5 Tips for Overcoming Data Quality Growing Pains

Transient

I'm sure that many of you are at the start of your data quality journey.

One of the biggest problems you will no doubt face is overcoming the early Data Quality growing pains that come with trying to convince your organisation of the need to get started and commit to data quality improvement.

Nigel Turner, who led a data quality team that delivered over half a billion pounds of data quality benefits whilst at BT and is now VP Information Management Strategy at Trillium Software, cited these tips that directly help organisations get through the growing pains of early data quality initiatives.

Tip #1: Start small, focus on key problem areas by improving data and associated processes

It’s often tempting when you download resources to create a data quality methodology to create huge, all encompassing plans for your organisation.

This often has a detrimental effect because the "powers at be” can be alarmed at what they will perceive yet another cost centre emerging.

By starting small and generating tangible value across a well defined problem area you can get far more traction for gradually piecing together your enterprise plan.

Tip #2: Don’t start any data quality project unless it has a clear business owner and business case

There are different schools of thought here.

Sometimes the only option is to go guerilla to mature data quality but everyone will agree that you still need a metrics based data quality business case and stakeholder for long term success. 

Even if your project stakeholder didn’t request one it still makes sense to master the art of creating a compelling data quality business case just in case there is a change of leadership down the line.

Tip #3: Data quality is not an end in itself but part of a wider improvement strategy that can always add value to the bottom line

The truth is that it doesn’t matter what you call your data quality initiative. What really matters is getting initial approval from sponsors, getting started and getting results. The easiest way to get your initiative off the ground is to align to wider improvements within the organisation that already have financial and executive commitment. It’s much easier to get buy-in for data quality when you can demonstrate how your initiative will help accelerate and de-risk someone elses project.

Tip #4: Prove the efficacy of your structure, approaches, methods and toolsets constantly

So you’ve had some success, great but don’t rest on your laurels, now is the time to constantly communicate your effectiveness. There are constant changes of leadership within any organisation so ensure that your communication and engagement across the organisation is continuous. Don’t become blinded by delivery, you need to constantly sell the value of your services.

The key to making data quality interesting is storytelling. Learn how to turn your case studies into compelling data quality stories that make sense to different audiences.

Tip #5: When faced with resistance you can’t overcome, move on and focus on more receptive and natural early adopters

You can often spend years trying to persuade a sponsor to come onboard and this can become a frustrating experience and stifle momentum. Find more receptive managers who are perhaps more open to trialling new techniques to break through their own performance obstacles. 

By constantly trying to push stakeholders to come onside you can reduce morale and stifle your own results so always create a pull for data quality by working with receptive sponsors who can then help you pull previously cautious managers in your direction.

What are some of those "Data Quality Growing Pains” that you’ve experienced? How did you overcome them?

Please post your comments below.


Nigel Turner

Nigel Turner