Global Supply Chain ManagementGraduate Certificate

What’s driving every aspect of this field? Data. And how to analyze it.

Data-driven supply chain management, also known as supply chain analytics, is the only way to manage the ever-expanding global reality confronting us today — that e-commerce is leaving brick and mortar businesses in the dust and requires an entirely new set of skills to keep the links in the supply chain in good working order.

The Global Supply Chain Management graduate certificate prepares students for positions in the fields of strategic supply chain management, process improvement and quality, and supply chain risk management. Students will gain a solid understanding of global supply chain management, as well as the analytical and managerial framework and tools necessary to be successful in a variety of business environments.

Upon completion of the program, graduates will be able to:

  • Explain how the key functional areas of supply chain management interact within the overall supply chain network.
  • Apply statistics and quality management frameworks to analyze the efficiency of supply chain for quality improvement.
  • Mitigate risk in the supply chain in order to respond to supply chain disruptions.
  • Construct and utilize supply chain performance dashboards.

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Required Courses
  • Global Supply Chain Management (3 Credits)

    This course discusses the managerial activities required to provide the right product or service in the right quantity, with the right quality from the right source at the right time for the right price, through the use of global supply chains. The course focuses on contemporary strategic issues that affect both large and small corporations. Topics include key supply chain metrics, basic tools for supply chain management, procurement and outsourcing decisions, supplier selection and relationship management, logistics, and supply chain integration and coordination for the highest customer service.

  • Managing Quality in the Supply Chain (3 Credits)

    This course introduces concepts and principles of business process improvement, and quality assurance in organizations. It examines the primary tools and methods used to monitor, measure, improve, and control business processes, and quality from a holistic supply chain perspective. Topics include statistical process control, Lean Six Sigma principles, and continuous improvement.

  • Power BI and Dashboarding (3 Credits)

    This course introduces key concepts, skills, and methods in Business Analytics for data-driven decision making in organizations. Using Microsoft Power BI, the course trains the student in dashboarding, and Power BI’s quantitative, and computational capabilities across various business domains. The mix of topics includes data access, data wrangling, visualization, and machine learning via R programming language in Power BI.

  • Risk Management (3 Credits)

    This course will provide an understanding and application of the methods for evaluating, analyzing, and managing risk within organizations. Students will learn to apply multiple risk-management tools to make high-quality decisions for balancing corporate risk and reward tradeoffs. Financial risk topics, enterprise risk topics, and cybersecurity risk topics will be explored to prepare students to see how risk management is an essential element of any firm’s strategic decision-making. Students are exposed to the role of the firm in crisis response as well as the systems and interactions necessary to assure continuous operations.

Admissions Requirements

As this is a Graduate level certificate, applicants must hold a minimum of a Bachelors degree to apply. While it is encouraged that applicants have a Bachelors degree in a scientific discipline, all disciplines will be considered.

For application – a resume, transcripts of former degree(s), and a brief statement of purpose are required. The GRE and letters of recommendation are not required.

Tuition and Fees

Click here to view our most-updated graduate tuition and fees for each academic year.

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