Street Fashion Company’s Optimal Order Quantity Using Newsvendor Model and Simulation Model

Abstract

The objective of this research is to study the demand forecasting to increase the forecast accuracy of each product category. The forecasting step is carried out using R Studio program to minimize the MAPE among several forecasting models such as the state space model for exponential smoothing (ETS), the autoregressive integrated moving average (ARIMA) model and the neural network autoregression (NNAR) model. Then, we study and analyze the data to find the suitable order quantity, using the basic newsvendor model. After that, we compare the order quantity, revenue, and profit between the company’s current company and the new policy with the basic newsvendor model. After we deploy the new policy, we find that the order quantity decreases 3,541 pieces or 12.31%%, compared to those of the current company policy, and the profit increases 575,682.49 Baht or 2.07% %, compared to those of the current company policy. Next, we study and improve the modified newsvendor model to incorporate the promotional sales events after the selling season ends. Taking the company’s practice, which has the seasonal regular sales and sales event, into account to run the simulation to find of the suitable order quantity for purchasing, revenue, and profit under three different scenarios, namely the current company policy, the new policy from the basic newsvendor model, and the optimization policy from the modified newsvendor model. As the conclusion of this study, using the optimization policy results in the total order quantity 21,141 pieces (decreased 7,613 pieces or 26.48% compared to those of the company policy) and the max profit 34,522,135.58 Baht (increased 15,818,564.43 Baht or 84.58% compared to those of the company policy). Additionally, when the order quantity decreases, the inventory after-seasonal regular sales will decrease as well, leading to the decreased in the inventory day from 10.91 months to 4.84 months and to the inventory cost saving.