THE USE OF ORDER FREQUENCY IN MULTI CRITERIA INVENTORY CLASSIFICATION TO REDUCE DAYS COVER IN FINISHED GOODS INVENTORY FOR FMCG INDUSTRIES

Abstract

A reasonable proportion of products produced for the ‘make for stock’ (MFS) business environment become obsolete or slow moving over time as organizations push products into the marketplace to gain competitive advantage and optimize profits. Supply Chain Managers categorize inventory into ABC categories so that management of the many stock keeping units (SKUs) for the FMCG business can be simplified to a few categories for ease of setting replenishment policies. A common variable used is order volume based on the total volume of orders received a period, usually 1 year but policies based on order volume do not consider popularity of products, hence, slow moving inventory can be caused by policies using order volume. While order volume relates very well to size of orders, and therefore helps to determine size of capacity needed to manufacture such items, a new variable called Order Frequency is used in this research. The Order Frequency variable is used to determine popularity of orders, hence, the approach to ‘make to order’ can be recommended for low frequency items so that such items are only produced for shelf replenishment when such orders are received from the market and inventory reaches zero. These items can be categorized as slow moving due to the fewer orders received within the period and the ‘make to order’ policy will help reduce obsolete inventory for these group of items. In the field of supply chain management, managers set policies on when to order and how much to order and the average inventory that results from these inventory replenishment policies become targets. This research attempts to develop specific software in the area of Sales & Operations planning (S&OP) and use simulations to develop scenarios of days cover policies for categories of inventory and compare the resulting target days of inventory with actual compare days of inventory held in warehouses for a single organization with many warehouses/SKUs. The aim is to consider the impact of the Order Frequency variable to improve inventory waste within supply chains. The findings in this study firstly showed that there are significant differences between actual and target days as per t-test findings. Secondly, it also shows that the use of the Order Frequency variable together the ‘coefficient of variation’ in terms of varying order size and ‘no orders in the last x days’ allowed such items to be categorized as make to order items, thus reducing days cover targets for finished goods inventory. Even though calculating safety stocks scientifically yielded the highest reduction in target days of inventory when setting Re-order points, the Order Frequency variable will help Supply Chain Managers determine items with low popularity. The coefficient of variation variable identified items that varied in size whilst the ‘no orders in the last x days’ variable helped determine items that were beginning to slow down in popularity. Interviews with 5 industries showed that there is scope to use such variables to help Supply Chain Managers plan finished goods more effectively.