ESD-AA-CEE Faculty Search Candidate Seminar Lecture Presentation by Gary Gaukler

RFID and Product Progress Information: Improved Dynamic Emergency Ordering Policies

About Gary Gaukler
Gary Gaukler is a Doctoral candidate in the Department of Management Science and Engineering at Stanford University, where he is affiliated with the Production and Operations Management research group.  In addition to his work at Stanford, Gary has done research at the Universitaet Karlsruhe (TH) in Germany and at the International Institute for Management Development (IMD) in Lausanne, Switzerland.  His research interest centers around pertinent issues in the field of Supply Chain Management (SCM) and radio-frequency identification (RFID).  He is currently working on the analytical evaluation of the use of RFID technology within a company's supply chain strategy.  Gary received his undergraduate education at the University of Karlsruhe in Germany, and he holds Masters degrees in Industrial and Systems Engineering from the Georgia Institute of Technology in Atlanta, and in Management Science and Engineering from Stanford University.

Abstract:
This talk focuses on inventory replenishment policies in an RFID-enabled supply chain. Such an RFID-enabled supply chain is characterized by complete visibility of the product in the system. We show how this visibility can be used to improve inventory replenishment. To this end, we examine a setting in which a decision maker orders a product from an upstream company. The lead time for order fulfillment is assumed to be stochastic, but dynamic product progress information is available through RFID.

We identify an optimal ordering policy that is based on the classical order quantity, reorder point(Q,R) policy, but which in addition allows for releasing emergency orders in response to this product progress information. We show that the general structure of this policy is straightforward and easily implementable: The optimal policy is given by a sequence of threshold values for each stage of the supply process. In a numerical study we analyze the performance of the improved emergency ordering policy versus the traditional (Q,R) policy. This study demonstrates that the total cost improvement is typically in the range of 3-5%, and that backorder-related costs are decreased by roughly 90% using this policy.