Healthy data practices to pave the way for a financial institution​

Financial Services

Background

The client is one of the nations oldest and largest financial institutions offering retail and commercial banking products and services to individuals, small businesses, middle-market companies, large corporations and institutions. The client’s operations team needed insights from their data, specifically focused on the reorganization. The data was thought to live in Content Manager On Demand (CMOD) but finding and making use of that data proved difficult. The Operations team knew in concept what they hoped to understand from the data but struggled to produce forward-looking insights – they mainly used reporting to track work volume and employee capacity, with a heavy dependency on Excel. Systemically, the organization was not able to use data to drive business decisions, to provide actionable views, or to realize any customer experience updates. A bridge team was necessary to better connect the data experts within the Data org to the reporting experts within the Operations org.​

Response

SingleStone evaluated the data usage patterns and techniques across the organization and provided recommendations, guidance, and plans to maximize the value of Consumer Deposits and Loan Servicing (CDLS ) data and reporting for business decision making.​

After a 3-sprint discovery phase, SingleStone fully understood the client’s goals and desired target state and identified key common data patterns. Through extensive review of the client’s data infrastructure and delivery mechanisms, and continual conversations with key stakeholders, SingleStone compiled a prioritized list of dashboard reporting requirements and a detailed backlog of future enhancements.​

SingleStone ultimately delivered a prioritized list of CDLS improvement opportunities; a future-state strategy roadmap/backlog and high-level implementation plan; and a proof-of-concept for data sourcing and data visualization (Tableau).

Result

  • A current-state assessment, providing initial findings and declaring a target end-state for the engagement.​
  • A data assessment focused on data infrastructure, delivery, and accessibility observations. This also included a data maturity assessment, detailed user persona-based requirements, and provided improvement opportunities.​
  • A CDLS roadmap providing a framework for business process management, metadata, data warehousing, and BI ecosystem management.​
  • A proof-of-concept data sourcing/visualization dashboard in Tableau.

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