Are poor business outcomes linked to poor data quality? If so, how do you ask the questions that deliver useful insights?

At least one data-wise enterprise architect believes that some poor business outcomes are linked to poor data quality. Our recent interview with this practitioner, who shall go nameless, revealed support for our thesis, and for the idea that business outcomes should be identified as specific categories of failure.

In prior posts that you can read in order, here, and here, Cal Braunstein, CEO of The Robert Frances Group and I advanced the theory that some poor business outcomes could be traced to poor data quality. Our aim is to survey business and IT leaders, to find out who has experienced poor business outcomes that they know or strongly believe are traceable to poor data quality.

What is a poor business outcome in our book?

The first step to asking the right questions about poor business outcomes is to define what we mean by a poor business outcome. We don’t want to leave our survey respondents wondering whether some possibly sub-par business performance qualifies as a poor business outcome.

Here is how we think about poor business outcomes:

A poor business outcome means a negative outcome to ongoing operations, projects, planning, or reporting, for which you were responsible, involved, or made aware in the course of your work.

Further, a poor business outcome means that a client was lost, a supplier disengaged, an employee resigned, an operations metric or service level objective was missed, a project was delivered late, with low quality or incorrect features, a plan or strategy based on flawed data was abandoned, or similar sub-par outcome.

As a result of the poor business outcome, our survey respondents may have suffered a career setback (missed a bonus or promotion, received a reprimand, a demotion), and/or their organization may have suffered (reputation damaged, stock price reduced, analyst rating declined, customers lost), or both.

We will instruct our survey respondents to answer a survey question in the affirmative if they know or strongly believe the poor business outcome was substantially due to poor data quality, and that the poor business outcome would have been avoided, or detected and corrected if the poor data quality situation did not exist.

 The Bottom Line

We are focused on developing, delivering, and analyzing a poor business outcomes survey that produces meaningful and actionable results for our sponsors and our readers. This blog series has presented, and will continue to present our progress toward fulfilling our poor business outcomes – poor data quality research.