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Best Way to Reduce Data Governance Resistance

Have you ever wondered why the most brilliant data governance implementations don't reach their full potential? The answer often has more to do with people resisting the new technology, not the technology itself!

I agree that this is not shocking news. What is shocking is that most data managers know this and just don't know how to address it.

The best way to reduce data governance is simple ─ focus your efforts on influencing the people who have to adopt the new technology or solution.

For that to happen, everyone (managers and staff) needs to shift from "my data" and "my way" to "our data" and "our way."
Thinking a New Way
The shift from "my data" to "our data" is not a slogan; it is a shift in how people view themselves, their data, and their role in the company's data quality.

Think about how the solution will impact each of the roles and groups of people. Consider what they need to hear to overcome the natural resistance to change and embrace the new solution; and who would most effectively deliver those messages, such as managers, executives, or subject-matter experts. You must find ways to motivate people to be involved, give them opportunities to take ownership of the data, and then adopt the new solution.

Focusing on People: A Case Study
Let's take one simple example of creating enterprise-wide definitions for well attributes. An oil and gas client created a new data governance team tasked with drastically improving data quality, so people trusted the data and made better decisions.

To do this, they started by establishing enterprise-wide definitions. Our client's new data governance team brought representatives from every business unit together in a conference room. No matter what the term - whether it was "first production date" or "spud date" - there was little agreement. It quickly became apparent that there were many different definitions. Some business units even had two answers driven by different management groups.

This also meant the client couldn't make trustworthy decisions about any other data attributes. This realization brought new meaning to the concept of "data-driven decisions."

Over the next several months, the data governance team ended up sitting in that conference room with their business counterparts and defining hundreds of terms. As they worked through the definitions, they built a team, appreciated how each business unit was different and learned how to collaborate so that the data worked for everyone. Then the business representatives reviewed every definition with key subject-matter experts (SME's) in their business unit. This elevated the way their business colleagues viewed them. It also engaged key people within their business unit. Any concerns raised were eventually resolved in the conference room.

Once the team reached an agreement on the definitions, they used the same process to build rules for each definition, such as minimum and maximum ranges for the input, or the best options for a drop-down menu that would satisfy all the business units.

It took a long time. Sure, it would have been much easier just to give them the best industry definitions and rules; but, it was so worth it. Our client now had a data governance team who had new insight into differences between the business units. The team created a partnership with business representatives who were data leaders for their business. Silo walls were disappearing within the business unit and across units. The business reps saw how they were making a difference for their business and their company by being stewards of their business data, building their motivation and commitment. Moreover, the business representatives created a partnership with the SME's in their business unit who were also becoming champions for this new way of working with and thinking about, their business unit's data. Our client was building a key group of "influencers."

Results from Focusing on the People
There was finally the ownership of the definitions and rules within each business.

As business rules were implemented, the business representatives facilitated the data correction within their business. Business staff corrected data that failed to meet the rules and started to focus on data quality at the time of entry.

Everyone gradually gained more trust in both the data and each other.

Most importantly, resistance to the new data governance solution - roles, processes, systems, and tools - was significantly reduced.

Let us know
What do your stakeholders need to commit to the new way of working; and how will you engage them so they will change how they think and work?

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