MS in Supply Chain Management

This course will provide students with the analytical tools to analyze, manage, and improve manufacturing, service, and business processes. Coverage includes various options to lower operational costs and improve responsiveness to customers' needs, including operating system design, product & service design, capacity analysis & buffering, waiting line optimization, and process quality analysis using statistical approaches. Quantitative methods include application of stochastic simulation, analysis of random outcomes, statistical analysis routines (confidence intervals, hypothesis testing, machine learning), system reliability analysis, and statistical process control. The Deming philosophy of management, Lean operations principles, and Six Sigma process improvement methodologies form the underlying foundation of the course coverage.  [ 4 cr. ]

Introduction to the concepts, methods and problems of accounting and financial analysis. Includes accounting principles, measurement and disclosure issues, financial statement analysis, time value of money, cash flow projection and analysis, capital budgeting and project evaluation, bond and equity valuation, cost of capital and capital structure. 4 cr. Effective Fall 2021, this course fulfills a single unit in each of the following BU Hub areas: Quantitative Reasoning II, Critical Thinking.  [ 4 cr. ]

This course covers the quantitative analysis tools to support operations management for a supply chain that is geographically dispersed and culturally diverse. The tools necessary to assure that the products/services are delivered/provided in the quality and timely manner include demand forecasting, inventory and capacity buffer optimization, delayed differentiation, statistical risk pooling, and stochastic inventory optimization. These tools are applied to decisions such as offshoring, multi-country outsourcing, push-pull, reverse supply chains, and risk mitigation. Particular attention is given to sustainability, information technology and digitalization, and creating resiliency.  [ 4 cr. ]

The purpose of this course is to help improve business problem solving and managerial decision-making through the use of quantitative and qualitative decision-making tools and techniques. This course will provide the student with an overview of how decisions are made to solve management problems in the business environment. It introduces the fundamental concepts and methodologies of the decision-making process, problem-solving, decision analysis, data collection, probability distribution, evaluation, and prediction methods. Students will learn how to apply different quantitative and qualitative analytical tools commonly used in business to provide a depth of understanding and support to various decision-making activities within each subject area of management. Through the use of case studies of decisions made by managers in various production and service industries and a business simulation package specifically prepared for this course, the scope and breadth of decision-making in business will be described.  [ 4 cr. ]

Prereq: AD100 Pre-Analytics Laboratory and ADR100 Introduction to R
This course presents fundamental knowledge and skills for applying business analytics to managerial decision-making in corporate environments. Topics include descriptive analytics (techniques for categorizing, characterizing, consolidating, and classifying data for conversion into useful information for the purposes of understanding and analyzing business performance), predictive analytics (techniques for detection of hidden patterns in large quantities of data to segment and group data into coherent sets in order to predict behavior and trends), prescriptive analytics (techniques for identification of best alternatives for maximizing or minimizing business objectives). Students will learn how to use data effectively to drive rapid, precise, and profitable analytics-based decisions. The framework of using interlinked data inputs, analytics models, and decision-support tools will be applied within a proprietary business analytics shell and demonstrated with examples from different functional areas of the enterprise. R, SQL, and Power BI software are used in this course.   [ 4 cr. ]

This overview course examines the management issues involved with assessing the security and risk environments in both the private and public sectors in order to assure continuous system-wide operations. The course studies the elements of operational and technological risk assessment and operational continuity using a project management framework and quantitative risk metrics. Students are exposed to the role of the firm in crisis response and management as well as the terms, systems, and interactions necessary to assure continuous operations. Topics include: the role and need for comprehensive assurance strategy and planning; information security; an overview of the system-wide structure; the social and emotional impact on the workforce as well as its effect on productivity; and the organizational infrastructure relating to national, regional, and international compliance.   [ 4 cr. ]

Prereq: METAD571
The course offers an overview of the key current and emerging enterprise risk analytical approaches used by corporations and governmental institutions and is focused on understanding and implementing the enterprise risk management framework on how to leverage the opportunities around a firm to increase firm value. The major risk categories of the enterprise risk management such as financial risk, strategic risk, and operational risk will be discussed and risk analytics approaches for each of these risks will be covered. Students will learn how to use interlinked data inputs, analytics models, business statistics, optimization techniques, simulation, and decision-support tools. An integrated enterprise risk analytics approach will be demonstrated with examples from different functional areas of the enterprise. R, SQL, and Power BI software are used in this course.   [ 4 cr. ]

