LoCs) where possible. Sopra Steria is identifying internally reusable components of high quality that can be used across the company’s software developers.

Areas of mid-term investment include COBOL migration to an object-based language. There are challenges in migrating between languages relying on sequential instructions (e.g., COBOL applications) to object-based programming languages. Sopra Steria is working with IBM and is taking a reverse engineering approach to identify specifications and generate code. It also points to proprietary programming languages (e.g., SAP ABAP) where the volume of LoCs in the public domain is insufficient to have best practices.

Prompt Engineering vs. Data Finetuning

Mr. Sijelmassi also provided some light on the LLM pre-training vs. client-specific (finetuning) discussion. The company believes that the quality of pre-trained LLMs is high enough for its own and its clients’ software engineering needs. Therefore, Sopra Steria is currently focusing on prompt engineering and creating libraries of standard prompts.

The company is exploring how to finetune LLMs on its own data and specially for its software products. Sopra Steria is selectively working with clients on this and has internal pilots around its HR Software and Sopra Banking products. The company finds that training LLMs on client-specific data is a relatively limited engagement (with costs ranging from €100k to €1m, depending of the size of available data). However, it points out that the finetuning exercise relies on the quality of existing data and its curation to avoid issues such as data bias. In other words, the finetuning effort will truly depend on the quality of the client’s data estate.

Internal Deployment is the Priority

Sopra Steria has embedded GenAI into its software development tools (Digital Enablement Platform) to improve productivity: so far, the company has purchased 10k Github Copilot licenses, which it is rolling out gradually, 1k per month in a phased approach aiming to build experience and gradually derive best practices.

Achieving developer buy-in is of course critical: in early internal surveys, Sopra Steria has found most developers believe that GenAI brings productivity gains and increases software quality. It expects different levels of GenAI adoption across its developers, with freshers/recent graduates and experts driving adoption. The company is accordingly targeting middle-aged developers with training and change management programs to raise GenAI awareness. Sopra Steria also intends to create career paths where developers can become experts rather than move to management positions.

Sopra Steria is targeting 10k licenses deployed and its current 58k employees by the end of 2024. 2024 will be the year of deployment and best practices.

Vertical Use Cases Are Next

Consulting with Sopra Steria Next still accounts for Sopra Steria’s bulk of GenAI activities. Sopra Steria Next continues to identify new use cases. Recently, it deployed Copilot 365 services to help clients use it and equipped 300 consultants to collect feedback.

Beyond best practices and use case identification, Sopra Steria Next highlighted its work around:

• GenAI and its impact on the environment (energy consumption)
• Selecting LLMs, differentiating between products and open-source models
• TrustAI.

Also, Sopra Steria Next is exploring vertical use cases, initially targeting conversational agents. The company has a project with a retail bank to use GenAI and help agents cross-sell products. It is also cross-pollinating the same approach to similar industries such as retail & distribution.

GenAI To Have a Contract Impact bv 2025

2024 is primarily a year for internal deployment. Sopra Steria expects to derive productivity gains from 2025 onward and embed them in its contract discussions. Depending on client maturity the company is looking to see productivity gains from 10% to 25%. Of course, this will not translate to an equivalent price drop: additional costs in terms of license, GPU, and training need to be factored in.

Beyond productivity, Sopra Steria’s investments in GenAI demonstrate two points:

• GenAI will go beyond the hype and bring productivity gains
• GenAI brings two easy-to-deploy use cases that are quick wins. Other use cases require investment and will take time to be rolled out.

2023 was a year of disruption after the 2021-22 digital catch-up. As the year unfolded, IT services spending slowed down, initially in the U.S. in the financial services, telecom, and high-tech sectors.

We expect 2024 to be a year of transition with a modest rebound in IT services spending, continued consulting interest in GenAI, a rebound in cloud infrastructure adoption after a slowdown in 2023, and an uptake in discretionary spending. U.S. spending will rebound and outgrow U.K./Europe.

A Modest Rebound in IT Services Spending

IT services spending growth in 2024 will increase by a modest 1 pt to +4%, driven by managed services/IT outsourcing spending in H2 2024.

Spending in the U.S. will rebound in H2 despite much uncertainty due to the U.S. elections, both in terms of stock market perceptions and also the possibility of squeezed federal government spending. In contrast, Europe will remain soft, as Germany suffers from its exposure to the quiet Chinese manufacturing sector. More information here for our subscribers.

Digital and GenAI Drive Consulting

Consulting remains a cyclical activity, and revenues in key sectors such as financial services, traditionally large buyers of consulting services, and telecom have been declining. A positive impact is the very high interest by firms across sectors in understanding the potential applications of GenAI in their organization. Interest also remains around UX/UI, SaaS, and front-office applications, though it is slowing down. Industry 4.0 generally remains solid but will be impacted by the manufacturing slowdown we predict for 2024. Sustainability has mid-to long-term potential.

IT infrastructure Services: Cloud Rebounds

Despite a slowdown in 2023, notably in the high-tech and financial services sectors, the migration of IT infrastructure and applications is a secular shift. NelsonHall sees no market saturation for public cloud migration in the short term. Security will continue to thrive.

Transformation of the digital workplace accelerates with a focus on Experience Management Offices (XMO) for centrally coordinating the UX and deploying XLAs such as user satisfaction in contracts. Vendors will continue to verticalize their persona-based offerings. e.g., nurses and doctors in healthcare, plant operators in manufacturing. Clients turn to vendors for guidance and OCM on GenAI, with agent assist utilizing KM as a typical early use case.

Application Services: Agile and Data/Analytics/AI Continue to Dominate

Data, analytics, and AI will be 2024’s priority, with GenAI (and traditional AI and IoT) driving spending growth. Another major theme is hosting data on the cloud. Key themes for other service lines include:

• ADM: agile transformation continues to be the major theme. Along with APIs, LC/NC tool usage, and sustainability. Many organizations will seek advice from their vendors about the role of GenAI in ADM (e.g., documentation, code migration, code development)
• Quality engineering/testing: continuous testing (i.e., agile testing transformation) is, like in ADM, a major theme along with functional automation. Traditional AI promises to automate the requirements/user stories-test case-test script cycle. GenAI will continue to monopolize the boardroom’s attention
• S/4HANA transformations with phased roll-outs will continue to be solid. Organizations will also assess the benefits of SAP initiatives such as Clean Core and BTP to lower maintenance costs and rearchitect applications. The agile transformation will continue
• Salesforce has made a strategic shift and now favors profitability over revenue growth. The company expects a 10% CC revenue growth (primarily organic) in 2023 and pushes its GenAI agenda. MuleSoft remains the core driver, while core Sales and Service Cloud grow faster than more recent products such as Commerce and Marketing Cloud. 2024’s key question will be whether Salesforce will push again on revenue growth for its subscription and service ecosystem.

U.S. Will Grow Faster than Europe

Growth in discretionary spending is likely to resume from H2 2024, led by the U.S. once inflation rates start declining and businesses have greater visibility on the likely outcome of the presidential election.

U.K./Europe’s recovery will be delayed by a semester (H1 2025). There will be increased uncertainty in the U.K. with a general election in H2, in both commercial and government sectors. Germany will continue to be impacted by less manufacturing equipment sales to China. France will have anemic growth, also impacted by a manufacturing slowdown.

2024: A Year of Transition

2024 will be a year of a transition from the slowdown of 2023, with the U.S. regaining its role as a traditional driver in IT services spending. IT services spending will return to stronger growth from 2025 as organizations reignite discretionary spending in digital, cloud, and security. Notably, GenAI and AI bring the potential to fundamentally transform how businesses operate across functions; none will want to be left behind.

To keep up to date with NelsonHall's IT services research and thought leadership in 2024, subscribe to our IT Services Insights newsletter on LinkedIn.

Not all IT KPIs are created equal, so Enterprise Automation Fabric incorporates a 3-level CMDB linking business processes, applications, and IT infrastructure. This mapping of business KPIs to application KPIs to infrastructure KPIs enables organizations to identify the potential business consequences of particular IT incidents. For example, for a retailer in the Netherlands, Enterprise Automation Fabric can predict the impact on shipping volumes if a particular issue happens with the IT infrastructure and this is not addressed within, say, 48 hours.

In general, Enterprise Automation Fabric can be set up to trigger automation or generate an alert to a business owner if a particular business KPI is identified as being at risk.

So, what is Capgemini Enterprise Automation Fabric?

As the name implies, Enterprise Automation Fabric is a reference toolset and framework consisting of a series of components that can be integrated with an organization’s current IT management investments. The toolset consists of interwoven third-party and Capgemini assets. It supports the management of the entire IT estate across cloud infrastructure, on-premise data center infrastructure, end-user computing, and applications. As appropriate, it links with the client’s existing monitoring solutions or utilizes its own preferred options.

Key components of the Enterprise Automation Fabric architecture include:

• Its CMDB (configuration management database)
• AIOps. This is central to “observability” with the CMDB structure captured by Capgemini’s AIOps solution, typically Splunk, augmented by proprietary Capgemini assets. AIOps covers functions such as anomaly detection, event correlations, and service impact assessment
• ITSM. Infrastructure management across multi-layer components, covering functions such as ticket management, incident management, and service request management
• Automation utilizing unattended and attended bots.

Once an anomaly is identified, Capgemini’s ITSM layer, built on ServiceNow, creates an incident. Capgemini data-driven assets augment ServiceNow in areas such as assisted resolution and intelligent dispatcher.

Once the incident is captured in the ITSM, it can be addressed using automation solutions. These include both intrusive automation, such as RPA and managing infrastructure as code, and human-in-the-loop automation. In infrastructure, autonomous automation can currently handle around 50% of incidents without human involvement, typically exceeding 50% in the service request space. For application-related incidents, the level of autonomous resolution is typically in the range of 20%-40%.

Enterprise Automation Fabric includes infrastructure-related automation bots for health checks, service requests, remediation, and reporting across:

• Servers (228 bots used across client engagements)
• SAP (82 bots)
• Storage & backup (66 bots)
• Network (~20 bots).

Enterprise Automation Fabric Capture is a Capgemini asset that can be deployed to speed up incident identification and resolution in SAP environments. It allows SAP users to capture all the details on the screen, including the error code, in a structured Excel format and create an incident with extensive pre-populated structured data in the ITSM.

Enterprise Automation Fabric is cloud-native but has an on-premise option. This latter option is particularly relevant for organizations requiring business measurement data to remain within their onsite environments.

Capgemini Reduced Alerts by 86% for Consumer Electronics Company

The complexity of this company’s IT estate had steadily increased over time, leading to high-priority production incidents (P1 alerts), particularly impacting the company’s SAP Order Management applications and infrastructure.

Capgemini deployed an AIOps solution to integrate various monitoring tools across applications and IT infrastructure and introduced a single dashboard for improved visibility across all the monitoring and custom application alerts. This significantly reduced the number of alerts by, for example, identifying and suppressing false alerts and avoiding duplication of alerts, enabling the team to focus on a smaller number of genuine alerts.

At the start of the engagement, the company was experiencing around eight P1 alerts per month, and Capgemini was able to eliminate P1 alerts over six months. Overall, an 86% reduction in alerts was achieved.

Capgemini also created a catalog of automation scripts to assist in resolving the issues identified by AIOps and developed knowledge articles to augment the capability of the team to resolve issues that could not be automated and required manual resolution.

In a similar exercise for a major airport, which had previously managed its systems manually, Capgemini streamlined its IT operations and cut alert queues by half. The auto-healing solutions helped boost efficiency and achieved a 10% increase in SLA response times, reducing the manual workload significantly. The net result was a 98% reduction in incident turnaround time, largely due to now correlating 88% of the previously unrelated alerts.

While organizations can adopt Capgemini’s Enterprise Automation Fabric on an incremental basis, the keys to its successful application lie in its multi-tier observability capability, its ability to resolve incidents autonomously before they impact users, and its ability to link business performance to application and infrastructure KPIs. The overall Enterprise Automation Fabric also meshes with existing client investments, reusing key assets from the client where appropriate.

Capgemini is now enhancing the existing Fabric components with GenAI proficiency, applying GenAI widely from incident routing to automated response and alert resolution to deliver enhanced efficiency within the framework. NelsonHall will bring you more updates as Capgemini incorporates the capabilities of GenAI into Enterprise Automation Fabric.

The CEO of Atos’ Tech Foundations business recently updated industry analysts on its transformation program.

We have commented about the turbulent period Atos Group is going through in splitting into two businesses (Tech Foundations and Eviden). The planned sale of Tech Foundations to Czech billionaire Daniel Kretinsky’s EP Equity Investment (EPEI) vehicle is going ahead, with completion now expected in early Q2 2024. Tech Foundations will retain the Atos brand name.

We were interested in portfolio developments at Tech Foundations and progress in its portfolio transformation and reducing the level of problematic (‘red’) contracts.

In terms of portfolio simplification, Tech Foundations is exiting its BPS activity in the U.K. And in October, it finally exited Unify, its UCC business, and divested to Mitel Networks. It has also significantly ramped down its VAR business to reduce its low-margin activities. The focus now is primarily on offerings such as digital workplace that it can provide in an industrialized manner, and on helping clients manage the complexity of hybrid multi-cloud.

There has also been some portfolio development in these areas; for example, digital workplace sustainability in office equipment: Tech Foundations is launching Atos Tech 4 Good Assistant, a dashboard to help end-users monitor their environmental performance and uninstall unused applications or switch off their laptops. It has also launched a dashboard, Sustainable Workplace, at the enterprise level.

Tech Foundations is also deploying its Technical Services unit in new geographies, primarily the U.S. and Spain. The unit has launched a consulting service targeting workplace and data center transformation and service integration. TS is its highest-growth unit and expands its position in build services rather than run services, which tend to have lower margins. Peers such as Kyndryl and DXC have similar initiatives.

In terms of red contracts, there has been substantial progress, often through exits rather than renegotiation. In 2021, these represented 13% of its contracts. That proportion reduced to 8% in 2022 and is now approaching 6%, much closer to the level of some major IT infrastructure service-centric peers. This continues, with some of the exits being major moves; e.g., the recent NEST exit in the U.K., a contract that was worth £1.5bn over 18 years.

There is a renewed focus on strengthening client intimacy, including a new client advisory group. The focus is driving conversations at the CXO level with priority clients in each region to understand and address critical client challenges through co-creation with Atos and its partner ecosystem.

Tech Foundations’ recovery is, of course, a multi-year journey. Recent financial results indicate some progress. In Q1-Q3 2023, its revenues were down 4.4% y/y in CC, impacted by the ramp-down in VAR and BPS activities. This performance lies between Kyndryl (-1.7%, NelsonHall estimate) and DCX GIS (we estimate -9.3%). For FY22-24, Tech Foundations is targeting 0% to 2% annual growth, with a rebound commencing in 2025.

Taking the Tech Foundations business private might be helpful. Its multi-year transformation will probably be more suited to an investor with a multi-year investment horizon than the quarterly mindset of many shareholders in public companies. We would expect EPEI to invest to help Atos expand its service portfolio. Security will be a priority even if the unit retains its security monitoring capabilities following the split. Application migration to the cloud is another potential acquisition area, complementing its expertise around infrastructure migration to the cloud.

The dust should settle for Tech Foundations (the new Atos) in H1 2024.

NelsonHall recently attended Compucom’s Analyst and Advisor Event 2023 in Charlotte, NC. It provided an opportunity to meet the executive leadership team, which has evolved over the last 12 months. Kevin Shank was appointed CEO in December 2022, having served as a senior executive at Compucom for nine years. He was joined earlier this year by Matt Olson as COO, also a previous senior executive at the company.

Founded in 1987, Compucom supports digital experience management through device lifecycle services, digital support, field services, and modern device management. The company provides end-to-end digital workplace services for large enterprises and mid-size businesses, supporting 9m devices and handling 8m service desk contacts per annum. In December 2021, it was acquired by Variant Equity Advisors, providing new impetus and investment to its focus on improving the digital experience in support of hybrid working.

Compucom is aiming to enhance its clients’ workplace transformation programs by:

• Implementing single points of contact for clients to drive innovation and NPS
• Establishing a Customer Experience Office and Experience Level Indicators to drive XLA discussions
• Driving the use of automation and AIOps across its digital support services.

Implementing Single Points of Contact to Drive Client Innovation & NPS

Compucom has reorganized its account management approach to drive innovation within its clients in a more cohesive and client-centric manner. A program director in charge of sales, solutioning, and client resourcing for the account now becomes the client’s single point of contact. The program director is also responsible to Compucom for the account P&L.

Compucom has deployed this model across its top 65 accounts (~80% of total business), driving greater account opportunities and improved client NPS.

The company continues to utilize its end-to-end capabilities across product provision, professional services, managed services, and staffing services at scale to provide a continuous lifecycle approach for the client.

Establishing a Customer Experience Office & Experience Level Indicators to Drive XLA Discussions

Compucom has established a Customer Experience Office (CXO) to provide a centralized and holistic approach to continuous improvements, increasing service efficiency and customer experience across clients. It includes a dedicated team building automations and improving proactive resolutions through AIOps.

