ISG Provider Lens™ Analytics Services - Data Science Services – Large - Europe 2023

23 Jan 2024
by Gowtham Kumar, Vartika Rai, Saravanan M S, Jan Erik Aase

CDOs will invest in analytics-led transformation programs to enable data and AI-driven decision intelligence.

The analytics services market in Europe saw significant traction and demand, which empowered providers to innovate and revolutionize to address enterprise challenges in sub-optimal utilization of the data and analytics investments. ISG’s analysis indicates that enterprises in Europe continue to face challenges like their counterparts in other regions. However, the market shows a clear distinction in approach and investments, given the varied levels of analytics maturity among large and midsize enterprises.

Enterprises in Europe face multidimensional challenges spanning geopolitical tensions, economic  uncertainties, rising operating costs, supply chain disruptions, and environmental regulations and  sustainability practices. The economic outlook uncertainties, including volatile currency value and market dynamics, disrupt operations and planning, thereby creating a challenging environment for enterprises in Europe. Enterprises also need to navigate the escalating operational costs resulting from macroeconomic factors such as fluctuating energy prices and shifts in labor costs. The increased awareness of environmental compliance has triggered a drastic shift toward sustainable practices. Enterprises in Europe are confronted with the peculiar challenge of aligning their operational strategies and methods to comply with stringent environmental norms and regulations. Recognizing the need, enterprises need to mandate a fundamental reevaluation of production processes, supply chain management and product offerings to ensure adherence to green standards.

Therefore, the approach to identifying challenges and the ensuing activities to ensure effective operational performance, reduced costs, increased governance and enhanced CX largely aligned with the enterprise’s analytics maturity. The market highlights the need to accommodate and align with the global trends in fostering data-centricity and a data-driven culture.

ISG has identified the following challenges enterprises face:

Analytics spending and rationalizing investments: European enterprises see heightened consciousness of technology spending amid rising fear of a potential recession and prevailing economic headwinds. These uncertainties directly impact the budget for analytics spending and restrain CDOs’ ability to invest in analytics tools. Enterprises in Europe are strategically focused on maximizing the utilization of their existing data and
analytics investments and tools, reflecting a prudent and cost-effective strategy and deliberate effort to rationalize and optimize data and technology assets. This emphasis on seeking to extract optimal value from their current data and technology assets in the face of economic challenges signifies the importance of rationalizing data assets.

Adoption of enterprise-wide analytics: Many European firms are confronted with the imperative of undergoing analytics adoption and transformation, which involves adopting cutting-edge technologies, churning out legacy systems, and instilling a digital mindset and culture within the enterprise. The adoption of analytics tools and systems demands a substantial upgrade of their existing infrastructure, involving  careful engineering and integration of data assets. This process requires meticulous planning, technical expertise and execution to ensure that the upgraded infrastructure effectively supports the analytics tools’ functionalities and provides the necessary foundation for datadriven decision-making. Cultivating a digital
mindset necessitates a cultural shift, requiring employees to adapt to and embrace a more data-driven approach to business processes. Overcoming these challenges is crucial for enterprises aiming to harness the full potential of analytics and position them competitively in the evolving market.

Efficient systems and models for use cases: Enterprises in Europe are hurdled with numerous challenges across business functions, including, but not limited to, expense efficiency, productivity, market expansion, product diversification, adaptability, innovation and operational agility. Enterprises must address these challenges, and this requires robust strategic planning, leveraging technology, and fostering a culture of
innovation and adaptability. European firms need to find a balance between compliance, cost-efficiency and innovation to thrive in a competitive and dynamic business landscape. Firms need to invest in technology-driven applications that facilitate swift transformation and automate every component of the business value chain.

High technology infrastructure costs: Technology infrastructure costs are drifting higher as enterprise data volumes are expanding. Managing these expenses through strategic decision-making can lead to  efficient and cost-effective solutions that support business objectives. European firms need to forecast future infrastructure needs and associated costs based on historical data and trends that could assist in better  budgeting and planning. This could aid business users with comprehensive data analysis, enabling them to make informed decisions about technology spending and strategies while considering cost implications.

Dynamic changes in data compliance and regulations: Data regulations and compliance are often complex, requiring a deep understanding. Applying them is more challenging for enterprises that handle diverse data sets and operations. The landscape of compliance and data regulations is dynamic, as regulatory bodies are introducing new requirements, posing significant challenges for enterprises. As data assets are siloed across the enterprise, it is difficult to meet compliance standards for data integration and management
across sources. Data complexity and massive data volumes make adherence more challenging. Addressing the changes requires a proactive approach as enterprises need to update, adapt and align with these regulatory and compliance changes.

