Data governance drives trust in decision-making (Image Credit: rishi on Unsplash)“Data quality and data governance, key components for achieving data integrity, work together to enable businesses to understand and trust their data for confident decision-making.” That is the conclusion from the latest Precisely report created with Drexel University’s LeBow College of Business (LeBow).

Titled Data Professionals Speak: Trends in Data Governance and Data Quality Programs, the report runs to 22 pages and makes interesting reading. Among the conclusions are that 75% of respondents say data quality is a top goal. Yet despite this, 39% of organizations don’t measure quality across the organization. It shows the problem of setting goals if you have no KPIs or measurement processes.

Emily Washington, Sr. Vice President, Product Management
Emily Washington, Sr. Vice President, