Data Governance

How to run a successful Information Governance program

Organizations are often mature in Business Intelligence and Master Data Management, but have struggled with complex, opaque and ineffective Information Governance (IG) programs or have completely avoided the challenge in the first place. By neglecting IG, they risk undermining their analytics, big data and data science ambitions. Also, large organizations often struggle with volumes of data policies and procedures that are either out of date or poorly enforced.

Enterprises often fully understand the benefits from IG programs such as:

  • Enabling better/smarter analytics, more credible reporting and forecasting
  • Reducing data complexity and process redundancies
  • Facilitating regulatory compliance around data lineage/traceability (e.g. Basel regulation BCBS 239 for larger banks)
  • Better understanding of what is being pumped into the large and complex data lakes
  • Preventing costly, data-related delays in large implementation programs.

ebenezer recommends a structured approach that:

  • Breaks down the often significant IG workload into manageable, prioritized activities
  • Engages and involves all relevant business and IT stakeholders
  • Iteratively produces a constant flow of deliverables
  • Usually takes a data domain-centric approach – this is where organizations often lack experience.
  • To ensure success, IG programs need to be practical, pragmatic, active, inclusive, business value-driven, and solution-focused. And once the IG foundation is built – and the guiding principles of efficiency, enforcement and enablement are being followed – these programs can become highly successful, with significant return on investment and deeply engaged stakeholder communities.