Supply Chain Management and Analytics (SCMA)

Description: Analytical approach to the design, planning, and control of operations management systems, including domestic and international, manufacturing and service operations.

Description: Taught predominately by the case method with a few classes for review and summary lectures. Concentrates on higher management decisions involving the manufacturing, service, and public sectors. Facilities planning, labor, aggregate planning, strategic planning, capacity management, and trade-off analysis.

Description: Advanced conceptual and methodological practices in designing and planning supply chain systems. Advances and strategies in supply chain procurement, transportation, distribution and warehousing, globalization, outsourcing, and technology.

Description: Focus on the improvement of supply chain operations through the application of lean management principles. Topics include just-in-time, six-sigma, theory of constraints, and associated tools and applications. The course would be offered primarily in the on-line MBA program.

Description: Planning and managing projects from initiation through implementation. Use of tools and techniques for bidding, planning budgeting scheduling, risk management and implementation.

Description: Analytical and simulation models for decision making in functional areas such as finance, accounting, marketing, personnel, operations, and inventory. Construction of decision models for practical applications. Emphasis on analyzing alternatives and implementing solutions that result in increased productivity.

Description: Focus on global aspects of supply chain managing with primary emphasis on sourcing and distribution strategies. Topics will include sourcing strategies, concepts and tools. Specific issues include make versus buy decisions, supplier evaluation and selection, total cost of ownership, contracts and legal terms, negotiation, and purchasing ethics.

Description: Examination of physical distribution activities in the marketing mix from the viewpoints of both providers and users of components of logistics systems. Logistics problems of concern to the marketing manager include time and place utility concepts, spatial relationships of markets, channel design, transportation modes, and inventory management.

Description: Business leaders must understand how to leverage advanced information technology (IT) for operations and innovation. Learn the foundations of IT, advanced IT trends, and how IT is used to operate, innovate, grow, and transform organizations.

Description: This course will focus on how knowledge management has been successfully applied in business in the form of predictive analytics. Predictive analytics extends statistical and/or artificial intelligence to provide forecasting capability. It will also describe in non-technical terms the statistical and artificial intelligence-based tools commonly used in forecasting and other business decisions involving big data.

Description: Technology of databases and related human and managerial considerations. Databases are studied from the perspective of the logical organization, as well as from the perspective of managers and applications programmers, in the use of organizational data. Consideration of physical organization and SQL. Practical applications of databases.

Description: Data mining applies quantitative analysis to support humans in identifying actionable information from large amounts of data. Actionable means that value can be obtained, which for businesses usually relates to making money. This course will focus on how data mining has been successfully applied in business. It will also describe in non-technical terms how the statistical and artificial intelligence-based tools commonly used in data mining work. The course will also address ethical issues related to use of information obtained through data mining.

Description: Covers advanced business analytics topics, including data cleansing, classification, clustering, reduction, exploration and visualization. Big data analysis platforms and tools are also covered.

Description: This course will focus on how optimization modeling techniques can be used to make the best decisions in a variety of business analytics applications. The emphasis will be on the formulation of different optimization problems and the use of the correct quantitative techniques to solve these problems.

Description: Provides an overview of decision theory and decision analysis with a focus on decision-making under uncertainty. Topics covered may include decision theory, which includes a set of mathematical tools for describing and reasoning about decisions, and decision analysis, which involves the application of decision theoretic tools to real world problems. Considers both the mathematical and statistical foundations of decision theory, including Bayesian inference, and the application of these techniques to problems in business.

Description: Overview of the uses of simulation and computation for analyzing stochastic models and interpreting real phenomena. Topics covered may include discrete-event simulation, Monte Carlo simulation, generating discrete and continuous random variates, the statistical analysis of simulated data, variance reduction techniques, and simulation optimization. Applications will be drawn from areas such as manufacturing, supply chain management and finance.

Description: Overview of the research literature in inventory management, including topics such as deterministic and stochastic models for inventory control and multi-echelon inventory theory. Introduce the research literature in the area of procurement, including topics such as supplier management and contract design.

Description: Provides an overview of the research literature in transportation and logistics modeling, including heuristic and optimization models with both single and multiple objectives, as well as empirical applications. Introduces the research literature in areas such as vehicle routing and location analysis.

Description: Provides theoretical and methodological background on service system design. Considers the design and delivery of service in industries such as healthcare, banking, retailing, and evolving service sectors, to improve the productivity and quality of the system. Covers different aspects of system design and service delivery, such as technology use and mechanisms to promote individual and organizational learning.

Description: Provides an overview of the research literature in demand management and the use of optimization to derive pricing and revenue management decisions in the context of operations management. Topics such as demand and revenue forecasting, customer segmentation, capacity allocation, dynamic pricing, assortment management, discounting, overbooking practices, and auctions that are relevant for industries such as airlines, hotels, restaurants, retailing, online advertising, cloud computing, and ride sharing.

Description: Provides an overview of mathematical programming theory and techniques, such as linear, integer and nonlinear programming, and will cover both problem formulation and solution approaches. Understanding of formulating and solving large-scale problems in broad application areas of supply chain management and business analytics.

Description: Provides the theoretical foundation in stochastic processes necessary to analyze complex systems that exhibit random behavior over time, which regularly arise in operations and supply chain management. Introduces the basic concepts of stochastic processes, describe the types of stochastic processes most commonly used in the study of operations and supply chain management, discuss how to identify the appropriate type of process to model a given system, and demonstrate the methods used to model and analyze stochastic systems.

Description: Exposure to the variety of methods used and topics studied in operations management, supply chain management and analytics, with a focus on state-of-the art research. Exposure to on-going research through methods such as attendance and participation in departmental and college seminars, and meetings with visiting speakers and scholars.

Description: Individual research or reading on a selected problem in operations management, supply chain management, or analytics.

Description: Research credits required for a doctoral dissertation for completion of degree.