Intern(Chow Jun Hoe)

 30/4/2025 I discussed the sales forecast method completed yesterday with Supply Chain Executive, and reported in detail the model principle used, the forecast results and the existing deviation problems. During the communication process, Executive made some suggestions, such as changing the time unit from "week" to "day" for analysis to improve the sensitivity of the model and the precision of the forecast.

 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.

 28/4/2025 Started to formally learn Holt's Method and deeply understood the principle of introducing trend components on the basis of traditional exponential smoothing. In the process of learning, not only mastered its formula setting and parameter adjustment skills, but also tried to apply Holt's method to actual sales data, conduct forecasting tests, and compare and analyze with previous forecasting results. After mastering Holt's method, further explore the more advanced forecasting technology - Holt-Winters Method, which introduces seasonality factors on the basis of Holt's. Subsequently, use Holt-Winters method to conduct forecasting tests on sales data and observe its performance in capturing seasonal patterns and trend changes.

 25/4/2025 In the process of continuously optimizing the sales forecasting method, we actively searched for and learned new forecasting techniques, and successfully found and understood the principles and application scenarios of the Exponential Smoothing method. Subsequently, we began to try to use this method to conduct forecasting tests on sales data of some products and time periods. After completing the phased forecasting content, we reported the overall progress and test results to the Supply Chain Manager. During the reporting process, the manager affirmed the current efforts and also provided new professional suggestions - guiding us to start researching and applying more advanced forecasting methods, such as Holt’s Trend Method, which adds trend factors to the basic exponential smoothing to better capture the upward or downward trend in sales data and further improve the accuracy of the forecast.

 24/4/2025 The improved forecast data report was submitted to Supply Chain Executive again, and it received positive affirmation and recognition in this report, indicating that the current analysis logic, data presentation method and forecast model have reached a relatively ideal standard. On this basis, we began to prepare the briefing content for the Supply Chain Manager the next day, focusing on the selection basis of the forecast method, actual test results and error evaluation. In addition, based on the established forecast model, we further conducted forecast analysis on this week's sales, selected the most suitable forecast method for the current situation, combined with the latest actual sales data, and tried to generate forecast results that are closer to actual needs.

 23/4/2025 Submit the updated forecast data report to Supply Chain Executive for review again, and explain in detail the adjustments made, the changes in the forecast results, and the data basis behind the optimization. After further comments and suggestions from Executive, optimize and organize the parts of the report that are not clearly structured, the data arrangement is not intuitive, or the charts are not clear.

 22/4/2025 Continue to optimize and modify the forecast data. To improve the efficiency and flexibility of data processing, the relevant sales, forecast values, actual sales, and error indicators are integrated into a unified data table through the VLOOKUP function. This method not only makes the data clearer when consulting and comparing, but also greatly simplifies the subsequent data update and modification process.