Calculating the costs of information and data quality defects is important in assessing the priority of quality improvement initiatives. The costs of poor quality information line up with the three main categories of defects: representational, procedural and judgmental.
Representational information quality refers to how objectively the IT system aligns with the business reality it is supposed to present. Poor quality information and defective data do not line up with reality. Redundant data storage and processing costs are often cited as the paradigm of representational costs within the IT data center. If the system contains a date field that is ambiguous due to an incomplete representation of the data (e.g., a missing century), one obvious cost is that of fixing the system to accurately represent the context. The Y2K data element reportedly required approximately $600 billion to correct. Rework, digital scrap and inefficiencies in data center operations are significant contributors to these costs.
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