Total Quality Management. Are information systems managers ready?

doi:10.1016/0378-7206(95)00028-0

Information & Management

Volume 29, Issue 5, November 1995, Pages 251-263

https://doi.org/10.1016/0378-7206(95)00028-0 Get rights and content

Abstract

The results of an empirical survey of information systems (IS) managers indicated that 41% understood the basic philosophy of Total Quality Management (TQM) fairly well. Furthermore, the IS managers typically indicated they thought most of the concepts/tools commonly associated with TQM would be useful to both the organization and the IS function. IS managers currently involved in implementing TQM reported their IS function had achieved the following benefits: improved customer satisfaction, enhanced quality of products and services delivered to the customer, and increased flexibility in meeting customer demands. It was also reported, however, that these benefits typically were not achieved until three-to-five years after TQM initiation.

References (33)

E. Rivard et al.
The Benefit of Quality IS
Datamation
(Jan. 15, 1989)
D.L. Weintraub
Implementing Total Quality Management
Economic Development Review
(Summer 1993)
International Quality Study: The Definitive Study of the Best International Quality Management Practices
(1991)
Quality Winners Credit IT
Information Week
(Oct. 1992)
G.M. Ashmore
Better Information Means Better Quality
The Journal of Business Strategy
(January/February 1992)
J.B. Ayers
Total Quality Management and Information Technology: Partners for Profit
Information Strategy: The Executive's Journal
(Spring 1993)
P. Block
The Empowered Manager: Positive Political Skills at Work
(1987)
R. Brownstone
Is TQM Enough?
The Journal of Quality and Participation
(July/August 1990)
P.B. Crosby
Quality Is Free
(1979)
W.E. Deming
Quality, Productivity and Competitive Position
(1982)

W. Eckerson

Total Quality Management Paying Off For Users

Network World

(April 16, 1990)

W. Eckerson

Total Quality Management Paying Off For Users

Network World

(April 16, 1990)

J.R Evans et al.

The Management and Control of Quality

(1993)

A.V. Feigenbaum

Total Quality Control

(1991)

H.S. Gitlow et al.

Total Quality Management in Action

(1994)

R. Johnson et al.

Production and Quality

(1989)

L.H. Jones

Information Systems, Organizational Change and Quality Improvement Programs

National Productivity Review

(Spring 1988)

Cited by (39)