At the same time, Compucom has developed multiple Experience Level Indicators (XLIs), covering metrics such as device and application performance, to measure experiences across four key indicators through its DEX platform and to drive XLA discussions with clients. The four key indicators, each containing multiple XLIs, are:

• Technology choice: covering device performance, application experience, and employee productivity
• Workplace flexibility: covering network, device, and connectivity experience
• Self-sufficiency: covering self-service resolutions, knowledge usage, and self-service support experience
• Well-supported: covering onboarding experience, device lifecycle experience, and support experience.

These XLIs are supported by Systrack, or clients’ end-user analytics tools, putting multiple telemetry points into dashboards to identify opportunities for experience improvement.

In addition, Compucom has a dedicated analytics team that works closely with account management. It takes data from multiple points, including digital support, endpoint, lifecycle, field services, cloud, and security, collecting data via telemetry and metrics from services and sentiment.

The analytics team then utilizes AI/ML to identify actionable insights, which are solutioned to drive service or content improvements. Service enhancement use cases include performance-based refresh to understand if a device is not performing at the level an employee needs to do their job effectively. It also looks at software license optimization to understand usage and identify opportunities for cost-out, including applications on devices not being utilized. Compucom has developed several support interaction use cases, including quality enhancement, knowledge content, AI-chat content, and process improvement.

It also has the opportunity to further support clients’ ESG agendas through its device lifecycle services, immersive technologies, AR/VR, remote support, OEM partnerships, and by developing Green apps to help users monitor, track, and reduce their carbon footprint.

Driving Use of Automation & AIOps across Digital Support Services

Compucom is continuing to invest in digital support models with more automation, self-service, conversational AI chat support, and generative AI POCs with clients. It looks at different telemetry and events from the devices deployed across the workplace and aggregates this data to view patterns and deliver appropriate automation as required.

This includes using AIOps to trigger actions, propose preventative measures to predict, prevent, detect, and fix potential issues before they reach the service desk, and enable self-healing to increase autonomous remediation. It is developing a field technician mobile application to track, for example, ETA and routing automatically.  

Compucom will continue to increase this focus on AIOps and drive a real-time data insight-driven approach across the workplace supported by dedicated skills, including data scientists, automation and AI architects, and UX/EX leads. It will need to ramp up its digital re-skilling and hiring to ensure the requisite skillsets are in place, and this is underway as part of its strategic roadmap.

The company is also investing in Microsoft IaaS and PaaS capabilities, and taking advantage of and securing technologies including Microsoft Copilot to enable GenAI use cases. In addition, there will be greater use of Intune, including Autopilot and cloud-based managed services in support of modern management.

Cybersecurity is also a key focus for Compucom, and it is investing in new cybersecurity tools and standards. The increasing client shift to SaaS is increasing the number of devices that require network connectivity and bringing new security and networking challenges to edge locations. It also provides the intersection between IoT, operational technology, and the workplace in support of hybrid working environments.

Outlook

We expect Compucom to expand its customer-centric approach across key accounts to drive innovation and overall experience.

Compucom is increasingly focusing on how its offerings can support specific client outcomes, and we expect to see contractual XLAs being deployed through its XLI-based approach in support of client outcomes.

We also expect to see increased tailoring of its services by industry, including a more persona-based focus on frontline workers and industry-specific roles across the workplace and via its GTM with key ecosystem partners and hyperscalers.

Sopra Steria is the latest vendor to announce a significant investment in GenAI/LLMs and its incorporation into its software engineering platform (Ingine).

We recently met with Mohammed Sijelmassi, who holds two roles at Sopra Steria: CTO and Digital Transformation Office. We discussed how Sopra Steria is deploying internally and helping clients externally with GenAI and LLMs.

There is undoubtedly a sense of urgency: Steria acknowledges that GenAI will likely disrupt the IT services industry within two years, and its clients’ industries. The company has seen its delivery teams using GenAI and wants to accelerate this initial movement at the group level. Accordingly, Sijelmassi is sponsoring an AI use case program around three priorities: application services and its software products; educating clients on using AI; and internally for sales and support functions.

Immediate Priorities include Level 1 Support and Software Engineering

Sopra Steria is assessing LLM use cases in application services. An immediate opportunity is level 1 application support, with LLMs complementing other tools, such as self-service portals and chatbots, to deflect inbound calls to the service desk. The intention is to use GenAI together with chatbots to bring higher-quality responses.

Other immediate opportunities are related to software development and reverse engineering, e.g., for creating software documentation from existing applications, reading through lines of code to understand what an application does, annotating lines of code with comments, or identifying the application’s requirements (with the intent of generating test cases).

Sopra Steria is also assessing use cases in software development; next year, following several months of preparation, the company will train LLMs on its code repositories, including its coding and architecture best practices and standards.

Governance Issues

GenAI will bring governance issues. The increased adoption of AWS CodeWhisperer, GitHub Copilot, Duet AI for Google Cloud, and Hugging Face will increase AI-generated code proliferation. This raises challenges such as:

• The proliferation of code will impact its readability and degrade the application performance, and potentially impact the CPU and memory of a mobile device
• IP issues. Sopra Steria wants to avoid code and business logic developed specifically for a client being reused by a different organization. This means controlling the training data, separating code and business rules owned by clients, and ensuring best development practices are embedded in the training data.

LLMs have implications beyond governance and will impact junior roles such as level 1 application support. The company will increase its new graduates’ upskilling investment and migrate them quickly to level 2 roles. GenAI might have an impact on the age pyramid.

Sopra Steria is embedding LLMs into its software engineering platform Ingine to spread GenAI usage rapidly. Ingine also includes enabling tools and services such as a development environment, DevOps, security, and testing tools accessible through an internal marketplace. Sopra Steria plans to have Ingine GenAI-enabled by the end of 2023.

Mid-Term Initiatives

Beyond software development, reverse engineering, and support, Sopra Steria is looking at mid-term application services initiatives, such as:

• Code migration, e.g., from COBOL to .NET or Java. This will come later, as programming language migration requires transformation beyond code and includes reengineering the application based on different architectural principles. Sopra Steria is exploring how to use reverse engineering to create software specifications and automatically generate new code
• QA/testing.

Sopra Steria is addressing increasing client demand for workshops to explore current GenAI use cases and understand the IT implications around application architectures through its consulting arm, Sopra Steria Next. The company is working with its clients on the EU’s AI Act. It believes that demystifying fears or fantasies around GenAI will take another year for its clients. Sopra Steria Next will help here.

The company is also deploying LLMs for several of its software products. For instance, it is currently combining GenAI and ML for its HR software products, such as identifying changes in payroll and HR regulation, reviewing its software products to look for defects, and improving quality.

Productivity Gains Ease the Talent Shortage

Sopra Steria envisions the coexistence of large generic and slower-performance LLMs with broad capabilities, and more focused ones specialized in specific topics and use cases requiring low latency. Examples are use cases where real-time applications, such as manufacturing or defense applications, favor speed rather than breadth of knowledge.

There is no doubt that GenAI will bring productivity gains to the IT services industry while presenting it with enormous challenges, not the least of which is demanding significant investments in training. Sopra Steria’s stance is that GenAI will ease the pressure on the shortage of IT talent.

Cognizant's non-U.S. business, Cognizant Global Growth Markets (GGM), recently held an analyst and advisor day and discussed its regional priorities.

New CEO Ravi Kumar has initiated a restructuring plan ('NextGen Program') to reduce Cognizant's cost base to fund investments.

While Cognizant had guided on flat topline growth in 2023, Q1 saw a 9% y/y growth in LTM bookings, indicating the company has started to gain momentum in IT outsourcing deals.

Where Cognizant in the U.S. is impacted by a large contract ramp-down, Cognizant GGM's priority is topline growth, with an aspirational goal to double revenues (without specifying a date). Cognizant GGM generated revenues of $5bn in 2022, spread almost equally between the U.K., Continental Europe, and RoW. Together, these international (non-U.S.) revenues represent 26% of Cognizant's total revenues (compared with around 47% for TCS), so the U.S. will continue to drag on overall company performance.

Replicating its success in the U.K.&I

In Europe, Cognizant GGM is looking to replicate its success in the U.K&I, its fastest-growing geography for several years (21.1% CC topline growth in 2022), driven recently by public sector awards such as those with Defra.

Cognizant GGM believes its deployment of a vertical GTM in the U.K. helped it scale rapidly and reaffirmed its positioning at the intersection of vertical and sub-vertical knowledge and technology expertise. Cognizant has grouped its business into six regions, presumably intending to develop a verticalized GTM in the larger clusters.

Consulting will play a significant role. Cognizant’s ambition is to double its consulting activities to 9% of GGM revenues as it looks to drive client intimacy, expand its reach to LoB executives, and negotiate sole-source contracts. Within consulting, Cognizant also emphasizes its sustainability advisory services.

Cognizant GGM is focusing on its top 100 clients to drive deeper relationships. This is a very significant refocus, as GGM has ~2k clients. Depth of the relationship and client selectivity will prevail over the breadth of the client portfolio. This approach is consistent with Cognizant's push in consulting.

Cognizant continues to build its international onshore and nearshore presence, with recent onshore centers in Leeds, U.K.; Adelaide, Australia; and Halifax, Canada, while deploying its digital studio network globally (out of ~60 delivery centers). In total, Cognizant GGM has ~4k employees working in its digital studios out of a total of 86k employees servicing international clients.

Another strand of the push for accelerated growth is investments with partners. For instance, Cognizant GGM emphasizes its Enterprise Platform Services, believing Europe is more advanced than other corporate regions. The unit emphasizes specialized offerings and joint GTM with SAP, Oracle, Salesforce, Pega, Workday, Adobe, and cloud migration (e.g., SAP S/4HANA and Oracle Cloud). Beyond ISV practices, Cognizant has selected three broad themes (revenue management, SaaS application interoperability, and omnichannel) across ISVs. Again, the approach resonates in promoting a business approach rather than a technology sale.

Portfolio investments

Cognizant is aligning its service portfolio around a dual cost savings and transformation agenda. The company is targeting large IT outsourcing deals. It is also ready to accept build-operate-transfer deals to help clients grow their technology expertise through captives in India.

Cognizant GGM is preparing for a market rebound around Q4 this year. Platforms remain a priority. In the U.S., TriZetto remains a cornerstone of Cognizant's IP-based business, driving software product sales, C&SI services, and BPaaS services. Outside the U.S., GGM is targeting opportunities in English-speaking countries with a healthcare payer model similar to the U.S. model.

Cognizant GGM is also deploying IPs relevant to a growth agenda. For instance, through its Zenith and TQS acquisitions, it gained several IoT-related IPs such as Apex (industry 4.0), 1Facility (smart buildings), and its Sustainability accelerator. Cognizant also has its Meritsoft product for post-trade processing.

Unsurprisingly, AI is a priority. Cognizant was early among the major IT services providers in announcing its launch of an enterprise-wide generative AI platform (Cognizant Neuro AI, on May 15), an extension of platforms including Neuro IT Operations (AIOps), and Skygrade (application cloud migration, monitoring, and management).

Engineering services and Germany

Cognizant is making bets on two (out of six) geographical clusters: the Nordics and Germany. In Germany, the unit has done well in financial services, manufacturing and life sciences. It is looking to expand its presence in the large automotive market to rebalance its presence in Europe's largest economy. Cognizant's 2021 acquisition of ESG Mobility, now Cognizant Mobility, brought in 1k employees and next-gen ER&D capabilities around electric, connected, and autonomous vehicles, and significant relationships with automotive OEMs and tier-one suppliers.

Cognizant's prioritization of ER&D services goes beyond Germany: it has made several acquisitions in this area, including Mobica (2023, U.K., 900 employees, including ~500 in Poland) and TQS (2021, Ireland, 200, data historian analysis), complementing the large Zenith acquisitions (2019, Ireland, 800, industry 4.0 for pharmaceutical firms). Zenith brought specialized capabilities combining sub-vertical and technology expertise. With ER&D services being more verticalized than IT services, Cognizant’s dual positioning is key.

Expect further IP investments and M&As

What's next? Despite its recent slowdown in M&As, Cognizant signaled an appetite for investments in its service portfolio and a focused approach to geographical expansion, signaling growth aspirations rather than a restructuring story. While its dual positioning on vertical and technological knowledge is common, Cognizant demonstrated concrete examples beyond traditional consulting and systems integration (C&SI). We think the next step is building more IP, e.g., industry solutions in C&SI, and continuing the AI momentum. Also, expect more tuck-in acquisitions in Cognizant GGM. We think Nordics is the next candidate.

We recently talked with TCS’ Salesforce practice about its verticalization initiatives.

Product verticalization has been one of Salesforce’s key strategies (along with Customer 360/cross-selling and geographic expansion) since 2014, when it launched its Industries business unit. Like SAP, Salesforce acknowledges that organizations spend time and effort customizing their enterprise applications, and so it has broadened and deepened its vertical cloud offering, strengthened by its acquisition of Vlocity in 2020.

Despite its vertical push, Salesforce continues to rely on IT services partners to complement its vertical capabilities, acknowledging the role of its systems integration partners. Yet, the role of the service partner raises many questions about the nature of their vertical offering. Should a partner’s vertical offering be a product (sold with a subscription) or a solution (provided with the service)? Should it have functionality and an enhancement roadmap or be project-led? Should the partner offer point functionality, integrate with Salesforce applications, or provide a more comprehensive sub-vertical solution? Should the solution be available on AppExchange and go through Salesforce certification?

Our discussion with TCS’ Salesforce practice helped clarify what clients should expect and its verticalization effort with TCS Crystallus™ on Salesforce.

With Clay Maps, TCS combines a transformation methodology with systematic sub-process mapping

In the past two years, TCS has articulated its Salesforce verticalization strategy through its Clay Maps, which have two components:

• A systematic mapping of key sub-processes, targeting sub-verticals under disruption. The company has mapped these sub-processes with Salesforce functionalities across Clouds, going beyond erstwhile Vlocity to the full range of sectors (Salesforce Customer 360)
• A transformation methodology based on identifying the client’s goal and how this goal impacts the client’s business and, eventually, processes. TCS calls this their ‘go-to-market plays’. Examples include fraud prevention and detection for claims management in insurance and wellness insurance for healthcare payers.

TCS Crystallus: Adapting to Client Demand

Based on Clay Maps, and as part of its TCS Crystallus on Salesforce initiative, TCS created 90 artifacts ranging from PoVs to demos and solutions. Crystallus includes:

• For each sub-industry: a problem statement, impacted processes and code remediating the problem statement. TCS has ~30 of these go-to-market plays
• Approximately 30 pre-configured applications (based on TCS’ best practices) and 10 PoVs that eventually will become pre-configured applications
• 20 functionality white spaces for which TCS has developed reusable code components.

TCS Crystallus goes across telecom, media, technology, manufacturing, life science, healthcare, retail & CPG, public sector, E&U, BFS, travel & hospitality, and professional services.

TCS takes a pragmatic approach to its Crystallus artifacts: it will initially design PoVs, invest in a demo, and then a reference architecture and a solution, depending on client demand.

An example of a Crystallus sub-vertical solution is for healthcare providers. TCS has developed several roles such as the clinical educator journey, where the educator looks at patient records, enrolls the patient in care programs, and shares knowledge articles with patients. The Crystallus solution also provides dashboards and drill-down capabilities.

The company has designed a roadmap for its most successful solutions and will enhance them, primarily based on upfront investments rather than project-led developments. Overall, TCS provides the solutions as part of the service, although it does not rule out selling them for a subscription or a license if the client asks for the standalone solution.

TCS asserts it has also anticipated the future. Should Salesforce develop its own sub-vertical process or point solution, TCS will work with the client transitioning to the off-the-shelf functionality and remove dead custom code. TCS highlights that it has designed its TCS Crystallus solution as modular and will integrate with the client’s applications. The practice asserts that, as a top five Salesforce partner (based on certifications), it has access to Salesforce’s product roadmap, which it reviews.

TCS asserts that Crystallus is for the long term, and that further sub-vertical expansion is part of the journey. The company launches assets in the verticals brought by Vlocity/Salesforce Industry Cloud, e.g., in media, energy & utilities, and healthcare providers, with recent solutions for gas and energy transition and new Salesforce Cloud (e.g., CPG). TCS increasingly wants to design solutions across Salesforce products (‘multi-cloud’). Salesforce finds that the more Cloud products its clients have, the more loyal they are. This makes sense and correlates with Salesforce’s claims that its clients use it for creating a front-office platform. We think that clients will be even more loyal if they find sub-vertical Salesforce solutions that reduce customization work and maintenance costs.

Atos recently held its Capital Market Day for Tech Foundations. It is a year since the company announced its intention to spin off its high-growth units into a new company, Eviden, and keep its historic IT infrastructure services (and U.K. BPO capabilities) in an entity called Tech Foundations. Alongside the spin-off, Atos initiated a massive €1.1bn restructuring plan for Tech Foundations. The plan came on top of an ongoing restructuring plan in Germany for €180m.

A year ago, the outlook for Tech Foundations was mixed, with uninspiring objectives to reach positive organic growth in 2026 and an operating margin above 5%.

After its profit warning in July 2021, Atos had indicated that its IT infrastructure services business was under pressure and could not reduce its data center costs as fast as declining revenues from clients migrating to public cloud. The scale of Tech Foundations’ challenge in its core infrastructure business was considerable and included a large burden of underperforming contracts, representing around €750m in revenue.

