As a Principal Industry Consultant in the Global Manufacturing Practice at SAS, Scott focuses on driving the success of SAS Supply Chain solutions, including SAS Demand Driven Planning and Optimization. Prior to joining SAS, Scott worked for leading ERP and Supply Chain Planning vendors including SAP, Oracle, PeopleSoft, i2 Technologies, Manugistics and Servigistics in a variety of roles in sales and marketing. Scott holds an M.S. in Systems Management from U.S.C. and a B.S. in Industrial Engineering from Cal Poly SLO. He has over 12 years of hands on manufacturing experience in high tech, semiconductor, electronics assembly, aerospace and defense contracting. Alongside his professional life and family life with his wife and son, Scott invests spare time in regular sports activities such as bicycling, skiing and wake boarding as well as performing semi-professionally on the guitar.
What if you could automatically detect supply chain anomalies as they happen, or even predict them in advance? You'd be able to take timely corrective action and help maximize revenue, margins, customer satisfaction and shareholder value. There's no question: Supply chain planning and execution is complex. From design and sourcing, to
The widespread adoption of the term "analytics" reminds me of the evolution of the term "supply chain management." Initially the term focused on supply chain planning. It involved demand and supply balancing and the heuristics and optimization tools that came out of advanced planning and scheduling. Over time practically everything was included
Over the course of my career as industrial engineer turned supply chain planning advocate I've had the opportunity to work hands-on with many manufacturing and supply chain planning solutions. This has included solutions offered commercially by the usual suspects of ERP and post-SCM consolidation supply chain solution providers. Most of these
