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(Practice Oriented) Katharina Baamann MioSoft

Abstract: 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 andmore 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 relevantdata 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.

Key Words: Data Quality, Revenue Assurance, SOX compliance, KPIINTRODUCTION
The magnitude of data quality problems is mostly unrecognized and is often treated like an unwelcomed necessity. The results of a data quality project are unpredictable and its worth for the company is hard to measure, which encourages executives to be very sceptical about embarking on such a project. On the other hand correct data is a key issue for correct financial reporting,especially for companies listed at a US stock exchange (SOX compliance). Analyzing data quality problems in respect to revenue assurance gives an instrument for a concrete measure of the revenue loss in money terms and hence of the project’s worth.

Revenue Assurance (RA)
Revenue Assurance is the use of data quality and process improvement methods to improve profits, revenues and cash flow withoutinfluencing demand. A set of techniques and methodologies is used to identify and repair revenue leakages as well as to detect and prevent errors resulting in unbilled or uncollected revenues. Revenue Assurance was defined and standardized in [3] by a TeleManagement Forum working group. It is mostly used in the telecommunication area. Reasons for revenue leakage are data quality issues likeinterconnect inconsistencies, loss of data or corrupted files, as well as problems with business processes like manual or ill-defined processes. Performing a revenue assurance project is important, not only to detect un-billed or mis-billed customers, but also to understand and in the end to eliminate the reasons for such undesired occurrences. In [2], different approaches to RA – Reactive, Active andProactive Revenue Assurance were defined. Reactive Revenue Assurance Reactive Revenue Assurance is used to just detect the existing revenue leakage. Here are projects set to identify and resolve the causes of actual revenue loss.

Active Revenue Assurance Active Revenue Assurance addresses problems as they occur. This approach is designed to initiate corrective responses prior to incurring anylosses. The actual business process is monitored in real-time. Discovering problems in real-time helps in correcting the leakage before it causes damage and impacts the customer. Proactive Revenue Assurance Proactive Revenue Assurance acts in anticipation. Controls and other measures are implemented in order to prevent problems from occurring in advance. The methods described above are complementary.As a first step, it is important to detect and fix the actual revenue leakage in a company. After finding the reasons for that, active or proactive RA should be implemented to prevent damage or as an ultimate goal to prevent the occurring of leakage. Data Quality Issues and Process Improvement RA can be approached by data quality or process improvement ([2]). The data quality approach uses data...
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