Restructuring Is the Priority…

One year into the reinvention, financials are gradually improving, and Atos shares a more positive outlook. Tech Foundations is now targeting €5.0bn in revenues by 2024, significantly higher than the previous guidance of €4.1bn. Positive organic growth continues to be expected from 2026. And the operating margin target range has increased from around 5% to 6-8%.

Tech Foundations has made progress in some aspects of its turnaround: for example, it has addressed two-thirds of its red contracts. Progress with personnel downsizing has been slower: so far, 900 positions have been cut, primarily onshore, out of the total 7,500 planned. This reflects Atos’ large employee presence in Continental Europe, which has strong labor laws. Tech Foundations aims to increase its offshore ratio by 10 pts, reshape its pyramid, and gain further efficiencies from automation. The business is ramping down its little-profitable or non-synergistic non-strategic activities (~€900m), primarily its standalone VAR and several U.K. BPO activities.

… With Commercial Momentum

Tech Foundations had lost some of its commercial rigor. It is now looking to reignite its commercial activity. The business should benefit from the current market appetite for in-year cost savings and managed services contracts. Tech Foundations is focusing on the usual suspects. With cross-selling in mind, it focuses on add-ons in its top 100 accounts, targeting 13% of additional revenue. It has also expanded its large deals (€30m+) team, creating 90 new positions, and looking to standardize its large deal processes to drive repeatability. Tech Foundations is also regionalizing its IT outsourcing approach, giving more independence to the geographies for their service portfolio priorities. The unit has changed its incentivization scheme, with bonuses based on the first three years of the contracts and KPIs focused on profitability rather than organic growth.

There is also a much closer focus on contract performance, with a team monitoring contracts weekly.

Continuing to develop partnerships with the hyperscalers is naturally important, with AWS as a priority: the current AWS-related pipeline is €0.5bn and is expected to double within the next 12 months. The AWS CloudCatalyst partnership includes a commitment for AWS to provide training for 20k certifications. Another element of the partnership is that AWS will utilize Atos’ servers left free by clients migrating to the public cloud, helping Tech Foundations reduce costs.

Four Units with Different Priorities

Atos is refreshing its organizational structure. Tech Foundations now has four units: Hybrid Cloud & Infrastructure (HCI), Digital Workplace (DW), Technology Advisory & Customized Services (PS), and Digital Business Platforms (DBP):

• HCI is Tech Foundations’ largest business (€2.1bn). It faces revenue decline and is about reinvention (with new services such as hybrid and multi-cloud orchestration, edge computing monitoring, and enlarged partnerships), proactively helping clients migrate to the public cloud and a service catalog. Of those initiatives, CloudCatalyst with AWS is probably the highest priority for getting HCI back to growth after a couple of years of transformative decline
• DW (€1.2bn) is in a better position, enjoying revenue growth. And with UCC/Unify set for divestment, the unit is offloading a declining business. It emphasizes its transformation capabilities and existing or new offerings, e.g., XLAs, IoT/connected device management, and as-a-service offerings. It is leveraging gen AI for service desk level 1 automation
• PS (€0.9bn) is another Tech Foundations’ growth driver. The unit operates in an apparently unattractive market, staff augmentation in IT infrastructure services and, to a lesser extent, in application services. However, PS is Tech Foundations’ highest growth business and is highly profitable. The unit is introducing new offerings, such as technology advisory services, having launched innovation labs (Inno’Labs) to ideate with clients and create PoCs. It also created expertise networks (Tribes) to share knowledge across its 8k employees
• DBP prefigures the future of Tech Foundations and includes its hosted platform business. The business is small (€0.3bn) but includes the visible Sports Event unit known for its work for the Olympics/Para Olympics and the UEFA. It also has a digital ID business (with contracts in Togo and Morocco) and sustainability software products. DBP is a disparate business that goes beyond Tech Foundation’s IT infrastructure-centricity. Expect Tech Foundations to scale this business strategically.

Ensuring Best Practices Are Engraved at Tech Foundations

The future of Tech Foundations depends on ensuring its commercial, delivery, and service portfolio priorities are engraved into the company’s DNA. Achieving this is clearly a priority in the highly competitive IT services infrastructure market.

The business focuses on transformation contracts and being highly selective rather than only addressing run services.

Investment in automation continues: Tech Foundations was reassuring, showing early deployments of generative AI use cases.

The mid-term future of Tech Foundations lies in portfolio development. Relevant areas include cybersecurity services, particularly SOC/managed security services, and application services around native cloud development and migration. In both of these, AI and generative AI will play important roles.

NelsonHall recently attended Unisys’ Analyst and Advisor Event 2023 in New York. The tagline for the event was ‘Imagination to Realization’ and reflective of the new Unisys branding.

Mike Thomson, President, and COO, started the event with Unisys’ new NetZero Goal by 2030 and its vision to provide a single pane of glass for clients to manage their ESG and sustainability goals. The company supports ~11m end-users and claims a >90% renewal rate and an average tenure of ~20 years across its top 50 clients. Thomson highlighted Unisys’ focus on next-gen solutions across its four business units, including:

• Modern workplace experience
• Digital platforms and applications
• Specialized services and computing solutions, including IP SaaS-based product delivery 
• Micro market solutions.

Unisys aims to increase its mix of next-gen revenue to 45% by 2026 (as a percentage of ex-L&S revenue), up from ~35% in 2022, through alignment with high-growth markets (e.g., smart workplace, IaaS, app modernization, next-gen compute (inc Quantum AI), hyperautomation, and digital mortgage processing). Its traditional solution focus includes technology support services, infrastructure management, classical compute, and BPS.

In addition to targeting large-deal pursuits, Thomson highlighted that Unisys will also target the U.S. mid-market, focusing on enterprises with revenues of $2-5bn. The target industries in this mid-market include insurance, manufacturing, energy & utilities, travel and transport, and healthcare. Unisys sees an opportunity to expedite enterprises’ digital transformation initiatives, utilizing its industry expertise, partner ecosystem, SMEs, and focus on client intimacy.

Focusing on digital workplace 2.0

Joel Raper, SVP of Digital Workplace Services (who joined Unisys through the Unify Square acquisition in 2021), highlighted Unisys’ focus on automation, proactive monitoring, experience, and making their clients' employees more productive. Raper reiterated the foundational tenets across DWS, including:

• Workplace business insights
• Frontline services (inc. field technicians)
• Next-generation service desk
• Enhanced employee experience.

Unisys continues to invest in AI, automation, and analytics to support the modern workplace and the foundational tenets above. These include its PowerSuite (AI-powered data analytics and insights engine),  and through its PowerSuite Insights Center it applies real-time data insights to different scenarios, including driving correct automation or identifying which devices to remediate. Other use cases include RTO efficacy across hybrid, enabling remote and in-office employees to communicate in productive and collaborative ways. Another example includes Smart PC refresh and providing clients with intelligent guidance on PCs that matter, extending device lifecycle (also utilizing DEM tools to identify degradation), reducing cost, and addressing ESG and carbon reduction requirements.

Another key investment includes InteliServe vNext multi-platform automation library to drive the fastest means of issue resolution by identifying the most common automations across clients. It can expose automation through a self-serve chatbot, for example. More importantly, it can expose automation to L1 service desk agents, empowering them with the tools to enable remote endpoint troubleshooting and remediation. Key use cases include user onboarding experience, M365 service automation, and field service dispatch integration.

Expanding Experience Management Organization (XMO)

Unisys utilizes its XMO to support a data-driven workplace, enabling clients to move from reactive to proactive and then predictive workplace services. It allows a data-driven employee experience through XLAs that directly relate to the experience.

Unisys was awarded a contract to provide XM by a global manufacturer with a proactive approach to experience management focused on the client’s business goals and key personas within the organization critical to these goals. Unisys identified personas for the client R&D team, given their criticality to business goals. Results to date have included higher engineering output and a 15% NPS increase. Unisys also jointly developed an experience governance board (XGB) with the client to manage the lifecycle of XLAs. As XLAs plateau over time, Unisys uses the XGB to focus on the next XLAs and business imperatives to start addressing higher-priority issues and finding a fix.

Unisys is utilizing ML/AI to support predictive endpoint health, self-healing, persona insights, and hybrid worker capabilities across the workplace. It is also prototyping use cases in generative AI across DWS to address market opportunities. These include humanized and frontline chatbot, service desk assist, developer acceleration, and insights query reporting. It is ingesting knowledge bases into Unisys to provide a more curated experience.

Driving application and infrastructure modernization

Manju Naglapur, SVP of Cloud, Applications, and Infrastructure Solutions (CA&I), highlighted business/client opportunities with hybrid infrastructure clients looking to utilize multi-cloud management and move to an SRE/DevSecOps model to transform its existing client base. It aims to accelerate through a cloud-native digital-first approach, automation, and microservices framework.

Unisys continues to invest in its cloud solutions through M&A (e.g., CompuGain) and its IP CloudForte Asset Suite across cloud, applications, data & AI, and automation. CloudForte AIOps seeks to reduce incidents through self-healing and automation and drive insights through AI/ML to prevent outages using proactive analytics, anomaly detection, and automated resolution. In support of DevSecOps, it is focused on an SRE-enabled agile model and utilizes Stealth to provide a cloud-managed security solution. Unisys is investing in AI use cases, including generative AI, continuous delivery through AIOps, and applied AI supporting CA&I.

Increasing BFS market presence

Unisys’ Financial Services practice accounts for ~$600m in revenues across 230 global clients. It is building on its BFS market presence to deliver new services for banks across three pillars of service: 

• Core renewal: Unisys is partnering with core platform vendors to modernize client platforms. Typical uses cases include enhancing the digitalization of processes, AI, and data management
• Branch: digitalizing branch services and integrating them with third-party services vendors
• Digital: Unisys is developing AI-based offerings for:
  • Portfolio optimization: analytics to mitigate portfolio risk 
  • AML/Fraud mitigation: enabling dynamic risk assessments
  • Customer acquisition: assessing partner risk using quantum annealing techniques.   

The launch of the first product is anticipated to be in Q2 2024, and these offerings will target regional and local banks.

Outlook

Unisys is focusing more on using a consulting-led approach to support client outcomes, and we expect to see a further increase in dedicated business consultants. Across client services, it focuses on personalized attention, innovation, and a proactive partnership approach. It is also bringing in CTOs across accounts to bridge the gap between business and technology.

In parallel with its large-deal pursuits, its mid-market approach in the U.S. should provide easier access to decision-makers, expedite RFPs, and enable Unisys to leverage its client-intimacy approach and industry SMEs to support the enterprise’s digital transformation initiatives. Unisys will apply its learnings from large-deal pursuits to mid-market opportunities. It also has the opportunity to utilize its dedicated BFS offerings across target markets, in particular across tier two and three banks and insurance.

We expect bolt-on acquisitions supporting CA&I across automation, analytics, AI, and joint IP and GTM offerings with key hyperscalers. Across digital workplace services, we expect to see greater utilization of generative AI as current POCs mature. We expect continued investment across PowerSuite, InteliServe vNext, and AI-based OCM.

Through its XMO, we expect to see an increase in XLAs across clients through a hyper-personalized approach, and in its experience governance board to evaluate and evolve client XLAs continually. This investment aligns well with market demand for experience parity across hybrid work. We also expect Unisys to utilize its field services capabilities further to target frontline worker opportunities, and greater use of immersive technologies, including AR/VR.

Finally, we expect Unisys to increase, train, and up-skill its resources across AI/ML engineers, cloud architects, data scientists, and automation engineers to support a platform engineering approach and increased focus on automation.

The IT services industry has entered a new growth cycle, with increased emphasis on portfolio management and vendors increasingly divesting their low-growth, low-margin businesses.

IBM was an early example of this trend with its Kyndryl spin-off. Several of its competitors are also following this pattern, including Atos. At the same time, in the Nordics, Tietoevry will go one step further: the company will divest its infrastructure and half of its application services business. A much smaller vendor, NNIT in Denmark, sold its IT infrastructure business to private equity in May 2023. In these four examples, the companies are targeting higher revenue growth and margins by offloading their low-growth, low-margin activities.

The move may sound obvious. But portfolio selectivity certainly wasn’t the dominant message in the past twenty years. When communication service providers or hardware vendors entered the industry from the late 90s to the mid-2010s, their message was about end-to-end services and bundled (‘integrated’) services. Most major IT services vendors offered the full range of IT infrastructure and application services and expanded selectively to BPO and ER&D services. That approach still works well for some leading IT services vendors such as TCS but increasingly less so for a number of others.

Tuck-In Acquisitions Will Continue Apace

A consequence of the current portfolio focus and rationalization is that large M&As are decreasing. Instead, most tier-one IT services vendors are increasing their emphasis on tuck-in additions in areas such as digital, cloud, and security, and to a lesser extent in traditional areas such as consulting and SAP services, frequently in support of geographic expansion. Accenture, NTT DATA, and, more recently, IBM Consulting have been the most active in this respect.

In addition to the areas listed above, we expect selective expansion in growth areas such as AI and data, and further investment in front-office applications such as marketing automation. Also, we expect selective investments in ER&D services, targeting connected products and digital manufacturing/industry 4.0. And with rising defense budgets globally and more digital products, defense IT should also be on the agenda. Yet, for sovereignty and security reasons, the increased defense IT spending will benefit only firms partnering with local defense firms.

Acquiring small but high-growth specialist firms currently makes sense. Yet, in previous cycles, many IT services vendors targeted mid-size to large competitors rather than tuck-ins to avoid talent exodus resulting from a small and flexible firm being absorbed into a larger and more process-oriented entity.

Overall, this growth cycle is about organic growth and increased margin. The leading vendors will avoid using their cash on major expansions into new, more speculative areas and stay close to their roots.

PEs Looking to Exit IT Services Investments

Private Equity attitudes towards IT services firms have also changed. With (still) rising interest rates, access to M&A funding has become more costly, primarily impacting PE. We will see less PE activity around acquiring IT services firms in the next few years, as highlighted by the failed DXC take-over. Valuations should go down. In the meantime, several PEs will want to exit their IT services investments (e.g., Virtusa, Coforge, Hexaware, Expleo, Inetum, Engineering).

We recently talked to Qualitest about its latest acquisition, Q Analysts, its sixth since 2019. Qualitest has been on an accelerated transformation journey under the ownership of PE BridgePoint. Q Analysts further strengthens Qualitest’s capabilities in next-gen digital QA, with expertise in testing AI-based devices such as AR/VR/MR headsets and generating data for training AI models.

Qualitest Has Accelerated its Transformation

Qualitest has bold growth ambitions targeting $1bn in revenues by 2026, and in support of this, it has further shifted its delivery network to India to gain scale. The QA Infotech and ZenQ acquisitions helped significantly in this respect. NelsonHall estimates that Qualitest has ~45% of its headcount in India, or ~3,400 FTEs. We expect this India-centricity to increase further.

Qualitest has also further verticalized its GTM, its salesforce now being organized around the following industry groups: technology, BFSI, healthcare & life sciences, telecoms, utilities, retail, and media & entertainment. In parallel, Qualitest has expanded its focus from its core technology clients to BFSI (now 30% of revenues, on par with technology). It recently strengthened its healthcare and telecom expertise with the Comply and Telexiom transactions.

The company is specializing its service portfolio and, at the same time, investing in automation. Continuous testing remains a priority. The 2019 acquisition of data science company AlgoTrace jumpstarted Qualitest’s expertise in AI-based testing. NelsonHall believes that AI-based automation will disrupt the QA industry by automating the generation of test scripts and breaking the lengthy requirement-test case-test script cycle by removing the test case phase.

Q Analysts Brings Specialized Testing Services for AI-based Connected Devices

Qualitest has developed its digital services portfolio beyond traditional mobile app testing, introducing next-gen offerings. The acquisition of Hyderabad-based ZenQ brought in capabilities around blockchain and testing connected devices such as smart homes, pet care, fetal health, and drones.

Now, the acquisition of Q Analysts further increases Qualitest’s investment in digital testing offerings, looking at products described as ‘AI-infused devices,’ i.e., AR/VR devices and virtual assistants.

Q Analysts currently services tier-one technology firms engaged in AR/VR/MR, wearables, and virtual assistant devices. The company has ~600 employees, is headquartered in Kirkland, WA, and has offices in Santa Clara, CA. Q Analysts has testing labs in Kirkland, Santa Clara, and Antananarivo, Madagascar. It has structured its portfolio around two activities: testing of ‘AI-infused devices’ (60% of revenues); and generating training data for these devices (40% of revenues).

The company has worked on AR/VR testing activities, often at the prototyping stage. It offers a full range of services, from devices to mobile apps, web applications, usability testing, and back-office integration testing. As with mobile devices, AR/VR devices bring specific QA activities, such as assessing the performance of an application on a device and estimating the impact of running this application on the device’s battery.

Q Analysts highlights its expertise goes beyond device testing. The company’s sweet spot is assessing image and video rendering on the device. The company has invested in its workforce to identify rendering issues such as image refresh rate or pixelization, a capability only a trained human eye can spot.

