16/7/2025

 16/7/2025

Today's main work focuses on re-studying and optimizing the Temporal Convolutional Network (TCN) model in order to improve the accuracy of sales volume forecasting by introducing external time series factors. Since the results of the previous TCN model were not ideal, today's task focuses on trying to observe whether the model performance improves by introducing holiday and starting price factors (such as sales volume changes before price adjustment).

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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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