Data Quality Aspects Of Revenue Assurance

Revenue Assurance describes a methodology to increase a company’s income by determining where revenue gets lost, and to maximize their profits by eliminating revenue leakage and lowering operating costs. Especially in times of increasing data volume and more and more complex business and operational systems infrastructure, it is a challenge to find methods for detecting revenue leakage and its reasons. In this paper we will focus on the data quality aspect of revenue assurance and introduce a method to detect revenue-related data quality problems and their root causes. For high parallelism and efficiency a grid-based database is used to load all relevant data according to a defined metamodel, calculate adequate quality criteria and generate cleansing reports. This method is supported with a case study in the area of telecommunication returning a significant result of underbilling. Sample of the used quality criteria and scenarios of the cleansing procedure are given in detail.