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Big Data Recommendations for Industrial–Organizational Psychology

Published online by Cambridge University Press:  17 December 2015

Richard A. Guzzo ,
Alexis A. Fink ,
Eden King ,
Scott Tonidandel  and
Ronald S. Landis
Richard A. Guzzo*
Affiliation:
Mercer, Washington, DC
Alexis A. Fink
Affiliation:
Intel, Portland, Oregon
Eden King
Affiliation:
Department of Psychology, George Mason University
Scott Tonidandel
Affiliation:
Department of Psychology, Davidson College
Ronald S. Landis
Affiliation:
Department of Psychology, Illinois Institute of Technology
*
Correspondence concerning this article should be addressed to Richard A. Guzzo, Mercer, 1050 Connecticut Avenue, Suite 700, Washington, DC 20036. E-mail: [email protected]
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Extract

The world is awash in data. Data is being created and stored at ever-increasing rates through a variety of new methods and technologies. Data is accumulating in all sorts of accessible places. Much of that data is of great interest to industrial–organizational (I-O) psychologists, often in ways never anticipated by those who develop technologies and processes that generate and store that data. I-O psychologists also generate data in the course of research and practice in ways that, especially if joined with data originating from other sources, create giant datasets. This abundance of data—variables, measurements, observations, facts—can be used to inform a vast number of issues in research and practice. This is the new “big data” world, and beyond opportunities, this new world also presents challenges and potential hazards.

Type
Focal Article
Information
Industrial and Organizational Psychology , Volume 8 , Issue 4 , December 2015 , pp. 491 - 508
Copyright
Copyright © Society for Industrial and Organizational Psychology 2015 

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