The company continues to invest in visual testing in the AR/VR/MR space. For example, the company tests new technologies such as foveated rendering (i.e., the devices have in-built inward-facing cameras to track a user’s eye movement and render images of higher resolution where the eye is focused) to minimize energy consumption and make device batteries last longer. The company considers visual testing to be key and requires advanced visual and technical skills.

Q Analysts’ second activity is generating training data or ‘ground truth data services’, a term borrowed from the meteorology industry. The company will generate training data in its labs and capture images and movements required using cameras and LiDAR scanners. Q Analysts’ know-how comes into play by generating datasets based on its client’s demographics and providing several real-world simulated set-ups, such as living rooms and offices and other variances (such as furniture and interior decoration). Q Analysts also provides related specialized services such as manual 2D and 3D image tagging to help train AI models.

High Potential Ahead

Qualitest has big ambitions for Q Analysts based on the expectation that demand for connected ‘AI-infused devices’ will expand from its product engineering niche. The use of AI-infused devices will become increasingly common across industries; for example, retail (virtual try-on), healthcare (physical therapy and 3D models), and energy & utilities (digital twin-based training). Longer term, Q Analysts targets the metaverse, expanding from its AR/VR and other AI device niche to the larger virtual world opportunity.

Complementing Q Analysts’ specialized capabilities, Qualitest brings increasing expertise in AI-based automation, including computer vision testing and connected device test automation. Client demand looks limitless, and Qualitest is building its next-gen testing expertise to address that demand year after year.

NelsonHall recently completed an in-depth analysis of cognitive & self-healing IT infrastructure management services, researching the capabilities of leading IT services vendors and the requirements of their clients. This blog looks at the investments vendors need to make to meet client demand, and how the market will evolve over the next 12 to 18 months.

While there is an increasing focus on utilizing AI and automation to deliver value across every business function within an enterprise including, for example, providing CFOs with contractual commitments to automation-led savings, the use of automation and AI is arguably most advanced in IT infrastructure management.

This increased use of automation and AI within IT infrastructure management is leading to:

• Increasing demand for SRE-led operations to support greater predictability across the full-stack
• A massive ramp-up in digital reskilling and the emergence of new skill sets
• Increased focus on sustainability and ESG.

Increasing demand for SRE-led operations to support greater predictability across the full stack

To achieve a NoOps environment, enterprises need to adopt a real-time data insights-driven approach, with SREs approving self-heal solutions and machine recommendations and developing algorithms for AIOps and automation use cases.

AIOps is already being deployed to trigger automation to auto-remediate, fix issues, detect anomalies, and reduce noise across operations. End-user outcomes typically achieved so far include ~40% improvement in MTTR, ~50% reduction in P1 incidents, and ~65% of incidents autonomously resolved. However, there is scope for more.

AIOps needs to support both full-stack monitoring and accommodate existing enterprise investments. It enables the accommodation of rapid infrastructure changes across hybrid, private cloud, and on-premise; and in addition, the full-stack monitoring of resources in the cloud and on-premise. Enterprises also want modular, plug-and-play AIOps platforms utilizing vendor IP and third-party tools across their ecosystems. The modular approach is important for supporting the existing brownfield automation investments made by enterprises.

There will be increased investment in automation and IaC to enable developer-centric models that extend from DevOps to DevSecOps to NoOps in an agile manner and use DevSecOps to support cloud-native applications. Vendors will continue to expand their use cases and focus on hyper-automation to enable client transition to a future NoOps environment. This involves continuing to develop libraries of AIOps use cases to manage operations across the full stack and achieve 40-50% reusability of assets.

In addition, over the next 12 months, vendors will increasingly focus on dedicated experience centers, supported by SRE teams that look at the performance and experience aspect of IT service delivery and proactively monitor end-users’ sentiments as they engage across services and XLAs (and increase client-specific XLAs by persona). At the same time, there will be greater standardization of XLAs in support of a NoOps environment.

Massive ramp-up in digital reskilling & emergence of new skill sets

The investment in digital reskilling and new partnerships continues at pace. We continue to see traction in digital re-skilling, hyperscaler, and ecosystem partner certifications along with AI architects, cloud-native SMEs, and business value specialists. All vendors are ramping automation academies, proactive experience centers, AI, and Cloud CoEs to monitor performance through a data-driven approach. They enhance what SRE and automation teams learn from operating cloud and infrastructure environments.

In addition, newer skill sets are emerging, including machine coaches developing algorithms for AIOps systems, data modelers, and domain SMEs to support unified business semantics. For example, Kyndryl is developing higher-level skill sets at L2/3, including automation assessment architects and client success engineers. TCS is using its cloud units as a catalyst for change across the organization, enabling infrastructure specialists to become full-stack architects. The company is also expanding its Cloud Service Reliability teams and service reliability engineering approach to operations supported by SRE CoEs, and expanding its value builders within TCS Cognix, to enable autonomous operations through AIOps and MLOps. Likewise, Infosys is developing SRE automation skill sets supporting its Polycloud platform across ~96k employees in the cloud and infrastructure services unit; and Cognizant has developed an automation-in-a-box self-service playbook for account delivery teams. Plus, DXC Technology has developed an automation roadmap by capability persona, with 90 big plays across ITO and cloud to improve each persona.

We see more focus on intelligent OCM to drive digital adoption and device and sentiment insights to inform training methodologies and technology adoption rates. Unisys, for example, applies AI to its OCM engine to target and tailor technology adoption and updates, training, and enhanced experience by persona.

We expect increased investment in AI-based platforms, strategic ecosystem partnerships, and a greater focus on joint IP and GTM with hyperscalers.

Increased focus on sustainability and ESG

Investment in cognitive and self-healing IT infrastructure management services will continue at pace, focusing more on SRE-led operations by default. This in turn will lead to an increased focus and investment in sustainability and ESG, helping clients reduce carbon footprints. TCS, for example, through TCS Cognix for agile infrastructure, adopts a sustainability-by-design approach to drive configurable, composable, and automated infrastructure to adapt the cloud to ESG needs. DXC Technology has developed an ESG data intelligence and reporting solution. In addition, Infosys is rapidly expanding its sustainability practice to support enterprises’ ESG agendas.

Outlook

Investment in cognitive and self-healing IT infrastructure management services will continue to ramp, focusing more on SRE-led operations, including full-stack organizational structure for delivering digital transformation through productized offerings.

Vendors need to focus on automation and cloud academies, AI-enabled learning assistants, and platforms to expedite training. We expect to see expansion in the developer community for automation use case development and deployment; and finally, more focus on hyper-personalization, including developing industry-specific personas and creating AI solutions and use cases to fit key business requirements.

A New Focused Division 

BT has announced the merger of its two ICT services units, Global and Enterprise, into a new division, BT Business. The new division will have pro-forma revenues of £8.5bn and an EBITDA of £2bn. The current CEO of Global will lead BT Business.

With this move, BT wants to unify its B2B market and focus its capabilities on connectivity, unified communication, networking, and security. It also wants to simplify its GTM for its corporate and public sector clients and remove duplication across Global and Enterprise.

Cost savings are an important element of the merger, with BT targeting cost savings of £100m by FY25 through consolidating management, support functions, product portfolios, and IT.

Financial Pressures

For the 3Q ending September 2022, the BT Group reported revenue of £10.4bn, up 1% due to growth in its Consumer and Openreach segments,  and partially offset by legacy declines in large corporate customers in Enterprise and lower equipment sales in Global. Large corporate accounts and the decline of legacy products continue to present a challenge to the BT Group.

Global and Enterprise suffered from the pandemic, with revenues down by 14% and 8% respectively in FY21 (the year ending March 31). However, the two units did not benefit from the digital and cloud catch-up after the pandemic. Revenues were still down in FY22 (by 10% and 5% respectively) and in H1 FY23 (by 2% and 5% respectively).

The decline of Global and Enterprise reflects, unsurprisingly, portfolio changes. Global suffered from lower equipment sales and divestments (in Spain, Latin America, and France). Enterprise has suffered from the decline in legacy services, such as fixed telephony, despite mobile and VoIP growth in the SME and SoHo segments.

EBITDA struggled under pressure despite efficiency actions taken by BT, from its FY 22 in March, where EBITDA was down for Enterprise and Global, by 4% and 23% respectively, YOY. The decline continued into the results for the six months reported in September 2022, with Enterprise (23% down) and Global (5% down) for the six months YOY.

Fiber Deployment

The creation of BT Business is part of a larger cost savings program, with BT targeting £3bn in cost optimization by FY25. BT announced in November 2022 it wanted to save operational costs to fund its investment in deploying fiber options, OpenReach, throughout the U.K. The company targets 25m home and business customers by December 2026, up from 9m in December 2022. The investment comes at a time when BT, like many other European firms, faces rising energy costs. BT’s needs for investments do not stop with fiber deployment. The company is also investing in deploying 5G.

BT Business Outlook

Global and Enterprise had overlapping offerings and also suffered from internal competition on the large U.K. accounts. The merger should help BT Business simplify its GTM and achieve cost savings. It should help the new division to invest more in specific areas, e.g., digital, cloud, and security for large enterprises.

The merger will, however, probably not solve BT Business’ exposure to traditional voice and equipment resale, whose revenue decline has been long-lasting. BT Business will need to develop high-growth offerings through M&As to increase its service mix. Also, given the growing overlap between telecom and IT services, we think that BT Business will need to further lower its cost structure by increasing its India delivery network.

BT Business keeps an important SoHo and SME business, which intrinsically have different dynamics than ICT services to large enterprises. BT has a good track record in packaging services and offerings to its clients. The deployment of fiber and 5G should help the company gain market share in this customer segment. The question is whether this customer segment should be part of BT Business or BT Retail.

Certainly, between the two divisions, better clarity on customer focus and reduction of duplicative services and roles like solution and deal architects, financial analysts, and bid managers will provide the focus that the two units need and assist in meeting BT Group’s financial goals.

The new BT Business division will report as a single unit from April 1, 2023.

We recently talked to Tata Elxsi, the engineering and R&D services vendor headquartered in Bangalore, India. We discussed where the adoption of AR/VR is currently among enterprises, how the metaverse differs from AR/VR, and which B2B use cases enterprises will prefer in the short to medium term.

The current demand for virtual reality (VR) is primarily driven by the gaming industry. With the advent of Augmented reality (AR), there is currently strong demand by enterprises in support of training; for example, for equipment setup, and remote maintenance & repair. Demand here was boosted by the pandemic and remains steady, partly because of reduced factory floor personnel and operator attrition. While metaverse use cases often take part in a virtual world, the metaverse is not VR.

Metaverse Will Encompass AR

Recent news from Meta has been mixed, with the company suffering from slow user acceptance. Yet, like Meta, Tata Elxsi sees a promising future for metaverse adoption by enterprises over the next decade. It highlights that metaverse use cases will cover a broad range of functionalities such as payments (enabled by blockchain), digital twins, and training. From a conceptual perspective, the range of possibilities is limitless.

An example of a digital twin use case, in the automotive industry, is vehicle twins, which display sensor data for things such as engine temperature that can be monitored and used for prescriptive and predictive maintenance. Tata Elxsi sees digital twins being widely used across sectors, such as car leasing firms, banks, and OEMs expanding their financial services arms. This digital twin use case already exists, and its adoption is rising independently of the metaverse.

So where does the metaverse help, compared to AR? Tata Elxsi sees the metaverse as multi-channel, therefore integrating AR and other interaction means (e.g., web browsers and .exe files on desktops). It also highlights that the metaverse has a richer ecosystem and can handle several individuals (as opposed to only one in AR applications). The metaverse also includes virtual passive objects and AI-governed avatars. Tata Elxsi believes that 40% of assets and persons in the metaverse will be virtual.

Tata Elxsi believes that the metaverse opens new use cases, such as virtual corporate events, which AR cannot currently handle. For the firm, UX will play a big role in driving the usage of virtual events.

The Metaverse Has a Ten-Year Horizon before Enterprise Adoption

Tata Elxsi sees, over the next decade, technologies aggregating and complementing each other to form metaverse applications. A key element of the metaverse’s success will be standards and reusability, driving standardization of technology and faster implementations.

The emerging notion of AR Cloud will bring standard architecture and technologies that can be reused as part of AR and within a metaverse. An example of a standard common feature is the GPS-based location of a virtual building in the metaverse. Tata Elxsi points out the potential use of virtual buildings as training centers where employees gather to attend classes and workshops.

The extent of widespread adoption of metaverse platforms and AR Cloud will depend on several requirements, including the deployment of 5G to handle the bandwidth-intensive AR immersive experience. The weight of AR devices, which will decrease from 1kg to 20 grams in the next few years, will drive user adoption and price reduction.

On a ten-year horizon, Tata Elxsi highlights that the evolution of metaverse platforms will be self-governed and cannot be directed by one specific company (meaning Meta, in NelsonHall’s opinion). The metaverse will be a result of a mixture of new or yet-to-be-discovered technologies. Tata Elxsi is maintaining a flexible approach to the metaverse and will continue to evaluate technologies and use cases.

We recently talked to Cognizant about its Salesforce Marketing Cloud capabilities.

Within the Salesforce portfolio, Marketing Cloud, along with Commerce Cloud, is a high-potential product that will eventually outgrow the more mature Sales and Service Clouds. More than any other Salesforce product, Marketing Cloud has grown through M&A, notably ExactTarget (that came with B2B marketing ISV Pardot) and Datorama (analytics for marketers).

Cognizant primarily built its Marketing Cloud capabilities with its 2020 acquisition of Lev, with Cognizant transferring its Marketing Cloud practitioners to Lev. As Cognizant’s Marketing Cloud practice, Lev has now reached around 600 consultants globally and is one of Salesforce Marketing Cloud’s largest service partners.

Lev’s preferred entry point with Marketing Cloud projects is consulting, with a maturity assessment of the client’s Marketing Cloud instance, followed by creating roadmaps for the transformation program to help the client exploit more Marketing Cloud features and functionality. Lev also offers organizational audits, process improvement, and license/subscription expense rationalization.

Addressing Marketing Cloud’s Large Portfolio

Lev’s capabilities span the full range of Marketing Cloud sub-products, ranging from the core Engagement sub-product (initially based on ExactTarget) to the emerging Customer Data Platform, Personalization (the former Interaction Studio), Intelligence (Datorama acquisition), and Account Engagement (Pardot acquisition).

Most of Lev’s work is around the Engagement sub-product, primarily Email Studio, Journey Builder, Mobile Studio, and Ad Studio. Lev works with clients to transform their email initiatives, automating email campaign management triggered across the customer journey. It uses Contact Builder to clean data and remove redundant accounts to improve data consistency.

Lev supports client scenarios such as organizations expanding multi-channel communications (e.g., expanding from email ISV to SMS and WhatsApp) and migration from legacy email service providers. In both scenarios, Lev will focus on migrating/transforming assets such as email templates, content areas, images, and documents to the Engagement sub-product.

Expansion in BPS

Lev has gone beyond IT services with Engagement and expanded to:

• Digital advertising agency activities such as campaign management BPS
• Creative services such as email visual design, copywriting, and content strategy and creation
• Paid ad management, helping clients define their campaign’s objectives, segment their audience, purchase the right advertising online, and monitor their effectiveness
• Translation and localization services for clients with multi-country campaign needs.

Lev sees campaign management and creative services as one of the entry points into an account.

Lev has developed two products that complement Salesforce’s Marketing Cloud:

• Campaign Studio, which helps organizations migrate marketing assets to Engagement and monitor campaigns at the enterprise level, and shorten time to create complex emails, audiences, and send schedules
• Abandoned Cart, which monitors abandoned carts on Commerce Cloud and can trigger email reminders.

Increased Joint Initiatives with Cognizant in Sales and Delivery

So, what next for Lev?

Lev continues to invest in emerging Marketing Cloud products:

• Personalization, formerly known as Interaction Studio, for tracking customer behavior, identifying customers to connect unknown and known customer profiles, and connecting with Sales Cloud to enrich customer profiles
• Intelligence, formerly known as Datorama, to offer a marketing reporting tool that can be used by marketing professionals and provide specific KPIs such as cost per lead or cost per click
• Salesforce Genie, formerly Customer Data Platform, for unifying the customer data profile, and enabling declarative segmentation and activation.

The emphasis is on helping organizations adopt enterprise-wide Marketing Cloud programs, focusing on marketing asset and data model standardization and application integration with Salesforce Sales Cloud and third-party applications. Lev believes that Cognizant’s capabilities around API and MuleSoft and overall data expertise will help while it specializes further in the marketing domain.

Lev is also looking to benefit from Cognizant’s scale and recruitment engine. It has now coordinated its sales and marketing activities with the larger Cognizant. Look to see some offerings verticalized, in conjunction with Cognizant’s sector units, other Salesforce practice units such as ATG, and of course, Salesforce’s vertical Clouds. Any such verticalization journey will require close internal and external coordination.

Software testing continues to be an industry of contrasts: the primary activity, functional testing, remains a human-intensive activity, despite the accelerated adoption of continuous testing (i.e., bringing functional automation as part of DevOps).

But testing has also grown in a highly specialized set of activities, earning the name of Quality Engineering (QE), ranging from support activities, test data and test environment management, shifting both left (early in the software lifecycle) and right (to application monitoring and now site reliability engineering).

