Supply Chain Management

SCM 4330 | DATA ANALYTICS

Business Modeling and Decision Analysis

Optimization and Technology

Course Overview

SCM 4330 equips students with the analytical and technological skills needed to model, analyze, and solve complex supply chain and business performance problems. This course emphasizes the use of quantitative modeling, optimization, simulation, and decision-support tools to improve operational efficiency, reduce costs, and support strategic decision-making in global supply chains.

Course Purpose

This course develops students’ ability to translate real-world business challenges into structured analytical models. Students learn to apply a wide range of statistical and business modeling software, tools, and techniques to evaluate trade-offs, manage uncertainty, and recommend data-driven solutions. The course integrates concepts from finance, operations, and analytics to prepare students for high-impact roles in supply chain planning, sourcing, logistics, and enterprise performance management.

Students report that this is one of the most valuable and broadly applicable courses in the Supply Chain Management curriculum — developing skills that consistently differentiate Bauer SCM graduates in the job market.

Learning Objectives

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

• Confidently integrate algebra, statistics, and Excel-based modeling to structure and solve business problems
• Translate complex decision scenarios into formal models and analyze them using optimization and simulation tools
• Build customized decision-support models using spreadsheet-based and statistical software
• Interpret model outputs and draw actionable managerial insights
• Apply modeling techniques to real-world supply chain challenges such as product mix, sourcing, logistics, and capacity planning
• Use tools such as Solver, SolverTable, regression analysis, simulation, and Palisade Decision Tools to support decision-making under uncertainty
• Communicate analytical findings clearly and persuasively to business stakeholders
• Understand the role of modeling in enterprise systems and digital supply chain platforms

Topics Covered

• Excel Modeling Principles and Advanced Techniques
• Business Analytics Foundations
• Time Value of Money and Financial Modeling
• Optimization with Solver and SolverTable
• Product Mix and Sensitivity Analysis
• Aggregate Planning and Blending Models
• Transportation and Assignment Models
• Binary and Nonlinear Optimization
• Regression Analysis and Predictive Modeling
• Simulation for Risk and Uncertainty
• Supply Chain Network Design and Cost Optimization
• Decision Support in ERP and Analytics Platforms

Experiential Learning & Course Pedagogy

Every class session includes hands-on modeling exercises using real business data and analytics software. Students work through applied problems that reflect the types of decisions faced by supply chain professionals in industry. Course content is designed to be immediately relevant to students’ career paths and includes:

• Real-world case studies and modeling challenges
• Exposure to industry-standard tools and platforms
• Practice with data interpretation and executive-level reporting

Course Format & Assessment

Students are provided with course notes, textbook resources, and lectures. Grades are typically based on:

• A series of quizzes that progressively build modeling proficiency
• Three progressively weighted exams requiring students to create, analyze, and interpret business models
• Participation in applied modeling exercises and case-based problem solving