Flex MBA Specialization in Business Analytics & Risk Management
Add a specialization in Business Analytics and Risk Management.
How do business analysts make tough decisions when the stakes are high and they have limited data or precedent to benchmark against? Bolster your ability to make decisions when facing the unknown with the latest tools from the emerging field of analytics. The business analytics and risk management specialization is a quantitative program with a focus on business decisions and applications, rather than code writing. While earning your business analytics degree you'll cover the essentials of statistical analysis, spreadsheet models, and data analysis, and add electives to delve deeper into analytical tools or focus on the use of those tools in marketing or operations management. Graduate with the expertise to harness data and navigate uncertainty with confidence.
Business analytics and risk management curriculum highlights
Required courses to earn the specialization
BU.510.650 Data Analytics (2 Credits)
Gather, describe, and analyze data, using advanced statistical tools to support operations, risk management, and responses to disruptions. Analysis is done by targeting economic and financial decisions in complex systems that involve multiple partners. Topics include probability, statistics, hypothesis testing, regression, clustering, decision trees, and forecasting.
BU.520.650 Data Visualization (2 Credits)
This project-based course prepares students to make informed decisions based on data using descriptive-analytical techniques. Students will view examples from real-world business cases in which data visualization helps the decision makers to visualize, discover, and decode the hidden information from within the data, and to exploit such information for making educated decisions. We will use Tableau to import, clean, transform, analyze, visualize, and present data. As the course progresses, students will learn to work with Tableau features such as data connectors, data blending, data preparation, interactive dashboards, and calculations and functions. During the eight weeks of the course, students will collaborate with each other in small teams to analyze real-world datasets as well as design, build, and deliver interactive visualizations and dashboards.
Electives (must take at least three to earn the specialization)
BU.520.620 Advanced Business Analytics (2 Credits)
This course trains decision makers to function in the face of multi-dimensional uncertainty, through the development and use of optimization models. Mathematical abstractions are created which deal with issues including resource allocation, scheduling, pricing, and other responses to the realization of a variety of “known unknowns”. Topics include linear programming, dynamic programming, multi-criteria optimization, and non-linear optimization.
BU.132.601 Business Law (2 Credits)
A thorough working knowledge of the legal and regulatory environment in which businesses operate is essential for well-prepared business executives. This course provides an overview of the legal and regulatory environment affecting business in the United States. Topics include forms of business organization, contracts, torts and product liability, intellectual property, constitutional law business transactions, and discrimination and employment issues. Students are expected to utilize electronic library and Internet resources to complete assignments.
BU.610.705 Crisis Management (2 Credits)
In this course, we will examine the entire crisis management lifecycle – from prevention and preparedness through response, recovery, and mitigation – and consider the lifecycle’s principles and practices. We will identify and use the entire crisis management toolkit to address challenges faced by managers when organizations face any crisis, due to either external factors outside the organization’s control or internal control or strategic management failures. We will develop a complete crisis management plan, including tools and methods to identify potential crises, implement response and mitigation strategies to limit exposure, manage crisis response teams, and create communications to address stakeholder and public relation issues.
BU.450.760 Customer Analytics (2 Credits)
Immerse yourself in the modern practice of customer analytics. And learn how marketers and business analysts can improve decision making by leveraging scientific approaches in the analysis of big data. Leading analytical techniques and data structures are illustrated in the context of their most prominent applications – for example, predicting customer responses to marketing campaigns and managing customer churn. The class has a strong hands-on component, enabled by several in-class examples and group assignments (implemented on Microsoft Excel and the statistical language “R”). You are not expected to become expert programmers or statisticians, but you will acquire basic skills and knowledge to orchestrate an effective analytics strategy.
BU.330.780 Data Science and Business Intelligence (2 Credits)
This course introduces a set of fundamental principles and a framework that guide extracting business insights from data to generate competitive advantage. We will discuss how the ubiquity and massiveness of digital data and the application of business intelligence have changed competitive landscapes. The business intelligence techniques that will be covered in this course include data visualization, online social network and sentiment analysis (for user-generated content), and predictive analytics (e.g. classification and clustering), which are widely used in the real world. The topics and cases discussed in this course cover a wide range of fields, including marketing, finance, healthcare, and more. This course is not a statistics or computer programming course. The emphasis will be on applications and interpretations of the results from business intelligence techniques for making business decisions. Students will apply these techniques in hands-on exercises as we analyze strategic concepts, which will allow students to deepen their understanding of the fundamentals and the applicability of business intelligence.
