Supply Chain Management

SCM 4330 | DATA ANALYTICS

Business Modeling and Decision Analysis

Course Purpose

This course develops extensive skills in the application of analytics tools to develop financial, performance decision-making, cost optimization, simulation, and risk management models utilized to analyze and recommend solutions to complex Supply Chain Management problems. These skills enable students to gather information from business processes, describe the relations and interdependencies of business variables mathematically, and utilize data analytics technology to make managerial decisions. Within this course, students manipulate real business data to analyze Supply Chain Performance and help leaders to manage global supply chains for the future. Students report that this is one of the most valuable and broadly applicable courses within the Supply Chain Management curriculum and develops skills that differentiate Bauer SCM graduates from competing programs.

Expected Learning Objectives

Upon completion of the course students will:

• Feel confident integrating algebra and Excel to structure problems and perform logical data analysis
• Translate descriptions of decision problems into formal models, investigating these models in an organized fashion
• Skillfully build customized computer models for use in decision support, interpretation of model results.
• Draw managerial conclusions from analytical results and effectively present these conclusions
• Identify settings within Data Analytics technology systems to utilize models effectively and apply modeling concepts in practical situations.

Selection of Topics Covered:

• Extensive overview of Excel Principles and Techniques
• Forms Controls
• Advanced Filters and Pivot Tables Techniques
• Business Analytics
• Mathematical Models and Time Value Models
• Utilizing Solver, Solver Table, and Optimization Techniques
• Product Mix Models and Sensitivity Analysis
• Aggregate Planning Models
• Blending Models
• Transportation Models
• Assignment Models
• Binary Optimization Models
• Nonlinear Optimization Models
• Regression Models and Regression Analysis
• Simulation for Supply Chain Management

Course Pedagogy and Immersive/Experiential Activities

Every class utilizes hands-on work with analytics technology focusing on practicing the concepts being covered. Examples covered in class are selected to be relevant to the student experience and for the career paths of our students.

Students are provided with course notes, textbook resources, lectures. Extensive practice problems are provided to students for the purpose of practicing the management of a wide variety of unique Supply Chain decisions.

Grades are typically determined by performance in a series of Quizzes that progressively cover key concepts utilized in solving these models and three progressively weighted Exams. Exams require students to create, analyze, and interpret business models.