Prereq: MET PM100
This course introduces students to macro and micro approaches to project cost estimation. Case studies of both pre-project and in- process estimating examine some of the more common perils of human irrationality associated with project estimation to help develop more sensible, achievable project outcomes. Students learn how to manage both project cost and schedule objectives throughout their projects using the Earned Value and Earned Schedule Measurement Systems. Students then study risk management through an examination of both individual and overall project risk and apply their learnings using advanced risk management software in an actual case study. Students also study project quality management, procurement/contract management, and project ethics and professional conduct using case study scenarios.  [ 4 cr. ]

This course covers quantitative approaches to logistics management. It teaches network optimization techniques and center gravity models for location analysis, mathematical programming for selecting the optimal transportation modality, statistical distributions for modeling the statistical uncertainty around the arrivals of trucks to a warehouse or a store, and inventory modeling for optimizing distribution centers. The course introduces mathematical models for warehouse layout decisions, learning curve models, and logistics network design in the context of today's increasingly digitalized supply networks.  [ 4 cr. ]

Course participants will be exposed to the fundamental principles involved in the analysis and management of quality for enterprises and their supply chain. Quality is defined in the broadest sense, encompassing all performance components that drive customer satisfaction. The course focuses on management principles, statistical modeling and analysis, and their application in a variety of industrial, service, healthcare, and educational environments. Topics include the Deming philosophy of management, Six Sigma and the DMAIC project framework, quality certification systems, statistical data analysis & presentation, statistical modeling using control charts, and statistical analysis of process capability. Students will earn a Six Sigma Green Belt based on satisfactory performance on the final examination.  [ 4 cr. ]

This course provides extensive insight into international trade practices and corporate decision-making criteria attendant to global import/export and other market entry strategies, and management of international logistics operations including global sourcing, global transportation, facility network design, intermediaries, and trade documentation. Topics include operations, government agencies, import/export channel networks, and the evaluation of international opportunities with the help of a business simulation package specifically prepared for this course. It is designed to provide students with the skills and tools necessary for international trade and international logistics management.   [ 4 cr. ]

This course provides an opportunity for supply chain students to apply various methodological tools to solve a real world problem supported by an external sponsor or generated as a research project. Projects require the use of quantitative and qualitative tools to analyze supply chain performance, quantify supply chain risks, optimize logistics networks, optimize inventory levels, or evaluate capacity decisions. Specific methodologies include mathematical modeling, data mining, statistical analysis, inventory optimization, network optimization, process analysis, and waiting line modeling and optimization.  [ 4 cr. ]

The goal of this course is to introduce to students foundational mathematics and statistics knowledge that will provide them skills and tools necessary to succeed in their area of study.   [ 4 cr. ]

Prereq: AD100 Pre-Analytics Laboratory and ADR100 Introduction to R
This course presents fundamental knowledge and skills for applying business analytics to managerial decision-making in corporate environments. Topics include descriptive analytics (techniques for categorizing, characterizing, consolidating, and classifying data for conversion into useful information for the purposes of understanding and analyzing business performance), predictive analytics (techniques for detection of hidden patterns in large quantities of data to segment and group data into coherent sets in order to predict behavior and trends), prescriptive analytics (techniques for identification of best alternatives for maximizing or minimizing business objectives). Students will learn how to use data effectively to drive rapid, precise, and profitable analytics-based decisions. The framework of using interlinked data inputs, analytics models, and decision-support tools will be applied within a proprietary business analytics shell and demonstrated with examples from different functional areas of the enterprise. R, SQL, and Power BI software are used in this course.   [ 4 cr. ]

This overview course examines the management issues involved with assessing the security and risk environments in both the private and public sectors in order to assure continuous system-wide operations. The course studies the elements of operational and technological risk assessment and operational continuity using a project management framework and quantitative risk metrics. Students are exposed to the role of the firm in crisis response and management as well as the terms, systems, and interactions necessary to assure continuous operations. Topics include: the role and need for comprehensive assurance strategy and planning; information security; an overview of the system-wide structure; the social and emotional impact on the workforce as well as its effect on productivity; and the organizational infrastructure relating to national, regional, and international compliance.   [ 4 cr. ]

Prereq: METAD571
The course offers an overview of the key current and emerging enterprise risk analytical approaches used by corporations and governmental institutions and is focused on understanding and implementing the enterprise risk management framework on how to leverage the opportunities around a firm to increase firm value. The major risk categories of the enterprise risk management such as financial risk, strategic risk, and operational risk will be discussed and risk analytics approaches for each of these risks will be covered. Students will learn how to use interlinked data inputs, analytics models, business statistics, optimization techniques, simulation, and decision-support tools. An integrated enterprise risk analytics approach will be demonstrated with examples from different functional areas of the enterprise. R, SQL, and Power BI software are used in this course.   [ 4 cr. ]

