This project conducts a systematic investigation of sales trends and growth opportunities for agricultural products. It serves as a final-term report for the BDM capstone project at the IITM Online BS Degree Program.
The analysis focuses on sales data from April 2021 to March 2024 for Sandesh Trading Company, aiming to uncover key performance insights through descriptive statistics, Pareto analyses, and time series analysis. The goal is to provide data-driven recommendations for inventory management, customer relationship strategies, and overall business growth.
The project employs several analytical techniques to derive insights from the sales data. The primary methods used include:
- Pie Chart Analysis: To identify dominant Stock Keeping Units (SKUs) based on the quantity sold.
- Pareto Analysis: To apply the 80/20 principle to both SKUs (by revenue and quantity sold) and customers (by revenue) to identify the most significant contributors.
- Time Series Analysis (Line Charts): To visualize monthly revenue and quantity sold, thereby detecting seasonal trends and demand fluctuations.
- Dominant Products: The analysis reveals that a small number of SKUs, primarily "MAKKA" (maize) and "CHANA" (chickpeas), account for the majority of sales volume and revenue.
- Customer Concentration: A significant portion of the revenue is generated by a small percentage of customers, highlighting a strong adherence to the Pareto principle.
- Seasonal Trends: Sales data indicates clear seasonal patterns, with peak sales occurring in the post-harvest season (Q4) and a noticeable slowdown during the monsoon months (Q3).
- Inventory Optimization: The findings suggest opportunities for strategic inventory ranking, optimizing stock levels for high-performing SKUs, and re-evaluating the strategy for slow-moving items.
- Credit and Collections: Analysis of payment behavior provides insights for better credit and collections management, including customer segmentation and tailored payment policies.
Based on the analysis, the report provides several strategic recommendations:
- Strategic Inventory Management: Prioritize high-performing SKUs for stocking and replenishment while reassessing the inventory strategy for low-performing products.
- Customer Relationship Management: Focus on nurturing relationships with top customers who contribute the most to revenue.
- Seasonal Planning: Align procurement, inventory, and sales strategies with the identified seasonal trends to maximize opportunities during peak seasons and mitigate risks during slower periods.
- Credit and Payment Policies: Implement a more data-driven approach to credit management, including targeted collection efforts and incentives for timely payments.
This project provides a comprehensive, data-driven analysis of sales trends and growth opportunities. The insights and recommendations presented offer a framework for optimizing inventory, strengthening customer relationships, and making informed business decisions to foster sustainable growth.
Declaration: The data and analysis in this project are for academic purposes and are specific to the context of this study.