Part-Time MBA concentration in Supply Chain Management

Explores new approaches for organizing the total enterprise, including structuring, processes, and culture. Using cases and simulations, new forms of organizing are linked to various competitive strategies and to performance, and skills for designing, implementing, and managing strategic transformation are developed.

Provides an introduction to the principles, practice, and processes of negotiations as a management skill with bosses, subordinates, peers, clients, and customers. Discussion of the preparation and planning for negotiation, the strategy and tactics of negotiation, issues regarding both distributive and integrative bargaining, and ethics in negotiation.

Introduces business-to-business marketing from the perspective of both the seller and the buyer. Covers marketing strategy and product/ market planning systems; selling and management of the sales force; marketing research and competitive intelligence; pricing and promotion; management of auxiliary services; and industrial buying behavior.

This course provides a broad overview of key supply chain strategies, issues and challenges. Successful supply chain management requires cross-functional integration of key business processes within the firm and across the network of firms that comprise the supply chain. The challenge is to determine how to successfully accomplish this integration. Other topics covered include the management aspects of logistics networks, forecasting, inventory management, supply contracts, strategic alliances, supply chain integration and design, procurement and outsourcing, customer value, international issues, and a quick review of supply chain software. Case studies, supplemented with a Supply Chain Simulation, and guest speakers are used to illustrate the issues discussed in lectures.

Prerequisite: Operations Analysis

Supply Management is the overarching cross-functional management framework that integrates all activities related to the acquisition and management of resources for the organization. It includes global sourcing, supplier relationship management, procurement and purchasing. Supply Management is now recognized as a key strategic initiative to create value for the corporation. This course reviews the demands placed on today's procurement and supply management from the firm's stakeholders and demonstrates their impact on the competitive success and profitability of the organization. Furthermore it describes ethical, contractual and legal issues faced by procurement, and recognizes the expanding strategic nature of supply management. The major areas covered are procurement as a functional activity, and how effective supply management impacts on total quality, cost, delivery, technology, and responsiveness to the needs of a firm's external customers (insourcing/outsourcing, supplier evaluation, supplier development, and global sourcing). We introduce the tools, techniques, and approaches for managing the procurement and sourcing process (cost/price analysis, negotiations, and contract management). Case studies and outside speakers will be used to illustrate the issues discussed in lectures.

Supply Chain Management is generally focused on product and information flow, but is largely driven by financial and accounting considerations. An often unknown fact is that the supply chain is designed to enhance the financial value of a corporation, or ultimately to serve the chief financial officer. The objective of the course is to introduce key financial and accounting aspects of SCM and instill a financially oriented mindset by integrating said aspects into the analysis of SCM issues and systems. Topics covered include supply chain costing, working capital management, supply chain financing, supply chain risk management, and supply chain contracts and purchasing. Some case studies will illustrate the concepts learned.

Supply chain management has become increasingly data-driven in the last several decades and traditional statistical techniques (e.g., forecasting) have been widely applied in supply chain planning. Well into the ecommerce age, there is great need for supply chain managers to understand artificial intelligence (AI) and machine learning (ML) methods, to organize/analyze “big” data and to integrate/automate data analysis into operations processes on newly emerging IT platforms (e.g., cloud computing). The main purpose of this course is to provide the most fundamental knowledge and programming skill sets to students so that they can understand the modern progress of AI/ML and how to apply AI/ML to supply chain management, glean data-oriented insights and develop actionable supply chain strategies. The course is structured as a combination of lectures, in-class case studies, and group projects. Students will understand the philosophy and history of AI and related information technology, develop data analysis and data visualization skills, and also get a practical introduction in machine learning (e.g., via the Python scikit-learn library) through supply chain-related case studies. Students are then expected to apply and demonstrate knowledge of machine learning and data science with a group project involving a real-life supply chain problem. Python (https://www.python.org/) will be introduced and used as the main platform and extant Python packages will be employed as tools in these case-studies and group projects. The major learning approach of this course is through case-studies (in-class) and group projects (after-class).

This course builds upon academic SCM learnings by working on "real life" supply chain management projects requested by our Rutgers Center for Supply Chain Management Advisory Board companies and corporate partners. Students in this course must identify and understand the key issues, formulate models, complete analyses, and apply SCM course learnings to solve real-world problems. Faculty members whose expertise lies in a particular area are available to assist students with complexities of the projects. The projects change each semester depending on the current requirements of the clients, but always focus on specific issues within the supply chain. Client visits may be included to better understand the project scope and work with the company executives. The culmination of the project will be a formal presentation to the client's SCM executives and management team along with delivery of a final report. The presentation and report will include the team's approach, data analysis, findings and recommendations.

