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The integrity of the data used to operate and make decisions about a business affects the relative efficiency of operations and quality of decisions made. Protecting that integrity can be difficult and becomes more difficult as the size and complexity of the business and its systems increase. Recovering data integrity may be impossible once it is compromised. Stewards of transactional and planning systems must therefore employ a combination of procedures including systematic safeguards and user‐training programs to counteract and prevent dirty data in those systems. Users of transactional and planning systems must understand the origins and effects of dirty data and the importance of and means of guarding against it. This requires a shared understanding within the context of the business of the meaning, uses, and value of data across functional entities. In this paper, we discuss issues related to the origin of dirty data, associated problems and costs of using dirty data in an organization, the process of dealing with dirty data in a migration to a new system: enterprise resource planning (ERP), and the benefits of an ERP in managing dirty data. These issues are explored in the paper using a case study.
Vosburg et al. (Thu,) studied this question.