Supply Chain Analytics (Coursera)

Offered by Rutgers University,
Supply Chain Analytics (Coursera)

Welcome to Supply Chain Analytics - the art and science of applying data analytics to assess and improve supply chain performance! A supply chain is a complex system with conflicting objectives of cost efficiency and customer satisfaction. Supply chain management is becoming increasingly data driven. Through the real-life story and data of a major US telecommunication company, you will learn the analytics tools / skills to diagnose and optimize a supply chain.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

Upon completion of this course, you will be able to:

  1. Use data analytics to assess the impact of various strategies on all aspects of a supply chain, from inventory, shipping, to warehouse order fulfillment, store operations and customer satisfaction.
  2. Customize the supply chain strategy by product to improve the overall cost efficiency without sacrificing customer service.
  3. Obtain hands-on experience on the application and financial impact of analytics in integrated supply chain and logistics planning.

VASTA (name disguised) is a major wireless carrier in the US selling cell phones through a national network of retail stores. Recently, it wrote off a huge amount of obsolete inventory each year and was suffering a significant cost inefficiency in an increasingly stagnant market. VASTA must assess the competitive environment, and renovate its supply chain to stay competitive. At the end of this course, you will help VASTA save $billions on supply chain cost and retain its leadership in a stagnant and saturated market.
I hope you enjoy the course!
This course is part of the Supply Chain Analytics Specialization.

What You Will Learn

  • Use data analytics to assess the impact of various strategies on all aspects of a supply chain.
  • One size does not fit all - customize supply chain strategies by product.
  • Conduct a competitive analysis and benchmarking to assess competitive environment and identify business opportunities.
  • Obtain hands-on experience on the application and financial impact of analytics in integrated supply chain and logistics planning.

Syllabus

Welcome!
Welcome to Supply Chain Analytics! In this week, I shall first tell you the story of VASTA and the challenge it faces, then provide an overview of the course, learning outcomes and weekly topics. You will then learn competitive analysis and benchmarking to assess a firm’s competitive environment and identify the business opportunity.

General Principles and Intuition
In Week 2, you will understand the general principles of supply chain planning, and develop intuitions on the benefits and concerns of the push / pull strategies. The intuitions and insights will guide you in the quantitative supply chain analysis in Week 3.

Data Collection, Cost Estimation and Supply Chain Analytics
In Week 3, you will learn what data to collect, how to estimate various types of costs, and how to use data analysis to assess the impact of various strategies on different aspects of a supply chain.

Customer Experience, Implementation and Project
In Week 4, you will learn how to assess the impact of the strategies on customer experience. You will get hands-on experience on the implementation and financial impact of supply chain analytics in a real-life example. You will complete this course by conducting a project to analyze the geographic difference for the strategies.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Global Statistics - Composite Indices for International Comparisons (Coursera) Coursera
University of Geneva

Global Statistics - Composite Indices for International Comparisons (Coursera)

In this course on global statistics, offered by the University of Geneva jointly with the ETH Zürich KOF, you will learn the general approach of constructing composite indices and some of resulting problems. We will discuss the technical properties, the internal structure (like aggregation, weighting, stability of time series), the primary data used and the variable selection methods. These concepts will be illustrated using a sample of the most popular composite indices. We will try to address not only statistical questions but also focus on the distinction between policy-, media- and paradigm-driven indicators.

Nov 23rd 2026
5-12 Weeks
Accounting Analysis I: Measurement and Disclosure of Assets (Coursera) Coursera
University of Illinois at Urbana-Champaign

Accounting Analysis I: Measurement and Disclosure of Assets (Coursera)

In this course, we will begin our review of key asset categories underlying the Balance Sheet concepts that were introduced in the previous course. We will begin our trek down the Balance Sheet by reviewing cash and receivables, which are normally the two assets listed first. We will continue our trek down the Balance Sheet by looking at inventory and long-Lived Assets, which are normally two of the largest asset values. We will review the measurement and reporting issues involving Inventories and the corresponding cost of goods sold expense in the Income Statement.

