The North American truck OEM needed a single system which would show complete commodity spending information together with sourcing performance data for all manufacturing sites and their respective product lines. The operational data existed in different storage systems with various file formats which forced commodity managers to perform extensive manual work while extending the duration of their sourcing activities.
The system encountered two primary issues because it processed extensive data collections and intricate models which decreased its operational speed and created problems with independent data verification. The organization faced difficulties when trying to evaluate different commodities because it lacked defined KPIs which would have measured cost performance and lead time and supplier evaluation metrics.
- The system combines all necessary data into one unified platform which includes spending information and supplier details and sourcing event records and uses a unified system to classify commodities.
- The system achieved two main benefits through its model optimization process which combined aggregation with star-schema design and calculated measures to decrease model dimensions and enhance refresh operations.
- The system used a KPI framework which established three essential performance indicators (cycle time and cost variance and supplier performance) together with their corresponding warning levels.
- The system includes Power BI application management with governance features which provide dashboards for different user roles and scheduled data updates and establish a regular review process (weekly reviews; KPI owners).
Commodity-level spend & performance control tower with daily refresh. Significant reduction in data model size enabling fast interaction. Model size reduced from ~1-1.5 TB to ~40-60 MB. Sourcing/analysis lead-time reduced by ~80%. Benchmark: spend-control-tower governance can drive rapid indirect spend savings.