Effective supply chain managemet framework based on forecasting for fast food chains

Abstract

In recent past with busy life style of people, consumption of fast food has increased. Despite numerous health concerns people eat fast food because of the taste and convenient of having ready-made food. As a result fast food chains has become an emerging competitive business now days. Accurate sales prediction is vital for any business. But due to the small lifetime of fast food, accuracy of the forecast is more critical since surplus of food is totally wastage and cannot be utilize further. In addition, shortage of the food too could lead to loss of profit. Different approaches have been employed for accurate sales forecasting. Although number of studies have been conducted, results are not clearly in favour of one particular method. Main concern is the accuracy of each modelling method. Another problem is sales forecasting accuracy depends on the accuracy of other forecasting factors such as weather. Considering these factors forecasting can be beneficial but not sufficient as well as cannot guarantee the perfect desired results. Applying composite forecasting methods and getting the best result would be more accurate. Proposed system aims to consider above problems, design, and develop an effective framework that maximize business results through growth, increase profit margins and helps to perform fast food chains daily functionalities easily. Overall system is built as a framework which fast foods chains can consume and customize accordingly. The main functionalities are implemented as restful web services and it can be consumed by broad client applications which are built in different language and platforms. System provide multiple methods for forecasting and the subscribed fast food chains can use the best suited method according its data set. It also provides a forecasting fail over mechanism that suggest efficient paths and amount of items to be transferred among branches in the chain in a way that branches with surplus food manage to share the extra food with the branches that has inadequate food item count. This helps chains to reduce wastage and earn profit. Apart from functionalities related to forecasting, framework provides services useful functionalities like efficient reports management and transferring data between branches and the management. This framework can be further improved by adding new effective forecasting techniques that consider holidays and hourly forecasting, improving the forecast failover algorithm by considering the traffic in order to address limitations in the current framework. Several functionalities like inventory management, Point of sales integration can be plug into this framework as future enhancements to provide complete framework for fast food chains.