Information sharing practices such as vendor-managed inventory (VMI) give manufacturers access to more accurate demand information, e.g. customer sales data, than before. The value of this type of information sharing has been established in many studies. However, most of the research has focused on the ideal situation of the manufacturer having access to information from all downstream parties. In practice, this is rarely the case. In this paper, discrete-event simulation is used to examine how a manufacturer can combine traditional order data available from non-VMI customers with sales data available from VMI customers in its production and inventory control and what impact this has on the manufacturer's operational ef®ciency. The simulation model is based on a real-life VMI implementation and uses actual demand and product data. The key ®nding is that even for products with stable demand a partial improvement of demand visibility can improve production and inventory control ef®ciency, but that the value of visibility greatly depends on the target products' replenishment frequencies and the production planning cycle employed by the manufacturer.

We develop actionable design propositions for collaborative sales and operations planning (S&OP) based on the observation of contexts in which benefits are generated d or are absent d from retail information sharing. An information sharing pilot project in a real-life setting of two product manufacturers and one retailer was designed. The project resulted in one manufacturer, serving a retailer from its local factory, developing a process for collaborative S&OP, while the other manufacturer serving a retailer from more distant regional factories abandoned the process. The evaluation of the outcomes experienced by the two manufacturers allows us to examine contexts in fine-grained detail and explain why introducing information sharing in the S&OP processes produce d or fail to produce d benefits. The paper contributes to the supply chain information sharing literature by presenting a field tested and evolved S&OP design for non-standard demand situations, and by a contextual analysis of the mechanisms that produce the benefits of retailer collaboration and information sharing in the S&OP process.

Modeling-based research provides strong support for collaborative forecasting as a means of improving supply chain efficiency. Yet, despite positive attitudes towards collaboration and several pilot implementations undertaken in the beginning of the millennium, large-scale implementations of collaborative forecasting are still scarce.This article presents the results of an exploratory case study examining four collaboration projects involving four manufacturers and one retailer operating in the European grocery sector. By analyzing the positive and negative experiences of these companies and the results of their collaboration projects, factors that have an impact on the feasibility and value of forecasting collaboration are identified. A main finding is that many collaboration models appear to build on invalid assumptions concerning retailers' forecasting needs, resources, and processes, as well as manufacturers' capabilities to benefit from the demand or forecast information made available through collaboration. #

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