Nevertheless, the most exciting event in QE remains the usage of AI to automate the creation and maintenance of test scripts. We think that despite somewhat limited adoption, automated script creation has the potential to redefine the QE industry.

Test Script Maintenance Will Become Easier

We talked to Cigniti about its recent investment in its iNSta IP to automate test script creation and maintenance. Cigniti repositioned iNSta two years ago, from a testing framework, as its primary automation point, aggregating all automation and specialized services. The company promotes it as an 'AI-enabled low code scriptless test automation platform'.

Now the company has enriched iNSta with its core Intelligent Recorder.

iNSta's Intelligent Recorder will create test scripts on the fly when a user goes through a transaction in an enterprise application. It will identify UI objects and build an object library to maintain test scripts. Intelligent Recorder will scan the UI for each release and identify changes in the UI. The maintenance of such test scripts is, we think, of high importance. Cigniti finds that 5% of test cases are outdated or not in sync with the current release and will lead to false positives or testing failures. The company continues to add incremental enhancements: should Intelligent Recorder fail to recognize that an object has changed, it will use computer vision to compare screen images of two different releases, identify the objects that have changed, and amend its object library.

Cigniti also accelerated the speed of execution of iNSta, relying on conducting test script execution in parallel across several VMs and containers. The company will add VMs/containers automatically through a scaling-out approach. With this offering, Cigniti wants to address development organizations operating in agile/DevOps with requirements for short testing timelines. It also targets applications that require extensive use of AI, which typically slows down test execution.

Cigniti also complements iNSta with automated test script creation, using NLP technology to translate English-written test cases from Excel and ALM into test scripts. Cigniti has created a dictionary and will custom dictionaries for its clients. The company finds that its English language translation AI model brings more benefits than the Gherkin language, as BDD requirements are done by testing specialists and not by business users. Nevertheless, Cigniti is also integrating its BDD framework in iNSta.

A strength of iNSta is that the Intelligent Recorder and the NLP translation are interoperable, and users can go back and forth between the two approaches. This maximizes, we think, the possibility of automation and helps with test script democratization.

New Opportunities with E2E Testing

AI is also opening QE to new testing opportunities. To a large extent, functional testing tools such as HPE/Micro Focus UFT and open-source Selenium have focused on one application technology. Still, they cannot operate across mobile apps, web, client-server, and mainframe applications.

Cigniti has expanded iNSta's Intelligent Recorder from web applications to mobile apps and client-server applications. This opens more automated test script opportunities. It also opens up business process/E2E automation opportunities. Several industries, including telecom, banking, retail, and government, have processes operating across different application technologies. Until now, E2E testing had to be manual or relied on RPA tools/bots.

Cigniti also intends to host iNSta on the cloud and sell it as a PaaS tool to favor its adoption. In the meantime, it will expand the Intelligent Recorder to SaaS applications (e.g., Salesforce), mainframe applications, and APIs.

We think the QE industry now has the technology to challenge the requirement-test case-test script model, and now is the time to focus on organization adoption. Cigniti highlights that initially, clients are hesitant to adopt iNSta due to organization and skill changes. We expect Cigniti to spend time with its clients evangelizing the market, relying on its QA consulting unit, and helping clients on OCM. More than ever, testing (and IT) is also about people's buy-in. We think tools like iNSta will help testers focus on more gratifying tasks such as analysis and remediation. This is good news for the industry.

We recently talked to ValueMomentum about its QE approach to product-centric development and testing. The company is helping its insurance clients improve the quality of their applications using agile best practices and DevOps tools. In support of this, ValueMomentum has refreshed its automation approach and created a continuous testing platform articulated around design (shift-left), execution (through automation), and monitoring (shift-right).

Most tier-one QA vendors today have their own continuous testing platforms, and these have become the backbone of test automation. Indeed, such platforms currently aggregate most of the existing automation and IP, running automation as part of each release cycle. These continuous testing platforms differentiate by adding new automation features to core automation.

Making Continuous Testing the Aggregation for Test Automation

ValueMomentum is investing in continuous testing through methodologies and adding new automation features. The company uses BDD, for instance, as it believes the Gerkhin language remains the best alternative for business users to write test cases that are automatically converted into test scripts, thereby reducing ambiguity in requirements. The company complements its BDD centricity with pre-defined business process diagrams for the insurance industry using MBT (Mantiz).

During the shift-left phase, to promote quality in the development phase of the project lifecycle, ValueMomentum has integrated code-related services into its continuous testing platform (e.g., unit testing and code review); test support services (e.g., test data management and service virtualization; AI-based analytics (such as code coverage and test impact analysis, and static code analysis); and non-functional (e.g., testing, and automated vulnerability assessment). As an example of its investment in AI, ValueMomentum is fine-tuning its defect prediction AI model by increasing data sources, from past defects to code changes in the release and developers’ coding quality.

In the testing environments, once the application release is completed, ValueMomentum uses a mix of full functional test automation (E2E testing) complemented by exploratory testing to maximize the chances of catching bugs before production.

Shift-Right Is the New Frontier. AI Will Help

Shift-right continues to be one of the open frontiers in the QE industry. Feeding back production information to the dev and test teams in an automated manner is still a challenge. AI is increasingly being deployed, but there remains considerable growth potential for its use.

ValueMomentum is accordingly investing in shift-right. Beyond APM tools for application monitoring, the company uses AWS tools for cloud applications, e.g., Canaries (monitoring of the performance of end-user devices), A/B testing (usability research), Game Day (simulating a failure or an event to test applications, processes, and team responses, similar to chaos testing), and rollbacks (redeploy a previous application release using CodeDeploy).

And indeed, ValueMomentum is gradually making its way to Site Reliability Engineering (SRE), where production specialists monitor applications and work with developers to remediate application issues quickly. For now, ValueMomentum is taking an AWS approach, relying on point solutions tools that AWS provides. It is fine-tuning AI use cases such as test case recommendations, defect triaging, defect-to-test case mapping, test case optimization, system comparison, and test case search. This is just the beginning of AI in shift-right for QE.

TCS recently briefed NelsonHall on its approach to site reliability engineering (SRE) in the context of quality engineering (QE).

SRE emerged almost a decade ago as part of the shift-right move, targeting production environments beyond traditional IT infrastructure activities such as services desk and monitoring activities. While no definition of SRE has fully emerged, TCS points out that SRE focuses on two topics: resiliency and reliability, through with observability and AIOps, automation, and chaos engineering as key services.

TCS prioritizes cloud-hosted applications for its SRE services, as cloud hosting increases the likelihood of application outage since applications that have been migrated were not initially designed and configured for cloud or multi-cloud hosting.

Generally, there has been very little SRE in QE activity, even though the industry has emphasized shift-right for several years. The shift-right notion in QE refers to feeding back production information to dev and test teams, breaking down the traditional silos between build and run activities. And in activities such as application monitoring (relying on the APM tools) and associated AI use cases (to make sense of APM-triggered events), the classification of defects found in production, and in sentiment analysis, have become common.

We think shift-right activities can still be improved, building on monitoring activities. Chaos engineering is a good example of a developing proactive service. More importantly, the feedback from production to dev and test needs to be improved, and we think SRE will help here.

Observability/Monitoring, AIOps, and Chaos Engineering

TCS' approach to SRE relies on application monitoring, AIOps, automation, and chaos engineering. Application monitoring ('observability') remains at the core of TCS' portfolio. For this, the company will deploy APM tools, collect logs and traces, and provide reporting. One of the challenges in application monitoring is data dissemination across different applications and databases. Accordingly, data centralization is a priority for TCS.

Once it has collected monitoring data, TCS deploys AI models (AIOps) to automate event detection and correlation and eventually move to a prediction phase. TCS' main AI use cases are predictive alerts, root cause analysis, event prioritization, and outage likelihood. The company will use third-party tools such as Dynatrace (combined with application monitoring) or deploy its own IP, depending on the client's tool usage.

For deployment and recoverability, its next step after AIOps, TCS will complement application deployment with automated rollbacks and ticket creation. At this stage, when facing application defects, the SRE team will also involve the development teams to conduct RCA and fix application defects.

TCS will also conduct chaos engineering. Chaos engineering complements performance engineering and testing in that it evaluates applications' behavior under more strenuous conditions. With chaos engineering, TCS will conduct attacks such as instance shutdown, increased CPU usage, and black holes to assess how the applications being tested behave. TCS has integrated tools such as Gremlins and Azure Chaos Studio in its DevOps portfolio to embed chaos engineering as part of continuous testing.

Demand Is Still Nascent

TCS typically deploys SRE teams of six engineers for monitoring applications. It highlights that SRE adoption is still nascent, and it will lead such programs with marquee clients initially.

In broad terms, the future of SRE lies in DevOps and becoming part of continuous testing, where all activities are scheduled and automated, for new build/release execution. TCS is an early mover in this area and is currently honing its tools and consulting capabilities. Platforms combining tools and targeting comprehensive services as part of continuous testing are the company's next step.

We recently talked to NTT DATA about its pending acquisition of Apisero, announced last month.

NTT DATA has been through significant changes recently with its merger with NTT Ltd. NTT Ltd. grouped a wide range of network and connectivity services, hardware and related services, data center hosting, IT infrastructure services, and resales. The resulting NTT DATA is now a giant with revenues of ¥3.5tn (~$26.2bn) and 180k personnel, larger than Fujitsu’s Services unit. NTT DATA has largely unified its brands over the years while maintaining the NTT DATA Services brand for its North American operations.

The company continues its M&A activity, with Apisero bringing scale in digital and cloud. Apisero is a MuleSoft and Salesforce consulting partner headquartered in Chandler, AZ, with additional offices in Vancouver, Strathfield, Barcelona, Dubai, and India. The company services U.S. mid-sized firms and has approximately 2,000 specialists, including around 1,500 MuleSoft practitioners and around 500 Salesforce consultants. Apisero has an India-centric delivery model, with 90% of its employees based in India (in Pune, Mumbai, Delhi, Kolkata, Ranchi, Bangalore, Hyderabad, Guwahati, or Chennai). NTT DATA highlights that Apisero is enjoying very strong growth (NelsonHall estimates around 30% topline growth), outgrowing even Salesforce, which continues to benefit from robust market demand. In its latest quarter, Salesforce reached the same revenues as SAP.

Apisero is a strategic acquisition for NTT DATA as it will almost double its size in the key Salesforce service market. We estimate that the combined Apisero NTT DATA will have around 5,000 Salesforce practitioners (including MuleSoft) globally: Apisero will definitively place NTT DATA among Salesforce’s largest partners.

Apisero will also significantly strengthen NTT DATA’s capabilities in MuleSoft’s API-based integration niche. Salesforce has positioned MuleSoft as the glue for integrating its Cloud products, especially around Customer 360, aggregating customer data from Salesforce and external applications. And, of course, MuleSoft continues to expand outside the Salesforce ecosystem. While Apisero will bring mostly professional services to NTT DATA, it also has several MuleSoft-certified connectors for ISVs, whether significant SAP Hybris and Splunk or niche, Redox (EHR) and Metrc (marijuana industry).

A Game-Changer for NTT DATA in North America and India

More broadly, Apisero will be a game changer for NTT DATA in North America. It will quadruple its headcount in North America/India to around 2,700 and rebalance NTT DATA’s delivery network to India, primarily around MuleSoft.

Finally, Apisero will bring to NTT DATA North America around 500 Salesforce consultants, primarily around Sales Cloud. Even though Sales Cloud is one of the more mature Salesforce products, it has continued to enjoy 15-20% organic growth. Its potential remains important, including in the SME sector.

A Recruitment Engine

NTT DATA’s short-term priority is to let Apisero continue with its high growth and disseminate Apisero’s best practices across the group. In one example, Apisero will bring in an automated and structured recruitment and upskilling engine primarily in India, which will help NTT DATA to scale up faster.

NTT DATA shows the offshoring potential for MuleSoft’s technical activities; the company is looking to expand from the U.S. and sell MuleSoft offshore services to its client base globally.

Meanwhile, NTT DATA continues to be busy with its existing Salesforce capabilities. It recently benefited from integrating NTT Ltd.’s operations, which brought a Salesforce service business in South Africa through the legacy Dimension Data.

NTT DATA will now need to digest its recent acquisitions: expect to see a pause in M&A activity while it focuses on sharing best practices, offerings, and its delivery organization across the Salesforce practice in its various geographies.

We recently talked to Infosys about how its Engineering and R&D services portfolio addresses sustainability and the circular economy, given the strong client interest in sustainable product design.

Infosys has accordingly evolved its sustainability engineering offerings from a series of capabilities into a portfolio that is articulated along three product lifecycle phases: design & development; manufacturing & operations; and aftermarket services, including product retrofitting and recycling.

Product Design and Development Is Core for Sustainability Engineering

Product and design development is at the core of any sustainability offering. Infosys’ design and engineering experience in this space ranges from energy-efficient products to sustainable products. An example of recent work is a radiant baffle, which Infosys initially designed for its internal needs. The radian baffle cools temperature by removing heat, mainly through heat transfer radiation. Infosys argues that the radian baffle internally reduced per capita energy consumption by 26%. The company points out that A/C equipment accounts for 40-50% of a building’s energy consumption in India, and Infosys  is now marketing it externally.

Infosys is also active in designing sustainable products. An example of a recent project is a green scoring dashboard that collects product-related components and parts information. It uses an AI model to determine a ‘green score’ based on the component impact on the environment and health.

Regulatory compliance is an important driver for sustainable product design. Infosys created its full material disclosure (FMD) dashboard designed for the chemicals industry. Chemical suppliers declare on the FMD dashboard the nature of chemicals supplied to the client. Infosys used FMD to identify restricted substances and for reporting purposes.

In another recent project around traceability, Infosys developed a crop transaction application suite for farms in India. The applications start with farm registration, recording the crop transaction and payment, up to the warehouse management and logistics stages, with integration into the ERP systems. The suite thus traces crops across their transaction phases.

Tapping the Immense Brownfield Opportunity

Beyond product design and development, sustainability has immense potential in brownfield manufacturing and operations. In this space, Infosys focuses on resource frugality, primarily around energy consumption and water management. The company draws on its own experience from achieving carbon neutrality in 2020 in its campuses/delivery centers. It monitors, in real-time, equipment such as chillers and HVACs, generators, and elevators, along with sewage and treatment plants. Much of its effort has been collecting data from facilities (through IoT systems), analyzing them, and building predictive models. Infosys now forecasts its energy and resource consumption based on models that include weather and conducts budget deviation analysis.

An example of a brownfield project is with a cable manufacturer that had designed a new electric cable coating that increased electricity transmission by 15-25% and was incorporated into its new product. It wanted to address its client base of aging installed wires (70% are 25 years old). Infosys designed a robot prototype installed on the power lines that take photos to identify dirty and deteriorated areas and then conducts wire cleaning and coating.

IoT has a key role in sustainable manufacturing operations. An example of a project is where Infosys collects data from sensors and equipment on a given production line. Based on the data, the AI models will determine when the production line is not running and, when applicable, turn off the air handling unit, to save energy costs.

Aftermarket Services: Reuse and Recycling Are Next

In aftermarket services, IoT use cases have centered around remote monitoring and predictive maintenance. Other potential use cases include focusing on reusability, repurposing, and recycling.

In aircraft decommissioning, Infosys is working on identifying components that can be resold and reused and triaging the level of recyclability of other components. Regulations in aircraft decommissioning require parts to be identified and traced from decommissioning to reinstallation into a new plane. Infosys is developing a blockchain solution for this. It is also working with SAE International on developing electronic transaction standards for the aerospace industry.

Infosys has largely completed its identification of sustainability capabilities and is now looking to fill gaps in its offerings and develop service repeatability with methodologies and accelerators. Infosys is starting with maturity assessments to help clients understand where they stand in their product sustainability journey and where they need to invest.

NelsonHall recently attended Compucom’s Analyst and Advisor Event 2022 in Paulsboro, NJ.  As in-person meetings and events resume, it was great to engage with Compucom executives, including CEO Mick Slattery, face-to-face once more.

Founded in 1987, Compucom provides end-to-end digital workplace services for enterprises, midsize and small businesses. In December 2021, it was acquired by Variant Equity Advisors, giving new impetus and investment to its focus on improving the employee experience in support of the future of work.

Digital workplace services are becoming increasingly important in driving the overall employee experience, and organizations continue to invest in digital workplace services at pace. In a recent NelsonHall study of multiple IT stakeholders across industries, 91% identified digital workplace services as highly important in improving the employee experience and supporting hybrid ways of working across the enterprise. In addition, 93% rated greater personalization of services as key to improving collaboration in support of hybrid working.

Compucom is aiming to enhance its clients’ employee experiences by:

• Assisting clients to move beyond XLIs to XLAs
• Using its CXO office to drive improved resolution
• Accelerating its investment in automation of its digital support processes.

Moving beyond XLIs to XLAs

As hybrid working becomes the norm, a key goal for Compucom is to provide a holistic employee experience, enabling its clients to achieve experience parity between working from home, office, and other locations in support of hybrid working collaboration.

