Resolving data conflicts is messy but essential work, as I talked about before on this blog. Definitions drive true clarity of business purpose — they’re how we come together to create a common vocabulary, a common language.
There can be fundamental disagreements in your organization about what certain data is supposed to mean based on their varied operational perspectives. It can be hard work bringing people to a consensus on data definitions, but there’s real value in doing so. Because before you can even begin to govern, measure or optimize your data, it needs to be defined.
One way to make the task easier is to be guided by four key principles that aid conflict resolution: avoid judgment, focus on the data, question the status quo and be pragmatic.
Principle 1: Avoid Judgment
Data doesn’t have emotions. But people do.
Data definition conflicts are actually about your organization’s people, their perspectives and the decisions they make on a day-to-day basis — for example, how they do their business processes.
Data is at the heart of how many people do their jobs. This means that data is part of their professional self-identity. No particular business usage of data is “wrong.” No employee is “bad” for having a different definition. Everyone is trying to get through their day and do their work — and they’re using the data in whatever way is needed to serve that goal.
When we say things like, That’s junk data, we ignore the fact that the junk data often had (or still has) a specific business purpose that we’re not aware of. It might be misplaced and misnamed, but don’t assume that it’s bad.
It’s probably safe to say that most everyone in your organization is trying to get through their day doing the best job they possibly can. What did we learn about in kindergarten? Treat people kindly — and I might add, be kind about the way we describe other people’s data, too.
Principle 2: Focus on the data
Remember, data is a tool that we use to do our work.
When working to resolve data conflicts, it’s good to focus on the fact we’re trying to make sure everyone has the right tools for their jobs. How we describe our intent can either make or break our efforts.
Try an approach like this that puts the focus on data:
I’m not here to judge you or your business goals. I’m here to talk about the data and how it all fits together and flows.
We need the data to interoperate, and it’s not doing that right now. Let’s talk about how we can resolve this together.
It can also help to look at the actual production data to see how well it conforms to the definition, rather than relying on “how it’s supposed to work” knowledge. By focusing on the data, we are able to cut across the business processes and systems that are part of the conflict.
Principle 3: Question the Status Quo
Business vocabulary (and the data associated with it) is the cornerstone of an organization’s culture. There are legitimate business purposes for why we describe things the way we do. However, those reasons may no longer exist. Yet, we often continue to enforce legacy constraints that are no longer needed.
Here’s a conversation-starter that questions the status quo:
Our data is how we reflect our reality in our systems. If some of our reality has changed, shouldn’t some of our data change, too?
Let’s talk about how we can let go of constraints we no longer need.
This doesn’t mean the old way is wrong — it’s that we need to be willing to consider a new way.
Principle 4: Be Pragmatic
The goal is to identify a resolution that will work for the organization from an enterprise perspective.
Sometimes we need to make a decision that isn’t the 100% theoretical ideal, but it will solve the issue and allow the organization to move forward.
We’re striving for progress, not perfection, and the progress we can make will be acknowledged and — who knows? — maybe even be celebrated.
Go Forth and Resolve Data Conflicts
The resolution of data definition conflicts is a high-value activity for any organization.
Data governance professionals are uniquely qualified to facilitate resolution activities. With effective communication and a “we can do this!” mindset, your data governance team can guide the organization through its conflicting data definitions, creating a common language for enabling broad data understanding and literacy.
If you’d like to keep exploring the topic of data conflict resolution, I welcome you to download a resource I authored, Resolving Data Definition Conflicts – Principles, Process and Progress.
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