vishal7095/RFQ-FInancial-Impact-Analysis

Welcome to RFQ Financial Impact Analysis System

# 📈 RFQ Financial Impact Analysis System

## 🧠 Overview
A smart Python-based system to analyze vendor quotations (RFQs), optimize selection using machine learning and knapsack algorithms, and generate detailed financial impact reports.

## 🚀 Key Features
- 🔍 **Smart Selection**: Combines **Fractional Knapsack** & **Random Forest** for optimal vendor-item mapping.
- 💰 **Impact Calculator**: Quantifies cost savings, overpricing, and potential losses.
- 📊 **Auto Reports**: Generates Excel reports with formatting for stakeholder review.
- ⚙️ **Custom Parameters**: Handles dynamic RFQ specs via user-defined configuration.

## 📁 Project Structure

📦 RFQ-Financial-Impact-Analysis
├── requirements/ # Material specs (input)
├── quotations/ # Vendor RFQ submissions
├── optimized_rfq/ # Selected cost-effective RFQs
├── comparision_report/ # Vendor-wise comparison
├── financial_impact/ # Final Excel reports
├── riq_analyser.py # Core ML + knapsack logic
├── riq_comparison.py # Vendor comparison module
└── riq_financial_impact.py # Financial summary generation

## 🏃 Quick Start
```bash
git clone https://github.com/your-repo/RFQ-Financial-Impact-Analysis.git
cd RFQ-Financial-Impact-Analysis
pip install -r requirements.txt

# Step 1: Add specs to requirements/*.xlsx
# Step 2: Add vendor bids to quotations/*.xlsx

python riq_analyser.py          # Runs ML + knapsack optimizer
python riq_comparison.py        # Compares all vendor quotations
python riq_financial_impact.py  # Outputs financial impact report

🧮 Algorithms Used

• 🧩 Fractional Knapsack: For cost-benefit ratio optimization on per-unit basis.
• 🌳 Random Forest Classifier: To classify and evaluate vendor quote quality.
• 📐 Rule-Based Thresholding: For financial impact scoring.

📤 Output Examples

• ✔️ optimized_rfq/optimized_rfq_iron.xlsx
• ✔️ comparision_report/quotation_comparison_report_iron.xlsx
• ✔️ financial_impact/Company30_Financial_Impact.xlsx

🧪 Requirements

• Python 3.8+

• Libraries:

  • pandas, scikit-learn, openpyxl, nltk

🛠️ Customization

Modify categorical_params or add filters in RFQAnalyzer inside riq_analyser.py to handle new materials or business rules.

📜 License

MIT License — Free for commercial and academic use.