If you haven’t been following along, in my previous posting I reviewed the Data Quality Positioning Gap as a non-traditional challenge to achieving data quality success. In this post, I will discuss the Perception Gap.
The Data Quality Perception Gap
Assuming we have properly met the challenges associated with customer expectations and solution positioning, chances are that our customer’s are still not “buying” because of the fifth non-traditional challenge…….data quality solutions are perceived as theoretical or impractical. Often times, data quality solutions appear to boil the ocean and our customers become overwhelmed with the scope and complexity or rightfully dubious of the likelihood of success. While this may not be readily apparent from the customer’s objections or from their rationale for why not to proceed, it is a leading reason why data quality solutions never see the light of day. In order to win our customers’ confidence and their business, we need to be viewed as a data quality expert. Proposing solutions that strain credulity calls this expertise into question.
Even if we are successful in proposing a practical and actionable solution, we need to be mindful of the sixth non-traditional challenge…….data quality solutions are perceived as creative ways not to address the problem. If the customer’s data quality problem can be solved by targeted data cleansing in the source system, then propose a solution that does just that. If the customer is unsure of the degree and impact of their data quality gaps, then propose a data quality solution to help them quantify and qualify their data quality issues. It is never a one size fits all and there’s no quicker way to lose credibility than to propose a solution that doesn’t address the customer’s needs.
My next posting will conclude the series on non-traditional data quality challenges. Stay tuned.