Data quality is an elusive subject that can defy measurement and yet be critical enough to derail any single IT project, strategic initiative or even a company as a whole. The data layer of an organization is a critical component because it is so easy to ignore the quality of that data or to make overly optimistic assumptions about its efficacy.
Having data quality as a focus is a business philosophy that aligns strategy, business culture, company information and technology in order to manage data to the benefit of the enterprise. Put simply, it is a competitive strategy. One day, like operational excellence, rich product features, everyday low prices, high product quality and short time-to-market, data quality will be expected by our markets.
Meanwhile, each company has the chance to differentiate itself through the quality of its data. Leading companies now are defining what the marketplace data quality expectation will be.
A parallel trend to data quality improvement in the marketplace is the comeback of return on investment measurement systems for technology-based initiatives. No longer is it acceptable to “throw money at problems,” target soft measures or lack accountability for results with technology spending. The approach of targeting ROI is even viable for efforts to improve the quality of data in a company, and many executives are demanding payback for quality initiatives.
Many benefits accrue from improving an organization’s data quality. Many of these benefits are “intangible” or unreasonable to measure. Benefits such as improved speed to solutions, a “single version of the truth,” improved customer satisfaction, improved morale, an enhanced corporate image and consistency among systems accumulate, but an organization must selectively choose those benefits to perform further analysis on and convert to hard dollars. ROI must be measured on hard dollars.
A program approach to data quality is required to measure data quality ROI. Data quality improvement is not just another technology to implement. We must change our way of doing business to fully exploit data. Investments in the technologies as well as in organizational changes are necessary to reap the full rewards. Data quality is right in the “sweet spot” of modern business objectives that recognize that whatever business a company is in, it is also in the business of data. Those companies with more data, cleaner data, accessible data and the means to use that data will come out ahead.
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