If your organization is large enough, it probably has multiple data-related initiatives going on at any given time. Perhaps a new data warehouse is planned, an ERP upgrade is imminent or a data quality project is underway.

Whatever the initiative, it may raise questions around data governance – closely followed by discussions about the need to "align" with the business. Aligning data governance to business value is where many initiatives falter, because it is not always easy to demonstrate tangible value.People understandably become skeptical during this alignment stage. Why would they want an added layer of complexity and accountability when they're already stretched?

The key thing here, of course, is to confirm that the business has bought into the data initiative in the first place. If the business is being forced down the path of a new IT system that creates huge upheaval with dubious benefits, then no amount of salesmanship is likely to persuade anyone of the need to have data governance on top.

But let's assume that employees understand the overall value of the new data initiative. In this case, what can you do to show them how data governance aligns with the business?

It's not enough to say data governance is "industry best practice" or to say "all our competitors are adopting it" or "I went to a conference and everyone was doing it." There is no business value in any of those statements.

Instead, you need to look at history. The history of your organization, that is.

If you are trying to align data governance with your business, you need to present the facts about what happened in the past, prior to data governance. Then you should outline exactly how data governance will prevent a recurrence of those issues. You need to emphasise to key stakeholders not just what this alignment means to the business, but what it means to them.

In other words, your job is to tell the story of past projects (with no data governance), and explain the outcome to the stakeholders. For example:

• What was the impact of any project delays?
• Did the results satisfy business objectives?
• Was customer satisfaction affected, positively or negatively?
• Were users happy with what they received?

Be specific – because simply stating that data governance is beneficial is not enough. Many people perceive data governance as another layer of risk to manage. If you can explain in some detail how past performance in these types of projects is a strong marker for future performance, you'll stand a better chance of outlining the risk of NOT moving forward with data governance.

It is a subtle shift in tactic, but it appeals directly to stakeholders' fears. They have objectives to meet. If you can outline how past gaps in strategy negatively affected other stakeholders just like them, you're much more likely to get the thumbs-up on alignment.