Client Overview
A large retail enterprise manages thousands of suppliers across merchandising, logistics, IT, and store operations. Spend data was scattered across multiple systems including Accounts Payable (AP), Purchase Orders (PO), and their core ERP platform.
Although the company captured enormous volumes of financial data, it lacked a unified, reliable view of total spend.
The Challenge
The retail group faced persistent problems with spend visibility and control:
- Fragmented data sources
AP, PO, and ERP systems operated independently, making it nearly impossible to understand total supplier exposure. - Manual data preparation
Finance and procurement teams spent weeks every month cleaning, merging, and rebuilding spend files before analysis could even begin. - Low categorization accuracy
Inconsistent supplier names and coding led to poor spend classification, hiding consolidation and savings opportunities. - Limited executive insight
Leadership lacked category-level views needed to identify risk, negotiate strategically, and reduce supplier sprawl.
The organization needed a single source of truth that could automatically unify and classify spend data at scale.
The Solution
A centralized spend intelligence platform was implemented to connect AP, PO, and ERP data into one unified spend model.
Key capabilities delivered:
AI-Driven Spend Categorization (New)
Automated classification models were deployed to normalize suppliers and categorize spend across all sources.
Categorization accuracy improved to 92 percent, dramatically reducing manual correction effort.
Unified Spend View (New)
All transaction data was consolidated into a single, continuously updated spend layer, giving procurement and finance teams a complete picture of:
- Total supplier exposure
- Category-level spend trends
- Cross-business purchasing patterns
Executive Dashboards (New)
Interactive dashboards were created for leadership, providing real-time views by:
- Category and subcategory
- Business unit and region
- Top suppliers and fragmentation risk
This enabled faster, more informed sourcing and negotiation decisions.
Automated Data Pipelines (Fixed)
Monthly manual spend file rebuilds were fully eliminated through automated ingestion and validation pipelines, freeing teams from repetitive, error-prone work.
Results & Impact
Within the first reporting cycles, the retail group achieved:
- 92 percent automated categorization accuracy
- Elimination of monthly manual spend rebuilds
- Identification of consolidation opportunities worth millions through supplier rationalization
- Immediate visibility into category-level savings and risk
Teams shifted from data preparation to data-driven action.
Key Takeaway
By unifying fragmented financial systems into a single intelligent spend platform, the retail group transformed raw transaction data into a strategic asset — unlocking hidden savings, reducing supplier fragmentation, and accelerating decision-making.