The course explores modern project management by providing an enterprise- level, experiential view of the discipline focused on connecting projects to the organization's mission, vision, and values. The theme of the course is applying key project management tools and techniques, through case-based group work, which will help students identify, analyze, and develop practical proposals to real-world issues. Groups select, plan, report, and then present on their project's scope, schedule, cost, risk, quality, and communications elements using tools such as the WBS, network diagram, PERT estimate, Gantt chart (including the use of MS Project), risk register, and heat map. Students also gain familiarity with important new concepts in project management: Agile frameworks, actionable sustainability thinking, and Benefits Realization Management, all of which will be important for their success not only in other graduate courses, but as they lead projects for their organizations so as to provide lasting, triple-bottom-line value. The course is aligned with the latest PMBOK? Guide from the Project Management Institute.   [ 4 cr. ]

Prereq: MET PM100
This course introduces students to macro and micro approaches to project cost estimation. Case studies of both pre-project and in- process estimating examine some of the more common perils of human irrationality associated with project estimation to help develop more sensible, achievable project outcomes. Students learn how to manage both project cost and schedule objectives throughout their projects using the Earned Value and Earned Schedule Measurement Systems. Students then study risk management through an examination of both individual and overall project risk and apply their learnings using advanced risk management software in an actual case study. Students also study project quality management, procurement/contract management, and project ethics and professional conduct using case study scenarios.  [ 4 cr. ]

The course provides a detailed examination of the history of e-commerce, along with important concepts related to the ways that businesses can successfully use Internet and Web technology. Students are introduced to the concepts and problems associated with electronic commerce. Topics include comparison of e-commerce procedures, payment mechanisms, applications in different industry sectors, security, the challenges of starting and maintaining an electronic business site, as well as a comparison with traditional business practices. The development of a WordPress-themed website is a minor feature of the course. 4cr.  [ 4 cr. ]

This course considers macroeconomic factors of relevance to the firm: aggregate economic activity, cyclical movements, and fiscal and monetary policies. The course reviews the problems of decision-making relating to demand, production, costs, market structure, and price, and provides an analysis of the interplay between governments, economic systems, labor, and multinational corporations (MNCs). Topics include: the basis for the existence, organization, and growth of MNCs; a comparison of major economic and government systems; areas include the impact on the firm's business transactions and trade due to taxation, regulation, legal environments and labor influences. This course additionally investigates the relationship between the interaction of national culture and development. Topics range from developing nations' rain forest and species management to pollution generated by developed nations. Culture, policy, and development are also discussed in relation to the impact of the business interactions (agriculture, fishing, technology transfer, etc.) among developing and developed nations.  [ 4 cr. ]

This course covers quantitative approaches to logistics management. It teaches network optimization techniques and center gravity models for location analysis, mathematical programming for selecting the optimal transportation modality, statistical distributions for modeling the statistical uncertainty around the arrivals of trucks to a warehouse or a store, and inventory modeling for optimizing distribution centers. The course introduces mathematical models for warehouse layout decisions, learning curve models, and logistics network design in the context of today's increasingly digitalized supply networks.  [ 4 cr. ]

This course will provide you with the theoretical understanding of the Internet marketplace necessary to adapt to its many changes, while also equipping you with the skills you'll need to perform vital daily functions. The course includes discussions of both B2B and B2C and looks at marketing and communications from an integrated, business-wide perspective. The goal is to appreciate principles and practice of online marketing. Topics include integrated innovative marketing strategy, search engine marketing, email marketing, and social media. 4cr.  [ 4 cr. ]

Addresses the specifics of new product and service development and fostering innovation and technology to increase performance. Topics include generating and screening initial ideas; assessing user needs and interests; forecasting results; launching, and improving products and programs; bringing innovation to commercial reality.   [ 4 cr. ]

This course provides extensive insight into international trade practices and corporate decision-making criteria attendant to global import/export and other market entry strategies, and management of international logistics operations including global sourcing, global transportation, facility network design, intermediaries, and trade documentation. Topics include operations, government agencies, import/export channel networks, and the evaluation of international opportunities with the help of a business simulation package specifically prepared for this course. It is designed to provide students with the skills and tools necessary for international trade and international logistics management.   [ 4 cr. ]