Data governance framework helps a global luxury retailer strengthen data quality, reduce data issues, and improve decision-making across HR functions.
When HR data lacks clear ownership and consistent definitions, teams struggle to trust insights, decisions take longer, and data issues multiply across regions. For global organisations with complex People Data landscapes, these gaps create operational friction and risk.
This case study shows how a global luxury retailer partnered with We+ Asia to establish a People Data Governance framework, improve data literacy across HR, and implement a unified Data Catalog and Data Glossary to enhance consistency, ownership, and data quality.
+ Delivery Stats
+ Multiple data domains in People Data covered (Ownership, CDEs, Data Quality, Data Privacy)
+ Comprehensive critical data elements list developed and validated
+ Data catalog and data glossary implemented using MS-Purview
+ Structured data qwnership model established (Owner, Steward, Custodian, Process Owner)
+ Weekly stakeholder sessions conducted across markets
+ Senior management alignment achieved on scope, roadmap, and objectives
+ The Challenge
The retailer faced growing challenges around People Data, including inconsistent definitions, unclear ownership, quality issues, and limited awareness of data governance best practices.
HR teams across markets maintained data differently, leading to discrepancies, difficulty aligning definitions, and delays in decision-making. The absence of a unified Data Catalog or Glossary made it difficult to maintain control and ensure compliance.
The organisation needed a structured governance framework, better data literacy, and clear documentation of Critical Data Elements to reduce issues and support long-term data quality.
+ The Solution
We+ Asia partnered with global, regional, and local HR teams to design and implement a full People Data Governance framework.
The engagement defined a complete roadmap, detailed task list, and timeline, supported through a Gantt-based project plan. Governance pillars included Data Ownership, Critical Data Elements, Data Quality, and Data Privacy.
A structured Data Ownership model was created (Owner, Steward, Custodian, Process Owner). Documentation for Critical Data Elements was drafted, consolidated, quality-checked, and prepared for Purview deployment, including definitions, quality rules, and meta data attributes.
We also improved data literacy by preparing presentations, materials, and tailored CDE lists for different stakeholders, helping each market understand expectations and deliverables. Weekly sessions aligned all teams on objectives, progress, and next steps.
+ The Results
+ Full roadmap and governance framework established
+ Critical Data Elements identified, consolidated, and validated for People Data
+ Data Catalog and Glossary prepared for deployment in MS-Purview
+ Data Ownership model implemented across global, regional, and local teams
+ Project delivered within the 7-month timeline thanks to strict tracking via Ganttand task lists
+ Improved awareness and literacy among HR teams regarding data governance
+ Reduced data issues related to inconsistencies, sharing, access control, and quality
+ Clear communication channel established between markets and senior management
+ Successful completion of phase 1 with aligned scope and deliverables