The Master of Science in Supply Chain Management's 12-course curriculum prepares you to be a responsible leader in the supply chain field. Additional prerequisite courses may be required, depending on your academic background.
The curriculum below is effective fall 2018 for students admitted in fall 2018 and thereafter. Students who began the program before fall 2018 may pursue the program curriculum in effect when they entered their program or may switch to the revised curriculum below.
All courses listed are three credit hours.
The purpose of the course is to provide the student with statistical and data analysis tools useful for managers. The course emphasizes all the steps and procedures required to successfully managerial problems in which data are useful - from the definition of the managerial problem to statistical formulation of the problem, to data collection and data analysis, and the use of the statistical information in decision making. Topics considered are measures of central tendency and dispersion, theoretical distributions, estimation, hypothesis testing, correlation, regression, and time series analysis. MS Excel and PHStat will be used to analyze data.
Introduction to concepts and methods for managing operations in manufacturing and service organizations. Topics typically include forecasting, capacity and aggregate planning, material requirements planning, scheduling, facility layout and location, inventory management, just-in-time, total quality management, project planning, and logistics.
Business analytics leverages the vast amount of streaming data (“big data”) to extract actionable insights and drive better business decisions. It incorporates the best in data engineering, analytics methods, visualization techniques, and communication of results. Business analytics relies heavily on statistical and quantitative analysis, and predictive and prescriptive models to provide a forward-looking business decision making.
This course covers current concepts in database theory and use with a focus on design, implementation, and utilization of business database management systems. This course provides coverage of operational (traditional) database systems. Main topics of the course include ER modeling, relational modeling, normalization, and a comprehensive coverage of SQL.
This course covers current concepts in forecasting methods and use, with focus on implementation of these concepts in context to demand projections, economic and financial data analysis. This course uses R statistical language to create and implement various models. Main topics of the course include Regression, Time series analysis, and Markov Processes.
This course examines how business partners along the supply chain can work together to gain competitive advantage in moving products and services around the world to satisfy customers. The course will be an examination of the planning and management of global supply chain operations. Emphasis will be placed on the areas of traffic management, carrier operations, and warehousing. Each area will be analyzed in terms of its key goals, operational processes, technology applications, and performance control mechanisms.
A study of organizational procurement processes and decision making framework. Topics include insourcing/out-sourcing decisions based on total cost of ownership, purchasing cycle and processes, developing material and technical specifications, supplier evaluation, selection and management, supplier quality management, purchasing capital goods and services, global sourcing and e-commerce, and purchasing tools and analytics.
A study of the fundamental principles of effective management of inventory with emphasis on inventory costs, product stratification, performance measures, demand forecasting, periodic and continuous review, safety stock, material requirements planning, customer service, and use of technology in inventory management. Issues related to storage and the handling of inventory stock are also studied.
A study of the design, development, and use of decision models for analysis of supply chain problems. This course provides an example-driven approach to learn about important supply chain models, problems, and solution methodologies.
This course will focus on the importance of ethical decision making within a business context. First, several decision making frameworks will be presented, applied and evaluated. Business cases will be used in order to illustrate the ethical and risk management implications of each framework. Second, social psychological and cognitive factors that influence decisions and actions will be discussed as well as strategies for mitigating these factors.
This course focuses on how to effectively use Microsoft Excel and its built-in programming language, Visual Basic for Applications (VBA), to build financial models. The course will examine equity, fixed-income, option, and portfolio optimization problems. The course is a combination of both lecture and lab.
This course focuses on helping future business leaders, in increasingly competitive environments, think about the strategic use of technology in the development and management of competitive advantages. The course will use case discussions, expert presenters, and real-world projects to help students understand how to leverage emerging technologies—i.e. machine learning, artificial intelligence, block chain, cognitive analytics—as well as an understanding of innovation processes—i.e. design thinking—in developing sustainable business strategies.
MGMT 573 analyzes the responsibilities of general management in formulating, communicating, and implementing a strategic plan. Whereas Corporate Strategy (MGMT 574) defines the scope of the firm with the emphasis on strategic insights and perspectives, Business Strategy (MGMT 573) is concerned with how the firm generates sustainable competitive advantage within a particular industry or product market with the emphasis on strategic analyses and frameworks.
Data Mining involves the search for patterns in large quantities of data. The fundamental techniques used in data mining include, but are not limited to, clustering, decision trees, neural networks, and association analysis.
The art and science of project management as applied to a variety of business and technical projects in commercial, public, and private sectors. The course covers: project life cycle and methodology; team-building; project organization, stakeholders and leadership; proposals and contracts; techniques for project planning, estimating, scheduling, and control; and PMO.
The course focuses on a process view of the organization and provides students with a formal approach to designing, monitoring and improving business processes. The course provides the tools, methods and practical examples to help managers learn how to think from a process standpoint and how to ensure critical processes are controlled and functioning efficiently and effectively in their organization.
This course covers current concepts, components, and design issues related to data warehouses and business intelligence techniques for extracting meaningful information from data warehouses. Oracle, Informatica, Greenplum, and Tableau tools will be used to demonstrate design, implementation, and utilization issues. Most recent technologies in context to big data like MPP system, NoSQL, Hadoop (Pig, Hive, and MapReduce framework, etc.) will also be covered in detail. Advanced analytical SQL methods will be taught as well.
Methods for managing operations in manufacturing and service organizations based upon the Toyota Production System. Topics include the principles lean production: employee empowerment, workplace organization, smooth process flow, pull production, setup reduction, TPM, cellular manufacturing, standard operations, visual management, and supplier partnerships.
This course explores the management of services in general, and the application of operations concepts to the design and management of service delivery systems in particular. A case study approach will be used, supplemented with lectures.
This course serves as the capstone to the Masters in Supply Chain Management curriculum; it is designed to integrate topics covered during foundational courses and engage students in critical topics surrounding leadership in a real-life supply chain. This course will offer a hands-on opportunity to consolidate the concepts learned during previous courses and apply them in a practical and useful way.
* The prerequisite requirement is met if you have completed a minimum of one undergraduate course (3 credit hours) of comparable content in the prerequisite subject area within the last seven years with a grade of B (or equivalent) or higher if the course is determined appropriate by their academic advisor.
** All required courses must be completed prior to or concurrently with SCMG 589.