Data-Driven Financial Analysis for Vegetable Retail Business

This project aims to provide data-driven solutions to address financial challenges faced by a vegetable retail business, Raj Kishore Kumar Gupta and Sons. The primary objectives are to optimize pricing strategies, enhance profitability, and implement structured credit management practices.

Project Overview

• Conducted a comprehensive analysis of transactional data spanning 31 days, including cost prices, selling prices, quantities, and credit transactions.
• Employed time-series analysis, statistical computations, and regression modeling to determine ideal pricing margins.
• Developed a structured credit management system by analyzing creditor data, identifying patterns, and recommending criteria for credit allocation.

Data Collection

The project involved the collection of two types of data:

1. Vegetable Transaction Data: This dataset includes details such as vegetable names, cost prices, selling prices, and quantities sold.
2. Creditor Data: This dataset contains information about major creditors, including customer names, transaction dates, credit amounts, repayments, and outstanding balances.

Analysis Methods

The following methods were employed for data analysis:

• Time-Series Analysis: Utilized to identify trends, patterns, and variations in financial aspects over time.
• Statistical Computations: Various statistical measures were calculated, including measures of central tendency and variability, to gain insights into the distribution of financial data.
• Regression Modeling: Linear regression was used to determine the ideal pricing margins for achieving desired monthly profits.

Results and Recommendations

The analysis provided valuable insights and recommendations, including:

• Strategies for optimizing pricing margins to achieve desired monthly income targets.
• Development of a structured credit management system with clear criteria for credit allocation and risk mitigation.
• Identification of opportunities for product diversification and expansion to increase revenue generation.

Files

The repository contains the following files:

• proposal.pdf: The project proposal outlining the problem statements, background, and proposed approach.
• Mid Term.pdf: A mid-term report detailing the data collection process, metadata, descriptive statistics, and preliminary findings.
• Final.pdf: The final project report, including detailed analysis, results, and recommendations.
• BDM Presentation.pptx: The project presentation, summarising the entire project.
• Presentation Notes.pdf: The Presentor notes along with the Presentation.