Course Overview

This course equips students with a holistic understanding of supply chain analytics, emphasizing statistical analysis, forecasting techniques, inventory management strategies, transportation logistics, and supply chain planning. Through real-world examples, assignments, and case studies, it provides practical insights into operating state-of-art businesses by optimizing supply chain operations, ensuring efficient resource allocation, and enhancing decision-making for a robust and responsive supply chain system.

Learning Outcomes:

Foundational knowledge:

• Understand the fundamental concepts, tools, and techniques used in supply chain analytics.
• Grasp how to collect, analyze, and interpret data to make informed decisions about supply chain operations.
• Develop a foundation in statistics, probability, and optimization techniques.

Key analytical skills:

• Effectively apply statistical methods to analyze supply chain data.
• Build and validate regression models to predict supply chain behavior.
• Utilize mixed integer linear programming (MILP) to optimize supply chain decisions.

Core supply chain functions:

• Generate accurate demand forecasts using various forecasting methods.
• Make informed inventory management decisions to minimize costs and maximize service levels.
• Design efficient transportation networks and analyze transportation costs.
• Develop effective supply chain planning strategies for production and resource allocation.

Integration and decision-making:

• Integrate supply chain functions to achieve overall optimization.
• Make data-driven decisions to improve supply chain efficiency, responsiveness, and profitability.
• Identify and solve supply chain problems using analytical techniques.

Practical application:

• Apply learned concepts and tools to real-world supply chain problems through case studies and assignments.
• Develop a problem-solving mindset for tackling complex supply chain challenges.

Career advancement:

• Position themselves for competitive supply chain management, analytics, and consulting roles.
• Enhance their professional value and expertise in a high-demand field.

What You’ll Learn

Module 1: Data and Statistics

• What is supply chain analytics?
• Characterizing a distribution
• Central Tendency Metrics
• Spread metrics
• Probability distributions
• Discrete theoretical distributions
• Continuous probability distributions
• Normal Distribution
• Unit or standard normal distribution
• Dependent vs. Independent variables
• Linear regression model
• Validating a model – first steps model evaluation metrics
• Modeling categorical variables
• The practice of regression
• Modeling issues and tips
• Assignment

Module 2: Mixed Integer Linear Programming

• Numbers, Numbers, Everywhere
• Integer Variables
• Optimization by MILP – Model 1
• Optimization by MILP – Model 2
• Optimization by MILP – Model 3
• Optimization by MILP – Model 3
• Assignment

Module 3: Forecasting

• Demand Process – Three Key Question
• Forecasting Levels
• Forecasting truisms
• Subjective vs. Objective Approaches
• Forecast Quality
• Forecasting Metrics
• Time Series Components
• Time Series Analysis
• Cumulative Vs Naïve Forecasts
• Time Series Models
• New Product Development Process
• Assignment

Module 4: Inventory Management- I

• Why hold Inventory?
• Three Levels of Inventory Decisions
• Classification of Inventory
• Total Relevant Cost (TRC)
• Replenishment Models
• Economic Order Quantity (EOQ)
• EOQ extensions (Case Study Based)
  • All time discounts
  • One-time only discounts
  • EOQ with planned backorders
• Assignment

Module 5: Inventory Management- II

• Examples of Inventory Management
• Inventory replenishment policy
• Quick Asid on Converting Time
• Base Stock Policy
• Continuous Review Policy (S, Q)
• Item Fill Rate (IFR)
• Safety Stock Logic
• Periodic Review Policy (R, S)
• Periodic vs. Continuous Review
• Assignment

Module 6: Transportation Analysis

• Passenger vs. Freight Transportation
  • Packaging
  • Pallets
  • Shipping Containers
  • Inland Transportation at Origin
  • Container Terminals
  • Loading/Unloading Containers
  • Ocean Shipping Options
  • Inland Transportation at Destination
  • Inland Transport
  • Transport Options
• Transportation Networks
  • Multi Layers of Networks
  • The Physical Network
  • Operational Network
  • Strategic and Service Network
• Impact on Inventory
• Transportation Cost Functions
• Lead time variability
• Assignment

Module – 7: Supply Chain Planning

• Supply Chain Integration
• MRP/DRP Integration
• Master Production Schedule (MPS)
• Manufacturing Strategy
• Time Phased Record
• Level Production Strategy
• Chase Production Strategy
• Production Strategies
• Examples
• Approaches for Solving the FPH Problem
• Simple Heuristics
  • One Time Run
  • Lot for Lot
  • Fixed Order Quantity
  • Periodic Order Quantity
• Production Planning MILP
• Comparing Different FPH Models
• Material Requirements Planning (MRP)
• Bill of Materials (BOM)
• Distribution Resource Planning (DRP)
• Assignment