Mitigating Supply Chain Risk: A Case Study of DHL and ZF Partnership

• Networks & Connectivity - WiFi
• Platform as a Service (PaaS) - Application Development Platforms

• Automotive
• Transportation

• Logistics & Transportation

• Inventory Management
• Supply Chain Visibility

ZF, a global leader in driveline and chassis technology as well as active and passive safety technology, was facing significant challenges in managing its supply chain risk. The company's scale and global scope, which involved delivering 35,000 parts weighing 4,000 tons to locations all over the world in 2013 alone, raised concerns about potential disruptions. Airfreight was considered a 'last resort' at ZF, used only when essential to maintain production schedules and avoid customer delivery delays. This made it a significant risk, especially if disruption occurred at a critical airport. ZF also identified inefficiencies in providing timely and accurate incident information to automotive OEMs detailing potential impact at supplier- and material number-levels. The company wanted to find ways to mitigate and effectively manage this risk to ensure business continuity in its end-to-end supply chain.

ZF is a global leader in driveline and chassis technology as well as active and passive safety technology. The company has a vast and complex supply chain, delivering thousands of parts to locations all over the world. Airfreight is a critical part of ZF's supply chain, used as a last resort to maintain production schedules and avoid customer delivery delays. However, this reliance on airfreight posed a significant risk, especially if disruption occurred at a critical airport. ZF also faced challenges in providing timely and accurate incident information to automotive OEMs. The company sought to mitigate and effectively manage these risks to ensure business continuity in its end-to-end supply chain.

To address these challenges, ZF entered a joint pilot with DHL Global Forwarding (DGF) on the ZF airfreight network controlled by DGF. DHL demonstrated the power of Everstream Analytics’ predictive innovative supply chain risk platform, which was customized with DHL’s existing data from the ZF network. This solution provided ZF with a tailor-made risk assessment study and a supply chain incident monitoring platform customized for ZF’s airfreight network and key suppliers. Everstream also contributed best-practice methodology in business contingency management, along with vast knowledge of supply chains generally and, through long association, specific understanding of ZF’s supply chain. For the survey phase, Everstream was able to identify contacts at each site without needing to involve ZF, saving time and money. The pilot succeeded because of clear, structured, available risk assessment methodology, and Everstream’s proactive analysis scoping.

• With the implementation of Everstream Analytics’ predictive innovative supply chain risk platform, ZF achieved end-to-end risk visibility and manageability of airfreight disruption in the supply chain. The company also gained insight into related costs and financial benefits, so it can measure the necessity of supply chain risk management efforts to the business. The company now knows where to focus attention and risk mitigation to ensure business continuity. The pilot identified five out of 167 airports as risk hotspots, locations where disruption could cause significant shipment delays. Using DHL’s proposed mitigation measures, ZF can increase the resilience of its supply chain to airfreight disruption and can apply these techniques to other parts of its business in future.

• More than 10,500 ad-hoc shipments are routed to 55 countries through the ZF airfreight network annually.
• Everstream Analytics mapped the end-to-end ZF airfreight network, and then assessed risk exposure for all 167 airports, 500+ ZF sites, and multiple customers and suppliers in the network.
• The pilot identified five out of 167 airports as risk hotspots, ensuring business continuity through strategic and operational mitigation measures.