Executive Summary: ISG Provider Lens™ Analytics Services - U.S. 2022
27 Jan 2023
by Gowtham Kumar Sampath
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ISG Provider Lens™ Analytics Services - Data Monetization Services - U.S. 2022
Analytics services are driven by enterprise data centricity
The demand for analytics solutions and services has gained significant traction in the U.S., given the growing realization among enterprises that they need to leverage data for driving their business objectives. The market reflects global trends in terms of IT and digital maturity, and analytics solutions act as a hub for centralized business decision-making for several enterprises.
The market is on the cusp of the realization that data and analytics are not only central and core to the successful performance of businesses but are central to their survival. The role of data has never been more important –there is a need to drive decision making and infuse analytics for delivering results beyond business expectations. In light of these developments, ISG’s analysis reveals that enterprises are focused on the following:
• Customer centricity: Investment in process and methodologies underpinned by solutions that drive high levels of personalization and customization
• Business centricity: Investment in tools and technologies that combine and augment human-machine collaboration to drive business decisions for operational and process excellence
• Data centricity: Approach and mindset that culturally identifies and understands data as the prime enabler of business, operations and the process to drive employee engagement Although these seem to be different focus areas, every enterprise must achieve optimum levels of harmony between these three facets to grow their businesses. Depending on their level of digital maturity, many enterprises are trying to achieve customer and business-centricity for driving analytics revenues. A handful of large firms and some small niche firms are already operating on high levels of data-centric or data-driven approaches. Some of them include Coca-Cola, Disney, McDonalds, DBS Bank, Uber and technology companies such as Netflix, Google and Apple.
Customer experience or customer engagement focus
This is viewed as an area that is addressable for implementing analytics solutions and yet a challenge for enterprises across several verticals. Hyperpersonalization and hyper-customization are becoming important tools for attracting new customers and preventing churn.
• The market is attracting significant investments from enterprises for customer service and customer-related solutions and services. Customer analytics has become a standardized and pre-packaged analytics solution across several large and specialist analytics providers. Service providers are also actively offering analytics solutions covering topics such as customer value, customer experience, customer journey, and customer engagement to better drive enterprise customer strategies.
• Service providers are looking at customer touchpoints including omnichannel AI, IoT and the edge, conversational AI platforms, chatbots, and other social media APIs to derive insights. Increasingly, these touchpoints are becoming embedded with simple and contextual AI capabilities to deliver an enhanced customer experience.
• Service providers are offering readily available and tailored versions of customer 360 and customer data platforms that are designed to address the specific demands of customer experience and management. In addition, the use of customer analytics is also promoting data monetization and data ecosystems that enable better data sharing and new revenue streams with existing data.
• In the U.S., enterprises across retail, telecom, banking, automotive and the public sector are investing in customer-centric solutions and services. Demography, buying behavior, buyer profiles and many data points are evaluated to address customer preferences, customer segmentation, product positioning, pricing and discounts, problem resolution, customer churn and other parameters.
Decision science, or intelligent decisioning, is taking center stage
Enterprises and service providers are starting to consider the business context while investing in analytics solutions and services, rather than viewing it as mere technology or infrastructure element.
• Data science is no longer viewed as the statistical or algorithmic approach that combines AI, machine learning and automation to offer solutions. The approach and projects are leveraged to empower deep intelligence and insights that drive business decisions. In fact, the term data science is slowly fading, with decision science becoming the norm across providers and enterprises.
• Decision science is becoming a critical aspect of most analytics projects for driving business and even life-saving impacts. In the U.S. healthcare industry for example, medical decisions on the treatment of anomalies and the presence of life-threatening illnesses and many other diseases are being handled by sophisticated AI systems that can deliver high accuracy.
• In certain cases, these systems were able to read and diagnose from images with low or poor resolution. In the life sciences and pharmaceutical industry, decision science is being leveraged to create drugs and other pharmacological inventions. In the agriculture sector, these technologies help detect viruses and crop-eating diseases in real time.
• From a business perspective, enterprises across retail, banking, telecom and even technology companies are leveraging data science and analytics to help them decide store locations, borrower profiles in lending and mortgage, rate fluctuations in utilities and many more advantages. Service providers, especially specialists or pure-play analytics providers, are taking advantage of these opportunities to offer highly customized services and solutions that are vertical- or domainspecific, especially for utilities, banking, telecom and retail.
Data literacy growing as an investment area: In the U.S., the aftermath of the pandemic and threat of a looming recession have created an impending necessity to become data driven, with key executives and business leaders investing to modernize their data infrastructures. Across large, mid-sized and small segments, enterprises also realize that becoming data centric is a steep challenge and can’t be realized with just investments in technology. ISG advises that enterprises should invest in fostering a data-driven culture that impacts every employee and line of business to change perspectives and view data as a lever for business outcomes.
• Enterprises in the U.S. are investing in opportunities for executives and employees that create a shift in their mindsets to drive business with dataled intelligence.
• Aside from offering training, service providers are also employing selfservice modules and capabilities in data science, data engineering, data governance and management and business intelligence solutions. These modules enable citizen data scientists, line of business managers and even executives to better capitalize the investment on analytics.
• Data literacy is gaining mindshare and investments across enterprises, including public sector agencies, emphasizing the need for better data strategy and governance. The Foundations for Evidence-Based Policymaking Act created a U.S. law that requires the federal government to modernize its data management practices. The act also envisages a 10- year national data strategy to encourage data to be used as a strategic asset and the appointment of chief data officers across every federal agency. The following are some of the key factors disrupting the market dynamics:
• Industrialized solutions continue to gain traction, with service providers offering analytics tools and accelerators built on rich experience from vertical and domain experience.
• Business-outcome-led delivery is a major facet that providers increasingly attach with solutions and services.
• Cloud-native solutions and services, as well as cloud migrations, continue to gain traction as enterprises continuously invest in transformation and modernization.
• X-Ops: The analytics market is abuzz with keywords such as AIOps, MLOps, DataOps, DevSecOps, signifying the heightened level of AI productization.
• X-First: Providers are taking a “data-first” approach and marketing their solutions to drive the importance of data, customer, AI and cloud. Consequently, the market is undergoing aggressive consolidation, with several acquisitions targeted at improving portfolio attractiveness and competitive strength. In addition, there is intense collaboration among providers and vendors to create a robust ecosystem of partners for addressing specialized industry needs, compliance requirements and future-proof solutions.
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