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Retail · Master Data Management·Alshaya Group (Starbucks)·2021–2023

Starbucks MDM: Automating 1,000+ Hours a Month Away

Retired multi-spreadsheet chaos with a governed Product & Location MDM program.

Role: Program Lead

1,000+
Man-hours/month saved
2
MDM domains
100%
Spreadsheet workflows retired
$20K/yr
Adjacent decommissioning savings

Business Problem

Starbucks operations under Alshaya depended on fragile, multi-spreadsheet workflows to manage Product and Location master data — slow, error-prone, and impossible to scale.

Architecture

A governed Master Data Management model for Product and Location, with authoritative records, controlled workflows, and downstream distribution to reporting and operational systems.

Technology

Master Data ManagementData GovernanceBI Platform Integration

Delivery

Led the MDM program end to end — stakeholder alignment, data model, and rollout — and migrated Key Finance Reporting to the new BI platform in parallel, decommissioning legacy assets.

Challenges

  • Replacing entrenched spreadsheet habits with governed workflows.
  • Ensuring master-data integrity across operational systems.
  • Sequencing MDM alongside a broader reporting migration.

Solution

Delivered a governed MDM capability that eliminated manual spreadsheet reconciliation and, alongside KFR migration, generated recurring operational savings.

Business Outcome

  • 1,000+ man-hours/month returned to the business.
  • $20K/yr operational savings from legacy decommissioning.
  • A durable, scalable master-data foundation.

Lessons Learned

The highest-ROI automation often hides in unglamorous back-office workflows. Master data is where quiet compounding value lives.

Future Roadmap

Extend MDM governance to additional domains and automate data-quality monitoring end to end.