According to W. Edwards Deming, American companies require nothing less than a transformation of management style and of governmental relations with industry. In Out of the Crisis, originally published in 1982, Deming offers a theory of management based on his famous 14 Points for Management. Management's failure to plan for the future, he claims, brings about loss of market, which brings about loss of jobs. Management must be judged not only by the quarterly dividend, but by innovative plans to stay in business, protect investment, ensure future dividends, and provide more jobs through improved product and service. In simple, direct language, he explains the principles of management transformation and how to apply them.

Out of the Crisis

How good is a company's data quality? Answering this question requires usable data quality metrics. Currently, most data quality measures are developed on an ad hoc basis to solve specific problems [6, 8], and fundamental principles necessary for developing usable metrics in practice are lacking. In this article, we describe principles that can help organizations develop usable data quality metrics.

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Data quality assessment

http://web.cba.neu.edu/~ywlee/publication/AIMQ.pdf

AIMQ: a methodology for information quality assessment

The literature provides a wide range of techniques to assess and improve the quality of data. Due to the diversity and complexity of these techniques, research has recently focused on defining methodologies that help the selection, customization, and application of data quality assessment and improvement techniques. The goal of this article is to provide a systematic and comparative description of such methodologies. Methodologies are compared along several dimensions, including the methodological phases and steps, the strategies and techniques, the data quality dimensions, the types of data, and, finally, the types of information systems addressed by each methodology. The article concludes with a summary description of each methodology.

Methodologies for data quality assessment and improvement

Understanding the successful adoption of information technology is largely based upon understanding the linkages among quality, satisfaction, and usage. Although the satisfaction and usage constructs have been well studied in the information systems literature, there has been only limited attention to information and system quality over the past decade. To address this shortcoming, we developed a model consisting of nine fundamental determinants of quality in an information technology context, four under the rubric of information quality (the output of an information system) and five that describe system quality (the information processing system required to produce the output). We then empirically examined the aptness of our model using a sample of 465 data warehouse users from seven different organizations that employed report-based, query-based, and analytical business intelligence tools. The results suggest that our determinants are indeed predictive of overall information and system quality in data warehouse environments, and that our model strikes a balance between comprehensiveness and parsimony. We conclude with a discussion of the implications for both theory and the development and implementation of information technology applications in practice.

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Antecedents of Information and System Quality: An Empirical Examination Within the Context of Data Warehousing

Information quality (IQ) is an inexact science in terms of assessment and benchmarks. Although various aspects of quality and information have been investigated [1, 4, 6, 7, 9, 12], there is still a critical need for a methodology that assesses how well organizations develop information products and deliver information services to consumers. Benchmarks developed from such a methodology can help compare information quality across organizations, and provide a baseline for assessing IQ improvements.

/pdf/information-quality-benchmarks-product-and-service-4mb9v6k2i9.pdf

Information quality benchmarks: product and service performance

Product and Service Performance Model for Information Quality: An Update.

The use of stolen personal-identifying information, like Social Security numbers, to commit identity fraud continues to be a major problem The fact that an impostor can pass as the genuine user by possession of stolen identification information is a weakness in current authentication systems Adding a biometric layer to the traditional knowledge and token-based authentication systems is one way to counter this problem Physical biometrics, such as fingerprint systems, are highly accurate; hence, they would be the first choice for such applications but are often inappropriate Behavioral biometrics, like biometric typing patterns, have the potential to fill this gap as another level of security but this research identified some deficiencies in performance quality Two research streams for improvements have emerged The first approach attempts to improve performance by building better classifiers, while the second attempts to attain the same goal by using richer identifying inputs Both streams assume that the typing biometric patterns are stable over time This study investigates the validity of this assumption by analyzing how students’ typing patterns behave over time The results demonstrate that typing patterns change over time due to learning resulting in several performance quality challenges First, the changing patterns lead to deteriorating authentication accuracy Second, the relevancy of the reference biometric template created during training becomes questionable Third, the deterioration in accuracy compromises the security of the whole system and fourth, the net effect brings to question whether the biometric keypad is no longer “fit for use” as an authentication system These are critical data quality issues that need to be addressed if behavioral biometrics are to play a significant role in minimizing authentication fraud Possible solutions to the problem, including biometric template updating and choice of uncorrelated PIN combinations, are suggested as potential topics for future research

Typing Biometrics: Impact of Human Learning on Performance Quality

This study tests the multi-cultural applicability of Huberâ€™s technological imperative framework by comparing the effects of the adoption of a new telecommunication technology, cellular phones, on the behavior of the sales force in several industry sectors in France and the U.S. The study investigates three areas of interest. First, the study finds that, though the sales strategies are the same in both countries, the actual behavior of the sales force to attain these strategic goals differs. Second, a comparison of these differences with the variables in Huberâ€™s theory shows that the differences in the variables are consistent with the sales representative behavior in the two countries. Third, the study asks what effect the use of cell phones has had on sales force behavior. Analysis on all the data combined shows the predicted results of new technology adoptionâ€”a shortening of decision making time occurs in both countries. When the data is stratified by country, however, changes in variables in the U.S. support Huberâ€™s theory, those from France do not. These results indicate a cultural bias in the generation of theory that has important implications for cross-cultural research.

Beverly K. Kahn

Papers

AIMQ: a methodology for information quality assessment

Information quality benchmarks: product and service performance

Product and Service Performance Model for Information Quality: An Update.

Typing Biometrics: Impact of Human Learning on Performance Quality

Organizational impacts of new communication technology: a comparison of cellular phone adoption in France and the United States