Accordingly, Compucom is increasing its focus on XLAs (Experience Level Agreements) and contracting on risk/reward in the areas it can control to support business outcomes. Heather Lockhart, Chief Marketing Officer, showcased Compucom’s new branding and reiterated the company’s focus on employee experience and the direct correlation between EX and, ultimately, CX for clients.

Compucom seeks to be the key enabler for XLA development across its client base and evolve Experience Level Indicators (XLIs) into XLAs working jointly with clients on business outcomes.

Current XLIs developed by Compucom include:

• Technology issues: age of devices and browser usage
• Self-sufficiency: self-service, knowledge use, and contacts per user
• Support quality: sentiment, response times, and onboarding
• Flexible workspace: cloud utilization, VPN usage, and peripheral access.

These XLIs will further translate into XLAs linked to contractual engagements to improve business processes and outcomes. The company will continue to expand these across its client base.

Compucom will increasingly focus on how its offerings can support specific client outcomes, and we expect to see more focus and investment in providing end-to-end experience across the workplace. Its persona-based approach will enable it to define personas by industry further and develop personalized experiences across the workplace.

In addition, digital workplace services have a key role in clients’ ESG agendas. This includes using remote support, immersive technologies, and Advanced Exchange to reduce onsite support to benefit carbon emissions and utilize Green apps to give end-users visibility of their carbon footprint.

Using its CXO Office to Drive Improved Resolution

Compucom has established a Customer Experience Office (CXO) to provide a holistic approach for continuous improvements, increasing service efficiency and customer experience.

It created the CXO office to look across its clients and enable more analytics and automation to drive a faster resolution or increased self-help. It has dedicated teams building automations and improving proactive resolutions. Through ITSM, it seeks to improve customer experience efficiency by driving SLA attainment, incident resolution, and reducing MTTR and contact volume while driving a knowledge management program to assist operations and improve customer experience through metrics including FCR and knowledge consumption.

Compucom’s CXO includes a single-pane view to track employee sentiment and performance across clients’ investments in end-user analytics tools such as 1E Tachyon, NexThink, Systrack, Medallia, and Qualtrics. This further enables the measurement of UX across devices, applications, networks, and home office WiFi environments.

Accelerating the Automation of Digital Support models

Compucom is investing in digital support models with more automation, self-service, and predictive AI-powered, natural language support options. This includes remote technician support, swapping deskside for remote support, and dispatches with remote and Advanced Exchange; in addition, looking at different telemetry and events from the devices deployed across the workplace and aggregating this data to view patterns and deliver appropriate automation as required.

This also includes triggering actions to propose preventative measures to improve configurations and predict, prevent, detect, and fix potential issues before they reach the service desk. Compucom also provides a catalog of automation, including scheduled maintenance for core applications and a simple interface for single-click resolutions and requests for assistance. Through analytics and telemetry, it is helping clients move from a group policy administration model to an Autopilot-driven approach that enables greater device choice.

Outlook

Compucom is ramping up digital re-skilling and hyperscaler certifications, and we expect it to continue investing in AI-based platforms and tools to enable a self-heal framework and increase autonomous remediation. In addition, we anticipate that Compucom will shift from a traditional L1/1.5/2/3 mindset to a real-time data insights-driven approach supported by site reliability engineers (SRE).

In general, we expect to see newer skill sets emerging, including machine coaches developing algorithms for AIOps systems, business value specialists, automation and AI architects, and experience and innovation leads. It will be important for Compucom to continue to ramp up its digital re-skilling, hiring, and retention initiatives to ensure the requisite skills are in place to meet future clients’ requirements and support business outcomes.

In addition, Compucom recognizes that the ever-increasing shift to SaaS and the increasing number of devices that require network connectivity is bringing new security and networking challenges to edge locations and continues to enhance its capabilities on the edge along with security. 

We also expect to see more emphasis on partner ecosystem and hyperscaler GTM initiatives and a greater focus on how Compucom’s offerings can support specific client outcomes.

We recently talked to TCS about the company’s involvement in connected plants, TCS’ terminology for digital manufacturing.

TCS has a broad connected plants portfolio, ranging from manufacturing IT systems, MES, Industry 4.0 and connected supply chain, to industrial control systems, and automation. The development of this portfolio currently emphasizes further specialization and digitalization. The specialization goes deep with, for example, a recent offering focusing on supply chain integration for discrete manufacturing clients that operate under a batch production mode.

Along with increased specialization, digital is a high priority for TCS. Areas of focus here include AI, digital twins, and edge-based automation. It recently launched its Neural Manufacturing initiative to spread AI use cases among manufacturing plants.

Neural Manufacturing covers the data life cycle from data collection and classification, to analytics and AI use cases, and knowledge management. TCS has created three modular solutions covering these areas: DMP, InTwin, and CPOA.

TCS Digital Manufacturing Platform Focuses on Data Classification & Dashboarding

Digital Manufacturing Platform (DMP) collects data from sources such as data historians, sensors and equipment, and RFID tags, connecting with applications such as MES through interfaces or APIs.

However, DMP goes beyond data collection. It also focuses on data classification by creating data models, metadata, ontology, and instances. Classification is primarily manual at this stage, with TCS working on its automation, though DMP can already upload spreadsheet-based asset hierarchies and graph tools. Complementing data classification, DMP has ~50 standard dashboards aligned by use case, and include standard metric and descriptive analytics.

TCS InTwin Digital Twin Platform Has ~120 Standard Algorithms

While DMP provides access to data, InTwin provides digital twin functionality using AI to help users make sense of their manufacturing data. With InTwin, TCS has created ~120 standard AI algorithms around standard use cases such as prescriptive analytics, anomaly detection, what if analysis, and image analytics. TCS helps organizations prepare the data for building and enhancing these AI models, including selecting which data to use or creating synthetic data as necessary.

AI models continue to be a priority for TCS. It highlights that organizations’ demands are expanding from point solutions, e.g., anomaly detection, to more comprehensive digital twin projects such as equipment simulation. The company can recreate the behavior of specific equipment and conduct what-if analyses.

TCS Cognitive Plant Operations Advisor Solution Supports Plant Operatives

Finally, with its Cognitive Plant Operations Advisor (CPOA) solution, TCS is targeting the world of manufacturing knowledge management. While many organizations have engaged in AI pilot activity to derive data from their manufacturing operations, few have engaged in knowledge management beyond document digitization. TCS uses several techniques to create this knowledge. The company uses NLP for semantics, captures knowledge from different data sources such as drawings, and uses methods such as fault tree models for root cause analysis.

Further Specialization and Investment are Underway

TCS continues to enhance its Neural Manufacturing software suite. The company has already moved beyond the development of point use cases and accelerators and has formalized its capabilities into more expansive software products.

And indeed, NelsonHall finds that the use of AI in digital manufacturing is relatively embryonic. AI opens many possibilities around data and a better understanding of the behavior of equipment and plants, bringing new possibilities such as equipment and plant simulation. The number of use cases is fast expanding. We are glad to see TCS is making the necessary investment in this strategic space.

We recently talked to Testbirds, the largest Europe-headquartered crowdtesting firm, founded in 2012. We found Testbirds upbeat after the pandemic. The company had an excellent year in 2020, achieving revenue growth of 30% as organizations, challenged by closed offices, turned to Testbirds to conduct crowdtesting of their digital initiatives. This was followed by another excellent year in 2021, with revenue growth reaching 40%, led by digital projects, and Testbirds is expecting similar growth for this year. In parallel to this continuing sales momentum, Testbirds has reached operational breakeven and is currently funding its expansion organically. The company continues to recruit and now has ~600k crowdtesters in its community.

Expansion in Europe, Now Targeting U.S.

Expansion remains a priority for the company, which is increasing its office locations in Europe with new facilities in Leipzig and London, complementing its existing presence in Germany and the Netherlands, and to a smaller extent in France and Italy. Testbirds is structured into regional hubs, Leipzig and London being sales and project management centers serving clients in the German and English languages respectively. London is also a hub for project management, delivery, and sales and marketing activities to the U.S.

In addition to its direct sales activity, Testbirds wants to grow its indirect channel, increasing the level of work with partners. The company recruited a channel head in 2020 and expects its indirect channel to contribute revenues in 2022.

More Consulting and Specialized Services

Testbirds highlights that its indirect channel strategy will somewhat change its value proposition as partners will deliver the crowdtesting project management and analysis work themselves. Consequently, Testbirds has already changed its portfolio. In addition to offering crowdtesting project management and execution, the company is also now highlighting capabilities such as consulting and methodologies for advising clients on their crowdtesting goals and approaches. With this consulting-led service, Testbirds looks to accompany clients across their digital product journey. It has aligned its service portfolio around consulting, from defining a digital product concept to prototyping, development, testing, and release.

Beyond its consulting approach, Testbirds has expanded its offering beyond quality assurance and usability testing to online surveys, market research, and customer feedback. While QA remains core to its value proposition, the company is expanding in usability research and testing.

Testbirds highlights the specialized offerings of its Testbirds Exclusives brand. It recently launched its payment testing service, addressing online, offline, and in-store PoS. The company has set up a dedicated offering that can be provided on a standalone basis, focusing on European regulations on authentication or, more broadly, covering the customer journey, from product order to payment and returns management.

Alongside payment, Testbirds is promoting its offering verticalization, usually in the field. Examples include connected home equipment testing or EV charging station testing. Usability testing plays a key role in such verticalization.

Incremental Automation

Testbirds continues to invest in the Nest, its platform used by crowdtesters, its project managers, and clients. A recent example of incremental functionality is its companion app, which allows crowdtesters to log defects and screenshots directly from their mobile devices. The companion app simplifies crowdtesters’ work by avoiding going through a PC to log defect screenshots.

The company continues to invest in AI, using ML for mining defect comments and classifying defects into categories. It continues its work around defect prediction and automatically transcribing video voice into transcripts. While we initially expected AI to bring automation and efficiencies to crowdtesting, Testbirds finds that deploying AI use cases has been slower than expected.

So what’s next for Testbirds?

The company believes it has reached the inflection point where demand will move to hypergrowth. It has hired sales executives and counts on its indirect channel to grab this rising demand. The company has reorganized its service portfolio, driving specialized services. In parallel, Testbirds believes it has structured its execution to make its service repeatable. The company also pushes defect analysis work to its community through the Bird+ program to drive efficiencies. Finally, Testbirds is now opening again to further private equity funding. The company believes it will enter a hypergrowth cycle and external funding will help scale up.

We recently talked to Cigniti about its digital ambitions and its acquisition of RoundSqr.

While remaining focused on quality engineering, Cigniti has quietly expanded its capabilities to RPA over the past three years. This extension is logical: RPA shares much with testing, relying on creating and maintaining bots or test scripts. This is the start: Cigniti has broad ‘digital engineering’ ambitions, and RPA was the first step.

With its recent acquisition of RoundSqr, Cigniti has taken another step in its digital strategy. RoundSqr has ~100 employees and revenues of ~$2.8m in its FY22. The company has ~30 clients, most of which are in the U.S., U.K., Australia, and India.

RoundSqr started as a digital company and currently offers data, analytics, and AI services. The company is also active in web and mobile application development services, including architecture design and APIs.

RoundSqr strategically invested in AI, particularly in AI model validation and computer vision. The company brings in a methodology and expertise to model validation. RoundSqr has also developed an IP called Zastra that helps with computer vision-related annotation services.

AI Is Strategic to QE

RoundSqr highlights that testing of AI models is primarily restricted to evaluating their accuracy and relies on separating data into training and testing sets; it looks to take a more comprehensive approach across the model itself and its data.

The company evaluates AI models across six parameters, namely Stability (conducting testing several times on the same data); Sensitivity (mitigating the impact of noise and extreme scenarios on the output); Data leakage (using non-training data when building the model), Performance (the model will have the same outcome even if the data is changed), Bias, and Predictability.

Beyond the AI model, we think RoundSqr’s AI capabilities will be instrumental to Cigniti’s QE activities. Organizations have started using AI to conduct focused testing to identify areas where they expect bugs. But AI is also relevant for automating test script creation and maintenance. The offerings are getting ready, and client adoption is now starting. We think AI has the potential to revolutionize the QE industry if it removes human intervention around test scripts.

RoundSqr Brings Computer Vision Annotation IP

Zastra, the IP that RoundSqr has built over the past 18 months, is a computer vision product that targets image tagging and annotation, the action of identifying objects, people, or living organisms in a picture. Zastra can provide the necessary steps for identifying objects, including image classification, object detection, and semantic and instance segmentation. RoundSqr targets several sectors with Zastra, primarily manufacturing, medtech, and utilities. Its use cases include defect detection, track and trace, CT and MRI scans, and satellite images.

Zastra links nicely, we think, with QE in the UX testing area. The role of testing has primarily revolved around testing the functionalities of an application. However, testing image rendering, e.g., on a website, has been far more limited, mostly around pixel-to-pixel comparison. We think AI models open new use cases for websites and digital technologies such as AR/VR and quality control in manufacturing plants.

RoundSqr’s product roadmap for Zastra includes synthetic data generation and audio annotation. The company will also expand its hosting options beyond AWS to Google Cloud Platform and Oracle Cloud.

Revenues of $1bn by FY28

This is the beginning of the journey. The priority for Cigniti and RoundSqr is now cross-selling and accelerating further organic growth.

However, RoundSqr alone is not sufficient for Cigniti to reach its $1bn revenue target by FY28, up from $167m in FY22. To achieve this objective, the company will rely on both organic growth and M&A.

Future organic growth will come from further expansion of its service portfolio to digital offerings such as data, AI and ML, blockchain, cloud computing and IoT. The company also plans to grow within engineering and R&D services, both industry 4.0/digital manufacturing and product/platform engineering services. Cigniti targets connected devices, taking an AI-based approach.

Cigniti’s client base includes BFSI, healthcare, medtech, travel and hospitality, and retail. The RoundSqr acquisition further strengthens Cigniti in BFSI. It also brings further focus on ISVs, and the supply chain and manufacturing functions, which Cigniti sees as having great growth potential.

To support its portfolio expansion, Cigniti will need to continue to acquire. Acquisitions such as RoundSqr will bring further specialization and are precious. Cigniti will, however, need a transformational transaction. Watch this space.

NelsonHall recently completed an in-depth analysis of end-to-end cloud infrastructure management services, in which we spoke to multiple leading IT services vendors and their clients. This blog looks at some of the key themes from this research, the investments vendors need to make to meet client demand, and how the market will evolve over the next 12 to 18 months.

There is an increasing focus on utilizing the cloud to deliver value across every business function within an enterprise; for example, improving security, compliance, and governance for the CSO and enabling HR to drive positive employee engagement and experience. In addition, cloud management and FinOps provide CFOs with greater visibility and management of the cloud ecosystem to control and optimize cloud costs and greater utilization of AI and automation to enable CIOs to focus beyond TCO. Vendors are creating cloud-native industry-specific solutions to support LOB heads and expedite enterprises’ ability to create and develop new products and services by sector.

The three overarching themes from this study were:

• Enhancing hybrid cloud management and employee experience
• Ramping digital re-skilling and empowering end-users
• Increasing focus on AIOps and cloud-native capabilities.

Let’s look at these three focus areas in more detail.

Defining and measuring cloud journeys through co-creation

Vendors need to take a collaborative design thinking approach to cloud transformation to co-create and innovate with clients to support business outcomes. This includes utilizing AI and analytics in the initial cloud advisory and assessment stages to improve the overall cloud transformation roadmap. This takes a three-phased approach, including:

• Advisory and assessment: enabling data-driven insights to provide deep discovery of infrastructure and application assets. Also, cloud architecture analysis and identifying the right cloud type (IaaS, PaaS, SaaS) and approach (private, public, hybrid). Then developing cloud maturity roadmaps including OCM to deliver the desired client outcomes through the identification of business needs and driving digital adoption
• Migration and modernization: identifying application modernization opportunities, including monolithic architecture implementation and deployment. Then deploying a migration factory approach with templates, repeatable tasks, and agile squads. This includes landing zone and platform build, including cloud-native and adoption of DevOps and serverless architecture. An example includes Capgemini’s Cloud Migration Factory, providing a highly automated and industrialized approach to application and infrastructure migration. This includes providing end-to-end migration from package to production using an automated release pipeline and a migration management portal. It also provides an assessment tool for cloud cost optimization for clients that have already migrated to the cloud
• Operate and manage:  Clients want to manage hybrid, multi-cloud environments through a single CMP console with self-service and automated provisioning with a single click. This also includes the integration of private cloud and edge. There is also a greater focus on cloud-native PaaS support, including microservices and containers. This includes a more open approach to orchestration, including cloud-native provisioning with cloud APIs. In addition, integration of third-party monitoring and visualization tools to tag, monitor, and optimize spend based on usage patterns, with automated reporting and chargebacks to business units through FinOps. 

Over the next 12-18 months, we expect vendors to rapidly increase the utilization of Cloud CoEs, labs, experience centers, and Digital Transformation Centers to help clients prototype and co-create cloud-first solutions to facilitate this approach.

Vendors need to identify and measure employee experience, define industry personas, and personalize experience services across the enterprise. They need to continue to invest in end-user analytics tools to measure employee sentiment and performance, with typical tools including 1E Tachyon, SysTrack, Nexthink, and Qualtrics. These measure UX across devices, applications, and networks.

