The Business Does Not Care About Your Data Governance Initiative

As data governance specialists and consultants, we tend to think that data governance is at the forefront of everybody’s mind. After all, we are intimately familiar with the costs and risks associated with not governing data well. The harsh reality is that most of the business does not care about data governance at all, and if they do care, they are generally worried it will impact their work in a negative way.

Data quality is important. Everything starts with properly defining business terms. Data should be managed as an asset. Anyone who has done any work in the data governance discipline knows such assertions all too well. So why is it that whenever we talk to business users, we are met with blank stares in the best circumstances and outright hostility in the worst? Or, alternatively, why do some business users seem to agree initially, but back out as soon as the data governance initiative requires additional work? My hypothesis is that, ultimately, the business does not care about your data governance initiative.

Business users do not want to get suckered into extra work

The first reason is that it involves a bunch of extra work that does not seem to directly contribute to their objectives. As data governance specialists, we tend to evangelize that many of the data related roles, such as data stewards, are not full-time positions. Of course, we mainly preach to the management we are trying to convince that a data governance initiative does not need to be expensive and that it can be largely rolled out and maintained by people who are already being paid. Obviously, these people are being paid to perform certain tasks already and can be assumed not to just idly sit around waiting for additional work.

Sure, many of the cognoscenti will warn for this trap, but the people being assigned data responsibilities intuitively feel that the promised reduction in workload will probably remain theoretical in the end. Something similar often happens when people start to work part-time. After all, if no new people are being hired, how will the same amount of work be done in less time? So the data governance initiative is perceived as potentially adding a bunch of extra work for which the people doing the work will not be compensated.

The business just wants to do its job

A second reason is that the business by and large wants to do, well, their business. Maybe their business is purchasing stuff, maybe it is selling goods or services, maybe it is production, but with few exceptions, it may not have much to do with data. “But data is important!” you might argue, and you would be right. However, it is very difficult to convince business people from doing additional work if this seems relatively far removed from their objectives and needs.

Take, for example, a salesperson, who, after making a sale, needs to fill out a form or register the sale in a CRM. Based on my own experience, asking those sales people to fill out additional information at a minimum results in a lot of complaining and often requires either bribes or threats (e.g. “if you do not fill out this form, you do not get commission for the sale”). The fundamental issue, however, remains that the business users do not see how doing these extra steps helps them achieve their objectives, which results in resentment and sloppy work.

Most people in the business have no idea what you are talking about

Metadata. Lineage. Traceability. Data elements. Physical and logical data dictionaries … Data Governance folks sure love their lingo and it does wonders in alienating the business we are trying to seduce into being part of our data governance solution. This is a problem we can often face during the assessment phase. When I did my first assessment, I can still recall asking a group of business users what kind of data quality issues they faced. The first asked me what I meant with a data quality issue, which was a lucky break. Nevertheless, not seeing the opportunity that this inquisitive person was giving me, I started reciting a list of data quality dimensions, with some definitions: completeness, accuracy, consistency, timeliness … Chances are, if you are reading this, you know what they mean. On the other hand, the business user did not, but he was afraid to say so.

Another business user in this group said they had no data quality issues and that as long as people entered the right data, the right data would come out of the system. Ok, I guess?

Should we just give up then?

In the case of my assessment, I had already talked to a few other stakeholders and I knew for a fact that there were all kinds of data quality issues, so I decided to make it more concrete. This time I asked them if that meant that if they were in a meeting and different people brought reports about the same thing, they always had the same numbers. “Oh, no! Not at all, happens all the time, but that has nothing to do with data quality, but more with the perspective on the data,” which then led to a fruitful discussion about definitions, glossaries, business terms and … data quality. That is basically the first step in getting business buy-in: talk to them in language and concepts that make sense to them.

On a more general level, this also goes for the data governance initiative as a whole: instead of seeing it as your data governance initiative, make sure it is just as much, or even more so, their data governance initiative. One of the best ways of achieving this is by involving business stakeholders soon and keeping them involved throughout the process. All too often, we tell these stakeholders what we will do, maybe invite them to a workshop to pull information from them, to then confront them with a fully developed roadmap at the end. Then their management tells these key players they have no choice to do as they are told. Not only do they not care about your data governance initiative, they actively resent it.

Instead, make sure a data governance roadmap is a work of co-creation, making sure that the activities you plan to have the business do make sense to them and contribute to their objectives. Obviously, their management has a big part to play there as well. Make sure the salesperson who has to register every contact in a CRM understands how doing so not only helps the company as whole (nice, but on a personal level maybe not worth the effort), but also helps them when they later want to contact or prospect. Similarly, the investment of documenting personal or sensitive data in a data governance tool might seem as overhead when presented in a vacuum, but probably far outweighs the ongoing investment of keeping a spreadsheet on a shared drive up to date.

Finally, communicate the advantages of the data governance initiatives widely and in a context that, again, makes sense to the business. Quantify the benefits it brings, either in amounts of work saved, in extra revenue generated, in increased customer happiness … Be sure to vocally show your appreciation for the efforts business stakeholders have made in making the data governance effort a success.



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