Online MS in Supply Chain Management—Analytics

At a Glance

Completion Time

8–16

Months

Credits Required

Tuition

$27,204–$28,956

Part-Time*

*Based on 2025–2026 Boston University tuition and fees. Merit scholarship may reduce cost.

Get an Edge through Supply Chain Analytics

The online MS in Supply Chain Management concentration in Analytics will prepare you to apply descriptive, predictive, and prescriptive analytical methods to supply networks using R programming language and other specialized programming languages. Focused on the needs of supply chain decision-makers who must navigate the ever-changing and increasingly complex networks of facilities, partners, suppliers, and other domestic and international stakeholders, the MSSCM Analytics concentration will prepare you to utilize mathematical modeling and optimization theory by choosing the appropriate quantitative tools to support supply chain operations, while applying systematic process-oriented approaches to evaluate supply chain performance using statistical modeling with Six Sigma principles and techniques.

By applying analytics to operations such sourcing, manufacturing, warehousing, and transportation, supply chain managers can improve efficiency in their organizations. The ability to analyze data also provides a clearer understanding of risk, increased accuracy in planning, enhanced end-to-end visibility, and a means of achieving a leaner supply chain. The Supply Chain Management Analytics concentration will examine decisions concerning the determination of supply chain strategies, analysis and mitigation of supply chain risks, management of performance, quality control, inventory and capacity management, and all other operations-related analyses will be stressed. Analytical techniques include statistical analysis, probabilistic decision- tree analysis, control charting, process capability analysis, and Monte Carlo simulation and optimization techniques.

The MS in Supply Chain Management, Analytics Concentration is also available on campus in Boston. Learn more.

Curriculum

A total of 32 units is required.

Students must complete the core courses and Analytics concentration requirements. Students who take MET AD 734 and meet certain performance standards will earn Six Sigma Green Belt certification. Students who take both MET AD 519 and MET AD 734 and meet certain performance standards will earn a Lean Six Sigma Green Belt.

Core Courses

(Four courses/16 units)

MET AD 519 Operations and Process Analysis

4 credits.

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.

Section A1, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Saluti	Independent	M	06:00:00 PM–08:45:00 PM	HAR 410

Section A4, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Maleyeff	Independent	T	12:30:00 PM–03:15:00 PM	SHA 206

Section O1, FALL 2025 Sep 2nd to Oct 20th
Instructor	Type	Days	Times	Location
Gunes Corlu	Independent	ARR	12:00:00 AM–12:00:00 AM

MET AD 632 Financial Concepts

4 credits. Fall and Spring

Critical Thinking
Quantitative Reasoning II

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.

Section A1, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
McGue	Independent	M	02:30:00 PM–05:15:00 PM	MET 101

Section A2, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
McGue	Independent	T	06:00:00 PM–08:45:00 PM	MET 122

Section A3, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Vizek	Independent	W	06:00:00 PM–08:45:00 PM	MET 122

Section A4, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Vizek	Independent	F	11:15:00 AM–02:00:00 PM	SHA 206

Section A5, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Mendlinger	Independent	T	06:00:00 PM–08:45:00 PM	PSY B53

Section A6, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Vizek	Independent	R	06:00:00 PM–08:45:00 PM	CAS 315

Section O2, FALL 2025 Oct 28th to Dec 15th
Instructor	Type	Days	Times	Location
Ge	Independent	ARR	12:00:00 AM–12:00:00 AM

MET AD 680 Global Supply Chains

4 credits. Fall and Spring

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.

Section A1, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Mayer	Independent	T	06:00:00 PM–08:45:00 PM	CAS 218

Section A2, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Gunes Corlu	Independent	R	12:30:00 PM–03:15:00 PM	MET 122

Section O1, FALL 2025 Sep 2nd to Oct 20th
Instructor	Type	Days	Times	Location
Mayer	Independent	ARR	12:00:00 AM–12:00:00 AM

MET AD 715 Quantitative and Qualitative Decision-Making

4 credits. Fall and Spring

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.

Section A1, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Dickson	Independent	M	02:30:00 PM–05:15:00 PM	CDS 262

Section A3, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Ritt	Independent	M	02:30:00 PM–05:15:00 PM	CDS 264

Section A4, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Dickson	Independent	T	06:00:00 PM–08:45:00 PM	PHO 201

Section A5, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Zlatev	Independent	W	02:30:00 PM–05:15:00 PM	EPC 206

Section A7, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Parzen	Independent	R	12:30:00 PM–03:15:00 PM	FLR 123

Section A8, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Valath Bhuan Das	Independent	R	06:00:00 PM–08:45:00 PM	CGS 527

Section O2, FALL 2025 Oct 28th to Dec 15th
Instructor	Type	Days	Times	Location
Zlatev	Independent	ARR	12:00:00 AM–12:00:00 AM

Operations and Process Analysis (MET AD 519) replaces Operations Management: Business Process Fundamentals (MET AD 605). Students who have already taken AD 605 DO NOT need to take AD 519.

