Theresye Yoanita Octora
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Analysis of the Application of the Rolling Forecast Method for Personal Care Products at PT. Kosmetiku Tenaka Budiman; Purwoko, Harry; Laura Malau; Theresye Yoanita Octora; Tri Mulyani Setyowati
Dinasti International Journal of Education Management And Social Science Vol. 5 No. 3 (2024): Dinasti International Journal of Education Management and Social Science (Febru
Publisher : Dinasti Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31933/dijemss.v5i3.2377

Abstract

Abstract: Demand planning is a significant factor that affects the performance of each stage of supply chain management in fast-moving consumer goods. An unavoidable problem is the inaccuracy of demand planning which has an impact on production planning for the procurement of personal care products. The more products, the more the accuracy of demand forecasting varies, so it is necessary to make efforts to improve the quality of demand planning to have an impact on effective, efficient demand planning and increase customer satisfaction. This research is a mixed method with a concurrent embedded strategy by providing a simulated rolling forecast process (to be) of the current rolling forecast process (as is). The analysis uses the method of rolling forecast, double moving average, double exponential smoothing, and forecast error calculation with Mean Absolute Percentage Error (MAPE). The purposive sampling method is used to calculate demand forecasting for 2022 focusing on product categories with the 80/20 Pareto principle, where 20% of products generate 80% of the company's revenue. This research improves the business process by implementing a planning time horizon that is dissected into 3 months consisting of frozen, slushy, and liquid periods in a rolling forecast and setting safety stock to be obeyed by distributors to get the smallest forecast error rate. The appropriate demand forecasting method for forecasting product demand based on test results shows that each product requires a different forecasting method, depending on the characteristics of each product's historical data. Keywords: Demand Forecast, Demand Planning, Personal Care, Planning Horizon, Rolling Forecast