Predictive Demand Analytics for Inventory Control in Refined Sugar Supply Chain Downstream

The Company's inability to overcome inventory problems leads to unprepared marketing distributor in anticipating a surge in consumer demand and unavailability of inventory in the warehouse. Long agricultural supply chain problems cause frequent information gaps, inaccurate and integrated inventory predictions from downstream to upstream supply chains, and uncontrolled inventory, these are the phenomenon of the bullwhip effect in the supply chain. To overcome these problems, the marketing distributor needs to predict the demand in the integrated supply chain downstream so that inventory in each chain can be controlled. Based on the data, the existing demand pattern is linear and the right method to use is SVR (Support Vector Regression), which produces the highest level of accuracy and the smallest error. Based on the results of SVR demand forecasting in the supply chain downstream, each chain is then integrated to control inventory, so that the occurrence of the bullwhip effect can be minimized. Then the company can use the aggregate mode to determine the safe upper and lower limit of inventory so that the stability of the demand for refined sugar from the supply chain downstream can always be fulfilled the company.