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A Classification and Analysis of Data Quality Costs
Type
conference paper
Date Issued
2004-11-05
Author(s)
Helfert, Markus
Abstract
Many information quality initiatives and projects need to demonstrate the potential benefits of their IQrelated activities already in their planning stage. In doing so, practitioners rely on cost estimates based on current non-quality data effects (that are then compared to data quality improvement costs). In producing such estimates on costs caused by low quality data, it is difficult to identify all potential negative monetary effects that are the result of low quality data (as well as all possible costs associated with assuring high quality data and their progression). Consequently, this article reviews and categorizes the potential costs associated with low quality data and examines their progression. This analysis can help practitioners to identify cost saving potentials and argue a more convincing business case of their data quality imitative. For researchers, the proposed classification framework and the cost progression analyses can be helpful to develop quantifiable measures of data quality costs and to prepare – subsequently – benchmarking studies, comparing different cost levels in different organizations. Thus, the paper contributes elements of a future cost-benefit analysis method for data quality investments.
Language
English
HSG Classification
not classified
Refereed
Yes
Book title
Proceedings of the 9th MIT Information Quality Conference
Start page
1
Event Title
9th International Conference on Information Quality (ICIQ)
Event Location
05.-07.11.2004
Event Date
MIT
Subject(s)
Division(s)
Eprints ID
54896