Supply chain collaboration for improved forecast accuracy of promotional sales

In general, demand for functional products is dependent on a range of promotions offered in various retail outlets. To improve promotional sales many retailers collaborate with manufacturers for planning, forecasting and replenishment. The purpose of this paper is to hypothesize that collaborative forecasting will improve the forecast accuracy if all the partners can relate their demand forecast with underlying demand factors.

In this paper, the author uses a case study approach to study various demand factors of soft drink products of the UK based company which offers frequent promotions in retail outlets. The paper represents the case study findings in a conceptual framework called Reference Demand Model (RDM). Further, the case study findings are validated empirically by means of multiple linear regression analysis using actual sales data of the case company.

Surprisingly, some of the demand factors specified as very important by the case company are not found to be highly significant for actual sales. The paper uses the identified demand factors to suggest levels of collaboration.

Understanding the importance of product specific demand factors through regression models and incorporating the same in managerial decision making will aid managers to identify the necessary information to make accurate demand forecasts.

This approach unveils the presence of three levels of collaboration namely preparatory, progressive and futuristic levels among supply chain partners based on the information exchange. The proposed method will aid decision making on information sharing and collaborative planning among manufacturer and retailers for future promotional sales.