Inventory Control in Operations Management: A Study on Wood Ear Mushroom

Abstract

Wood ear mushroom is a high-value commodity with beneficial nutritional content and growing consumer demand, thanks to its high fiber, vitamins, and cholesterol-free status. However, CV. XYZ faces persistent inventory issues because it does not operate cultivation facilities and relies entirely on fixed purchases from farmers. This condition often leads to oversupply, quality deterioration, and high storage costs, indicating a mismatch between procurement decisions and actual market demand. This study aims to forecast demand using the Single Exponential Smoothing method, analyze inventory con- trol through the Wagner-Within Algorithm and Silver Meal method, and compare their cost efficiency with the company’s existing policy. The analysis uses historical data on demand, holding costs, ordering costs, and time periods from April 8, 2024, to June 1, 2025, followed by projections for 30 future peri- ods. The results show that total forecasted demand reaches 160.195 kg with α = 0.1, which produces the lowest forecasting error. Both the Wagner-Within Algorithm and Silver Meal method achieve 33% cost efficiency, generating an inventory cost of IDR 46,551,418 with 15 orders, compared to the existing policy’s IDR 60,849,090 with 30 orders. These findings indicate that the Wagner-Within Algorithm provides a more comprehensive and effective framework for formulating inventory policies. Optimizing order timing and quantities helps reduce storage costs, minimize quality losses, and enhance operational efficiency, making it a strategic approach for managing high-value and perishable commodities such as wood ear mushrooms.