Concentration Requirements

(Four courses/16 units)

Note that MET AD 571 is a prerequisite to MET AD 616.

MET AD 571 Business Analytics Foundations

4 credits. Fall and Spring

Prerequisite: METAD100 Pre-Analytics Laboratory. 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.

Section A2, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Padalkar	Independent	M	06:00:00 PM–08:45:00 PM	CAS 324

Section A5, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Parzen	Independent	W	02:30:00 PM–05:15:00 PM	CDS 262

Section A6, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Ritt	Independent	W	02:30:00 PM–05:15:00 PM	MET 101

Section A7, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Page	Independent	R	06:00:00 PM–08:45:00 PM	PSY B53

Section O1, FALL 2025 Sep 2nd to Oct 20th
Instructor	Type	Days	Times	Location
Rabinovich	Independent	ARR	12:00:00 AM–12:00:00 AM

MET AD 616 Enterprise Risk Analytics

4 credits. Fall and Spring

Prerequisite: MET AD 571. - The course offers an overview of the key current and emerging enterprise risk analytical approaches used by corporations and governmental institutions and is focused on understanding and implementing the enterprise risk management framework on how to leverage the opportunities around a firm to increase firm value. The major risk categories of the enterprise risk management such as financial risk, strategic risk, and operational risk will be discussed and risk analytics approaches for each of these risks will be covered. Students will learn how to use interlinked data inputs, analytics models, business statistics, optimization techniques, simulation, and decision-support tools. An integrated enterprise risk analytics approach will be demonstrated with examples from different functional areas of the enterprise. Python, R, SQL, and Power BI software are used in this course.

Section A2, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Yu	Independent	T	06:00:00 PM–08:45:00 PM	PHO 203

Section A3, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Yu	Independent	R	12:30:00 PM–03:15:00 PM	FLR 121

Section O2, FALL 2025 Oct 28th to Dec 15th
Instructor	Type	Days	Times	Location
Yu	Independent	ARR	12:00:00 AM–12:00:00 AM

MET AD 734 Six Sigma Quality Methods

4 credits. Fall and Spring

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.

Section A1, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Maleyeff	Independent	T	06:00:00 PM–08:45:00 PM	MCS B29

And one course selected from the following:

MET AD 510 Mathematics and Statistics in Management

4 credits. Fall and Spring

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.

Section A1, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Ritt	Independent	R	12:30:00 PM–03:15:00 PM	MCS B31

MET AD 654 Marketing Analytics

4 credits. Fall and Spring

Prereq: METAD 571. Become familiar with the foundations of modern marketing analytics and develop your ability to select, apply, and interpret readily available data on customer purchase behavior, new customer acquisition, current customer retention, and marketing mix optimization. This course explores approaches and techniques to support the managerial decision-making process and skills in using state-of-the-art statistical and analytics tools. Students will have an opportunity to gain a basic understanding of how transaction and descriptive data are used to construct customer segmentation schemas, build and calibrate predictive models, and quantify the incremental impact of specific marketing actions. Python, R, SQL, and Power BI software are used in this course.

Section A1, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Page	Independent	W	02:30:00 PM–05:15:00 PM	KCB 104

MET AD 688 Cloud Analytics for Business

4 credits. Fall and Spring

Prerequisites: AD571. - Explore web analytics, text mining, web mining, and practical application domains. The web analytics part of the course studies the metrics of websites, their content, user behavior, and reporting. The Google Analytics tool is used for the collection of website data and doing the analysis. The text mining module covers the analysis of text including content extraction, string matching, clustering, classification, and recommendation systems. The web mining module presents how web crawlers process and index the content of websites, how search works, and how results are ranked. Application areas mining the social web and game metrics will be extensively investigated. R, SQL, and Power BI software are used in this course.

Section A1, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Padalkar	Independent	M	02:30:00 PM–05:15:00 PM	EPC 208

Section O1, FALL 2025 Sep 2nd to Oct 20th
Instructor	Type	Days	Times	Location
Padalkar	Independent	ARR	12:00:00 AM–12:00:00 AM

MET AD 690 Supply Chain Logistics

4 credits. Fall and Spring

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.

Section A1, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Mayer	Independent	W	06:00:00 PM–08:45:00 PM	CGS 527

MET AD 699 Data Mining for Business Analytics

4 credits. Fall and Spring

Prerequisites: AD571 Enterprises, organizations, and individuals are creating, collecting, and using a massive amount of structured and unstructured data with the goal of converting the information into knowledge, improving the quality and the efficiency of their decision-making process, and better positioning themselves in the highly competitive marketplace. Data mining is the process of finding, extracting, visualizing, and reporting useful information and insights from both small and large datasets with the help of sophisticated data analysis methods. It is part of business analytics, which refers to the process of leveraging different forms of analytical techniques to achieve desired business outcomes through requiring business relevancy, actionable insight, performance management, and value management. The students in this course will study the fundamental principles and techniques of data mining. They will learn how to apply advanced models and software applications for data mining. Finally, students will learn how to examine the overall business process of an organization or a project with the goal of understanding (i) the business context where hidden internal and external value is to be identified and captured, and (ii) exactly what the selected data mining method does. Python, R, SQL, and Power BI software are used in this course.

