Application of Six-Sigma for Data Quality Improvement in an Insurance Company

Abstract Billions of dollars annually is what poor data quality costs Insurance businesses according to the Data Warehousing Institute. Poor data is also the leading cause of many IT project failures. Many companies are designing their data management programs and quality initiatives to deal with this problem of erroneous and inconsistent data. This paper discusses these topics as well as those detailing how companies can improve their data quality using the quality improvement technique of applying Six-Sigma. The method of creating a new initiative for identifying measuring and controlling the data errors is discussed in this paper. Finally the paper ends with a conclusion and expected results and benefits of the technique. The insurance industry is data-dependent. Today carriers and intermediaries are engaged in improving data capture to help them to better manage their business manage their risk and know their customers. Business and regulatory drivers are pushing the industry to manage its data better.