Promotional readiness at enterprise retail scale
Owning the 19-week pre-launch pipeline governing product, pricing, and promotional data for 18,300+ North American retail locations.
The problem
A launch fails upstream of the register
At enterprise retail scale, a promotional launch succeeds or fails long before a customer orders. Before a single SKU appears at a Tuesday morning point-of-sale, eight or more systems have to hold a perfectly synchronized view of the same product, price, taxonomy, and channel attributes.
A single defect in master data doesn't degrade gracefully. It rolls back the launch across thousands of locations at once, in real time, with the customer already in line. The fixed launch date is the constraint everything else bends around.
The system
One MDM layer, eight downstream consumers
Marketing briefs, merchandising plans, and pricing strategy converged into a single master data layer built on PEGA and Enterworks, where taxonomy and governance rules were enforced before anything propagated outward.
From there, data flowed into point-of-sale, mobile order and pay, Oracle Retail, JDA, and digital menu boards. The MDM layer was the only place a product was defined. Everything downstream inherited it.
The framework
Nineteen weeks, five gates
- Week 19–15
Brief and strategy
Marketing intake. Promotional scope, pricing, and channel mix locked before any data work begins.
- Week 14–11
Master data build
Item setup in Enterworks. Taxonomy and attributes validated against governance standards at entry, not at QA.
- Week 10–7
System propagation
Data flows downstream. PEGA workflow drives cross-team handoffs with an audit trail on every transition.
- Week 6–3
Cross-system QA
Integration testing across all consuming systems. SQL and Python validation of the full dataset. Readiness dashboards live.
- Week 2–0
Go/no-go and launch
Final readiness gate with cross-functional sign-off, then synchronized in-store activation.
What worked
Four decisions that carried the rest
- Migrating coordination out of spreadsheetsMoving from a Smartsheets-based coordination model into a structured PEGA workflow eliminated manual chase cycles and replaced them with a repeatable, audit-ready system of record.
- Enforcing taxonomy standards at entryMaster data and taxonomy standards defined in Enterworks meant fewer launch-day defects and cleaner propagation into every downstream system.
- One readiness dashboard for everyoneOracle Analytics Cloud and Databricks dashboards gave every cross-functional partner the same view of launch readiness, which ended the weekly reconciliation meeting.
- Validating datasets before they movedSQL and Python validation caught anomalies in large promotional datasets before they propagated to POS, mobile, and store-facing systems.
Outcomes
Results
Client names and proprietary specifics omitted. Detailed figures available under NDA.
Contact
Facing a launch date you can't move?
If your promotional or product data has to be right across several systems at once, that's the work. Twenty minutes is usually enough to tell whether I can help.
Robert@brandywinedata.com