To gain a comprehensive understanding of the client’s current data management strategy and practices, we conducted discovery sessions and workshops. These sessions were guided by Marlabs’ design thinking framework and involved separate discussions with stakeholders to assess the current state of data management, its alignment with organizational goals, and identify any gaps or inconsistencies across teams. Additionally, we conducted a series of interviews with data producers and consumers across the organization, which served as the foundation for redefining the data management strategy. The outcome of these efforts was a roadmap outlining the client’s desired future state, including a detailed list of actionable gaps in the areas of People, Process, Technology, and Data. It also revealed the need for a foundational enterprise architecture that would act as a central hub for aggregating data from various data providers and distributing it to all relevant consumers.

To implement this significant change, we began with small, incremental steps to ensure that all stakeholder concerns were addressed while prioritizing scalability. Our approach involved:

• Configured data quality parameters to address data trust concerns
• Designed and implemented a data governance process to control the data
• Refined business expectations on use case delivery through real-time data feeds
• Articulated change management process aimed at providing finer control over processes between data providers, data processors, and data consumers
• Designed and presented a plan for periodic data maturity measurement and improvement goals