📦 Supply Chain Analysis: Winter Rock Retailer

📘 Project Overview

In this project I have analyzed sales trends, forecasts demand, and optimizes the distribution strategy for Winter Rock (a imaginary company made for this project), a UK-based retailer specializing in winter sports gear.

The key focus is to forecast sales, develop an optimal distribution plan, and evaluate the impact of new product launches on the company’s operations. The project uses time series analysis, forecasting methods, and decision-making models to improve operational and marketing strategies.

🎯 Objectives

• Analyze historical sales data to uncover seasonal trends.
• Forecast future demand for year-round and seasonal products.
• Optimize the distribution strategy to meet demand in various regions while minimizing costs.
• Evaluate new product demand and provide recommendations on inventory management.

🛠️ Tasks Performed

1. Data Analysis & Cleaning:

   • Historical sales data cleaned and prepared for analysis.
   • A centered moving average was calculated to detrend the data.

2. Sales Trend Analysis:

   • Seasonal trends were analyzed by generating seasonal matrices and charts.
   • Key insights were drawn from sales peaks and off-peak periods.

3. Forecasting:

   • Implemented forecasting models using Single Exponential Smoothing (SES) to predict future sales.
   • In-sample and out-of-sample accuracy of the models were evaluated using metrics like Mean Error (ME), Mean Absolute Error (MAE), and Mean Squared Error (MSE).

4. Distribution Planning:

   • Linear programming models were used to develop an optimal distribution plan to meet regional demands (East Midlands, West Midlands, and Northwest).
   • The distribution plan minimizes costs while meeting capacity and demand constraints.

5. Decision Tree Analysis for New Product Launch:

   • Created decision trees to assess the profitability of different suppliers for the new product launch.
   • Evaluated supplier options using decision-making rules (Maximin, Maximax, Expected Value).

6. Simulation:

   • Simulated demand using Excel’s random number generator to evaluate the impact of demand variability on revenue and profit.

🔍 Key Insights

• Sales for Winter Rock’s products exhibit strong seasonality, with peaks during the winter months.
• The decision-making process for supplier selection is critical in balancing risk and maximizing profit.
• An optimized distribution plan significantly reduces shipping costs and ensures efficient supply chain management.

💡 How to Use

• The Excel file contains the complete sales data analysis, forecast models, and distribution optimization results.
• Open the Excel file to explore the time series analysis, decision trees, and optimal distribution plan.

📈 Tools Used

• Microsoft Excel (for data analysis, forecasting, and decision tree simulation).
• Linear programming tools in Excel (Solver) to optimize the distribution strategy.

⚙️ Files in This Repository

1. Excel File: (Supply Chain Analysis.xlsx)
   • Contains the cleaned data, analysis, forecasts, and simulation results.
2. PDF Report:
   • Supply Chain Analysis pdf contains detailed business report outlining the analysis, methodology, and business recommendations.

📝 Conclusion

This project demonstrates how data-driven insights can enhance supply chain decision-making and improve operational efficiency. By leveraging historical data, forecasting models, and optimization techniques, the recommendations aim to help Winter Rock better manage inventory, forecast demand, and maximize profits.