Sales Forecasting of Products for a Yarn Company

Abstract

This research aimed to forecast the sales volume of products for a certain Yarn company. This study employed a mixed-method approach through selective data collection. The data, which constituted a sample group, included sales figures from the year 2015 to 2022, totaling eight years. The research methodology followed the Cross-Industry Standard Process for Data Mining (CRISP-DM) to discover insights using sales forecasting techniques consisting of 1) date/month/year, 2) invoice, 3) delivery note, 4) buyer's name, 5) yarn number, 6) weight, 7) selling price, and 8) total price per invoice. These data were then transformed into a format suitable for analysis by sales forecasting techniques. The research results revealed that: 1) The forecasted monthly sales for the year 2566 amounted to 322.31 million Baht, with an average monthly sale of 26.85 million Baht 2) The forecasted monthly sales for the year 2567 totaled 316.55 million Baht, with an average monthly sale of 26.37 million Baht And 3) The forecasted monthly sales for the year 2568 amounted to 379.75 million Baht, with an average monthly sale of 31.64 million Baht. The abovementioned sales forecasting of yarn companies was utilized for planning future business operations effectively.