29/4/2025

 29/4/2025

In order to further improve the accuracy and model diversity of sales forecasts, we actively searched online and explored more advanced forecasting methods, including the Multiple Decomposition model. During the learning process, we gained a deeper understanding of how this method separates trends, seasonality, and residuals in sales data. After mastering the basic principles, we began to try to apply Multiple Decomposition to actual sales data for forecasting, preliminarily tested its performance during holiday peaks and promotion cycles, and compared and analyzed it with previously used methods such as Holt and Holt-Winters.

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21/3/2025

 21/3/2025 Continue to explore and test various sales forecasting methods, including using different time periods for forecasting, to find the most accurate forecasting method. Attend meetings in the afternoon to discuss inventory status during the promotion period with relevant teams (such as managers and executives), focusing on products that have already started or are about to start promotions, especially products that are at risk of being out of stock (OOS), and develop corresponding response strategies to ensure the smooth progress of promotions.
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19/3/2025

19/3/2025 Data related to Soh (Stock on hand), Sales (Sales data) and Warehouse Stock (Warehouse Stock) from January 2, 2025 to March 19, 2025 are extracted from Qlik Sense, and the data integrity is checked and initially cleaned. Subsequently, the stock level and warehouse stock allocation are analyzed by building visualization charts such as line charts and bar charts. Finally, the analysis results are discussed and corrected with the Supply Chain Forecast and Promotion Executive.
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