The methodology to inventory management that has taken the most extensive account in recent decades is the lean inventory philosophy that sights excess inventories as waste and emphasizes fostering inventory efficiency in firms. Given the significance of inventories as valuable strategic resources for organizations, inventory management has always been one of the dominant areas of investigation in the operations management (OM) literature.
This study’s proposed hybrid framework is the first of its kind that encapsulates all four dimensions of inventory classification criteria, forming a multi-criteria hybrid model within a DSS framework.
Even though the DSS framework is based on data from a single organization, the application is expected to manage inventory stock in a wide range of manufacturing and services industries. Third, the paper suggests how these forecasting criteria can be integrated into a single interactive DSS to maintain optimum inventory level stock.
Second, a Multi-Criteria Forecasting Model is developed to capture a wide range of operations. First, a new comparative analysis matrix concept for identifying the most critical items is introduced. The research work aims to contribute to the inventory management literature in three ways. These HS items are forecasted through three different forecasting methods, i.e., Weighted Moving Average, Exponential Smoothing, and Trend Projection, with Minimum Absolute Deviation to significantly reduce the forecasting error while predicting the future required quantity. Application of price and quantity based analysis identifies that 65% of the annual budget is significantly dependent upon only 9% (in terms of quantity) of "High Price and Small Quantity" Items (HS). The study’s finding shows a forecast error of 142.5 million rupees in the last five years, resulting in the accumulation of more than 25 thousand excessive inventory stock. Finally, a decision criterion (Forecasting Model) is proposed using three primary forecasting techniques with minimum error calculations. Both these analyses set a solid foundation for the formulation of a comparative analysis matrix based upon price and quantity based analysis of inventory. The paper presents a statistical analysis of historical data and a comprehensive fault trend analysis. The proposed framework is based on a case study of one of Pakistan’s leading Technical Services Organization. Owing to the significance of inventory control and analysis, this paper reports on developing and successfully implementing a hybrid framework for optimum level inventory forecasting in Technical Services Organizations. Therefore, an organization ought to make the correct and timely decisions based on precise demand information to avoid excessive inventory accumulation resulting in enhanced competitive advantage.
The two most pressing concerns to handle in inventory management are: how much to order and when to order. To cope with erratic demands, organizations have to maintain excessive inventory levels, sometimes taking up to one-third of an organization’s annual budget. Inherent uncertainties in demand and supply make it problematic for supply chains to accomplish optimum inventory replenishment, resulting in loss of sales or keeping excessive inventories.