Informação

Information & Management 40 (2002) 133–146

AIMQ: a methodology for information quality assessment
Yang W. Leea, Diane M. Strongb, Beverly K. Kahnc, Richard Y. Wangd,* a b

College of Business Administration, Northeastern University, Boston, MA, USA Worcester Polytechnic Institute, Management Department, Worcester, MA, USA c Sawyer School of Management, Suffolk University, Suffolk, VA, USA d MIT, UC, Berkerley and Boston University, Boston, MA, USA

Received 16 July 1999; received in revised form 28 May 2001; accepted 8 November 2001

Abstract Information quality (IQ) is critical in organizations. Yet, despite a decade of active research and practice, the field lacks comprehensive methodologies for its assessment and improvement. Here, we develop such a methodology, which we call AIM quality (AIMQ) to form a basis for IQ assessment and benchmarking. The methodology is illustrated through its application to five major organizations. The methodology encompasses a model of IQ, a questionnaire to measure IQ, and analysis techniques for interpreting the IQ measures. We develop and validate the questionnaire and use it to collect data on the status of organizational IQ. These data are used to assess and benchmark IQ for four quadrants of the model. These analysis techniques are applied to analyze the gap between an organization and best practices. They are also applied to analyze gaps between IS professionals and information consumers. The results of the techniques are useful for determining the best area for IQ improvement activities. # 2002 Elsevier Science B.V. All rights reserved.
Keywords: Information quality; Information quality assessment; Information quality benchmarking; Information quality analysis; Information quality improvement; Total Data Quality Management (TDQM)

1. Introduction Information quality (IQ) has become a critical concern of organizations and an active area of Management Information Systems (MIS) research. The growth of data