Introduction
The Department of Transportation, Logistics, and Finance offers a Master's degree in Supply Chain Management (MSCM). The degree is awarded through the College of Business in collaboration with the Upper Great Plains Transportation Institute to provide high-quality graduate programs for students.
The program takes an interdisciplinary approach to transportation and logistics and attracts students with a multitude of backgrounds. The online MSCM program targets aspiring logisticians, industry professionals, military officers, and DOD civilians who want to meet the logistical challenges of the 21st century. A wide range of career opportunities exists in the sectors of the logistics industry, including logistics and supply chain management, operations management, purchasing and demand management, emergency management, consulting, retail, and many more.
Core Competencies
The uniqueness of the Master of Supply Chain Management program is reflected in its core competencies, which are a direct derivative of the Army's National Logistics Curriculum and private industry needs. The following core competencies define a framework for expected outcomes and curricula:
Supply chain management in the military and private sectors
Global supply chain management and the design of international logistics systems
Change management in a turbulent environment
Hands-on experience with SAP software, including data analytics
Spreadsheet modeling for transportation analysis and planning for logistics
Crisis analysis and rapid logistical response
Logistics support for homeland security
Admission Requirements
The Master of Supply Chain Management program is open to qualified graduates of universities and colleges of recognized standing. To be admitted with full standing, the applicant must:
Hold a baccalaureate degree from an educational institution of recognized learning with a minimum grade point average (GPA) of 3.0 or equivalent. For those with GPAs of 2.99 or less, the applicant must also submit a GMAT/GRE score to be considered for acceptance;
Have shown the potential to undertake advanced study as evidenced by prior academic performance and has stated interest in logistics;
Submit official transcripts;
Submit a two-page resume;
Submit a one-page "Letter of Intent" outlying your reasons for pursuing the Master of Supply Chain Management degree;
Submit three letters of recommendation;
Submit an online application through the NDSU Graduate School website;
International applicants whose first language is not English and who do not possess a U.S. bachelor's degree or higher are subject to additional requirements when they apply for admission. They must meet the minimum requirements on measures of general English language proficiency. The accepted measures of language proficiency are the TOEFL ibT 71 and IELTS 6.
Students who do not meet all requirements for admission or have deficiencies in prerequisite course work, but show satisfactory potential for graduate study, may be admitted conditionally. The conditional status may be changed to full graduate standing after the first or second semester of study, based on the student's academic performance.
Degree Requirements
The Master of Supply Chain Management (MSCM) is an online graduate program and is a non-thesis degree. A minimum of 30 credits is required for the MSCM and must be completed using the core courses below. Students will participate in a multitude of interdisciplinary courses that will enhance and develop their supply chain skills, research abilities, and their capacity to apply them in real-world situations. An overall GPA of 3.0 or higher must be maintained to remain in good academic standing.
Core Courses
(≥ 30 credits)
TL 711 Logistics Systems
3
TL 715 Introduction to ERP
3
TL 719 Crisis Analysis and Homeland Security
3
TL 721 International Logistics Management
3
TL 723 Advanced Supply-Chain Planning Across the Enterprise
3
TL 725 ERP Configuration
3
TL 727 Organizational Change Management
3
TL 731 Logistics Decision Analysis
3
TL 733 Case Studies in Logistics
3
TL 735 Practical Data Analytics
3
