README.md

metadata

title: Push/Pull and Category Analysis Tool
emoji: 📊
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 5.29.0
app_file: app.py
pinned: false
license: mit

Push/Pull and Category Analysis Tool

A supply chain optimization tool that analyzes inventory strategies and categorizes stores based on their performance.

Overview

This application helps supply chain professionals optimize their inventory management strategies by analyzing push versus pull fulfillment models and performing ABC (Pareto) analysis on store performance data.

Project Background

Based on knowledge gained from the "Supply Chain Analytics" specialization offered by Rutgers University on Coursera.

Features

• Push/Pull Analysis: Compare costs between push and pull inventory strategies across multiple stores
• Category Analysis: Classify stores as A/B/C categories using Pareto analysis principles
• Customizable Parameters: Set product values, salvage rates, life cycles, capital return rates, freight costs, and picking costs
• Visual Analytics: Generate charts for cost breakdown, store savings, and Pareto distribution

How to Use

Step 1: Set Parameters

In the "Parameter Inputs" tab:

1. Enter values for Product A (e.g., Smart phones)
2. Enter values for Product B (e.g., Feature phones)
3. Set freight costs and picking costs
4. Define product keywords for store mapping
5. Click "Compute Derived Rates" to calculate and display the derived rates

Step 2: Upload Data and Run Analysis

In the "Upload & Run" tab:

1. Upload a CSV file with the required columns
2. Click "Run Both Analyses" to generate results
3. View the push/pull summary, cost breakdown chart, and savings by store
4. Review the category analysis summary and Pareto chart

Input CSV Format

Your CSV file must include the following columns:

• Store: Store identifier/name
• Strategy: Either "Push" or "Pull"
• Onhand_Inventory: Current inventory level at the store
• Weekly_Sales: Weekly sales volume

Optional column:

• Product_Type: "A" or "B" to specify product type (alternative to using store name keywords)

Expected Outputs

Push/Pull Analysis

• Cost breakdown by strategy (inventory, shipping, pick/pack)
• Percentage savings comparing pull vs. push
• Store-by-store savings visualization

Category Analysis

• A/B/C classification of stores based on annual spend
• Pareto chart showing cumulative percentage of spend
• Summary of items and spend by category

Example

For demonstration purposes, upload a CSV with multiple stores showing a mix of push and pull strategies to see how the tool identifies cost-saving opportunities and classifies stores by importance.