Shapiro_Joel
Joel K. Shapiro

MARKETS & CUSTOMERS
Clinical Associate Professor and Executive Director for the Program on Data Analytics at Kellogg

Print Overview

Joel Shapiro, JD, PhD, is clinical associate professor and executive director of the program on data analytics at Kellogg.

Joel teaches graduate courses in decision analytics and policy analysis, with a strong focus on how to apply analytic solutions to solve real-life problems.  He has deep experience in leading education institutions to become truly data-driven, helping them build capacity to engage in, and craft strategies resulting from, analytics initiatives.

At Kellogg, Joel is building a robust analytics ecosystem to engage faculty, students, and industry, creating synergies around the use of data analytics to to solve important problems.  Prior to joining Kellogg, Joel served as associate dean of academics of Northwestern University School of Professional Studies, where he led the creation and growth of new graduate, undergraduate, and non-credit programs in technical and analytic sciences, social sciences, humanities, and the arts.  Joel is also a recognized expert in the creation and management of online learning programs and the impact of new methods of teaching and learning on traditional models of higher education. 

Joel holds a PhD in policy analysis from the Pardee RAND Graduate School in Santa Monica, CA, a JD from Northwestern University School of Law in Chicago, IL, and a BS in physics from the University of Michigan in Ann Arbor, MI.  In his free time, Joel likes to play golf and basketball, garden, and spend time with his family and dogs.



Print Vita
Education
Doctor of Philosophy, 2003, Political Analysis, RAND Graduate School
Juris Doctor, 1998, Northwestern University School of Law
Bachelor of Science in Physics, 1994, University of Michigan, School of LSA

Academic Positions
Adjunct Faculty, School of Continuing Studies, Northwestern University, 2003-present
Adjunct Faculty, Graduate Statistics, School of Education, Loyola University, 2003-2003
Physics Teacher, Lincoln Park High School, 1994-1995

Other Professional Experience
Attorney, Schwartz & Freeman, 1998-1999
Policy Analyst / Doctoral Fellow, RAND Corporation, 1999-2001
Senior Researcher, ROCKMAN ET AL, 2003-2007

Print Research
Articles
Shapiro, Joel K.. 2011. Improving Retention and Enrollment Forecasting in Part-Time Programs.. Continuing Higher Education Review. 75
Other
Shapiro, Joel K.. "3 Ways Data Dashboards Can Mislead You.".
Shapiro, Joel K.. "Analytics Meets Decision Making: What Does Automation Mean for the Future of Data Scientists?.".
Shapiro, Joel K.. "How to Go From Awful to Awesome at Presenting Data Analytics.".
Shapiro, Joel K.. "3 Must-Knows on Distance Ed.." Inside Higher Ed.
Shapiro, Joel K.. "Competency-Based Degrees: Coming Soon to a Campus Near You.." The Chronicle of Higher Education.

 
Print Teaching
Full-Time / Evening & Weekend MBA
Data Analytics Decisions (KMCI-940-0)
Evidence-based decisions are no longer a luxury, as firms are capitalizing on the tremendous value that data analytics can bring to their decision-making. These analytic techniques and tools are widely applicable to myriad industries and business contexts. This course will give students the opportunity to practice their existing data analytics skills to solve diverse real-world cases. Students will also deepen their ability to select the appropriate method to solve each problem, clearly and concisely present results, and clearly articulate the strengths and limitations of their analyses.

Data Analytics Decisions (KMCI-940-5)
Evidence-based decisions are no longer a luxury, as firms are capitalizing on the tremendous value that data analytics can bring to their decision-making. These analytic techniques and tools are widely applicable to myriad industries and business contexts. This course will give students the opportunity to practice their existing data analytics skills to solve diverse real-world cases. Students will also deepen their ability to select the appropriate method to solve each problem, clearly and concisely present results, and clearly articulate the strengths and limitations of their analyses.