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SmartData Collective > Uncategorized > Resistance is NOT Futile
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Resistance is NOT Futile

JimHarris
JimHarris
6 Min Read
Resistance is NOT Futile
Illustration generated with FLUX.2 [klein 4B] via Cloudflare Workers AI.
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“Your opinion is irrelevant.  We wish to improve ourselves. 

We will add your business and technological distinctiveness to our own. 

Your culture will adapt to service us. 

You will be assimilated.  Resistance is futile.”

Continuing my Star Trek theme, which began with my previous post Hailing Frequencies Open, imagine that you have been called into the ready room to be told your enterprise has decided to implement the proven data quality framework known as Business Operations and Reporting Governance – the BORG.

Contents
  • Frameworks are NOT Futile
  • Resistance is NOT Futile
  • Avoid Assimilation
  • Related Posts

Frameworks are NOT Futile

Please understand – I am an advocate for methodology and best practices, and there are certainly many excellent frameworks that are far from futile. I have worked on many data quality initiatives that were following a framework and have seen varying degrees of success in their implementation.

However, the fictional BORG framework that I am satirizing exemplifies a general problem that I have with any framework that advocates a one-size-fits-all strategy, which I believe is an approach that is doomed to fail.

Any implemented framework must be customized to adapt to an organization’s unique culture. In part, this is necessary because implementing changes of any kind will be met with initial resistance. An attempt at forcing a one-size-fits-all approach almost sends a message to the organization that everything they are currently doing is wrong, which will of course only increase the resistance to change.

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Resistance is NOT Futile

Everyone has opinions – and opinions are never irrelevant. Fundamentally, all change starts with changing people’s minds. 

The starting point has to be improving communication and encouraging open dialogue. This means listening to what people throughout the organization have to say and not just telling them what to do. Keeping data aligned with business processes and free from poor quality requires getting people aligned and free to communicate their concerns.

Obviously, there will be dissension. However, you must seek a mutual understanding by practicing empathic listening. The goal is to foster an environment in which a diversity of viewpoints is freely shared without bias.

“One of the real dangers is emphasizing consensus over dissent,” explains James Surowiecki in his excellent book The Wisdom of Crowds. “The best collective decisions are the product of disagreement and contest, not consensus or compromise. Group deliberations are more successful when they have a clear agenda and when leaders take an active role in making sure that everyone gets a chance to speak.”

Avoid Assimilation

In order to be successful in your attempt to implement any framework, you must have realistic expectations. 

Starting with a framework simply provides a reference of best practices and recommended options of what has worked on successful data quality initiatives. But the framework must still be reviewed in order to determine what can be learned from it and to select what will work in the current environment and what simply won’t. 

This doesn’t mean that the customized components of the framework will be implemented simultaneously. All change will be gradual and implemented in phases – without the use of BORG nanoprobes. You will NOT be assimilated. 

Your organization’s collective consciousness will be best served by adapting the framework to your corporate culture. 

Your data quality initiative will facilitate the collaboration of business and technical stakeholders, as well as align data usage with business metrics, and enable people to be responsible for data ownership and data quality. 

Best practices will be disseminated throughout your collective – while also maintaining your individual distinctiveness.

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Data Governance and Data Quality

Not So Strange Case of Dr. Technology and Mr. Business

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You’re So Vain, You Probably Think Data Quality Is About You

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