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Case Study: Aligning the Data Management Lifecycle to Industry Standards

Challenge​

The organisation faced fragmented data management practices, with inconsistent processes across teams and limited alignment to recognised industry frameworks. This lack of standardisation hindered stakeholder confidence in data governance and slowed adoption of enterprise-wide initiatives.

Approach​

Working in partnership with the client, we delivered a structured programme to align the Data Management Lifecycle with DAMA International’s Data Management Body of Knowledge (DMBOK). Our approach included:

  • Process alignment: Rewriting work management procedures, lifecycle guidelines, and instructions to fully align with DAMA principles.
  • Enterprise modelling: Building Business Process Models (BPM) in the Enterprise Architecture toolset to provide a single reference point for processes.
  • Change enablement: Preparing stakeholder assessments, impact analyses, and detailed change management plans to ensure smooth adoption.
  • Communication & training: Creating enterprise-wide training materials in SuccessFactors and facilitating stakeholder workshops to drive a common understanding of data governance.
  • Advisory services: Supporting existing Data Technology teams with guidance, including the design of Power Apps to automate workflow processes.
  • Business engagement: Capturing “it would be great if we…” statements across the business to inform priorities and validate enterprise data platform use cases.

Outcomes​

  • Consistent standards: Data Management processes are now aligned with recognised DAMA standards, ensuring industry credibility.
  • Enterprise-wide adoption: Stakeholders gained a shared understanding of data governance, reinforced through formal training and clear procedures.
  • Operational efficiency: Automated workflows and aligned processes reduced manual effort and improved governance compliance.
  • Strategic insight: Business-driven use cases provided a strong foundation for enterprise data platform decisions, ensuring investment was tied to real business needs.

Conclusion​

By aligning the Data Management Lifecycle with DAMA standards and embedding change through clear communication, training, and governance, the organisation strengthened its enterprise data capability. The result was not only improved efficiency, but also greater trust in data-driven decision-making across the business.

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