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Supply-Chain-Analytics

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This is a supply chain analytics project using Python, Tableau. In which conducted an analysis of supply chain inefficiencies, and developed informative dashboards to inform business stakeholders of potential issues, along with proposing strategic business enhancements.

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# Moving from Complexity to Clarity in Supply Chain
![](https://github.com/poojapatel26/Supply-Chain-Analytics/blob/main/Tableau_Dashboard.png)

This is a supply chain analytics project. In which conducted an analysis of supply chain inefficiencies, and developed informative dashboards to inform business stakeholders of potential issues, along with proposing strategic business enhancements.

**Blog Post** : [Here](https://medium.com/@poojapatel26/moving-from-complexity-to-clarity-in-supply-chain-d9d7db66f776)

**Tableau  Dashboard Link** :  [Here](https://public.tableau.com/app/profile/poojapatel26/viz/SupplyChainAnalytics_16964651727060/SupplyChainAnalytics)

## Project Description :
The project provides a real-world dataset focusing on supply chain analytics. As the main data analyst for Just In Time, you will help solve key shipment and inventory management challenges, analyze supply chain inefficiencies, and create insightful dashboards to inform business stakeholders about potential problems and propose structural business improvements.

## Objective 
In this project, my primary focus is on addressing key challenges related to shipment and inventory management within the supply chain. To achieve this goal efficiently, the project has been divided into few objectives:

## METHODOLOGY

Business demand analysis

Requirements: Create dashboard to analyze the business problem and improve the supply chain’s efficiency

Method: descriptive and exploratory analysis

Tool used: Python (Data preprocessing, data cleaning, EDA, inventory segmentation); Tableau (Dashboard)

Business Performance :

=> Dashboard of overall business performance including Profit & Cost of Products, total profit, best products etc

Inventory Management :

=> Dashboard of inventory management including warehouse inventory, Supply/Demand by Product Department, Inventory Storage Cost, Most Overstock products, Most understock products etc

Shipment Invenstigation :

=> Dashboard of shipping management including delay shipping like % of delapy orders, overall delay evolution, shupping delay by location, Most deplayed products etc

Order Fullfillment :

=> Dashboard of average warehouse inventory fullfilment by Product Category

Overall story of Create an interactive dashboard to summarize the research of the problem of the supply chain and suggest the solution

## Data Pre-Processing & Data Cleaning

The data pre-procesing and Data cleaning is done using Python. 
Detailed Notebook : [Here](https://github.com/poojapatel26/Supply-Chain-Analytics/blob/main/Supply_Chain_Analytics.ipynb)

## Data Overview 
The dataset provides three data tables including order_and_shipment, inventory and fulfillment. After examining the data fields, I noticed that the dataset generally represents the following key information

Customer: General information about customers including identifiers and addresses

Order: Information about the order including date of order, product and quantity ordered, order value

Shipment: Shipping information including shipping date, shipping mode

Product: Specific information about the ordered item including product name, product category, product department

Warehouse Inventory: Information on inventory management for each product name including monthly inventory, warehouse location, storage costs, order fulfillment

## Key Insights 
**1 Profit & Cost :**
* Most Profitable Product Department
* Most Profitable Products
* Goods with Highest Profit Margin
* Highest Inventory Storage Cost

**2 Inventory Analysis :**
* Supply Vs Demand
* Overstock Product Category :
* Under stock Product Category :

**3 Shipment Delay Analysis:**

**4 Order Fulfillment Days:**

Detailed analysis including feature metric, Key insights and suggestion can be found of medium Blog Post : [Here](https://medium.com/@poojapatel26/moving-from-complexity-to-clarity-in-supply-chain-08fe4f8eb2d2)

## Sugesstions

**Optimize Product Inventory :**
To improve profits and save on storage costs, we need to optimize our inventory, especially for most profitable and popular products worldwide. It is important to study demand patterns and adjust stock levels to avoid running out during peak periods and reduce excess inventory during slower times. Maintaining a reasonable buffer above expected demand during busy seasons can prevent shortages and optimize inventory expenses.

**Reorganize Inventory Distribution :**
The Fan Shop department’s inventory is insufficient compared to its demand, which may result in missed the sales opportunities. The company should take steps to increase inventory
Consider reorganizing inventory distribution between warehouses to reduce shipment delays. Minimizing delays in highly demand products can improve customer satisfaction.

**Marketing Strategies :**
Focus on promoting products with the highest profit margins to increase overall revenue. Consider advertising the top products with the highest profit margins and offer targeted discounts during peak seasons to boost sales and customer engagement.

**Monitor Shipment Delays :**
A further analysis is needed to identify the reasons for shipment delays and implement corrective measures to reduce them. Analyzing shipment processes and addressing potential bottlenecks can lead to improved fulfillment efficiency and customer satisfaction.

Supply-Chain-Analytics

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