Risk analysis of supply: comparative performance and short-term prediction

Managing risk in the supply of inbound parts for the assembly of complex engineering systems is a key activity for manufacturing companies to avoid production delays and disruption. We present novel analysis of empirical data typically available in enterprise resource planning systems. The information generated through such analysis can provide useful information to support decisions to better manage supply risk. For example, identifying suppliers at risk of poor performance under different loadings or relative to peers, and assessing the financial value of investing in learning and developing suppliers. Our analysis is based on new methods developed for robust ranking, valuation of due diligence as well as more established regression modelling principles. We focus upon the ways our methods can be used to support supply risk decisions by showing how they have been applied in an industry case and the implications of our findings to date.