Prerequisite: Operations Analysis 

Properly addressing risks and facing possible disruptions are of primary importance to supply chain management. With the wake of high-consequence disruptive events, risk identification and disruption response activities have become ever more critical. The objective of the course is to provide an overview of key supply chain risk areas, particularly with the proliferation of outsourcing, use of information technology and global logistics. Equally important is how companies are managing the preparation, mitigation and response strategies to major disruptive events. Topics covered include science of catastrophes, vulnerability and threat assessments, resources and capabilities identification/integration, basic crisis management, contingency planning, disaster recovery and business continuity in supply chain settings. Scenario-based experiments (table-top exercises) will provide mock situations where students will make decisions on how to handle supply chain disruption. Case-based studies will be used to provide hands-on learning to illustrate the issues discussed in lectures.

Business intelligence (BI) is a set of technologies and processes that allow people at all levels of an organization to access, interact with and analyze data. In a data-rich business environment, BI can help a management team to operate efficiently, discover new market opportunities and improve business performance. This course focuses on data science techniques, analytical toolboxes and business applications in supply chain and marketing management. The course is structured as a combination of lectures, in-class case studies and group projects. All data analysis, optimization and simulation models are implemented in R (https://cran.r-project.org/ and https://www.rstudio.com/). R is a powerful, extensible and free programming language, which is gaining popularity for data scientists and business analysts. Students are expected to learn how to integrate BI with supply chain and marketing management, improve their data/analytical skills and deepen their knowledge of supply chain and marketing science from a quantitative perspective.

Prerequisites: Operations Analysis 

There is global experience and examples that show how sustainability criteria in the 'upstream' supply chain management and procurement process. Corporations can both improve environmental performance, while addressing ethics, social regeneration and economic concerns (e.g. the 'triple bottom-line'). This course will allow students to participate in applied research to explore the application of environmentally responsible supply chain principles which includes: designing supply chain management and procurement schemes which address environmental, social and ethical considerations in organizational policy development as well as the procurement process. Research themes may include: the public and private supply chain management and procurement process, green purchasing process, contract design, procurement which promotes low carbon emission considerations and zero waste (avoidance and minimization), social and economic regeneration, civic infrastructure policy, e-procurement applications, and cost cutting measures derived from life cycling costing modeling. The goal is to provide students with different experiences to examine environmental management from a supply chain management perspective.

Lean six sigma is an application of the quantitative six sigma quality management techniques within a lean enterprise. The goal is to create an efficient organization that continuously reduces waste and operates at the most efficient levels possible. In addition to covering the fundamentals of Lean and Six Sigma, this course will equip students with other important tools and strategies to improve the performance of business processes. Students will practice solving business problems and improving processes through case studies, team exercises and simulations, self-assessments, and guest lectures. Topics covered will include: six sigma improvement methodology and tools, lean manufacturing tools and approaches, dashboards and other business improvement techniques. Students will also gain an understanding of: the strategic importance of business improvement, the need for fact based management, the significance of change management, and how to deploy these tools in different parts of the value chain.

Prerequisite: Operations Analysis

Global Logistics Management is designed to provide students with an understanding of the strategic and tactical elements of logistics management. This course will examine the forward and reverse forms of transportation and storage for supply chain management. In addition to studying transportation modal choices, logistics and transportation infrastructure in the U.S. and around the world will be discussed. Other relevant topics will include cross-docking, reverse logistics tactics, multi-modal freight operations, high-tech automated warehousing and order delivery and current topics in the logistics industry. We will take a total systems approach to the management of all those activities involved in the forward and reverse movement and storage of products and related information through the supply chain. The teaching method will be a combination of case analysis, lecture and class discussion. Also, guest executives will discuss how they created and managed logistics innovation.

This course introduces trends, strategies, techniques, and best practices to improve unit, organizational, and integrated delivery system performance by applying key concepts from operations and supply chain management to the healthcare context. The first half of the semester focuses on the value-based purchasing programs including cost/efficiency, patient outcomes, patient safety, patient experience, and clinical processes. The second half of the semester focuses on service components including vertical integration and professional services outsourcing, service process design, quality improvements, healthcare supply chain management, project management, and healthcare analytics. The objective is to effectively manage information, material and financial exchanges for healthcare provider organizations to improve the quality of services and efficiency.

Introduces statistics as applied to managerial problems. Emphasis is on conceptual understanding as well as conducting statistical analyses. Students learn the limitations and potential of statistics, gain hands-on experience using Excel, as well as comprehensive packages, such as SPSS®. Topics include descriptive statistics, continuous distributions, confidence intervals for means and proportions, and regression. Application areas include finance, operations, and marketing. Introduces the basic concepts of model building and its role in rational decision making. Knowledge of specific modeling techniques, such as linear and nonlinear programming, decision analysis, and simulation, along with some insight into their practical application is acquired. Students are encouraged to take an analytic view of decision making by formalizing trade-offs, specifying constraints, providing for uncertainty, and performing sensitivity analyses. Students form groups to collect and analyze data, and to write and present a final report.