BU.230.750 Financial Crises and Contagion (2 Credits)
What and when will the next financial crisis be? No one knows, but the past provides clues. This course takes students through the history of finance in the United States, with a focus on the last 100 years of financial bubbles, manias, and scandals, from the crash of 1929 to the thrift crisis of the 1980s; Enron and other accounting debacles; and the mortgage meltdown known as the Great Recession. Examining the upheavals is key to understanding how the landscape and laws of modern financial markets evolved and where they might be headed. With the Great Recession of 2007–2012, the United States experienced the biggest economic crisis and ensuing downturn since the crash of 1929 and Great Depression of the 1930s. While every boom-and-bust is unique, all share certain characteristics—most notably, the seemingly inexhaustible ability of humans to forget the lessons of financial history. This forgetfulness comes at great expense to society. This course provides a tour of the country’s major boom-and-bust-cycles, with a focus on last century, and particularly the last three decades, when such events became more numerous. After each debacle, laws and rules changed. Executives must know what those changes are and the reasoning behind them, but they also will have a competitive edge in recognizing future crises if they remember and understand the events underpinning those of the past.
BU.003.900 Global Immersion: United Kingdom - Navigating Through Crises (2 Credits)
Whether financial collapse, public health emergencies, infrastructure failure, or geopolitical tension, business leaders across all industries face a variety of risks that can quickly evolve into crises. Using recent events in both the United Kingdom and continental Europe as case studies, students in this course will sharpen their skills to manage effectively through a wide variety of challenging business situations. This course includes two pre-departure lectures (accessible remotely), with a week-long travel component in London, United Kingdom. Combining interactive seminars, guest lectures, and site visits to corporate and/or governmental organizations, students will depart with in-depth knowledge and practical leadership skills.
BU.230.730 Managing Financial Risk (2 Credits)
The course offers an introduction to financial risk management. Risk management is a complex process of identifying, measuring, and controlling risk exposure. The course will balance theory and practical application. Topics include market and credit risks, liquidity, and operational and legal risks, including volatility modeling, and derivatives as tools for controlling risk. Using modern econometric models, such as ARCH and GARCH, along with widely used quantitative methods (Monte Carlo simulation and Filtered Historical simulation), the course will describe how to measure and control risk exposure towards various types of risks, especially market and credit risk.
BU.610.615 Simulation for Business Applications (2 Credits)
This course provides a foundation for applying Simulation in managerial decision making in all areas of an organization. These decision areas could be in both predictive and prescriptive analytics area. Students learn to build quantitative models, in the presence/absence of reliable data, for quantifying and understanding impact of uncertain future on performance metrics under consideration. Simulation constructs probabilistic estimates of quantities of interest such as net present value of an investment, rate of a disease spread under a certain policy, or cost and time of a mega-project. This provides a very insightful information for decision makers to evaluate risks involved and make decisions accordingly. Results of Monte Carlo Simulation could be used for short-term and strategic planning of an organization. @Risk software package will be used for this part of the course. Additionally, in real world complex problems, where closed-form solutions, offered by classical mostly deterministic optimization methodologies, are not readily available/reachable, Simulation enables decision makers to see the distribution of all possible outcomes as a function of underlying uncertainties and using simulation-optimization methodology to make the best decision in the presence of uncertainty. Students will learn RiskOptimizer for this part of the course.
BU.450.765 Social Media Analytics (2 Credits)
The rapid growth of social media has given mass consumers a powerful tool to create knowledge and propagate opinions. At the same time, social media has created an unprecedented opportunity for companies to engage in real-time interactions with consumers. In addition, the size and richness of social media data have provided companies an unusually deep reservoir of consumer insight to transform their business and marketing operations. The social media analytics course will enable students to grasp the analytics tools to leverage social media data. The course will introduce tools such as engagement analytics, sentiment analysis, topic modeling, social network analysis, identification of influencers, and evaluation of social media strategy. It will involve many hands-on exercises.
BU.610.750 Supply Chain Analytics (2 Credits)
For a firm to execute its competitive strategy successfully, its supply chain must be able to deliver on the firm’s promise to its customers. Therefore, it is important for all managers to have an understanding of key supply chain concepts. With this in mind, this course introduces the main trade-offs involved in supply chain management, and provides analytical, data-driven tools that can be used to evaluate supply chain trade-offs. The course emphasizes (i) building spreadsheet-ready models that capture supply chain challenges, (ii) using these models to ask what-if questions by applying simulation and optimization tools (e.g., @Risk, a powerful Excel add-in for simulations), and (iii) distilling managerial insights from what-if questions and communicating recommendations based on those insights.