Flexible framing: the greatest skill of a data quality manager?

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We’re in the process of trying to find a builder to complete an extension on our home. My "project" is five years overdue, behind budget and struggling with supplier issues.

What is interesting is that every builder we interview for the new build brings his own frame of reference to the table. Some builders believe we should push the planning authorities to the very edge, others believe we should play it safe.

One builder says our current plans are excellent and exactly how he would have used the available space. Another builder says we’re being too ambitious and we should scale right back.

All of these people are proficient in their field, yet have very different ideas on how the final product should be created.

In data quality we have this same challenge. I call it the personal frame of reference.

If you talk to data architects about data quality, their frame of reference will be very different to that of a data entry worker. A compliance director will have a different frame of reference to a database administrator. They will have different experiences with data, different goals and frustrations.

I believe the truly proficient data quality leaders are those who can understand these different frames of reference and adapt their language and communication to suit. If you spend some time on the data quality forums you’ll see these "frame of reference" conflicts emerging time after time.

It took me a long time to realise that conflicting points of view with data quality are not necessarily right or wrong; they’re just speaking a different language based on their frame of reference. For example, I meet a lot of consultants who complain the "business just doesn’t get it" or their boss is "obsessed with profitability." To mature as a data quality professional, you have to really invest time to understand these conflicting frames and build a model showing how they impact your projects.

Now for some homework.

On your next data quality project, identify all the different stakeholders involved and document their individual frames of reference. What language do they use? How do they describe systems and data, rules and relationships?

Make a note of their language and terminology, attitudes and frustrations. Now use this in your response to objections and questions. Perhaps create guides and presentations for them using the language they prefer.

Let me know how you get on and share your experiences in the comments below.

 

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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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