Report quality, level of trust, decision quality


I have frequently seen “improved decision making” as a value driver used as a motivating factor for data quality and data governance activities. However, I often note that while the decision-making process can be informed with information, most frequently the actual decisions are made by individuals relying on their own instincts and experiences. So can one truly positively impact a decision-making process by ensuring that the data quality is at an acceptable level?

My problem is the subjectivity of this measure of success – most organizations don't have well-defined metrics for “quality of decisions,” and in many cases the impacts of poor decision making are cumulative over time. If someone is inherently a bad decision maker, will improving the data add a measurable benefit to the process?

It might be interesting to deconstruct the process of making a decision. Assume that a decision maker is presented with a piece of data and is asked to make a decision. Of course, there are many variables that feed that process, but let’s try to simplify it a little bit by boiling the number of variables down to two: whether the decision maker is “good” or “bad” and whether the data is “good” or “bad.”

Data is good

Data is bad

Decision maker is good

Decision is good

Decision is probably good

Decision maker is bad

Decision is probably bad

Decision is bad

Again, this may be an oversimplification, but if I could use this model as a generalization, it helps put some things into perspective: for a good decision maker, improving the data reinforces the level of trust in the result, while for a bad decision maker, improving the quality of the data only somewhat reduces the level of mistrust in the result. In other words, the quality of the result is only somewhat dependent on the underlying data, and the perception of the decision maker’s capabilities factor into whether the actual decision is considered to be “good” or “bad.”

This is not the only way we can spin this scenario, and in the next entry we’ll consider an alternative view.


About Author

David Loshin

President, Knowledge Integrity, Inc.

David Loshin, president of Knowledge Integrity, Inc., is a recognized thought leader and expert consultant in the areas of data quality, master data management and business intelligence. David is a prolific author regarding data management best practices, via the expert channel at and numerous books, white papers, and web seminars on a variety of data management best practices. His book, Business Intelligence: The Savvy Manager’s Guide (June 2003) has been hailed as a resource allowing readers to “gain an understanding of business intelligence, business management disciplines, data warehousing and how all of the pieces work together.” His book, Master Data Management, has been endorsed by data management industry leaders, and his valuable MDM insights can be reviewed at . David is also the author of The Practitioner’s Guide to Data Quality Improvement. He can be reached at

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