Client Inventory Management Agent (Replenishment Engine)

This project implements a Replenishment Engine designed to optimize inventory levels across pharmacy branches. It automates the identification of stock requirements, manages stock allocation from a central warehouse, facilitates external procurement (Local Purchase Orders - LPOs), and identifies excess inventory.

Key Features

• Identifies Branch Replenishment Needs: Determines which products at each branch require additional stock based on minimum inventory levels and dynamically calculated Min_Stock and Max_Stock (based on 30-day sales and lead time).
• Stock Allocation & LPO Generation: Allocates available stock from the central warehouse to fulfill branch requirements. For any unfulfilled demand, it generates Local Purchase Orders (LPOs) for external procurement.
• Excess Stock Identification: Identifies and flags products at branches that hold inventory exceeding optimal levels, using a "Days of Stock" (DOS) metric.

Tech Stack

• Python: The core programming language used for the engine logic.
• Streamlit: Used for building the interactive web application interface.
• Pandas: Utilized for efficient data manipulation and analysis of CSV files.

Operational Logic Overview

The engine processes inventory data through a systematic flow:

1. Identify Branch Replenishment Needs: Calculates ReorderQty for each product at each branch if Branch_Stock is below Min_Stock. Min_Stock and Max_Stock are dynamically calculated based on Sales_30D and Lead_Time_Days.
2. Check Warehouse for Stock Availability: Attempts to fulfill ReorderQty from Warehouse_Stock. If warehouse stock is insufficient, a partial allocation is made, and the remaining quantity is flagged for an LPO.
3. Create Transfer Orders: Generates a detailed list of products to be moved from the central warehouse to specific branches.
4. Prepare and Flag LPO Needs: Consolidates and lists all products requiring external procurement due to insufficient warehouse stock.
5. Identify Excess Stock: Calculates excess stock using a "Days of Stock" (DOS) metric, based on Branch_Stock and Sales_30D.

Input Files

The application requires the following CSV files to be uploaded:

• Branch_Inventory.csv: Contains current stock levels for products at each branch.
• Warehouse_Stock.csv: Contains current stock levels in the central warehouse.
• SKU_Master.csv: Contains master data for SKUs, including Min_Stock, Max_Stock, Sales_30D, Lead_Time_Days, and Vendor information.

Output Files

Upon completion of each replenishment engine run, the following CSV files are generated in the outputs/ directory:

• Transfer_Orders.csv: Details all products and quantities to be transferred from the central warehouse to specific branches. Includes Min_Stock, Max_Stock, Branch_Stock, and Warehouse_Stock for easier review.
• LPO_Needs.csv: Lists all products, required quantities, and associated vendors for external procurement.
• Excess_Stock.csv: Identifies products at branches that are overstocked, including the calculated excess quantity based on Days of Stock.

Demo Video

Watch a quick demonstration of the Replenishment Engine in action:

How to Run the Application

This application is built using Streamlit.

1. Ensure Python Environment: Make sure you have Python 3.8+ installed. It's recommended to use a virtual environment.
2. Install Dependencies:

   pip install -r requirements.txt

   (Assuming requirements.txt exists and contains streamlit, pandas, etc.)
3. Run the Streamlit App:

   streamlit run streamlit_app.py

   This will open the application in your web browser.