TexInsight - A Comprehensive Business Intelligence & Sales Forecasting

This paper proposes a sales analytics framework with a focus on category-level forecasting and analysis for a small-scale yarn production unit.Unlike most existing literature, which concentrates on overall sales, this paper proposes a sales analytics framework that breaks down sales data based on yarn count and color.Using historical transactional data (purchases, sales, profits) from 2021 to 2025, data preprocessing was performed using Python, and visual analytics were created using Power BI.The analytics framework includes analysis of revenue and profit trends, product profitability matrices, supplier and customer dependency analysis, and operational efficiency analysis.For example, peak sales (around 6.5 million) and low sales (around 0.4 million) in a particular season were analyzed, and an integrated Power BI forecast showed steady growth in 2026 (see Figure 2).The profitability analysis (see Figure 3) shows that high-count yarns have modest positive profit and revenue, while low-count yarns are grouped around the zero-profit margin.The supplier analysis (see Figure 5) shows that no supplier has a major market share (top supplier share ≈ 5.6%), although supplier concentration risk is indicated.Operational efficiency analysis (see Figure 7) shows that the average inventory turns over every 23.5 days with 50% wax usage.All results are valid based on the provided data.