This course introduces students to the use of data in model-based decision making. Technological improvements have resulted in businesses having access to more data and more types of data than they have ever had before. This wealth of data means that it is now critical for managers to understand how data can and should be used as part of the decision-making process. In this course, we make the case that there is a difference between “what data say” (facts) and “what data mean” (relationships). Facts provide information about “how the world looks” while relationships provide information about “how the world works”. Mistaking facts for relationships can result in misguided and potentially very costly decisions. Thus, a key challenge that businesses face is determining when the facts observed in data can be interpreted as relationships on which decisions should be based. The objective of the course is to provide students with the skills to think carefully, critically, and creatively about the data available to them and the facts presented to them to improve their ability to integrate data into their decision-making process.

The premise in this course is that customer value is a prerequisite to business success. We explore what the term “customer value” means, how to align the company’s product or service with customer needs, and distinguish it from competitive offerings. The task involves marshalling the efforts of the company and its network partners to provide customers with a superior total package of benefits – comprising the product itself, associated services, brand image, appropriate pricing, and availability. An intimate understanding of customers’ needs and behaviour is critical and we will focus strongly on this topic. Students will be engaged in active research and interpretation of information about potential areas for delivering value. The course develops skills in strategy development, research and analysis, and judgment in making business decisions that touch on customer value.

This course teaches future managers how to extract information from data using statistical tools and how to apply probabilistic thinking to managerial problems. Topics include statistical study design, inference, regression analysis, and decision analysis. Applications to all functional areas of management are discussed. Upon course completion, the student will be better able to: (1) Identify and formulate problems where statistics can have an impact (2) See the relevance of statistics and apply what has been learned to career practice and to other business courses (3) Distinguish between routine and special problems requiring statistical analysis (4) Understand statistical methods for quality improvement (5) Assess data with healthy skepticism and seek expert help when needed and (6) Recognize when better data and information are needed for decision-making.

Marketing research involves four steps: collecting information, analyzing information, interpreting information, and communicating information. In this course, both qualitative and quantitative techniques will be used to collect and analyze information. By the end of the course, students will have designed a questionnaire, moderated a focus group, and used regression, factor, and cluster analysis to understand data. The course draws on a variety of applications including the automotive industry, the diamond industry, the Italian national railway, consumer packaged goods, newspapers, politics, and others.

This course explores the role of emerging media in marketing. The course examines how the online setting is different from the offline setting and how access devices (PCs, mobile phones, tablets) affect business decisions. Topics include search engines, online advertising, electronic commerce, social media, mobile media, and privacy.