Stochastic automata and supply chain agility in the time-limited supply industry.

Abstract

This paper presents a stochastic automaton approach to stock ordering for retailers of time-limited goods, in the modern supply chain network. The rationale applied is that by ordering in small quantities frequently, overstocking will be reduced, capital liquidity improved and wastage limited. A consequence for the complete supply chain is that such an approach could substantially minimise the reactive bullwhip effect, leading to more efficient utilisation, production and agility throughout the chain. Such agility and flexibility can only be achieved by full integration of stock inventory monitoring technologies (such as RFID) with enterprise integration systems (such as ERP) connected to suppliers, mediated by the internet. We undertake a comparative simulation study of stock ordering using a stochastic automaton and a naive traditional approach. This shows that stochastic ordering, prompted by a stochastic automaton, exhibits characteristic properties that are a prerequisite for reducing the bullwhip effect, thus enabling agile inventory management.