Case Study: Global Retail Group
A multi-brand retailer operating in North America and Europe needed one reliable source of truth for pricing, inventory, and demand planning. Their analytics estate had grown organically across regions and teams, creating inconsistent metrics and delayed decisions.
Challenge
The client had 42 active data sources and over a dozen reporting tools. Pricing teams, category teams, and supply planners used different definitions for margin, stockout risk, and sell-through. Leadership meetings often started by debating which report was correct instead of discussing what action to take. Data refresh windows were long, and analysts spent significant time reconciling files.
What We Did
- Built a governed ingestion layer on AWS for POS, e-commerce, ERP, and supplier feeds.
- Implemented a semantic model in Snowflake so merchandising, finance, and operations used a shared KPI layer.
- Replaced high-friction spreadsheet workflows with near-real-time dashboards for pricing and replenishment teams.
- Set up observability and data quality checks for freshness, schema drift, and outlier anomalies.
Business Impact
- 31% improvement in demand forecast accuracy for top-volume categories.
- 27% reduction in stockout incidents in priority regions.
- 45% faster executive reporting cycle during weekly business reviews.
- Significant reduction in manual reconciliation work for analysts.
Why It Worked
We aligned technical architecture with commercial decision points instead of only migrating pipelines. The outcome was not just cleaner data, but faster and more confident pricing and assortment decisions across the retail organization.