Gaining Benefits from Joint Forecasting and Replenishment Processes: The Case of Auto-Correlated Demand

Abstract

In this paper we consider a cooperative, two-level supply chain consisting of a retailer and a supplier. As in many practical settings, the supply chain members progressively observe market signals that enable them to explain future demand. The demand itself evolves according to an auto-regressive time series. We examine three types of supply chain configurations. In the first setting, the retailer and the supplier coordinate their policy parameters in an attempt to minimize systemwide costs, but they do not share their observations of market signals. In the second setting, resembling many original vendor-managed inventory (VMI) programs, the supplier takes the full responsibility of managing the supply chain's inventory, but the retailer's observations of market signals are not transferred to him. In our third setting, reminiscent of collaborative forecasting and replenishment partnerships, inventory is managed centrally, and all demand related information is shared. We propose a set of stylized models to study the three settings and use them to provide managerial insights into the value of information sharing, VMI, and collaborative forecasting.Collaborative Forecasting, CPFR, Supply Chain Management, VMI

Competition and Cooperation in a Two-Stage Supply Chain with Demand Forecasts

“…Commenting on this paper, Raghunathan (2001) argues that the supplier can use the retailer's order history to forecast demands, and then the benefits of sharing demand information disappear. Aviv (2002) develops a similar model, but customer demand evolves according to an auto-regressive time series with market signals, and both a retailer and a supplier have their own signals that are not shared. With this setting, he examines the value of information sharing, VMI and collaborative forecasting.…”

Forecasting and operational research: a review

“…More information and shorter lead times lead to lower variance. More recent papers consider a variety of mathematical models of collaborative planning and forecasting arrangements: sharing inventory and demand information (Aviv, 2002), vendor managed inventories (Yu et al, 2002), and, by using simulation approach, an examination of the effects of forecasting model selection (Zhao et al, 2002).…”

Investing in Forecast Collaboration

“…More recently, researchers have focused on the benefits of collaborative forecasting (Aviv, 2001(Aviv, , 2002 and its strategic complexity (Miyaoka, 2003;Cachon and Lariviere, 2001;Özer and Wei, 2006;Lariviere, 2002;Terwiesch, Ren, Ho and Cohen, 2004). Aviv (2001) models a collaborative forecasting process among privately-informed supply chain partners, finding that collaborative forecasting may provide substantial benefits for the supply chain, especially when the correlation between trading partners' forecasts is low.…”

“…Aviv (2001) models a collaborative forecasting process among privately-informed supply chain partners, finding that collaborative forecasting may provide substantial benefits for the supply chain, especially when the correlation between trading partners' forecasts is low. Aviv (2002) extends this model to the case of autocorrelated demand. Both papers assume that forecast accuracy is exogenous and that partners reveal their local demand forecasts truthfully.…”