Overview

This report summarizes the findings from a Data Analytics Maturity Self-Assessment completed by credit unions. The assessment aimed to evaluate the current state of data analytics capabilities within these institutions, highlighting strengths, challenges, and areas for improvement. The survey collected responses across five key areas: Strategy, People, Process, Technology, and Outcomes.

Key Findings

1. Strategy

   • Defined Strategy: 23.75% of respondents indicated that their organization does not have a specific defined strategy for data analytics, while 37.5% mentioned that there is an activity-based strategy present in organizational pockets. Only 22.5% of organizations have tied their data and digital strategy to corporate objectives.
   • Measurement and Reporting: A significant majority (57.5%) reported that analytics are primarily used to monitor and track individual activities with Key Performance Indicators (KPIs) defined for less than 50% of the business functions. Only 5.63% of organizations have an enterprise-wide dashboard with KPIs defined and reported for all business functions.

2. People

   • Staffing: Over half of the respondents (52.87%) stated that data analytics roles are defined, though one person often performs multiple roles. Only 4.46% reported that data analytics is the integral focus of each department.
   • Self-Sufficiency in Data Access: 54.78% of respondents mentioned that less than 50% of functional business users have access to data and are trained to pull their data for operational reporting. A small percentage (2.55%) indicated that business functions are extremely data-savvy and capable of advanced analytics modeling.

3. Process

   • Engagement in Data Analytics: 55.77% of respondents reported that less than 50% of the business functions are mature enough to act on the data in a timely manner. Only 5.13% stated that their organization functions in a streamlined manner to act on data insights in quick, repeatable cycles.
   • Data Delivery: 24.36% of respondents indicated that the delivery of data is ad-hoc. Only 7.69% have predictable data delivery across 100% of the organization.

4. Technology

   • Data Technology Platforms: A large portion (39.10%) of organizations have less than 50% of their business function applications connected to an integrated data technology stack. Only 3.21% use unified technology platforms that drive end-to-end closed-loop data integration.
   • Data Integration: 44.87% of respondents reported using a disparate system with mostly canned reports, and only 2.56% have all organizational systems integrated with appropriate platforms.

5. Outcomes

   • Member Experience: 35.86% of respondents described their member experience as unremarkable. Only 8.28% reported organizational alignment on the value of total member experience.
   • Team Member Experience: 36.55% of respondents noted that their team members spend a lot of time on repetitive work and reconciling numbers. Just 2.76% mentioned that their business functions operate with the highest efficiencies, providing value to members with few internal data challenges.
   • Successes from Data Analytics: Nearly half of the respondents (48.28%) reported 1-5 successes yearly with minimal impact on the top or bottom line. A small fraction (4.83%) indicated that data is seen as a key differentiator, with more than 20 significant successes per year.

Trends in the Credit Union Industry

The credit union industry is experiencing several key trends related to data analytics that are expected to continue in the coming years:

1. Increased Focus on Data-Driven Decision-Making: As the financial landscape becomes more competitive, credit unions are increasingly recognizing the importance of data-driven strategies. The trend is moving towards integrating data analytics into core business processes, although many are still in the early stages.

2. Adoption of Advanced Analytics and AI: There is a growing trend towards leveraging advanced analytics and artificial intelligence (AI) to enhance member experience, optimize operations, and drive growth. However, this trend is still in its nascent stage within many credit unions, with significant room for growth and maturity.

3. Emphasis on Member Experience: Improving the member experience through better data insights is becoming a top priority. This involves creating unified member journeys and ensuring data is used effectively to personalize and enhance interactions.

4. Challenges in Data Integration: Many credit unions face challenges in integrating disparate data systems, which hampers their ability to fully leverage analytics. There is a trend towards investing in integrated technology platforms, though progress is gradual.

5. Investment in Data Governance: As data becomes a more critical asset, credit unions are increasingly focusing on establishing robust data governance practices. Ensuring data quality, consistency, and security across the organization is becoming a key area of investment.

Recommendations

To improve their data analytics maturity, credit unions should consider the following actions:

• Develop a Comprehensive Data Strategy: Align data analytics strategies with corporate objectives to ensure they support broader business goals.
• Enhance Data Literacy: Invest in training and development to improve data literacy across the organization, empowering more users to engage with data-driven insights.
• Streamline Processes: Work towards integrating data into decision-making processes across all business functions, enabling quicker and more informed decision-making.
• Invest in Technology: Focus on building or acquiring integrated technology platforms that facilitate end-to-end data management and analytics.
• Prioritize Member Experience: Use data to drive improvements in member experience, ensuring that analytics contribute directly to enhancing service quality and member satisfaction.

By addressing these areas, credit unions can accelerate their journey towards becoming data-driven organizations, positioning themselves for sustained success in an increasingly digital and competitive environment.

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