BIDQI: The Business Impacts of Data Quality Interdependencies Model

As the data volumes within enterprises grow, the number of errors in stored data and the organizational impact of these errors is likely to increase. CIOs and business executives must be able to justify the expense of the initiative and convey the value proposition effectively to senior management. In order to do this, data quality needs to be expressed terms of costs and organizational consequences, to be able to convey the value of improving data quality correctly. By creating the Business Impacts of Data Quality Interdependencies (BIDQI) model in which data quality characteristics are linked to business impacts arising from data quality issues, this research aims to provide a highlevel method to discover the consequences and costs of poor data quality within organizations. The model will be able to assist researchers and practitioners in determining the actual costs of a data quality problem within an organization by giving them a tool to identify partially hidden costs which are caused by poor data quality. The constructs of the model are based on an extensive literature review and expert interviews were conducted to establish the interdependencies