Demystifying Data: Managing with Analytics

Course Number 2175

Assistant Professor Ariel D. Stern
Visiting Professor Amitabh Chandra (Harvard Kennedy School)
Spring; Q3; 1.5 credits
14 sessions
Exam

Demystifying Data: Managing with Analytics is offered as both a 1.5-credit course and as a 3-credit course. The 1.5 credit course (course number 2175) takes place entirely in Q3. The 3-credit course (course number 6277) takes place in Q3 and Q4. Students can sign up for either.

Course Requirements

Demystifying Data: Managing with Analytics (DDMA) is designed for students who will manage and collaborate with data scientists, statisticians, and other analysts. The techniques covered will be applicable to all industry settings.

Educational Objectives

The educational objective of this course is to understand how to incorporate complex data analytics into organizational decision-making. The course equips students with the quantitative tools and data fluency necessary to succeed in a data-rich environment. The focus of the course is on managerial decisions that require analytics.

DDMA will overlap minimally with Big Data in Marketing (course number 1957), but excludes enrollment in Team Analytics (course number 6208 in Q3Q4 and course number 2085 in Q3).

Content and Organization

The focus of the course is on managerial decisions that require an extensive and nuanced understanding of complex data sets. As preparation for each class, students will analyze both an organizational context as well as a companion dataset. A goal of the course is to make the analysis as straightforward as possible in order to focus on managerial implications. The course consists of two modules:

  • This first module introduces core techniques and decision-making informed by data analytics. Technical topics include: bivariate and multiple regression analysis, time-series analysis, and data visualization. Managerial topics include managing in a multichannel world, leveraging variation in performance, and managing individuals in an organization who may be more skilled than their managers at specific analytic techniques.
  • The second module extends the foundations of the first module into more complex environments. Each class session will explore new techniques for analytically informed decision-making.

 

In exploring these topics, we take the perspective of a data-fluent leader.