Introduction
First San Francisco Partners (FSFP) assessed a large U.S. credit union’s data governance (DG) function and delivered a future-state vision, prioritized improvements, and a multi-year roadmap with an implementation playbook. The work gives client leadership a clearer path to strengthen data ownership and decision-making while preparing the organization’s data for analytics and AI.
About
Our client is one of the largest credit unions in the United States. Essentially, the client provides the exact same banking, lending, and investment services as a traditional commercial bank, but with a strictly defined focus on their targeted members. Because they are a credit union, they do not answer to Wall Street or private shareholders. Instead, all excess earnings are channeled back to their large number of members in the form of lower loan rates, higher savings yields, and minimal fees. In addition, they provide personalized member experiences by combining their industry expertise with data-driven advisory and innovative technology capabilities across multiple platforms and delivery channels.
Industry: Financial Services
Background
The client conducts a periodic recurring Data Governance Maturity Assessment to align its DG practices with emerging technology and advanced analytics initiatives. This initiative builds upon a long-term partnership with First San Francisco Partners, which previously established a successful, enterprise-level data governance function. Recognizing that data governance is critical to the success of its strategic, data-driven initiatives—including advanced analytics and Artificial Intelligence (AI) solutions—executive leadership sponsors these periodic assessments to maintain a competitive edge amidst rapidly evolving industry standards and to continuously accelerate organizational capabilities.
Engagement Type
Enterprise Data Governance Maturity Assessment, Future State Visioning, Gap (current>future states) Analysis, Business Impact Assessment, Recommendations (Organizational, Process, Technology, and Data) including Data Decisioning Model, Data Strategy & Roadmap Development (multiple year time horizon), Actionable Strategy Implementation Playbook.
Opportunity Areas
- AI data readiness by default
- Need to improve the effectiveness and efficiency of enterprise level data decisioning (and its integration with AI decisioning (operating) model)
- Need to formalize enterprise data ownership and definitions
- Need for formalized business data stewardship
- Need for better DG policies and standards enforcement
- Need to integrate data governance “data” perspectives into project prioritization processes
- Need for a clear, comprehensive enterprise level data strategy understandable by business
Engagement Snapshot
Our client engaged FSFP to conduct an external, structured assessment of its current data governance function, benchmarked against FSFP’s maturity model, that produces a prioritized gap analysis, future state vision, and actionable roadmap the organization can execute against, measure progress on, present to executive leadership and examiners over time.
- Conducted a current state assessment of the data governance function
- Guided development of a data governance future state vision
- Identified and prioritized maturity level gaps across the in-scope data governance capabilities and for each capability – across its dimensions of people (organization), process, technology, and data
- Analyzed and identified the major business impacts resulting from the maturity gaps
- Delivered an enterprise level data governance strategy and roadmap that outlines priority capabilities and resource needs
- Delivered an very detailed, agile, and comprehensive playbook to implement the data governance strategy
Outcomes
Client leadership has an updated vision of what is required for its enterprise data governance function to build on its current foundation and focus on the formalization and expansion to modernize data governance in a rapidly advancing data ecosystem with a focus on data ownership, decision rights, enforcement, and AI data readiness.
The engagement resulted in the following:
- Better understanding of what is required to progress data governance current maturity to achieve leadership’s desired future state – a data governance function that not just supports and enables, but helps accelerate growth, efficiency and future innovation
- Clear understanding of the maturity level gaps between current and future state across people (organization), process, technology and data
- Recognition of gaps’ business impacts – each one names a capability that, once built, unlocks value rather than just closing a deficiency — clearer prioritization, faster and better decisions, less rework, and a data ecosystem better positioned to enable and accelerate for AI, analytics, etc.
- Multi-year enterprise level data strategy and roadmap including a comprehensive detailed and actionably playbook to implement the strategy and roadmap that enables stronger planning and execution alignment, so teams pull in the same direction
- Clearer recognition of key business leaders’ savvy understanding of the need for and value of better decision-making so leaders and teams can achieve faster time to value
