MS-SCM Business Intelligence track

Explores supply chain management topics including environmental, project and supply chain processes. Additionally, covers processes in the areas of new product introduction development; quality control; TQM (Total Quality Mgt).

Understanding how organizations make use of Business Intelligence (BI) to gain a sustainable competitive advantage. Builds the foundations for evidence-based managerial decision making. Covers technologies for data warehousing and data mining from a managerial perspective. Covers contemporary topics such as real-time BI, business analytics, and business performance management with the help of case studies, audio-video content, guest speakers, online forums to generate creative thinking and discussion.

Applies principles, philosophies and processes of supply management to facilitate the continuous improvement and strategic design of an organization's supply management system on a global basis. Focuses on topics like performance management and analytics, project management and governance and finance. Provides a comprehensive understanding of supply management and its impact on the organization.

Covers decision modeling approaches for supply chain management such as optimization, simulation and decision analysis. Focuses on technology enablement, performance management and analytics, and strategy change and management. Emphasizes modeling using spreadsheet-oriented approaches. Additionally, focuses on financial spreadsheet analysis and its use in optimization.

The best descriptor of sustainability is “dynamic.” This creates a great deal of both uncertainty and opportunity: uncertainty about what is expected by regulators, consumers and watchdog groups. Opportunity to innovate and develop or use new technologies, leverage new markets, and alter business processes for the better. Our focus will always be on profitably increasing a firm’s sustainability and social responsibility. The course is largely a seminar format relying primarily on discussion of cases and articles.

Covers theories and practices of modern logistics management within a market-driven supply chain. Begins with an outline of reasons why some operations are not efficient, then introduces management tools to improve efficiency and responsiveness followed by application of analytical tools to evaluate the current logistic management practices. Topics include logistics strategy, demand management, distribution and warehouse management, distribution/warehouse design and location decisions, transportation and delivery frequency, reverse logistics, humanitarian logistics and responsive supply chains.

Strategic design and development of supply chains. Focus on cost-management tools applied to supply chain design and supplier management.

Provides a comprehensive understanding of project management with particular focus on planning, scheduling and control of business processes. Emphasizes understanding team dynamics and risk analysis, as well as program management tools, governance and enabling of technology to drive supply chain processes.

Studies management of the conversion of raw materials to finished goods including scheduling, work-in-process inventory management, and postponement/customization. Students gain a deeper understanding of the integrated supply chain of plan, source, make, deliver and return.

Explores the supply management process of selecting, developing and executing of appropriate sourcing strategies and processes. Covers the importance or driving cost, quality and relationship management, as well as organizational change impacts on supply management of a business.

Ensuring the foundational understanding of contextualized analytics within the business enterprise continuum by covering how data flows and is managed across the landscape of enterprise business processes.

Charting a roadmap for data-driven decision making and getting a practical understanding of how IT tools and techniques can allow managers to extract predictive analytics and patterns from primarily numeric data.

Provides a survey of concepts, structure and analytical tools that lay the foundation for employing quantitative techniques (descriptive and predictive) to gain insights that help decision makers make better decisions. Familiarizes students with descriptive statistics, probability and probability distributions, confidence intervals, hypothesis testing, linear regression, logistic regression and forecasting methods.

Addresses the use of analytics tools and techniques to enhance the ability of quality management approaches to improve processes. Introduces modern quality management approaches including six sigma and design for six sigma. Covers the define, measure, analyze, improve and control (DMAIC) improvement cycle: the core process used to drive six sigma projects. DMAIC refers to a data-driven improvement cycle used for improving, optimizing and stabilizing business processes and designs. Provides an analytics roadmap to help users work through the DMAIC problem-solving process.

Preparation of a supervised applied project that is a graduation requirement in some professional majors.

Focuses on a system designed to help students take an active role in their career development through self-reflection, skills and values assessment, market research and identifying potential roadblocks to obtaining an internship or full-time role after graduation. Also introduces the concept of a personal narrative and provides experiential learning opportunities to refine their own personal narrative and understand how to fine-tune and tailor it for a variety of career applications.