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Impact of Information Exchange on Supplier Forecasting Performance

Research output: Working paper

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Abstract

Forecasts of demand are crucial to drive supply chains and enterprise resource planning systems. Usually, well-known univariate methods that work automatically such as exponential smoothing are employed to accomplish such forecasts. The traditional Supply Chain relies on a decentralised system where each member feeds its own Forecasting Support System (FSS) with incoming orders from direct customers. Nevertheless, other collaboration schemes are also possible, for instance, the Information Exchange framework allows demand information to be shared between the supplier and the retailer. Current theoretical models have shown the limited circumstances where retailer information is valuable to the supplier. However, there has been very little empirical work carried out. This works assesses the role of sharing market sales information obtained by the retailer on the supplier forecasting accuracy. Data have been collected from a manufacturer of domestic cleaning products and a major UK grocery retailer to show the circumstances where information sharing leads to improved accuracy. We find significant evidence of benefits through information sharing.