Online Master of Science in Supply Chain Management Concentration in Risk 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 credits]

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 credits]

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 credits]

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 credits]

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 credits]

The course presents, assesses, and discusses the contemporary theories, methods and practices related to business continuity (BC), business continuity management (BCM) and resiliency planning. The course incorporates the underpinnings of enterprise-wide risk management (ERM); however, it is designed to focus on broad-based threats, vulnerabilities, unexpected events, emergencies, and crises that may impacts organizations and their leaders and professionals. The course focuses on the design, development and applications of resilience, emergency planning, crisis management, BC, and disaster recovery used by organizations in the private sector. It presents a comprehensive, cutting-edge technologies pertaining BCM in complex organizations and challenging environments. Technological innovations are used to involve a complex array of high-level developments that result in transitions and transformations of businesses. Finally, the environmental considerations center on connections between business and the natural law. [4 credits]

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 credits]

This introduction to core statistical and mathematical concepts builds the foundation needed to thrive in a management career. Develop the skills, tools, and knowledge essential to offering quantitative insights in management and administrative settings. [4 credits]

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 credits]

Prerequisite: MET AD617 -This course takes concepts covered in MET AD617 and applies them in more detail mainly to the corporate-private sector environment. During this course, we will first review the organization and processes necessary to effectively respond to and manage incidents, including the transition from emergency response and incident management to business recovery. The course will focus on disaster recovery, an absolutely essential but sometimes overlooked component of any successful corporate recovery program. Here, the emphasis is on technology recovery. This includes reviewing the key components of the IT infrastructure; how these components are accounted for in the response and recovery processes; and some best practices in technology recovery modelling. Several emerging technologies relative to cloud computing, information security, etc., are also examined. Prereq: MET AD617 [4 credits]

Prerequisite: MET AD 610 - Discover how leading organizations manage a wide array of technology-related threats and vulnerabilities, ranging from routine outages and operational errors to infrastructure breakdowns and systems failures - right up to significant data breaches, denial of service and ransomware attacks. You will review principles of technology resilience and its role within the organizational enterprise risk management structure. From there, the greater technology risk landscape is evaluated, the importance of governance and compliance are reinforced, and the infrastructure and processes necessary for organizations to effectively manage technology-related incidents are examined. The course also includes an examination of how enterprises transition from incident management to technology recovery, and how leading companies design and implement cybersecurity and privacy programs. [4 credits]

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 credits]

A communications skills course designed to better understand the nature of conflict and its resolution through persuasion, collaboration, and negotiation. Students will learn theories of interpersonal and organizational conflict and its resolution as applied to personal, corporate, historical, and political contexts. Students will assess their own styles, skills, and values, and develop techniques to better resolve disputes, achieve objectives, and exert influence. [4 credits]

Undergraduate Prerequisites: METAD642 - Prereq AD642
This course will introduce students to Project Value - - a unique perspective on classical Project Management that is focused on assuring that a project delivers value that is aligned with the mission, vision, and values of an organization. This increasingly popular framework with which to view projects and project management is derived from current research, standards, and thought leadership from PMI and other international bodies . Students will learn how to create value in projects even in today's disruptive, turbulent environment. They will learn how to apply the conceptual framework of benefits realization management (BRM) and to use tools to manage a portfolio of programs and projects strategically with an aim of sustainable project value. Value in Agile projects will be discussed. The element of the Triple Bottom Line and a focus on sustainability is part of the subject matter. Case studies and real life experiences, illustrated with guest lectures, will be intertwined with current research in project management. [4 credits]

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 credits]