Are you looking for support and sponsorship to get your data quality initiative off the ground?
This article provides some practical tips and advice for transforming data quality dimensions into engaging, customer-focused benefits instead of an endless torrent of project features that fail to engage and convert your sponsors.
Presenting Data Quality Dimensions For Impact
In the field of data quality we talk about data quality dimensions a great deal.
We frequently measure data against dimensions of accuracy, completeness, consistency, timeliness and even some more abstract dimensions – trust, believability, accessibility.
Dimensions have become a kind of “DNA” for data quality. By measuring certain dimensions we can even compare different data to see how the “quality of their DNA” compares.
I do have some issues with dimensions. I’ve witnessed practitioners and data quality vendors over-simplify their use. Poorly implemented they don’t often align with what the business really needs out of their data. However, I accept that as an aggregation tool and reporting method they do have merit.
But I digress.
My main issue with dimensions is that we often focus on the features instead of the benefits, particularly when talking to potential sponsors, managers and other stakeholders.
The Features vs Benefits Challenge of Data Quality Dimensions
What triggered this post was a white paper I read recently. Aimed at business people, this paper explained the benefits of a data quality assessment process. The paper stated that by following a structured methodology we can establish how complete, accurate, timely and consistent our data is. What I found completely missing from this paper was the focus on the end customer – the project sponsor.
Picture the scene if you will…
I’m a business manager and you’re a data quality analyst. You have the unenviable job of convincing me all this data quality voodoo is really worth the pain of me releasing budget to do “some data stuff” I assumed was already adequately taken care of.
In the mind of the business manager just trying to hit their targets, you telling me that you can help our data possess greater accuracy, uniqueness, precision, timeliness, availability, completeness and consistency is a totally alien language.
However, turn these “data related dimensions” into “sponsor related dimensions” and suddenly everything takes on a new focus.
So, you’re saying that you can HELP ME deliver more accurate decisions?
I’m skeptical but tell me more.
You can HELP ME demonstrate that my team gets its work done more timely?
Interesting, this is a common complaint against my department.
You can HELP ME create more consistency in the business services we deliver?
This sounds promising, keep going.
You can HELP ME reduce duplicated effort across my team.
You’re getting warmer.
You can HELP ME be more precise and accurate with those quarterly figures I present at the steering group?
Sold. When do we start?
Make Data Quality Dimensions Personal
See how we’ve switched those data focused dimensions to personal dimensions that push the buttons of the sponsor? It is so easy as a data quality practitioner to get lost in the features and technicalities of data quality.
Business sponsors don’t care about technicalities. They really want to know what THEY will GET with their money AFTER you’ve done all the data quality voodoo.
This quote from UK based data quality expert Kathy Hunter sums up this problem.
As Kathy clearly demonstrates, most business leaders are far more interested in what all this means to them, it’s just simple human nature.
Without any tangible benefit to sponsors it can often be impossible to release cash for improvements but isn’t it incredible how quickly organisations can find cash when corporate (i.e. personal) embarrassment is a reality?
There is always cash somewhere, you just need to discover the levers to release it.
Data Quality Dimensions Need To Be Personally Aligned
Another common mistake is to focus on how data quality will improve life for the data consumer, not the customer. In many cases, the dimensions of data quality you are aiming to improve are completely at odds to the goals of the person funding your project.
“So you want to help my team get rid of duplicate customers so they can manage service calls more effectively.
But my annual staffing budget is set by the number of customers we have on file and you’re telling me you want to eliminate that figure by 30%, what’s going to happen to my budget!
Close the door on the way out please.”
Do Your Data Quality Dimensions Pass The “So What” Test?
The next time you are about to present a bunch of data quality dimensions to a potential sponsor, ask yourself if your presentation answers two simple words.
Even if you think they are listening intently to your “features” story they will be totally focused on the personal benefits to them. Do some research, find out what emotional buttons to press and connect the dots.
If your data quality dimensions are not presented in a way that is compelling to them personally then you may be in for a long wait until a tipping point of embarrassing proportions pushes them into action.