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JUN 23, 2011 8:57am ET

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Stuck in the Middle with Data Governance

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Perhaps the most common debate about data governance is whether it should be started from the top down or the bottom up.

Data governance requires the coordination of a complex combination of a myriad of factors, including executive sponsorship, funding, decision rights, arbitration of conflicting priorities, policy definition, policy implementation, data quality remediation, data stewardship, business process optimization, technology, policy enforcement – and obviously many other factors as well.

This common debate is understandable since some of these data governance success factors are mostly top-down (e.g., funding), and some of these data governance success factors are mostly bottom-up (e.g., data quality remediation and data stewardship). However, the complexity that stymies many organizations is most data governance success factors are somewhere in the middle.

Stuck in the Middle with Data Governance

At certain times during the evolution of a data governance program, top-down aspects will be emphasized, and at other times, bottom-up aspects will be emphasized. So whether you start from the top down or the bottom up, eventually you are going to need to blend together top-down and bottom-up aspects in order to sustain an ongoing and pervasive data governance program.

To paraphrase The Beatles, when you get to the bottom, you go back to the top, where you stop and turn, and you go for a ride until you get to the bottom – and then you do it again. (But hopefully your program doesn’t get code-named “Helter Skelter”)

But after some initial progress has been made, to paraphrase Stealers Wheel, people within the organization may start to feel like we have top-down to the left of us, bottom-up to the right to us, and here we are – stuck in the middle with data governance.

In other words, although data governance is never a direct current only flowing in one top-down or bottom-up direction, but instead continually flows in an alternating current between top-down and bottom-up, when this dynamic is not communicated to everyone throughout the organization, progress is disrupted by people waiting around for someone else to complete the circuit.

But when, paraphrasing Pearl Jam, data governance is taken up by the middle – then there ain’t gonna be any middle any more.
In other words, when data governance pervades every level of the organization, everyone stops thinking in terms of top-down and bottom-up, and acts like an enterprise in the midst of sustaining the momentum of a successful data governance program.

Data Governance Conference

Next week, I will be attending the Data Governance and Information Quality Conference, which will be held June 27-30 in San Diego, California at the Catamaran Resort Hotel and Spa.
If you will also be attending, and you want to schedule a meeting with me: Contact me via email
If you will not be attending, you can follow the conference tweets using the hashtag: #DGIQ2011

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Comments (1)
I suggest the most common debate about data governance is "what is it"? Data governance is beginning to resemble a discussion about democracy and the question "what is the essence of democracy".

Top down, bottom up and inside out are all esoteric conversations about a concept that has no common meaning. We've had corporate governance and enterprise architecture which are equally ill defined so why spend all this time debating how to deploy a concept no one has yet defined in a consistent way?

Why not just deploy data management best practices and leave the debate on data goverance to politicians?

Posted by Richard O | Monday, June 27 2011 at 10:50AM ET
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Blog Archive for Jim Harris

Pondering a Big Data Philosophy
Galileo, the Hubble and Clear Data Insight
When Poor Data Quality Lands on the Ledger
Poor Data Quality That Kills
Data Quality and the OK Plateau

More from Jim Harris »

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