Section A2, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Athaide	Independent	R	06:00:00 PM–08:45:00 PM	PSY B55

Section O2, FALL 2025 Oct 28th to Dec 15th
Instructor	Type	Days	Times	Location
Athaide	Independent	ARR	12:00:00 AM–12:00:00 AM

MET AD 804 Capstone Project for Supply Chain Management

4 credits. Fall and Spring

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.

Section A1, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Courtney	Directed Study	R	06:00:00 PM–08:45:00 PM	FLR 123

Dates & Deadlines

View BU MET’s academic calendar for online programs, including important dates and deadlines.

Application Requirements

Learn about application requirements for BU MET graduate degree and certificate programs.

How You Benefit from a
Boston University Education

A BU credential can help lay the foundation for career advancement and personal success.

Benefit from a 24:1 student-to-instructor ratio.
Work closely with highly qualified faculty who draw from active research and substantial professional achievements in areas such as global supply chains, operations management, logistics management, quality and production management, enterprise risk analytics, international business and trade, e-commerce, data mining, econometrics, and more.
Collaborate with professors and industrial practitioners in BU MET’s Decision Sciences Research Laboratory, while applying your analytical skills to solve current problems facing industrial organizations.
Experience BU’s advanced pedagogy in the online environment, such as video conferencing, live lectures and seminars, proctored assessments, access to proprietary software applications within virtual labs and cloud servers/technologies, creative learning, teamwork, and competitive games offered with the help of advanced business simulations.
Gain access to free, self-paced laboratories that prepare you for the analytical curriculum, such as MwAM: Mathematics with Applications in Management and SwAM: Statistics with Applications in Management.

All graduate students are automatically considered for merit scholarships during the application process and nominated based on eligibility. Learn more.

Rankings & Accreditations

Accredited member of AACSB International

The Association to Advance Collegiate Schools of Business (through BU’s Questrom School of Business)

Six Sigma Certification

MET AD 605 and MET AD 734 may qualify you for Green Belt Training accredited by the Council for Six Sigma Certification

Graduate with Supply Chain Expertise

Students who complete the Supply Chain Management master’s degree concentration in Analytics will be able to:

Demonstrate the ability to use interlinked data inputs, analytics, and systems to support decision-making in a supply chain that is geographically dispersed and culturally diverse.
Apply descriptive, predictive, and prescriptive analytical methods to supply networks, including optimization, simulation, forecasting, risk analysis, queuing models, using R programming language and other specialized programming languages.
Apply a systematic process-oriented approach to evaluating supply chain quality using statistical modeling with Six Sigma principles and techniques.
Utilize financial statements, create performance metrics, develop inspection systems, and evaluate performance in manufacturing, service, and business processes using statistical calculations and displays.
Utilize mathematical modeling and optimization theory by choosing the appropriate quantitative tools to support supply chain operations.

Supply chain vulnerability is a concern for 41% of business leaders, many of whom are investing in strategies to de-risk their supply chains.

Source: Capgemini Research Institute, 2024

“I am constantly using concepts from the MS in Supply Chain Management program in my current job as a supply chain manager.” Read more.

Scott Miller (MET’19)
Senior Supply Chain Manager, The Willamette Valley Company LLC
MS, Supply Chain Management

Advance Your Career

BU MET’s Supply Chain Management master’s prepares you for a wealth of different roles, such as director of operations, quality assurance manager, logistics supervisor, distribution manager, director of procurement, sourcing manager, operations analyst, and supply chain manager, among others.

Recent graduates have found job opportunities and career paths at companies such as:

ABclonal Technology
Aflac
Apple
Collins Aerospace
Construction Specialties
Dune Sciences
Essendant
Henkel
iBasis

Overstock.com
Philips
Pratt & Whitney
Raytheon
Straumann Group
The LEGO Group
Walmart
Willamette Valley Company

Take Advantage of Career Resources at BU MET

You will find the support you need in reaching your career goals through MET’s Career Development office, which offers a variety of job-hunting resources, including one-on-one career counseling by appointment for online students. You can also take advantage of tools and resources available online through BU’s Center for Career Development.

Supply Chain Management Faculty

Can an Gunes Corlu

Associate Professor, Administrative Sciences

Coordinator, Supply Chain Management

12-5730-CORLU-008 9/26/12 1:49:12 PM -- Boston, Massachusetts..MET Faculty Portrait of Canan Gunes Corlu..Photo by: Vernon Doucette for Boston University Photography

John Maleyeff

Associate Professor of the Practice, Administrative Sciences

Coordinator, Enterprise Risk Management

Peter Mayer

Lecturer, Administrative Sciences

View All Faculty

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Online Master of Science in Supply Chain Management, Analytics Concentration

At a Glance

Get an Edge through Supply Chain Analytics