Data modernization is a digital imperative for enterprises to create business and customer value

Fundamentally, data is too federated across legacy systems, databases, storage silos, pipelines, and warehouses. Designed and implemented over decades, these legacy systems and architectures posed limitations in flexibility, interoperability, security, and scalability when pressed to deliver insights for current organizational needs.

With the emergence of cloud computing, enterprises are migrating, building, and integrating cloud-ready data solutions that help process, store, and analyze data efficiently and at speed. However, hybrid data estates vex many firms, which seek partners that can assess their data needs and co-develop with technology teams to modernize solutions that are fast, secure, and ready for new artificial intelligence, analytics, and automation technologies.

As technology teams transition from cloud-focused digital transformation and application modernization (covered in our HFS Top 10: Application Modernization Services, 2022 report), the mountain of data is a significant hurdle. Given its complexity, leading service providers and advisory firms must offer a mix of domain knowledge, certified professionals, governance best practices, and hybrid cloud capabilities. While data generation and its collection, processing, and storage have been part of legacy data systems, a data estate also requires a coordinated effort from business and IT stakeholders to handle security, quality management, governance, and compliance.

HFS sees this effort as essential to developing a data estate that addresses the next phase in the life of a data record, which is deriving insights from analyzing the data estate of an enterprise via visualization and analytic tools to help the enterprise make informed and timely decisions (see Exhibit 1).

Exhibit 1: The life of a data record is visibly divided into two phases: the data estate and insights and decisions

Source: HFS Research, 2023

Data modernization is about re-architecting the data estate from siloed, federated repositories serving few to a far-reaching cloud-native architecture

Enterprises must adopt an integrated, accessible data architecture that business and technology teams can readily collaborate upon to discover, build, manage, and securely access and build meaningful, actionable insights and applications that deliver results. HFS defines data modernization services as a value chain of capabilities and professional services across the following six value chain areas:

• Discovery and assessment
• Platform architecture design
• Migrate, create, and retire
• Integrate, automate, and orchestrate
• Operate, run, and deliver
• Govern and secure

Service providers and advisory firms in data modernization services are entrusted to build a robust data estate for their customers. In our HFS Horizons: Data Modernization Services, 2023 report, we assessed and profiled 23 service providers and advisory firms, identifying their unique strengths and weaknesses.

Firms need to accelerate their data modernization to create a foundation for insights, analysis, development, and innovation

The primary data modernization challenge for enterprise firms is moving away from legacy architectures and systems (see Exhibit 2). These firms cite limitations on talent and budget needed to address the changes required to re-architect their legacy data estate. Additionally, these firms expect the service providers and advisory firms to proactively help them address the regulatory requirements as part of the larger data modernization strategy. The contributions from data and technology vendors are also crucial as they help service providers and advisory firms co-develop software and services go-to-market and delivery across regions and markets.

Exhibit 2: Moving away from legacy data architectures and systems is the toughest part

Sample: 33 business and operation leaders, HFS Horizons Report: Data Modernization Services, 2023
Source: HFS Research, 2023

Enterprise firms need help from their service providers to turn data into analytical insights and provide valuable partnerships with data and technology vendors to aid in the selection, negotiation, and implementation of their products and ready the technology and business teams to adopt and use these solutions (see Exhibit 3).

Exhibit 3: Service providers and advisory firms must be ready to help customers go beyond data into analytics and insights

Sample: 33 business and operation leaders, HFS Horizons Report: Data Modernization Services, 2023
Source: HFS Research, 2023

Many service providers, including LTIMindtree and Hitachi Digital Services, have begun giving due importance to orchestrating data from IT, IoT, and OT (operational technologies) across hybrid (on-premises and cloud) architectures. OT and IT create tons of data that helps suppliers with manufacturing tools, systems, and transportation, for example. The result is a modern federated model that uses logic to improve how data flows across the organization and supports the growing need for composable applications, integration AI, and analytics in a secure, governed manner.

A successful data modernization journey is about defining how your data fulfills the enterprise’s needs as an asset and a product

Service providers and advisory firms approach a future state for data not as a technological solution but as how the desired state allows a firm to see its data as an asset or a product. This is an important consideration we cannot underscore enough for enterprises beginning or amid their data modernization journeys. Have you asked yourself where your improvements in your data landscape can lead to unleashing the untapped value of your data assets? Can this asset allow your teams to make better, faster decisions? Or does improving your data estate lead to data becoming further ingrained or extracted as a product? Data-as-a-product is well understood in the technology industry and sought in mainstream enterprises; however, the planning for structuring and managing data and making it available differs for each model.

Enterprises must differentiate the data technologies they are modernizing with the insights and decisions they want to drive

Enterprises need services providers’ help defining and implementing sustainable strategies for building data-led solutions to monetize their data as an asset and a product. While data used as an asset shows technology and operational impact, data used as a product drives business and customer impact (see Exhibit 4).

Exhibit 4: Interoperability between data-as-an-asset and data-as-a-product is crucial to building trust in data and its outcomes

Source: HFS Research, 2023

The Bottom Line: Service providers and advisory firms must bring an ecosystem of partners, domain knowledge, and tools to aid their customers in the data modernization journey.

An enterprise’s data modernization journey must begin by focusing on the business outcomes. With the right focus, the enterprise can pivot and close existing technology gaps, widen innovation channels, and adapt better to market changes. A successful data modernization journey will require disruptive, forward-looking service providers and partners to adopt emerging technologies and provide truly experiential rewards to customers. Selecting the right partner is about knowing your firm’s outcomes, from addressing legacy data to intertwining your data with an extensive global ecosystem to optimize operations through insights.