Data Quality (DQ) is seen as critical to effective business decision-making. However, maintaining DQ is often acknowledged as problematic. Asset data is the key enabler in gaining control of assets. The quality asset data provides the foundation for effective Asset Management (AM). Researches have indicated that achieving AM DQ is the key challenge engineering organisations face today. This paper investigates the DQ issues emerging from the unique nature of engineering AM data. It presents an exploratory research of a large scale national-wide DQ survey on how Australian engineering organisations address DQ issues, and proposes an AM specific DQ framework.

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This chapter discusses the critical issues of information quality (IQ) associated with engineering assets management. It introduces an asset management (AM) specific IQ framework as a means of studying IQ in engineering asset management. It argues that it is essential to ensure the quality of data in monitoring systems, control systems, maintenance systems, procurement systems, logistics systems, and range of mission support applications in order to facilitate effective AM. There is also a growing need to address the issue of IQ in enterprise asset management (EAM) systems, by analyzing existing practices and developing frameworks/models to assist engineering enterprises to capture, process and deliver quality data and information. Furthermore, the authors hope that a better understanding of the current issues and emerging key factors for ensuring high quality AM data through the use of the AM IQ framework will not only raise the general IQ awareness in engineering asset management organisations, but also assist AM and IT professionals in obtaining an insightful and overall appreciation about what AM IQ problems are and why they have emerged.

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