Jing Gao

Andy Koronios

Sasa Baskarada

Contemporary organizations are producing and storing more information then ever before in history. The resulting information overload, combined with the lack of quality assurance for information management, has led to a questionable state of information quality in many organizations. Furthermore, assessing, enhancing, and managing information quality has proven to be a notoriously difficult undertaking. This paper presents a capability maturity model approach for information quality management process assessment and improvement. The paper first presents a set of criteria, as identified from extensive literature review and exploratory case studies, which are thought to be of importance when considering a holistic approach for information quality management. The paper then presents the results of a Delphi study, which was used to validate those criteria and organize them into a staged capability maturity model - Information Quality Management Capability Maturity Model (IQM-CMM). The paper finally presents the preliminary results of a case study, where IQM-CMM was applied in a large Australian engineering asset management organization, and used as a comprehensive approach for evaluating their existing information quality management practices. As a result, it is believed that IQM-CMM may help organizations in assessing their existing information quality management practices, and in identifying potential gaps and improvement strategies.

A Framework for Assessing Organizational Information Quality Management Capability Maturity

IQM-CMM

Dimitris Kiritsis

Joseph Mathew

Christos Emmanouilidis

Engineering Asset Management discusses state-of-the-art trends and developments in the emerging field of engineering asset management as presented at the Fourth World Congress on Engineering Asset Management (WCEAM). It is an excellent reference for practitioners, researchers and students in the multidisciplinary field of asset management, covering such topics as asset condition monitoring and intelligent maintenance; asset data warehousing, data mining and fusion; asset performance and level-of-service models; design and life-cycle integrity of physical assets; deterioration and preservation models for assets; education and training in asset management; engineering standards in asset management; fault diagnosis and prognostics; financial analysis methods for physical assets; human dimensions in integrated asset management; information quality management; information systems and knowledge management; intelligent sensors and devices; maintenance strategies in asset management; optimisation decisions in asset management; risk management in asset management; strategic asset management; and sustainability in asset management.

Proceedings of the Fourth World Congress on Engineering Asset Management (WCEAM) 2009

Engineering Asset Management

Andy Koronios

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