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George Easton - Emory University, Goizueta Business School. Atlanta, GA, US

George Easton George Easton

Associate Professor of Information Systems & Operations Management | Emory University, Goizueta Business School

Atlanta, GA, UNITED STATES

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Biography

Professor Easton was formerly Associate Professor, Department of MS/CIS, Faculty of Management, Rutgers University, and Associate Professor of Statistics and Quality Management, Graduate School of Business, University of Chicago before joining the Goizueta Business School Faculty in 1996. His research interests include quality management and statistical methodology. He is also Editor of the Quality Management Journal published by the American Society for Quality Control. Professor Easton has worked extensively with industry in both quality management and statistics. He served as an Examiner for the Malcolm Baldrige National Quality Award in 1989 and 1990 and a Senior Examiner in 1991 and 1992.

Areas of Expertise (5)

The Impact of Quality Management on Corporate Performance

The Development of Quality Management Systems

Strategic and Business Planning

Robust Estimation

Graphical Methods for High Dimensional Exploratory Data Analysis

Education (4)

Princeton University: PhD, Statistics 1985

Princeton University: Master's, Statistics 1983

University of North Carolina: Master's, Operations Research and Systems Analysis 1981

Duke University: Bachelor's, Mathematics and Zoology 1979

Media Appearances (1)

Coffee with… George Easton

emorybusiness.com  online

2015-05-09

A few years ago, George Easton was listening to a business news program when he heard the interviewer ask his entrepreneur guest if he hired MBAs. The entrepreneur said “No,” calling MBAs “code unfriendly.” Given Easton’s background in data analysis and his nearly 30 years of teaching MBAs, the comment struck a chord. Easton, associate professor of information systems & operations management, decided to change that perspective with Advanced Data Science, his new course. His goal? To create “code friendly” MBAs: dual threats who can provide business insight and interact positively with technical teams. The class proved so popular that Easton had to purchase folding tables to accommodate overflow.

EB: Besides being motivated by the entrepreneur’s com-ments, why was this a good time to launch the Advanced Data Science class?

Easton: Since 2008, I’ve observed a big change in the attitude of MBAs toward this type of technology. It wasn’t just the economy. Google Analytics and Amazon Web Services were catching on, and the ideas of analytics and big data really got the attention of our students. It made them much more receptive both to analytics in general and to the idea of coding and software. So the environment was ripe for this course.

EB: What were some of the considerations in designing the class?

Easton: I wanted to capitalize on our students’ vast scope of knowledge and talent. While the students appropriate for this course needed to be advanced in math and/or computing, it could be a mix. That way, they could teach each other.

I also wanted to give students exposure to tools that are hot in this area—programming languages like Python and a statistical programming language called “R.” And I wanted them to understand computer architecture in regards to how to process vast amounts of data.

EB: But you’re not trying to create programmers, right?

Easton: I’m not teaching them to be programmers, but if they wanted to be, I am giving them enough of a start. A big part of what I teach is learning how to find information through open source communities. Students learn that they’ll have to deal with ambiguity and incompleteness. You have to be persistent in order to answer these questions.

EB: The focus of this issue is the future of work. What might the future of work look like regarding analytics?

Easton: It’s going to be the cloud and dealing with the Internet of Things—devices that communicate data over the Internet, such as your television or thermos

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Articles (4)

Team leader experience in improvement teams: A social networks perspective Journal of Operations Management

2015

In this research, we disentangle the relationship between several key aspects of a team leader's experience and the likelihood of improvement project success. Using the lens of socio-technical systems, we argue that the effect of team leader experience derives from the social system as well as the technical system. The aspects of team leader experience we examine include team leader social capital (a part of the social system) and team leader experience leading projects of the same type (a part of the technical system).

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Enterprise Content Management Should Be Academic International Journal of Management and Information Systems

2014

The ‘digital divide’ that was formed by a curriculum that affords no direct exposure to any business-oriented enterprise content management system and the surprising ubiquity and dependency on enterprise content management systems in business provided the motivation to class-test SharePoint as a surrogate for a university-supported course management system.

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Effects of Total Quality The Practice of Quality Management

2013

This article explores the impact of the adoption of total quality management techniques on the performance of a pilot sample of 39 U.S. firms. Actual performance is compared to an improved benchmark performance measure of how the firms would have performed had they not adopted TQM. The findings indicate that performance, as measured by profit margin, return on assets, asset-use efficiency, and stock returns, is marginally better for firms that have implemented TQM. For a subsample of firms identified as having clearly more mature and well-integrated quality management approaches, the improved performance result is noticeably and consistently stronger.

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The role of experience in six sigma project success: An empirical analysis of improvement projects Journal of Operations Management

2012

Recent learning-by-doing research highlights the importance of examining multiple measures of experience and their relationship to the performance of work teams. Our paper studies the role of individual experience, organizational experience, team leader experience, and experience working together on a team (team familiarity) in the context of improvement teams. To do so, we analyze successful and failed six sigma improvement team projects at a Fortune 500 consumer products manufacturer with multiple business groups. Such improvement project teams focus on deliberate learning, which differs from the primary focus of work teams.

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