The Data Quality of Dorian Gray
Jim HarrisThe Picture of Dorian Gray was a 19th century novel written by Oscar Wilde, which told the story of a young man who sold his soul to remain forever young and beautiful by having his recently painted portrait age rather than himself. One of the allegories that can be drawn from the novel is our desire to cling, like Dorian Gray, to an idealized image of ourselves and of our lives.
I have previously blogged that when an organization’s data quality is discussed, it is very common to encounter data denial.
This is an understandable self-defense mechanism from the people responsible for business processes, technology, and data because of the simple fact that nobody likes to be blamed (or feel blamed) for causing or failing to fix data quality problems.
But data denial can also doom a data quality improvement initiative from the very beginning.
Of course, everyone will agree that ensuring high quality data is being used to make critical daily business decisions is vitally important to corporate success. However, for an organization to improve its data quality, it has to admit that some of its business decisions are mistakes being made based on poor quality data.
But the organization has a desire to cling to an idealized image of its data and its data-driven business decisions, to treat its poor data quality the same way as Dorian Gray treated his portrait—by refusing to look at it.
However, The Data Quality of Dorian Gray is also a story that can only end in tragedy.
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Reader Comments (5)
Well put, Jim! I bring up the Dorian Gray analogy frequently.
Just because you can't see change (or data degradation) happening, doesn't mean it's not going on.
From your post "Of course, everyone will agree that ensuring high quality data is being used to make critical daily business decisions is vitally important to corporate success. However, for an organization to improve its data quality, it has to admit that some of its business decisions are mistakes being made based on poor quality data."
In communicating with the Business it may be helpful to describe their "mistakes" as "errors in judgment" since although the meaning is the same, the message is softer.
From your post "But the organization has a desire to cling to an idealized image of its data and its data-driven business decisions, to treat its poor data quality the same way as Dorian Gray treated his portrait—by refusing to look at it."
Keep in mind the most probable results for the organization is what actually happened in the end of the Dorian Gray story. He eventually killed himself by trying to destroy the painting (i.e., the data):
"In a rage, he picks up the knife that killed Basil Hallward and plunges it into the painting. His servants hear a cry from inside the locked room and send for the police. They find Dorian's body, stabbed in the heart and suddenly aged, withered and horrible. It is only through the rings on his hand that the corpse can be identified. Beside him, however, the portrait has reverted to its original form."
From the LinkedIn Group for TDWI, Guillermo (Bill) Cabiró commented:
“You have a very good point. I think data quality is the weakest link (constrained resource) in today's sophisticated BI environment. I’ve seen errors in business data cause widespread inefficiencies, misleading management into potentially expensive decisions.
Many folks recognize the transactional data has plenty of errors, at least at the customer, product line, brand, market and segment level, but they never get fixed and, even worse, they populate BI systems.
Marketing and Sales people think this is an IT problem and expect the data warehouse analysts to fix it, while IT thinks it’s a business problem and expects Sales or Marketing to take action. The result is that data seldom gets corrected, people give-up, and running raw or bad data through sophisticated BI systems becomes the norm.
After a while, Sales and Marketing people don’t see the value of BI, quit using the system and continue making decisions the old fashion way: based on intuition.
My experience tells me that the solution should be a partnership where IT owns the physical aspects of the data, (storage, security, format, connectivity, etc.) while the different areas of the business own the structure and meaning of their data, as well as its cleanness, maintenance, and quality.”
Dorian Gray's denial is a great analogy for the majority of organization's treatment of data quality.
It really is too bad that qualification of data is treated as a judgment rather than just a measurement of today's situation.
If the data quality metric could be treated as a baseline, "from which to aspire", it might make the improvement steps seem more like goal affirming rather than painful Botox treatments. :)
Thanks everyone for your comments, your feedback is always greatly appreciated.
@Gwen — Yes, change is the only universal constant, and therefore the organization must be willing to face the reality of its current data quality—as well as continue to monitor its data quality over time.
@Ira — Thanks for completing the metaphor of the most probable results for the organization by explaining what happened to poor Dorian Gray at the end of the Oscar Wilde novel :-)
@Bill — Thanks for providing some excellent points from the BI perspective.
@Gordon — Great point, especially the Botox analogy since a more modern rendering of the Oscar Wilde novel might be The Cosmetic Surgery of Dorian Gray :-)