Data Governance and the Buttered Cat Paradox

Buttered Cat Paradox
Buttered Cat Paradox

One of the most common questions about data governance is:

What is the best way to approach it—top-down or bottom-up?

The top-down approach is where executive sponsorship and the role of the data governance board is emphasized.

The bottom-up approach is where data stewardship and the role of peer-level data governance change agents is emphasized.

This debate reminds me of the buttered cat paradox (shown to the left as illustrated by Greg Williams), which is a thought experiment combining the two common adages: “cats always land on their feet” and “buttered toast always lands buttered side down.”

In other words, if you strapped buttered toast (butter side up) on the back of a cat and then dropped it from a high height (Please Note: this is only a thought experiment, so no cats or toast are harmed), presumably the very laws of physics would be suspended, leaving our fearless feline of the buttered-toast-paratrooper brigade hovering forever in midair, spinning in perpetual motion, as both the buttered side of the toast and the cat’s feet attempt to land on the ground.

It appears that the question of either a top-down or a bottom-up approach with data governance poses a similar paradox.

Data governance will require executive sponsorship and a data governance board for the top-down-driven activities of funding, policy making and enforcement, decision rights, and arbitration of conflicting business priorities as well as organizational politics.

However, data governance will also require data stewards and other grass roots advocates for the bottom-up-driven activities of policy implementation, data remediation, and process optimization, all led by the example of peer-level change agents adopting the organization’s new best practices for data quality management, business process management, and technology management.

Therefore, recognizing the eventual need for aspects of both a top-down and a bottom-up approach with data governance can leave an organization at a loss to understand where to begin, hovering forever in mid-decision, spinning in perpetual thought, unable to land a first footfall on their data governance journey—and afraid of falling flat on the buttered side of their toast.

Although data governance is not a thought experiment, planning and designing your data governance program does require thought, and perhaps some experimentation, in order to discover what will work best for your organization’s corporate culture.

What do you think is the best way to approach data governance?  Let’s conduct an unscientific data governance poll:

What is the best way to approach Data Governance?online surveys

Additionally, please feel free to post a comment below and explain your vote or simply share your opinions and experiences.

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