Celonis

The client, a leading global Auto OEM, faced challenges in reducing rework efforts and costs, despite having mature Lean manufacturing standards in place and over one hundred automated in-line quality checks and possible repair stations. The client was looking to identify opportunities to improve production cost per unit. To address this challenge, we used data mining to create virtual value stream maps for over 100,000 vehicles and map sources of thousands of hours of rework. As a result of our approach, we were able to identify an overall 20% improvement opportunity in reducing repair hours. Our data-driven approach enabled the client to identify and prioritize opportunities to improve production efficiency and reduce costs per unit.

The auto parts manufacturer was facing challenges in reducing change notice (CN) cycle times due to delays caused by sequential completion of process steps, loss of impact from long release times, and varying implementation techniques across global design centers. As a result of our approach, we were able to identify a 12% cycle time reduction through review/approval process optimization and a 10% rework rate reduction to levels of best-performing sites. Our data-driven approach enabled the engine manufacturer to identify and prioritize opportunities to optimize the product and part change process and improve overall efficiency.

The client wanted to create a supply chain roadmap with initiatives that deliver the targeted multi-million dollar top-down potential during the next 4 years. The support aimed to pressure test existing initiatives (impact, approach, timelines), detail new initiative ideas, and fill gaps as a foundation to capture the aspired impact. To achieve this, process mining was for example used to size the impact of improving transport efficiency across regions, through process and commercials levers. The technique helped to identify improvement opportunities, such as increasing truck utilization, reducing spot shipments, shifting transport mode to rail, and reviewing and renegotiating terms. Our data-driven approach enabled the client to create a supply chain roadmap with ‘push-button-ready’ initiatives that would process efficiency and reduce costs.