Remember the early days of cellular telephones, when a call routinely started with a few minutes of “Can you hear me now?” Each of those minutes cost the caller without contributing to the desired communication. Today we have a similar situation with analytics when meetings routinely begin with “Where did you get this data?” The time taken when several people—generally high-level and high-salary people—spend several minutes questioning data trustworthiness has a very real cost and contributes little to knowledge, understanding, insight, or decision making.

Trusted data is a critical element of analytic culture and data-driven business. Companies today consider data a key asset that influences every aspect of business from strategy to operations. Lack of trust in the data inhibits decision making, slows progress, and seeds confusion and miscommunication at all levels. Repeatedly and redundantly establishing trust with each data use case is inefficient and costly. This paper describes an analytics scenario and illustrates the high cost of untrusted data and the cost savings possible when trust becomes a data management priority.