Information Sharing in Supply Chains: An Empirical and Theoretical Valuation

We provide an empirical and theoretical assessment of the value of information sharing in a two-stage supply chain. The value of downstream sales information to the upstream firm stems from improving upstream order fulfillment forecast accuracy. Such improvement can lead to lower safety stock and better service. According to recent theoretical work, the value of information sharing is zero under a large spectrum of parameters. Based on the data collected from a CPG company, however, we empirically show that if the company includes the downstream demand data to forecast orders, the mean squared error percentage improvement ranges from 7.1% to 81.1% in out-of-sample tests. Thus, there is a discrepancy between the empirical results and existing literature: the empirical value of information sharing is positive even when the literature predicts zero value. While the literature assumes that the decision maker strictly adheres to a given inventory policy, our model allows him to deviate, accounting for private information held by the decision maker, yet unobservable to the econometrician. This turns out to reconcile our empirical findings with the literature. These “decision deviations” lead to information losses in the order process, resulting in strictly positive value of downstream information sharing. We prove that this result holds for any forecast lead time and for more general policies. We also systematically map the product characteristics to the value of information sharing.