Exploring the relationship between information technology competence and quality management
2015, BRQ Business Research Quarterly
Citation Excerpt :
The literature review shows that QM plays an important role in improving the firm's competitive position (Reed et al., 2000) and that the proper application of IT can influence this relationship (Murray, 1991; Aiken et al., 1996; Cortada, 1995; Forza, 1995; Ahmed and Ravichandran, 1999; Perez-Arostegui et al., 2012). Thus, the development of an IT competence will improve the efficacy of QM practices, enabling firms to achieve a better competitive position (Pearson et al., 1995). Various studies have examined the relation between IT and QM.
The introduction of information technology (IT) has become a necessity to compete in most industries, so simple implementation of an IT strategy is not enough to achieve a better firm performance. Literature review shows IT as a useful tool only when it is combined with other firm resources and practices. The purpose of this paper is to analyze the complementarity between IT and one of the most prevalent and well-established set of organizational practices, Quality management practices (QMP). Structural equation modeling with data collected from managers in 230 Spanish firms shows a positive and significant relationship between IT and QMP. The findings provide us with in-depth understanding of both disciplines and several conclusions for its success.
Data quality assessment: The Hybrid Approach
2013, Information and Management
Citation Excerpt :
While these may be extreme examples, many organisations rely on having good quality data to make decisions for their every-day operations. Furthermore, even organisations with advanced data management practices, that implement continuous improvement methodologies, find that employees have a greater need for high quality data [16]. To be assured that data is “fit for use” – where “fit for use” data is of required quality [19] – the first step is the DQ assessment (see Fig. 1), the aim of which is to inspect data to determine the current level of DQ and the extent of any DQ deficiencies [6].
Various techniques have been proposed to enable organisations to assess the current quality level of their data. Unfortunately, organisations have many different requirements related to data quality (DQ) assessment. For example, some organisations may need to focus on ensuring regulations are met rather than reducing costs. Due to this, organisations may be forced to follow an assessment technique, which may not wholly fit their needs and current situation. Therefore, we propose and evaluate the Hybrid Approach to assessing DQ, which demonstrates how to dynamically configure an assessment technique as needed while leveraging the best practices from existing assessment techniques.
A multidimensional analysis of data quality for credit risk management: New insights and challenges
2013, Information and Management
Citation Excerpt :
It is argued in the literature that organizations should implement a Total Data Quality Management (TDQM) program that includes DQ definition, measurement, analysis and improvement. This enables them to achieve a suitable DQ level [39,28]. The DQ definition phase is the starting point for a TDQM program.
Recent studies have indicated that companies are increasingly experiencing Data Quality (DQ) related problems as more complex data are being collected. To address such problems, the literature suggests the implementation of a Total Data Quality Management Program (TDQM) that should consist of the following phases: DQ definition, measurement, analysis and improvement. As such, this paper performs an empirical study using a questionnaire that was distributed to financial institutions worldwide to identify the most important DQ dimensions, to assess the DQ level of credit risk databases using the identified DQ dimensions, to analyze DQ issues and to suggest improvement actions in a credit risk assessment context. This questionnaire is structured according to the framework of Wang and Strong and incorporates three additional DQ dimensions that were found to be important to the current context (i.e., actionable, alignment and traceable). Additionally, this paper contributes to the literature by developing a scorecard index to assess the DQ level of credit risk databases using the DQ dimensions that were identified as most important. Finally, this study explores the key DQ challenges and causes of DQ problems and suggests improvement actions. The findings from the statistical analysis of the empirical study delineate the nine most important DQ dimensions, which include accuracy and security for assessing the DQ level.
The impact of software process improvement on quality: In theory and practice
2003, Information and Management
Citation Excerpt :
Despite rapid advances in all facets of technology, the software industry is still struggling with the formidable task of developing software applications that meet quality standards, time pressure, and budget constraints [26,29].
To remain competitive, software companies must establish practices that enhance quality and advance process management. To this end, they have increasingly turned to software process improvement (SPI) methodologies, of which the ISO 9000 standards and the capability maturity model (CMM) are the best known. The underlying principle of both methodologies is to assess organizational capabilities to produce quality software, but they depend on different underlying processes.
Whether the practices advocated by these methodologies lead to high-quality software has been the topic of ongoing debates. Both scholars and practitioners are looking for hard evidence to justify the time and effort required by such guidelines to improve the software-development process and its end product.
In this paper, we investigate the impact of SPI methodologies on software quality, first by theoretical comparison and then with empirical data. Our findings reveal that each methodology has had a different level of impact on software quality factors. These findings could help software-development organizations select the methodology or combination that best meets their quality requirement.
Linking big data and total quality management: A proposed theoretical research framework of digital maturity mediation
2023, AIP Conference Proceedings
Electronic health records using a resource advantage theory perspective: an interdisciplinary literature review
2022, Records Management Journal

View all citing articles on Scopus

View full text

ResearchTotal Quality Management. Are information systems managers ready?

Abstract

Datamation

Economic Development Review

International Quality Study: The Definitive Study of the Best International Quality Management Practices

Quality Winners Credit IT

Information Week

Better Information Means Better Quality

The Journal of Business Strategy

Total Quality Management and Information Technology: Partners for Profit

Information Strategy: The Executive's Journal

The Empowered Manager: Positive Political Skills at Work

Is TQM Enough?

The Journal of Quality and Participation

Quality Is Free

Quality, Productivity and Competitive Position

Total Quality Management Paying Off For Users

Network World

Total Quality Management Paying Off For Users

Network World

The Management and Control of Quality

Total Quality Control

Total Quality Management in Action

Production and Quality

Information Systems, Organizational Change and Quality Improvement Programs

National Productivity Review

Research
Total Quality Management. Are information systems managers ready?