AUBURN HILLS, Mich., Feb. 18, 2014 /PRNewswire/ -- BorgWarner's Supplier Performance Monitor (SPM) system uses artificial intelligence and sophisticated mathematical theories to analyze current supplier performance and forecast future trends. The easy-to-install software can be transferred to new locations and improves supply chain response times significantly. Originally launched in Germany and Ireland, BorgWarner intends to implement the user-friendly software in the United States and other parts of Europe beginning in early 2014 followed by India and China later this year. BorgWarner's SPM system has been awarded several honors such as the Supply Chain Innovation Award 2012 and the VDA (German Automotive Industry Association) Logistics Award 2013. (Photo: http://photos.prnewswire.com/prnh/20140218/DE66539) "BorgWarner's Supplier Performance Monitor system analyzes actual data on quantity and delivery reliability, and significantly simplifies processes," said Brady Ericson, President and General Manager, BorgWarner BERU Systems. "We have received fantastic feedback from our suppliers on this ground-breaking innovation. The SPM system helps us jointly identify problems and proactively manage situations at an early stage." To accommodate the dynamic global economy where suppliers must work in close partnership with their customers throughout the supply chain, BorgWarner developed the SPM system to optimize its supplier network as well as its own performance. Based on the stochastic Hidden Markov Model, BorgWarner's software tool uses artificial intelligence and probability methods to evaluate existing mass data from enterprise resource planning (ERP) systems including data on orders, deliveries and cancellations as well as master, financial and quality data. Users receive information on past, current and future performance as well as the status of specific measures and indicators. BorgWarner's SPM system improves collaboration between all supply chain functions by involving all suppliers, revealing potential risks early.