SCM 7320

Supply Chain Analytics

Optimization and Technology

Course Overview

SCM 7320 prepares students to lead data-driven decision-making in modern, digitized supply chains. The course emphasizes the integration of advanced analytics, financial acumen, and technology tools to solve complex, unstructured business problems. Students will learn to model, simulate, and optimize supply chain systems using real-world data and financial reports, including the Balance Sheet, Income Statement, and Statement of Cash Flows.

This course is designed for future supply chain leaders who must speak the language of finance and analytics to drive performance, cost optimization, and strategic alignment across global operations.

Course Purpose

The purpose of this course is to develop analytical leaders who can translate business challenges into actionable models and solutions. Students will gain fluency in the tools and techniques of descriptive, predictive, and prescriptive analytics, while also learning to interpret and apply financial data to supply chain decisions.

By combining technology enablement with a strong foundation in business finance and performance management, this course empowers students to make informed, strategic decisions that enhance supply chain resilience, efficiency, and value creation.

Learning Objectives

Upon successful completion of this course, students will be able to:

  • Apply advanced analytics techniques to model and solve real-world supply chain problems.
  • Use financial statements (Balance Sheet, Income Statement, Statement of Cash Flows) to inform supply chain strategy and investment decisions.
  • Build and interpret optimization, simulation, and forecasting models using tools such as Excel Solver, @Risk, R, and LINGO.
  • Evaluate trade-offs between cost, risk, and performance in supply chain design and operations.
  • Translate complex data into clear, actionable insights for stakeholders across finance, operations, and marketing.
  • Utilizing technology, analytics, and financial metrics to meet customer-centric goals.
  • Integrate managerial accounting and performance analytics into supply chain planning and execution.
  • Leverage technology tools to enable digitized, agile, and resilient supply chain solutions.

Topics Covered

  • Structured Modeling of Business and Supply Chain Problems
  • Descriptive, Predictive, and Prescriptive Analytics
  • Financial Modeling and Decision-Making Using Business Reports
  • Optimization Techniques (Linear, Non-linear, Genetic Algorithms)
  • Monte Carlo Simulation and Risk Analysis
  • Advanced Forecasting and Regression Techniques
  • Performance Analytics and Cost Optimization
  • Digitized Supply Chain Design and Technology Enablement
  • Inventory, Sourcing, and Network Optimization Models
  • Managerial Accounting for Supply Chain Decision-Making
  • Scenario Planning and Strategic Trade-off Analysis

Experiential Learning & Course Pedagogy

This course blends in-person instruction with digital learning tools to create a highly interactive and applied learning environment. Students engage in:

  • Guided Practice: Pre-class activities including video lectures, readings, and software tutorials.
  • Self-Assessments: Quantitative exercises to reinforce foundational concepts.
  • Classroom Problem Solving: Collaborative sessions focused on real-world modeling challenges.
  • Concept Quizzes: In-class assessments to reinforce mastery of key topics.
  • Modeling Projects: Three major projects using real-world data to solve complex supply chain problems, requiring students to present results in business-relevant formats for decision-makers.

Students will work with financial data and performance metrics to simulate the decision-making environment of supply chain executives, bridging the gap between analytics and strategic business finance.

Course Format & Assessment

The course combines in-person sessions with asynchronous digital content. Assessment is based on:

  • Practice Problem Sets (progressive skill development)
  • Three Applied Business Modeling Projects (real-world data and financial integration)
  • Three Exams (technical and strategic application)
  • Participation in class discussions and problem-solving sessions