Nov 23rd 2026
5-12 Weeks
Gestión del análisis de datos (Coursera) Coursera
Johns Hopkins University

Gestión del análisis de datos (Coursera)

This one-week course describes the process of analyzing data and how to manage that process. We describe the iterative nature of data analysis and the role of stating a sharp question, exploratory data analysis, inference, formal statistical modeling, interpretation, and communication. In addition, we will describe how to direct analytic activities within a team and to drive the data analysis process towards coherent and useful results.

Nov 16th 2026
1 Week
Population Health: Predictive Analytics (Coursera) Coursera
Leiden University

Population Health: Predictive Analytics (Coursera)

Predictive analytics has a longstanding tradition in medicine. Developing better prediction models is a critical step in the pursuit of improved health care: we need these tools to guide our decision-making on preventive measures, and individualized treatments. In order to effectively use and develop these models, we must understand them better. In this course, you will learn how to make accurate prediction tools, and how to assess their validity. First, we will discuss the role of predictive analytics for prevention, diagnosis, and effectiveness. Then, we look at key concepts such as study design, sample size and overfitting.

Nov 23rd 2026
4 Weeks
Supply Chain Principles (Coursera) Coursera
Georgia Institute of Technology

Supply Chain Principles (Coursera)

This course will provide a solid understanding of what a supply chain is all about. The course: provides an introduction to Supply Chain; leverages graphics to promote the Integrated Supply Chain model; emphasizes understanding the Extended Supply Chain; presents a holistic approach – Incorporating People, Process, and Technology; calls-out industry-specific supply chain; leverages discussions, videos, quizzes, and questions for consideration; provides awareness of career path opportunities; presents emerging and futuristic trends in supply chain and given that at GT we are focused on developing what’s next in the world, we include Discussion of emerging and futuristic trends in supply chain. There is very little math involved in this course – so don’t worry at all about your math skills.

Nov 23rd 2026
5-12 Weeks
Fundamentos de estadística aplicada (Coursera) Coursera
Universidad de los Andes

Fundamentos de estadística aplicada (Coursera)

El curso está orientado a profesionales de diferentes campos, que estén interesados en adquirir conceptos fundamentales de estadística aplicada. El contenido del curso será particularmente útil para profesionales que estén interesados en adelantar estudios de postgrado en ingeniería, administración o economía, entre otras profesiones, y que requieran de una adecuada fundamentación en estadística.

Nov 23rd 2026
4 Weeks
Data Processing Using Python (Coursera) Coursera
Nanjing University

Data Processing Using Python (Coursera)

This course is mainly for non-computer majors. It starts with the basic syntax of Python, to how to acquire data in Python locally and from network, to how to present data, then to how to conduct basic and advanced statistic analysis and visualization of data, and finally to how to design a simple GUI to present and process data, advancing level by level.

Nov 23rd 2026
5-12 Weeks
Bioinformatic Methods I (Coursera) Coursera
University of Toronto

Bioinformatic Methods I (Coursera)

Large-scale biology projects such as the sequencing of the human genome and gene expression surveys using RNA-seq, microarrays and other technologies have created a wealth of data for biologists. However, the challenge facing scientists is analyzing and even accessing these data to extract useful information pertaining to the system being studied. This course focuses on employing existing bioinformatic resources – mainly web-based programs and databases – to access the wealth of data to answer questions relevant to the average biologist, and is highly hands-on.

Nov 16th 2026
5-12 Weeks
Supply Chain Management for E-commerce (Coursera) Coursera
Starweaver

Supply Chain Management for E-commerce (Coursera)

Immerse yourself in the dynamic realm of e-commerce supply chains with our course, "Supply Chain Management for E-commerce." Designed for emerging entrepreneurs, small business owners, and career switchers, this immersive journey equips learners with comprehensive insights. From foundational supply chain components to the strategic integration of technology and sustainability, participants will gain practical knowledge to navigate challenges and optimize operations in the e-commerce realm.

Nov 23rd 2026
1 Week
Bayesian Statistics: Mixture Models (Coursera) Coursera
University of California, Santa Cruz

Bayesian Statistics: Mixture Models (Coursera)

Bayesian Statistics: Mixture Models introduces you to an important class of statistical models. The course is organized in five modules, each of which contains lecture videos, short quizzes, background reading, discussion prompts, and one or more peer-reviewed assignments. Statistics is best learned by doing it, not just watching a video, so the course is structured to help you learn through application.

Nov 16th 2026
5-12 Weeks