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Supply chain dataset focused on analyzing key metrics in manufacturing or production.

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Supply-Chain-Project

Abstract

Dataset of 100 unique values for a Fashion and Beauty startup company, with different variables that has effect on the profit, revenue and the overall welfare and deficiencies of the business. The purpose of the analysis is to demonstrate the effect of these variables to understanding key inventory metrics, e.g., product type, price, lead times, stock levels etc

Variables

There are varieties of variables that will impact the outcome of this analysis:

Product Type

• Skin Care

• Hair Care

• Cosmetics

Price

Availability: availability of Products

Revenue Generated: process of creating sales of products

Stock Levels: level of stock required for effective control of goods.

Lead Times: the amount of time when a company has all necessary resources on hand to manufacture a product and when it finally completes the manufacturing process.

Location: cities where manufacture of different product types listed above in India

• Mumbai

• Kolkata

• Delhi

• Bangalore

• Chennai

Production Volumes: volumes or quantity of products produced

Manufacturing Cost: cost of production

Inspection Results: quality check to verify if the product meets the required standard

• Pending

• Fail

• Pass

Defect Rate

Transportation Mode: different means of transportation mode to get products delivered

• Road

• Air

• Sea

• Rail

Total Cost: overall cost

Objectives

The objective of the analysis is to analyze the effect of variables relevance for operations and logistics roles; to demonstrate understanding of key inventory metrics.

The analysis seeks to answer the following questions:

Cost Analysis

  1. The costliest products to produce
  2. How manufacturing cost relate to selling price

Supply Chain Analysis

  1. The average lead times of different product type
  2. Are there correlation between defects rates and inspection results

Logistics Chain Analysis

  1. How different transportation mode affect total cost
  2. How different routes also affect total cost

Quality Analysis

  1. How do average defect rates correlate with inspection result and manufacturing costs

Production Analysis

  1. Are production volume aligned with market demands

Performance Insight

  1. Revenue generated from different location
  2. Revenue by product type
  3. Revenue contribution percentage from different location
  4. Profit from different location
  5. Profit by product type
  6. Profit contribution percentage from different location
  7. Revenue generated and their profit margin

Data Repository

  • Access Report HERE
  • Access Dashboard HERE

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Supply chain dataset focused on analyzing key metrics in manufacturing or production.

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