Is It Time to Reboot Your Organization’s Data Strategy?

Is It Time to Reboot Your Organization's Data Strategy?Data and analytics are at the heart of the digital revolution in the banking and financial services industry. Yet, most legacy financial institutions (FIs) struggle to unlock the full value of data assets when making informed decisions that enable strategic business outcomes like managing down overhead costs and generating higher revenues through personalized product offerings.

Having the right technology and processes in place is not enough to enable organizations to fully leverage data and analytics for business transformation. Banks and FIs need a strategy that addresses how insights are derived from data to shape business decisions.

Data Analytics Challenges Persist

While data and analytics are being leveraged to drive the industry’s transformation, banking and FI CIOs and CTOs consistently tell us that their organizations are still behind when it comes to realizing the full potential of data to achieve strategic business objectives. Antiquated processes and tools coupled with the massive, increasing volume of data coming into organizations render current approaches insufficient to capture and transform data into insights that support business outcomes.

In addition to having the right tools and applications to do high-value analytics, organizations’ strategies are not fully aligned to enterprise-level priorities. Traditionally, strategies were developed within the individual business lines, resulting in ad hoc investments and the absence of a formal data governance program to define common practices for data collection, transformation, use, etc.

Therefore, it’s unsurprising that banks and FIs are struggling to mature their analytics on the effectiveness of operations and services that drive sustained improvements in business performance.

The Enterprise Needs a Data Strategy

To derive insights that drive business decisions, banking and FI CIOs and CTOs should redesign or create a new, unified, enterprise-level data strategy that addresses people, processes, and technology as well as how these components are leveraged to get value from data assets while maintaining regulatory compliance.

A comprehensive strategy serves as the framework for how an organization uses data to drive transformation initiatives, centering data collection and use cases (and required investments) on supporting the realization of mission-critical objectives. However, given the diversity of practices, tools, and data flows, it’s difficult to develop a data strategy that looks across the entire business.

Data Strategy Checklist Considerations for CIOs and CTOs

To support bank and FI CIOs and CTOs in successfully defining and adopting a comprehensive enterprise data strategy, Aite-Novarica Group recommends auditing the organization’s current approach (or set of business line practices) to address several considerations.

The following are essential to developing or redeveloping a strategy that provides a unified framework to steer how data is integrated into high-value decisions:

  • Has a comprehensive data ecosystem assessment been conducted in the past two years?
  • What tools and applications does the organization deploy to collect, store, transform, and facilitate extraction of data for analytics? Are different tools/applications required?
  • Does the organization have a formal (documented and cascaded) data governance program that defines key practices like guidelines for how data can and cannot be transformed, along with a data dictionary? If so, how consistently is it adopted across the organization?
  • What progress has been realized in building and executing on a data blueprint to prioritize investments in data governance, quality, and security?
  • Does the organization have or need an updated data architecture that defines how all the various data components (data flows, technologies, processes) interconnect?

Answers to these questions enable IT leaders to address challenges related to current constraints and inadequate practices that hinder deriving insights. For example, a comprehensive data strategy enables FIs to get better returns on investments in AI to analyze business performance metrics like internal rates of return, portfolio management insights, algorithmic trading outcomes, customer retention through personalized offers, and optimal regulatory compliance.

How We Will Help You Develop an Enterprise Data Strategy 

By defining or redefining a comprehensive data strategy, IT leaders enable their organizations to effectively conduct analytics that improve operational efficiency and make informed decisions to support growth and achievement of non-financial strategic outcomes.

The considerations outlined above form the basis of a new, proprietary checklist brief exclusively for IT leaders who are members of Aite-Novarica Group’s Financial Services CIO/CTO Advisory Practice.

Interested in learning more about how our strategic insights can help you advance your organization’s maturity in using data to make smarter, more informed business decisions?

Join the conversation at our May 24 Financial Services CIO/CTO Advisory Research Council to engage with best practices and insights. Research Council members get free access to a subset of the research we deliver to executives who join our new Financial Services CIO/CTO Advisory Practice. 

Email me, and I’ll reach out to schedule an introductory conversation on our Financial Services CIO/CTO Advisory Research Council.

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