Enhanced,Business,Performance, business, insurance Enhanced Business Performance with Ontological Engineering
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Companies are constantly seeking new ways to improve products, services, and support for their customers. This requires a thorough understanding of customer needs, which is most often accomplished by effectively utilizing information systems and applying Business Intelligence tools capable of converting data into meaningful, actionable information.Customer data, an important aspect of any successful business, is used by various entities within an organization to perform multiple job functions, for example: Product strategy, product management, and marketing may have a need to review customer data related BI reports in order to design better products and services. Customer care may have a need to collect and analyze customer information from multiple data sources to serve customers better. Internal IT may have a need to consolidate disparate customer data dispersed over multiple systems in order for the business to function smoothly. Business needs may include customer care, billing and processing, and BI data for intelligent decision making. Businesses may have a need for a Decision Support System (DSS) to process, review, and overlay complex data results depicted visually in order to arrive at a satisfactory customer-related decision.It is clear that a comprehensive data view across various domains or areas of operation is best suited to support these activities. However, with customer data dispersed over multiple systems and often represented differently, semantic mismatches between terms and undefined or underrepresented relationships may cause pertinent data to be unavailable in a seamless manner when required by interested users and applications. Obviously, partial data and information-driven analysis can negatively impact decision quality and, therefore, business performance. The use of data integration processes attempts to solve this problem. However, conventional data integration processes are poor at capturing concepts, relationships, and semantic differences between dispersed and disparate data. The context in which data is used, concepts within a particular domain (e.g., products/services and customer service), and the frequently complex relationships between each of them are often lost or not easily captured. Therefore, full or meaningful data availability issues still persist, and businesses are forced to make decisions based upon partial data. In todays globally competitive environment, enterprises that possess a comprehensive understanding of customer data have an edge over their competition due to better understanding of customer response to various stimuli. Businesses are coming to understand that this knowledge can be very effectively utilized in behavioral marketing. Emerging trends in software ontologies and ontological engineering can help solve or reduce the issue of poor data integration. The use of ontologies in software systems can support a fuller range and quality of data availability. One software developer, in particular, is a pioneer in this new field. They have developed a unique and easily adaptable ontology-based Decision Support System (DSS) that solves the problem of incomplete data retrieval which can lead to incomplete information and inferior decision making processes.This DSS leads directly to enhanced business performance through the dramatic cost efficiencies afforded by faster, more effective data processing. All of this results in greater profitability for those companies which take advantage of such a system.For more information, please contact TerraFrame http://www.terraframe.com, a leading ontological engineering software development company, or call 877-444-3074 or email Ray Hutchins at [email protected] or JP Batra at [email protected].
Enhanced,Business,Performance,