Digital re-skilling continues at pace

We continue to see traction in digital re-skilling, hyperscaler certifications, and new skill-sets, including machine coaches developing algorithms for AIOps systems, automation, AI architects, cloud-native SMEs, data analytics, and business value specialists. Also, vendors are ramping cloud academies, experience centers, and site reliability engineers (SRE) to monitor cloud ecosystems’ performance through a data-driven approach and building capabilities and enhancements based on what SRE teams learn from operating cloud environments for clients. For example, across cloud operations, TCS takes a service reliability engineering approach with dedicated teams resolving issues and platform and architecture teams automating activities and enabling greater self-service.

TCS also uses its cloud units as a catalyst for talent change across the organization, enabling infrastructure specialists to become full-stack architects. In addition, developing industry-specific skillsets across cloud delivery resources by utilizing TCS’ industry SMEs.

Vendors are now hiring beyond STEM and across tier 2/3 cities in India, with Tech Mahindra recently opening a delivery center in Coimbatore. Vendors are further utilizing AI-enabled learning assistants and platforms to expedite training. For example, Infosys utilizes its Wingspan learning platform to support cloud training, and its talent strategy focuses on emerging technologies, with 350 learning paths and 46 digital skill tags.

Over the next 12 months, the focus on dedicated experience centers will increase, supported by SRE teams that look at the experience aspect of IT service delivery and proactively monitor end-users’ sentiments as they engage across services and XLAs (and work with clients to create specific XLAs by persona). We also expect to see more focus on end-user empowerment using low code/no code platforms and managing, for example, M365 through the Microsoft Power Platform.

Expanding AIOps use cases to meet client-specific requirements

AIOps are being deployed to trigger automation to auto-remediate and fix issues, including utilization of resolver bots (L0, L1, and L1.5 functions). Also, to detect anomalies, reduce noise across operations, and use ML and diagnostics engines to manage L2/L3. End-user outcomes include ~40% improvement in MTTR, ~45% incident elimination, and ~65% of incidents autonomously resolved.

We expect vendors to expand their use cases to enable transitions to future no-ops. Vendors look to orchestrate tasks using AI and automation and use recommendation engines to provide the best-fit SOP for the issue through one-click automation. There is increased focus on standardization through template-based provisioning of environments and standardized monitoring and data collection frameworks. NTT DATA, for example, adopts a data bias in support of cloud transformation where it makes decisions based on data insights to influence new application features, developments, and architectural improvements.

Vendors must build libraries of standard AIOps use cases to meet clients’ business outcomes, manage operations across the full stack, and achieve ~40-50% reusability on standard assets through enterprise bot stores. This includes increasing the use of cloud architects and administrators to develop infrastructure and industry-specific cloud blueprints, including templating application blueprints. They need to focus on developing service patterns that provide repeatability through a combination of hyperscaler technologies and vendor IP to address specific industry and client requirements. In addition, they need to integrate with and utilize client toolsets where required through an agnostic approach. Also, taking a modular approach to reflect clients’ Brownfield automation capabilities.

Outlook

Investment in end-to-end cloud infrastructure management services will continue at pace, with a greater focus on developing a full-stack organizational structure to deliver cloud transformation through productized offerings. We expect to see increased focus and investment in sustainability and helping clients reduce carbon footprints. This includes continuous monitoring through cloud management platforms, green apps, and observability tools. TCS, for example, adopts a sustainability by design approach to drive configurable, composable, and automated infrastructure to adapt the cloud to environmental, social, and governance needs.

There will be an increase in modernization accelerators and methodologies to enable clients to modernize legacy applications and take advantage of the latest hyperscaler technologies. This includes modernization factory, CoE, and dedicated squads deploying an agile approach and making recommendations for modernization. Application modernization investments will focus on microservices, service mesh, API factory development, and serverless functions.

It will be important to ramp digital re-skilling, hiring, and retention initiatives to ensure the requisite cloud skills are in place to meet specific client requirements and support business outcomes.

Expect vendors to ramp cloud-native services and practices to provide complete end-to-end hybrid services for containerization and move containers off datacenters to the cloud. Also, to provide a unified view of observability, management, and deployment across containers and expand their mainframe as a service capability.

Finally, we expect increased investment in AI-based platforms and tools to enable a self-heal framework, increase autonomous remediation and an SRE-led approach to cloud operations, and a greater focus on joint IP and GTM with hyperscalers.

Find out more about NelsonHall’s ‘End-to-End Cloud Infrastructure Management Services’ market assessment report here or contact Guy Saunders.

We recently talked to Qualitest regarding its acquisition of ZenQ.

ZenQ is the latest in a series of recent acquisitions by Qualitest, under the ownership of PE BridgePoint. The company acquired four firms in 2021:

• QA InfoTech (QAIT) in Bangalore, doubling Qualitest’s presence in India
• Olenick in the U.S.
• Telexiom in Germany
• Comply, an Israeli company that added a specialized capability in healthcare regulatory compliance.

The latest addition, the Dallas-headquartered ZenQ, aligns with Qualitest’s objectives to build digital transformation capabilities. It strengthens Qualitest in DevOps/continuous testing consulting and brings specialized digital expertise such as AI and blockchain. Finally, it opens Qualitest to the world of product engineering QE, around high-growth areas such as connected devices/IoT, including AI-intensive equipment such as drones.

Continued Expansion in Digital

ZenQ brings capabilities in digital, including blockchain testing. The company has worked primarily for ISVs across various verticals and use cases. Blockchain QE adds a niche high-growth area of expertise to Qualitest’s expanding digital testing portfolio. The company has already expanded to RPA/bot testing and application migration to the cloud testing. Also, its December 2019 acquisition of Israeli start-up AlgoTrace helped kickstart its AI offerings, focusing initially on data science. Since then, Qualitest has expanded its AI analytics and automation portfolio in visual testing and test case optimization areas.

Qualitest Enters Connected Device Testing

Importantly, ZenQ adds expertise around connected devices across various products, including drones, petcare and medtech devices, smart home and logistics products, and solar panels. The company is active in product engineering, in specialized services such as communication protocol QE and interoperability. This brings Qualitest to a new world of bundled hardware and software, where software (e.g., embedded software, mobile apps) plays an increasing role and where Qualitest has its roots. With ZenQ, Qualitest expands to hardware testing, where lab-based automation emerged only a few years ago.

Importantly, connected product testing also brings AI, notably computer vision, e.g., for use cases such as inspecting the quality of goods produced in a manufacturing plant, monitoring the health of forests and crops, or animal geo-fencing. Qualitest has experience in this space and has developed its AI-based IP Test.Validator for image recognition.

Further Scale

In addition to its portfolio expansion toward digital QE, ZenQ reinforces Qualitest’s capabilities in three countries:

• Its onshore presence in the U.S. and Canada (Toronto)
• Its delivery capabilities in India, adding Hyderabad to Qualitest’s presence in Bangalore and Noida.

In total, ZenQ has ~700 employees.

The integration journey for ZenQ and Qualitest is in its early stages. Cross-selling is a priority. From a portfolio perspective, expect Qualitest to bring further quality engineering and AI capabilities to ZenQ’s projects. For Qualitest, assuring product engineering is a new field with tremendous growth potential, and we expect the company to invest in QE automation in this space.

Meanwhile, Qualitest still has bold growth ambitions. The company has aggressive plans to reach $1bn in revenue in the next two years. Further acquisitions to gain scale both onshore and offshore and expand the portfolio to digital are likely.

There is a big divide between IT sustainability and quality engineering (QE). In IT, sustainability is emerging from a carbon emission niche, expanding from a consulting to an execution phase. In QE, the focus remains primarily on functional automation with continuous testing/DevOps and AI as primary drivers. In short, the two have little in common.

As such, we had not anticipated that QE could soon become part of sustainability initiatives. However, Sogeti, part of Capgemini, recently briefed NelsonHall on how it is adapting its QE offering to sustainability with QE for Sustainable IT.

Measuring carbon footprint at the transaction level

Sogeti has designed QE for Sustainable IT, targeting the environmental side of sustainability (which also includes economic and social aspects). The company promotes a stepped transformation of IT rather than through big bang approaches. It highlights that once a client has started measuring its carbon footprint, it implements its strategy primarily by reducing its application estate and migrating its applications to the cloud.

Sogeti wants to offer a different approach to transformation, looking at the transaction level. The company will initially conduct its Green quality assessment, relying on its VOICE model, to understand the client’s sustainability objectives. Sogeti will then identify the most used ones in the production environment. It will then estimate how each transaction impacts the usage of hardware and networks (e.g., CPU, storage). Once done, the company will calculate the carbon footprint of each ERP transaction in production environments in the past 12 months. Once the applications have been transformed, Sogeti will reculcate the carbon emissions and measure its progress.

Where does QE fit within IT sustainability?

With its test case/test script approach, Sogeti highlights that QE already has the required experience and tools. The company will conduct the transaction, using functional test execution tools to measure the usage of hardware and networks. It will then capture each transaction’s hardware and network usage using APM tools.

Sogeti has worked with its development peers on the transformation side. The development teams will work on the code related to the ERP transaction, streamline the code, and remove dead code.

Sogeti looks to extend beyond this transformation phase and become a “sustainability quality gate”, mirroring the traditional role of testing in deciding if an application in development can be deployed in production environments. To do so, the company is currently working with a partner to build accelerators, e.g., a sustainable static code analysis to measure the “sustainability technical debt” of an application. The tool relies on checking if developers used sustainable development best practices.

This is just the beginning of Capgemini’s QE journey into sustainability. It sees increasing traction, thanks to regulatory pressure and consumer expectations, to reduce the carbon footprint of enterprises.

Capgemini’s roadmap for QE for Sustainability goes beyond ERP applications. The company wants to expand to other COTS and custom applications. With Capgemini’s CEO driving the company’s sustainability effort both internally and to external clients, expect to see more of these offerings in the next few months.

NTT DATA recently announced the long-planned merger of its international business with NTT Ltd., the overseas ICT unit of Japanese telecoms giant NTT. The combined NTT DATA and NTT Ltd. will have revenues of ¥3.5tn (~$26.2bn) and 180k personnel.

With this move, NTT unites its two ICT units into a single entity, driving its vision of One NTT. The merger will remove some overlapping capabilities and should help drive revenue synergies by FY25. The larger NTT DATA organization will spearhead NTT's technology presence in enterprises.

The merger comes when NTT DATA has completed one cycle of its strategy for overseas growth. After several significant international acquisitions (Dell Services, everis, itelligence, and Value Team), the focus turned to cost savings, portfolio management, and through its Global One initiative, driving coordination across the firm. In FY21 (the year ending March 31, 2021), NTT DATA's overseas business reached an EBITA margin of 6.5%, a notch below its 7.0% target.

The addition of NTT Ltd. Doubles NTT DATA's Overseas Presence

With around $10bn in revenues and 38k employees, NTT Ltd. more than doubles NTT DATA's international business to $18bn.

One of the primary benefits of the merger centers on cost synergies. NTT DATA expects to achieve ¥30bn (~$150m) in savings by FY25 (the year ending March 31, 2026), improving margins in its overseas business. NTT DATA now expects to reach an EBITA margin of 10% in its overseas business, a 50% improvement. The absorption of NTT Ltd. into NTT DATA (and its transformation) will take time, with the synergy target suggesting a fast two-year effort from the day the merger is operational in July 2023.

NTT Ltd. Brings A Diverse Network and IT Infrastructure Portfolio

From a service portfolio perspective, NTT Ltd. brings a wide range of network and connectivity services, hardware and related services, data center hosting, IT infrastructure services, and resales. The company is particularly well known outside Japan for its Dimension Data business, a significant acquisition in 2o19, which brought in around $4.0bn in revenues and 11.5k personnel at that time.

Dimension Data, itself a regular acquirer, had strengthened its network capabilities through multiple transactions, including Nextira One. It had also expanded into application services in APAC, mainly in ANZ and Singapore.

NTT Ltd. brings a diversity of attractive and perhaps some less attractive IT and telecom/network services capabilities. The company started unifying its capabilities back in 2019 when it regrouped all its units under the NTT Ltd. brand. This transformation continues, with NTT Ltd. still going through a portfolio and cost transformation to drive margins up.

NTT Prioritizes the U.S. for Further Expansion

Last October, NTT DATA revised its mid-term plan, targeting ¥4.0tn in revenues in FY25. The services portfolio will focus on five primary offerings: Cloud, Data and Analytics, Security, ADM, and Enterprise Applications Services. Similarly, the target markets are five industries: healthcare & life science, automotive, insurance, telecom, and banking.

The structure of the new arrangement is interesting: parent company NTT will own 45% of NTT DATA's overseas business, with NTT DATA controlling the remaining 55%. It is unclear why NTT did not increase its share in NTT DATA directly rather than holding a stake in the overseas business. NelsonHall expects a change in the capital structure in the mid-term.

Acquisitions will be on the agenda. NTT DATA feels that, despite its ¥476bn FY21 (~$3.5bn) revenues in the U.S., it still has room for further expansion, with an ambition to expand its capabilities in digital.

Indian offshoring is also likely to be on the agenda. NTT DATA, despite the Indian presence brought by KEANE and Dell Services, still needs to grow in the country, especially considering its U.S. ambitions. Expect to see acquisitions to expand delivery capabilities in India.

On June 14, 2022, Atos announced the unexpected separation of its IT infrastructure services unit, Tech Foundation, from its BDS and Digital units. With this move, Atos has aggregated its high-growth and high-profitability units into a new company, Evidian. Its infrastructure services capabilities will stay in legacy Atos, with the objective of stopping the revenue decline and improving its profitability. This announcement raises several questions, which Dominique Raviart, NelsonHall’s IT Services practice manager, addresses in this video blog.

NelsonHall recently attended Unisys’ Analyst and Advisor Event 2022 in Boston, MA. As IRL meetings and events begin to resume, it was great to engage with Unisys executives face-to-face once more.

The $1.2bn sale of its Federal business to SAIC back in February 2020 is being partly used to fund acquisitions and portfolio investments for Unisys’ digital workplace and cloud & infrastructure solutions businesses. Unisys has made three acquisitions to date: two have enhanced its digital workplace services capabilities, the third its cloud and infrastructure management services capabilities.

Unisys has well-established capabilities in cybersecurity, particularly Stealth and digital workplace services. There is now an increasing emphasis on cloud-native applications and taking a more consultative-led approach across Unisys.

There has been a nearly total refresh of the senior leadership over the last 18 months, with new appointments for CFO (Debra McCann; former CFO Mike Thomson is now COO), CTO (Dwayne Allen), CMO (Teresa Poggenpohl), CCO (Maureen Sweeny), and new heads for Digital Workplace (Leon Gilbert), Cloud and Infrastructure Solutions (Manju Naglapur) and Enterprise Computing Solutions (Chris Arrasmith). All are external hires (Naglapur came with CompuGain, acquired in December 2021). We note much greater diversity in the senior leadership.

The tagline for the event was ‘what’s next – accelerating success’. CEO Peter Altabef focused on Unisys’ new emphasis of driving outcomes that enable enterprises to be more profitable with supporting hybrid, cloud, and multi-cloud environments playing a pivotal role.

Digital workplace solutions: focus on the proactive UX

Leon Gilbert, SVP of Digital Workplace Solutions, highlighted the traction gained since his appointment in February 2021 and the increased focus on driving proactive experiences across the workplace and helping clients transform through next-gen capabilities. Unisys has enabled all existing clients with the latest technology, including journey analytics, at no charge. It also exited some non-strategic DWS contracts in 2021. Unisys claims to be enabling ~1.4m end-users with proactive experiences, up from 50k just 18 months ago.

Two recent acquisitions enhancing Unisys’ digital workplace services capabilities are:

• Unify Square, acquired last June for $150m, whose cloud-based PowerSuite solution for Enterprise Communications and Collaboration captures an individual's experience and can operationalize and improve that experience in real-time through analytics. Unify Square also brought in ~50 digital workplace consultants who can support Unisys’ consulting-led approach
• Mobinergy, a much smaller acquisition last November, has enhanced Unisys’ UEM capabilities and its positioning around modern device management.

There is an ongoing emphasis on VDI (Dell, VMware, Azure) and cloud-native VDI services to support secure and modern workspace environments and AIOps in support of first-time fix across field services, AR, and automation in service desks. Again, there have been several recent senior hires supporting these capabilities.

Priorities for Unisys’ digital workplace services include aligning offerings by geography, optimizing hybrid working models, and driving more outcomes-based engagements.

Driving application modernization and containerization

Unisys is also investing in its cloud and infrastructure business and recently acquired CompuGain, bringing 400 employees with capabilities across cloud-native, application modernization, and data analytics.

Unisys continues to invest in its CloudForte portfolio, including CloudForte CMP AIOps for AI-led operations. In addition, CloudForte Containers automate the end-to-end container infrastructure, application modernization, and DevSecOps deployment processes. This enables applications to be brought quickly into production and provides automation across the entire lifecycle, including security. It is also investing in Stealth and its hybrid cloud-managed security solution (MDR), providing AI-enabled threat response.

Unisys continues to ramp its investments across automation, self-healing, and AI/ML capabilities in support of cloud services.

