Assuring the quality of the data you capture is crucial to success. The old adage "Garbage In, Garbage Out" certainly applies to all analysis. Using poor quality data at best will create sub-optimal analysis. It is akin to trying to build a Mercedes out of rusty steel.
You must have an attitude that cuts across all levels and groups in your organization that is sensitive to data. You must demand that everyone touching customer data do their best to ensure its integrity. This is true in customer service, collections, credit originations and all other customer contact points.
Data quality checks can be implemented at the point of data capture. Specific values may be required for some fields. Certain ranges may apply to others. Negative numbers may or may not be permitted. Checks against other data for consistency purposes is ideal but is rarely done at most companies. For example, comparisons of social security number, name and address can all be made to ensure that all data is current and accurate. This improves the process of consolidating account data at the customer and household levels.
CDG can help you get a handle on data quality. What issues have been identified? How can they be fixed? Ensuring that the data is credible is crucial to improved decision-making.
