Data is an Asset
Corporate data should be viewed as a key strategic asset. Inquiries from potential customers, transactions with existing customers, customer service communications, and new product/service marketing opportunities are all best served by a pro-active approach to data quality throughout the enterprise. Simply capturing and storing data is insufficient. Like other corporate assets, data and information quality needs to be effectively managed. There are immediate cost reduction and revenue benefits from doing so which will create positive return and increase shareholder value.
Left unmanaged, the quality of the data asset will only degrade over time and the overall cost of doing business will increase. Data quality processes and continued data management provides the necessary infrastructure to transform raw items of information into a reliable and valued corporate asset.
As businesses and organizations become more reliant on technology, data and information quality becomes an increasing concern. Customer expectations today in the instant gratification world we live in dictate greater sensitivity be given to each opportunity for customer and potential customer interactions. Customers are more demanding, more informed, and more able and prepared to take their business elsewhere in the highly competitive environment we find ourselves within.
As reported by TDWI, poor data quality costs businesses in excess of $600 billion per year. Financial service organizations face increased difficulties as they struggle to comply with various regulations including Sarbanes-Oxeley, The US Patriot Act, International Accounting Standards, plus others. These government initiatives implore the need for change in the way data is captured, processed, and otherwise managed. Many financial service providers are struggling to make business decisions on substandard data and information.
Financial service organizations are not alone in this struggle. All business organizations are faced with problems created by various data quality issues. Manufacturing, Insurance, Retail, and Direct Merchants all face problems of poor data quality which results in losses that can be measured in revenue, profit, and decreasing shareholder value. Lack of standardized data across the organization prevents effective data exchange within individual departments and extends to suppliers and outbound customer communications.
Many studies have been done that identify the compounding nature the impact of poor data quality represents to business. Failure to properly record correct information at the initial point of capture creates additional unnecessary expense which includes wasted materials, higher postage, and duplicate work effort that in turn causes poor strategic planning and unhappy customers.
The best solution to poor data quality issues should include executive management support for an enterprise wide approach that addresses the many points to which data enters the organization, the processes and technology that are applied once it arrives, and the long term benefits and improvements that can be realized from a pro-active data quality strategic plan.
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