New revenue streams: Many enterprises in Europe struggle to identify markets and niche segments that are untapped at present. The challenge is largely in identifying and capitalizing on opportunities that can
significantly impact their revenue streams. Investment in analytics yielded robust insights on identifying the uncatered markets and segments and also led to the development of new products and solutions, creating new revenue streams. Enterprises can also monetize their data and create additional revenue streams by selling data-related products and services through packaged data as reports or insights; providing subscription-based access to data platforms; licensing secure data access; partnering for joint services; and providing targeted customer insights.

Skill and talent gap: The continuous advancements in digital technologies such as generative AI (GenAI), ML and big data analytics necessitate specialized expertise. While European enterprises rapidly embrace these technologies, there is a substantial shortage of skilled professionals with these niche skill sets. The exponential surge in data volumes further demands proficient advanced technology and digital  professionals capable of effectively managing, analyzing and extracting valuable insights from extensive and complex data assets. This shortage of skilled talent poses a significant obstacle for businesses aiming to fully harness the potential of these cutting-edge technologies, impeding their ability to capitalize on the wealth of data and information available and, in turn, hindering innovation and competitive edge.

CDOs are actively seeking the following solutions to enhance their current circumstances in handling data, particularly to incorporate business transformation through AI/ML-led enhancements. They are keen on solutions that empower them to derive meaningful insights, foster innovation and drive strategic decision-making through their data initiatives.

Aligning with business objectives and KPIs: CDOs are looking for solutions that help them better prioritize their data-centric initiatives and align them with enterprise business objectives. Service providers can equip enterprises to establish a solid foundation to build their AI strategy utilizing their IP assets such as accelerators, frameworks and platforms that are powered by digital technologies like AI/ML, deep learning, NLP and computer vision.

Unlock analytics investments: Enterprises aim to foster an innovation mindset and culture that significantly pushes them to invest in digital capabilities, analytics and AI. They want to unlock value quickly, responsibly and sustainably from analytics to embrace an AI-led operating model. Service providers can help enterprise shift their approach to deliver impactful data-driven decisions at a considerably reduced cycle time. Enterprises aim to realize and unlock value from existing data and analytics investments in identifying new business opportunities and optimizing processes utilizing advanced analytics technologies. Establishing key performance indicators (KPIs) is critical to validate the alignment with business goals. KPIs can include metrics related to revenue growth, customer retention, operational efficiency, cost savings and improved decision-making to track the impact of AI initiatives in real time and make data-driven adjustments to ensure continuous improvement.

AI and automation-driven intelligence: European enterprises aim to adapt to an AI-driven approach for operational decisionmaking, fully utilizing the value of data, including AI, in their workflows and processes. The evolution to an AI-driven approach amplifies the swift processing of structured data, augmenting human intelligence, decision-making and problem-solving capabilities utilizing AI algorithms, ML models, NLP and other advanced analytics to process vast amounts of data, recognize patterns and generate insights. Service providers are highly equipped to drive the entire transformation that could further lead to automated decision intelligence.

Decision-making with real-time insights generation: Real-time insights provide enterprises with instant updates on information that enables proactive decision-making and rapid response to market dynamics. Service providers have invested and developed capabilities to overcome the limitations of batch processing and delayed reporting, which causes lags in decision-making that cost time and resources. Enterprises need to be equipped with complex event processing, large-language models (LLM), GenAI, ML, NLP and other advanced analytics capabilities to derive actionable real-time insights from streaming data for agile decision-making with higher accuracy.

Robust data architectures and governance: Enterprises need to democratize data management, envisioning data not in silos but freely accessed between different systems, applications and users. Data mesh architecture shifts toward automated analytics at scale, delegating dataset ownership from centralized to individual teams or business users, enabling agility and scalability within a decentralized governance framework to power real-time decision-making in businesses.

Notes on quadrant positioning: In this study, several data analytics service providers that offer similar portfolio attractiveness in most quadrants have been assessed. This reflects the relative maturity of the market, providers and offerings. It is a given that not all are equal in circumstances. The vertical axis positioning in each quadrant reflects ISG’s analysis of how well the offerings align with the full scope of enterprise needs. The market has also been segmented into large, midmarket and specialists to showcase the varying analytics requirements of enterprises based on their size, scale and industry dynamics. It also reflects providers’ strategy to align their portfolio and offerings to suit market demand and enterprise needs.

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