Do you have a data quality alliance strategy?


Whether you’re embarking on a data quality mission for the first time or your presence is well known, it never hurts to have allies throughout your organization. By finding and gaining these supporters, you can gain influence and achieve your data quality goals. It may be difficult due to the many intersecting groups and initiatives, but the results are well worth the effort.

When I started working in data quality more than 20 years ago, the big problem I faced was getting traction in a small organisation. I knew we needed to make improvements, but it was hard to get the mandate from senior management.

One day I was invited to an ISO 9001 accreditation planning meeting, which I desperately tried to get out of. I just couldn’t see how improving processes and creating endless paperwork benefited my role.

However, after a few weeks into the accreditation process, it was clear that leveraging quality assurance processes was the perfect solution for getting data quality embedded within our business unit. I was able to introduce new local processes for data quality collection and reporting. Procedures for training new staff and raising skill levels were automatically improved. There were countless benefits of linking up to this QA initiative.

As my career in data quality developed, I quickly realized that just forging on with my own direction of data quality, irrespective of the other initiatives, was foolhardy.

You’ll get far more traction if you work out a quid pro quo relationship with those groups who have a company-wide remit and are building those tactical and strategic relationships you desperately need.

Your future allies are out there. Here are my suggestions on where to find them:

Six Sigma, Lean and process improvement projects

The big challenge with data quality is getting the source process overhauled when issues are found. It’s all too easy just to cleanse the data downstream, but ideally you want to be transforming legacy processes so that defects simply can’t be created.

Six Sigma, Lean and other process improvement projects are vital for this role as they often have an executive mandate to help you drive through faster change.

Human resources

While this group is often overlooked, quite often the HR team will be working towards strategic objectives that happen to align with your goals. For example, in one organisation we found that many staff were unable to reach their performance goals because they were constantly having to tackle non-value added data quality cleanup work. By improving the process, we dramatically improved team morale and they became much more efficient workers.

HR leaders often have to show they are investing in training and career development. By building a data quality education curriculum, you can also discover potential new hires internally to help fuel the growth of your team whilst helping HR hit their goals for career development.

Sales and marketing

An obvious candidate for alliance building are the sales and marketing leadership team. They will be measured on performance and any improvements you can deliver will directly benefit their operation.

For example, in one organisation we helped reduce the total number of duplicates across multiple customer databases dramatically. This actually reduced the total number of live customers, but helped the sales director understand the lifetime value of their customer segments far more clearly. Identifying quick wins like this that help the leadership team make better decisions can be invaluable for alliance building.

Here are just three examples of early alliances you can make to help accelerate your data quality presence and influence within the organisation. What others have you used? Please share your views in the comments below.


About Author

Dylan Jones

Founder, Data Quality Pro and Data Migration Pro

Dylan Jones is the founder of Data Quality Pro and Data Migration Pro, popular online communities that provide a range of practical resources and support to their respective professions. Dylan has an extensive information management background and is a prolific publisher of expert articles and tutorials on all manner of data related initiatives.

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