Nathan Craig

Background

Nathan Craig is an assistant professor in the Department of Management Sciences. He earned a DBA in Technology and Operations Management from Harvard Business School as well as an MS in Operations Research and a BS in Integrated Systems Engineering from The Ohio State University.

His teaching experience includes courses in operations management and stochastic modeling as well as custom and executiveeducation programs at Harvard Business School and the University of Chicago Booth School of Business.

His current research interests focus on retail supply chains, including capital structure and liquidation in the retail industry as well as mechanisms for improved manufacturer service levels and their impact on retailer demand. Craig’s research has been presented at various conferences and seminars, including annual meetings of the Institute for Operations Research and the Management Sciences (INFORMS) as well as the Production and Operations Management Society (POMS).

His research has been published by Harvard Business School Press, the_ Journal of Operations Management_, and Manufacturing & Service Operations Management. Nathan is the recipient of the Wyss Award for Excellence in Doctoral Research presented by Harvard Business School.

Areas of Expertise

Data Analytics Retailing Inventory Finance Supply Chain Coordination

Education

DBA, Technology and Operations Management, Harvard Business School MS, Operations Research, The Ohio State University BS, Integrated Systems Engineering, The Ohio State University

Courses

MBA 6273 Data Analysis for Managers

Introduction to data analysis and statistics for business. Emphasis on achieving an applicationoriented understanding of statistical inference and regression analysis and their use in decision making. Prereq: Enrollment in MBA or WPMBA program, or permission of instructor. Not open to students with credit for 6271 or 870.

BUSMGT 2320 Decision Sciences: Statistical Techniques

Examination of the use of statistical techniques in managerial decisionmaking processes; statistical inference, simple and multiple regression, time series. Prereq: Math 1131 (132), or 1151 (152); and Stat 1430 (133); and CSE 1113, or 2111 (200); and Econ 2001.01 (200). Prereq or Concur: Econ 2002.01 (201). Not open to students with credit for 330. This course is available for EM credit.