Data quality is an elusive subject that defies measurement and yet is 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. Simply put, data quality 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. In the meantime, each company has the opportunity to differentiate itself through the quality of its data. Leading companies are now defining what the marketplace data quality expectation will be.
Improving the data quality of an organization creates many benefits such as improved speed to solutions, a “single version of the truth,” improved customer satisfaction, improved morale, an enhanced corporate image and consistency between systems accumulate. And organizations must selectively choose those benefits to perform further analysis on and convert to hard dollars. ROI must be measured on hard dollars.
Data quality improvement is not just another technology to implement. A program approach to data quality is required to measure data quality ROI, and organizations 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. Companies with more data, cleaner data, accessible data and the means to use that data will come out ahead.
CSI-DeLeeuw helps companies differentiate themselves as leaders through proven data quality services.
A Data Quality Program Implementation is a program approach to data quality for articulating and improving data quality ROI. Abstracting quality into a set of agreed data rules and measuring the occurrences of quality violations provides the measurement in the methodology, which was developed in conjunction with IT best practice, successful data quality efforts. Examples of data quality success include targeted marketing, churn management, market basket analysis, cross-selling, channel parity, procedure analysis, inventory tracking, and contact center analysis.
For more information:
Download FREE White Paper on Continuous Data Quality Improvement by Establishing a Data Quality Competency Center
Download FREE White Paper on Implementing an Integrated Methodology for Data Profiling and Cleansing
Client Success: CSI's Data Quality Center of Excellence helps client improve overall data quality, reduce total cost of ownership, reduce risk with a strategic data migration and enhances overall decision-making processes