Challenge
A global manufacturing enterprise faced persistent inefficiencies across its supply chain — from procurement and production planning to fulfillment and logistics. Each function operated in silos using separate systems (ERP, WMS, TMS, spreadsheets), leading to fragmented visibility, poor coordination, and reactive decision-making. Efforts to optimize one part of the chain often created bottlenecks or compliance issues elsewhere.
Objective
Unify cross-functional supply chain visibility to:
- Improve service levels and delivery accuracy
- Reduce working capital tied up in excess inventory
- Contain logistics and warehousing costs
- Enable proactive, data-driven supply chain decisions without disrupting existing systems
Solution
Process mining was applied to event logs from ERP, warehouse, and transport systems to reconstruct the true end-to-end supply chain journey. The effort provided a connected view across procurement, production, inventory, and fulfillment — revealing where planning assumptions diverged from execution reality.
The analysis surfaced:
- Cross-functional process maps and lead-time variances
- Hidden rework loops in fulfillment, such as repeat truck rolls and misrouted deliveries
- Root causes of delivery delays tied to outdated safety stock policies and poor handoff coordination
- Systemic issues in supplier lead time reliability and order change propagation
- Opportunities to simulate improvement scenarios and predict downstream impacts
- These insights helped teams make faster, more coordinated decisions while continuing to work within their existing systems and workflows.
Outcomes
- 27% reduction in end-to-end fulfillment lead times
- 18% improvement in on-time, in-full (OTIF) delivery
- Significant reduction in working capital requirements through better inventory alignment
- 30% drop in expedited shipments due to early anomaly detection
Established a scalable model for global supply chain visibility and harmonization
*Results described on the website are based on specific engagement and may vary depending on environment and implementation.