Outlook

Unisys has overhauled its senior leadership team and is looking to pivot to a business-unit-led organization to increase traction in selected markets and geographies. There will be a stronger focus on using a consulting-led approach and on driving client outcomes: expect to see a further increase in dedicated business consultants. Also expect to see additional bolt-on acquisitions in support of application and data modernization capabilities, plus further developments in its CloudForte container services roadmap, and a greater focus on DevSecOps and automation enablement across the entire lifecycle. We also expect to see more joint-IP and GTM offerings with key hyperscalers.

With digital workplace services, expect to see greater traction across Unisys’ XMO organization, proactive experience, dedicated XLAs through the PowerSuite platform and partner ecosystem, and expansion of modern device management with Mobinergy capabilities. This should enhance field services, including AR/VR and immersive technologies. We also expect to see further acquisitions supporting digital workplace transformation advisory and a greater focus on AIOps and SRE-led operations.

Unisys will be rebranding this year: expect to see a greater emphasis on how Unisys’ offerings can support specific client outcomes.

John Laherty and Rachael Stormonth

The war in Ukraine has brought EPAM Systems (EPAM) under the spotlight. Although headquartered in Newton, PA, EPAM has a delivery network heavy in Central and Eastern Europe. It was founded in 1993 in New Jersey and specializes in service development, digital platform engineering, digital product design, and custom software. However, with its first offshore development center opening in Minsk, Belarus, in 1995, EPAM then expanded into Russia and Ukraine for delivery. In February 2022, on the eve of the invasion of Ukraine, 58% of the company's headcount remained in these three countries. Ukraine was the largest country with ~14k personnel at the end of 2021.

Reflecting on this situation, EPAM is adjusting its support model, moving people out of the region, and establishing brand new sites. The company acted quickly by deciding to exit Russia last month, but the relocation from the region continues EPAM’s diversification strategy already in play. There have been growing geopolitical and social uncertainties across the region. In 2014, with the Russian annexation of Crimea and the following Donbas invasion, EPAM started diversifying its delivery network to other countries in Central and Eastern Europe, Latin America, and India.

Yet despite the most recent developments in the region, the company announced excellent financial Q1 2022 results. During the quarter, EPAM generated revenues of $1.17bn, a year-over-year increase of 50.1% (40.1% organically). Profitability remained higher: its adjusted operating margin was 16.1%, down 1.4 pts.

Moving employees at scale within and outside Ukraine

The company is helping to relocate most of its employees in Ukraine during Q2 2022 to billable positions. The impact of the relocation effort goes beyond travel and setup costs, with EPAM highlighting that relocated employees are now in more expensive countries and have increased their wages. EPAM is currently renegotiating with clients to adjust rate cards.

Amid the war-torn conditions, the company helped move thousands of people from east to west inside the country and abroad (e.g., Poland, Hungary, Turkey, and Serbia, and across countries). Approximately 2k Ukrainian employees relocated abroad.

Accelerating delivery diversification

With phase 1 of its relocation strategy well in progress, EPAM launched phase 2 in parallel and has accelerated its delivery diversification effort to India, Mexico, and Colombia and across locations in CEE and Asia. By 2022, EPAM expects Ukraine and Belarus to account for just 30% of its capacity.

One of EPAM's challenges is to grow its presence in India. Its Alliance Global Partners acquisition in 2015 brought an estimated 1k personnel to India. The company recognizes it took time to learn about the market and has started developing the Indian talent market, doubling its presence in the country in 2021 to 4.3k personnel. This is the beginning of EPAM's expansion into India. Mexico, with its ~1k employees, will complement India.

Next steps: revenue growth and profitability

EPAM is now turning its attention to revenue growth and profitability, both of which the company has indicated will be under pressure in Q2, with y/y organic growth around 28% and its operating margin in the 3-5% range.

The utilization rate will be down in Q2. EPAM highlights that in Ukraine, despite the challenges, it did not record a drop in utilization as would have been expected. Q1 2022 utilization was 78.4% compared to 76.8% in Q1 2021. However, the company suffered from a "considerably lower utilization" level for employees remaining in Russia. The situation is also complicated in Belarus: EPAM plans to stay in the country, but because "a defined number of clients" are looking for alternate delivery, utilization rates are under pressure.

In the coming months, as EPAM gradually moves from delivery resiliency to revenue growth, it will start business expansion, initially within its current client base. EPAM expects a fast rebound, and is targeting H2 2022. However, it has not provided guidance for the full year. Nevertheless, we think the company is doing very well in mitigating the circumstances of the Russian-Ukraine conflict.

Outlook

EPAM is more than a financially-sound firm. The company is demonstrating its commitment to Ukraine, pledging $100m in aid to help its employees and relatives with a wide range of requirements. Also, EPAM established the Ukraine Assistance Fund to support humanitarian aid organizations that provide direct assistance to persons in need across Ukraine. This fund exists in addition to and apart from the $100m humanitarian commitment.

NelsonHall recently attended the ‘Infosys Cobalt World Tour’ conference in New York and, as the world begins to open up again, it was great to engage with Infosys executives face-to-face.

Infosys presented its Cobalt Cloud strategy and use cases to increase awareness of the benefits to the marketplace and highlighted that its cloud approach is focused on achieving business objectives rather than simply moving current solutions to the cloud.

To set the context, Infosys launched Infosys Cobalt in 2020, which includes services, solutions, and platforms to enable cloud-powered enterprise transformation. The Infosys Cobalt Cloud Community currently provides a catalog of 225 industry cloud-first blueprints and 35k cloud assets curated from Infosys' experience in delivering cloud programs for G2K enterprises. The Cloud Community includes Infosys experts plus partners, clients, academic institutions, start-ups, gig workers, and cloud developers.

Expediting the move to the cloud

Infosys takes a three-layered approach to the cloud through Infosys Cobalt to develop new business capabilities to meet emerging business needs and faster time to market. It also aims to reduce multi-cloud complexity through a secure cloud platform, bringing elasticity to the resource layer. The three approaches are:

• Consumption Layer (Business Services): Infosys sees a new paradigm in the consumption layer, utilizing data analytics to derive business outcomes within the organization, including industry-specific solutions
• Platform Layer (Technology Platforms): Infosys aims to move clients up the value chain, including helping them transform data lakes to the cloud, refactoring apps to be cloud-native, and using PaaS
• Resource Layer (Cloud Resources): most clients start here with IaaS and cloud for consumption, network, and storage, and establishing virtual private cloud and connection between private, public cloud, and on-premise. This approach includes accelerating migration, taking native services from hyperscalers, and building on top of the cloud platform.

Infosys enables clients to create services consumable within their enterprise utilizing multi/hybrid cloud services, with platform technology enabling leaner operations with a heavy focus on engineering. Automation and IaC enable a developer-centric model that extends from DevOps to DevSecOps to NoOps in an agile manner. Key assets utilized in cloud platform engineering include Polycloud Platform, Cloud Automation Café, and Security Reference Architecture.

Enhancing security

Infosys enables enterprises to build cyber-resilient and compliant cloud ecosystems by adopting their ‘Secure by design, ‘Secure by scale’ and ‘Secure the future’ approach. Infosys assures ‘Digital trust’ through a structured execution process of diagnose, design, deliver and defend. From a Cobalt perspective, the blueprints and assets provided to their clients have regulatory and security compliance built into its solution and technical and financial governance. The security strategy utilizes strategic partnerships and pre-negotiated contracts in a platform security stack.

Sustainability is top of the agenda

Infosys looks to enable and accelerate sustainability solutions and drive impact through a business-to-business model and unlock long-term sustainability thinking across global enterprises. It aims to deliver the following benefits to its clients:

• Making an impact on the triple-bottom-line of people, profit, and prosperity
• Attracting a new wave of sustainability-minded clients, supply chain partners, and employees
• Enhancing ESG attractiveness to investors and brand reputation
• Securing resiliency in uncertain conditions.

Cloud is providing a vehicle for achieving carbon neutrality for its operations. Infosys offers Smart Buildings and Spaces services that enable the physical workplace to become digital by installing and managing Internet of Things (IoT) devices and sensors. Water management, carbon monitoring and control, solid waste management, energy assessment, and greenfield building consultancy are crucial sustainability competencies.

Outlook

Enterprises are accelerating their migration to private, public, and hybrid multi-cloud environments to satisfy greater demands for flexibility, scalability, resiliency, and security. This includes migrating on-premise infrastructure to hybrid cloud, including legacy application modernization to cloud-native systems. We expect Infosys to continue to build assets and cloud-first blueprints. In addition, in support of the Polycloud platform, we expect continued investments in the smart catalog and cloud-native services. The Cobalt suite of tools and assets enables enterprises to begin their cloud journey quickly and effectively with security in mind and an eye toward carbon-neutral outcomes.

There is history behind this merger. Known as India’s first hostile takeover bid in the IT sector, Larsen & Toubro (L&T) acquired a 60% stake in Mindtree in July 2019, despite the opposition of Mindtree’s founders and board members.

LTIMindtree will be the sixth largest India-headquartered IT services vendor

Since then, a merger of both these firms has been on the cards. And on May 6, 2022, L&T decided to merge Mindtree and L&T Infotech (LTI) into a new entity, LTIMindtree, to create India’s sixth largest IT services company by revenue. L&T offers 73 LTI shares for 100 Mindtree shares. The company will own 68.7% of LTIMindtree, with the merger set to be completed in the next three to four quarters. LTIMIndtree will have combined FY22 revenues of $3,513m, a 17.8% EBIT margin, and 81.7k employees. Mindtree’s current MD & CEO, Debashis Chatterjee, will head LTIMindtree. The LTI CEO, Sanjay Jalona, has quit citing personal reasons.

LTI and Mindtree have complementary client bases: LTI’s two largest verticals are BFSI (47% of revenues) and manufacturing (16%). Mindtree is primarily present in communications, media & technology (43%) and CPG, retail, and manufacturing (24%). The merged company will have a more balanced client base dominated by BFSI (35%), communications, media & technology (25%), and manufacturing, CPG, retail & healthcare (26%). The company will derive 69% of its revenues from the Americas, which is a strength considering the current macro conditions. It is primarily active in IT services, with limited BPO and ER&D presence.

Scale and revenue synergies

The merger is about scale and revenue synergies. LTIMindtree hopes to secure deals over $100m, to which it does not currently have access. The company’s new scale should also help secure solid relationships with cloud vendors and hyperscalers. The impact on personnel should be relatively limited but will affect middle management to some extent. LTIMindtree will gain further visibility in the labor market and accelerate recruitment in a tight labor market. The two companies are already attractive employers: in calendar 2021, the combined LTI and Mindtree hired a net 20k personnel, close to Tech Mahindra’s 23.2k.

Digital is next

This is not the end of the story for LTIMindtree. Cross-selling to each other’s client base is, of course, a priority. Also, the company will have net cash of ~$1bn after the stock-based merger. NelsonHall expects LTIMindtree to accelerate its digital, cloud, and security investments and continue its deployment of digital centers, IP, and platforms. We also think the company will increase its business consulting presence to address digital transformation projects earlier in the life cycle. Also, L&T has a majority stake in L&T Technology Services (LTTS). LTTS is a high-growth E&RD service vendor with an attractive portfolio. By merging it, LTIMindtree would join India’s top five with significant ER&D capabilities.

The world of quality assurance (QA) is continually evolving, alternating between cycles of centralization and decentralization. QA became part of testing CoEs in the 2000s, driving process standardization, test coverage and automation. More recently, in its latest organizational model, it has become part of the agile development structure and is spread across agile projects. Quality engineers work alongside developers in agile teams of three to seven specialists, focusing on test automation and targeting the holy grail of QA: in-sprint automation.

We recently spoke with Amdocs’ Quality Engineering (AQE) organization about how the unit is embracing this trend. While Amdocs is well known for its software products for communication service providers (CSPs), the company now primarily operates under an IT service model, with AQE enjoying rapid growth. For example, AQE recently won a significant standalone testing contract from a tier-one CSP. The scope is large and involves ~200 applications, including new builds and applications in maintenance. The company will scale up to several hundred quality engineers at peak time. AQE is approaching the project by implementing a new organizational model based on agile and continuous testing principles.

Amdocs adapts function points for agile QA

For this project, AQE reinvented the function point estimation model for QA that is common in software development. The unit uses certification points to estimate the time and effort required to complete a QA activity. Beyond functional testing, the pricing model also covers non-functional and other areas such as test environment provisioning.

The function point-like approach is not new (a few vendors already took that route back in the mid-2010s) and has both advantages and disadvantages. On the positive, it has helped CSPs and vendors move past a T&M model to mitigate risks in fixed-price projects. Yet function points had drawbacks, e.g., counting function points took time and were manual, with experts sometimes diverging on their function point estimates. AQE aims to resolve this challenge by automating most counting of new functional features using agile program increment (PI). Also, AQE provides its estimate two months before the PI gets to development, giving clients visibility of upcoming costs to refine the scope of PIs.

Redefining agile QA teams

In the organization space, AQE is promoting a different approach, incorporating both centralized and decentralized aspects. The idea is that rather than embedding QA into an agile development team, AQE relies on a separate team of functional and technical experts, independent from the agile development unit.

For example, for the abovementioned project, AQE created standalone atomic QA teams to provide a broad spectrum of quality engineering activities, from functional to non-functional and quality engineering. In addition, AQE employed its automation IP and accelerator portfolio to increase the level of test automation.

By covering processes and analysis, AQE’s organizational approach goes beyond just setting up standalone QA expert teams. The organization highlighted that, as part of this project, it discovered that the client had focused most of its QA activities on integration testing.

AQE took a broader pespective on the project, helping the client shift from integration testing to E2E testing. In addition, AQE introduced unit testing among developers, thereby detecting defects earlier in the lifecycle.

AQE’s targets for the client include improving velocity by 80%, achieving cost savings of up to 50%, moving from quarterly to monthly releases, increasing resiliency, and improving customer satisfaction rankings. They demonstrate that QA is having an increasing and quantifiable impact on business outcomes.

NelsonHall is currently updating its bi-annual IT services forecasts, and here’s a quick look at some of the headlines for 2022.

COVID-19 no longer a threat to IT services spending growth

The world has evidently changed since our November 2021 update. The pandemic now seems largely under control, despite spikes in China. India, the world’s IT services hub, is gradually opening its offices. IT services providers now have substantial experience of operating primarily in a work from home environment, as indeed have their clients. Should there be another widespread spike in cases coming from a new COVID-19 variant, delivery disruption will be minimal.

A deteriorating economic environment

IT services spending is cyclical and dependent on GDP growth expectations. The macro-economic environment has deteriorated with the February 24 Russian invasion of Ukraine, amplifying existing trends at play. In its January 2022 World Economic Outlook Update, the IMF warned, beyond COVID, of “rising energy prices and supply disruptions” leading to higher and more spread inflation globally. In January, the IMF revised down its global GDP growth estimates.

There is no doubt that the Russian invasion of Ukraine, with its impact on energy, will accelerate trends at play before the invasion. In late April, we expect the IMF to further reduce its GDP growth expectations, for both North America and Europe.

Digital drives higher spending

However, the connection between IT services spending and GDP growth has changed. In a previous blog, IT Services in 2022: Entering A New Growth Phase, we highlighted that until 2019, IT services spending typically grew around 100 bps slower than GDP growth. From 2021 onward, we expect IT services spending to grow faster than GDP growth, driven by digital, security, and cloud. IT services spending growth in 2022 will be similar to 2021, between 6% and 7%.

Prices will remain under control despite the talent shortage

The hiring effort supports our growth hypothesis. Despite the many discussions about the lack of talent in the industry, data from the top eight India-centric IT services vendors⁽¹⁾ show they recruited in calendar 2021 at scale. Net recruitments reached ~330k employees. This headcount increase is exceptional.

We are entering the calendar Q1 2022 financial announcement season and will be tracking net headcount growth. An early indication came from Accenture for its Q2 FY23 results (ending February 28, 2022): the company increased its headcount by 24k (vs. 28k in Q2 FY21). Hiring remains sustained.

Despite the talent shortage, vendors have the ability to scale up and wage inflation is likely to remain under control. Meanwhile, vendors continue to accelerate their use of automation and cognitive technologies to drive further efficiencies and reduce, to some extent, their dependency on recruitment.

The Russian war in Ukraine brings great uncertainty

And then of course are the uncertainty factors, and this year they center on Russia, notably the duration of Russian’s invasion of Ukraine. If the war lasts longer or expands, the IMF predictions will again lower GDP growth.

We expect two scenarios form a long-lasting conflict.

• Most enterprises set up their annual budgets in the September/October period: if the war continues (or concerns remain about new Russian conflicts in Central Europe), many large enterprises will seek to reduce their IT budgets. A significant freeze in Q4 2022 spending (and for full-year 2023) is still possible. 2022 may be a year of high spending increase in Q1-Q3 with a sharp decline in Q4. In parallel, enterprises will increase their cybersecurity funding and will delay their digital projects, should the war continue or expand
• IT services spending will shift. While it will decline for enterprises, it will increase among central governments, around defense IT, data analytics and AI, and cybersecurity.

This year will be bumpy.

(1): Accenture, TCS, Cognizant, Capgemini, Infosys, Wipro, HCL Tech, and Tech Mahindra.