Data quality and Paleolithic Rhythm


Early in the terrific book What Technology Wants by Kevin Kelly, he discusses the concept of Paleolithic Rhythm, which describes the short bursts of intense effort followed by long periods of rest employed by the hunter-gatherer tribes of early humans during the Paleolithic Era.

Paleolithic Rhythm is also an apt analogy for how many organizations approach data quality. The majority of data quality initiatives are reactive projects launched in the aftermath of an event when poor data quality negatively impacted business performance. Some examples include a customer service nightmare, a regulatory compliance failure or a financial reporting scandal. A common response is data quality suddenly becomes prioritized as a critical business problem and a temporary tribe is gathered to hunt for a short-term data solution.

These reactive data quality projects are a business triage for the most critical data issues that simply can’t wait for the effects that would be caused by implementing a proactive data quality program, which may have prevented the data-related business problems from happening in the first place.

However, these short bursts of intense data quality efforts are often followed by the organization taking a long period of rest in regards to ongoing data quality management. In other words, when the project is over, the data quality hunting party disbands and returns to their previous activities only to be forced into triage once again when the next inevitable crisis occurs where poor data quality negatively impacts business performance.

The short-term reactive cycles of Paleolithic Rhythm were eventually replaced by the long-term proactive cycles of agriculture, and nomadic hunter-gatherer tribes eventually evolved into sedentary agricultural societies.

Just as agriculture became a key component in the evolution of human culture, every organization must evolve its data quality culture by supplementing short-term reactive projects with long-term proactive practices. This plants the seeds of a high-quality data agriculture that consistently yields a bountiful harvest of business success.

Does your organization still approach data quality with a Paleolithic Rhythm?


About Author

Jim Harris

Blogger-in-Chief at Obsessive-Compulsive Data Quality (OCDQ)

Jim Harris is a recognized data quality thought leader with 25 years of enterprise data management industry experience. Jim is an independent consultant, speaker, and freelance writer. Jim is the Blogger-in-Chief at Obsessive-Compulsive Data Quality, an independent blog offering a vendor-neutral perspective on data quality and its related disciplines, including data governance, master data management, and business intelligence.

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