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Purpose – The purpose of this paper is to identify measure and prioritise the perceived importance of supply chain issues within the automotive industry related to information flow during product development (PD). Design/methodology/approach – This study analyses empirical data captured from semi-structure interviews with 15 multinational companies operating in the automotive sector. Data collected are analysed using a standard methodology identified from the literature. The individual issues captured are classified against 14 clusters that represent the core and the fundamental supply chain issues of information flow. Findings – This study showed that half of the issues captured are related to the inadequate information systems used. The cluster that had the majority of individual issues is related to suppliers that are not directly connected with their customers through an enterprise system. However it was identified that two fundamental clusters justify the decision of not being directly connected. Implementing and maintaining multiple enterprise systems can be a big overhead for multinational companies working with a high number of customers. Originality/value – Although several studies have proved the benefits that can be obtained through supply chain collaboration, there are relatively little empirical studies that seek to explore the understanding of supply chain issues in regards to information flow especially during PD. By identifying, measuring and prioritising the importance of supply chain issues this study provides researchers and practitioners guidance in developing better tools and defining more efficient processes.

A B S T R A C TThe purpose of this paper is to demonstrate a system architecture for integrating Product Lifecycle Management (PLM) systems with cross supply chain maintenance information to support root-cause analysis. By integrating product-data from PLM systems with warranty claims, vehicle diagnostics and technical publications, engineers were able to improve the root-cause analysis and close the information gaps. Data collection was achieved via in-depth semi-structured interviews and workshops with experts from the automotive sector. Unified Modelling Language (UML) diagrams were used to design the system architecture proposed. A user scenario is also presented to demonstrate the functionality of the system.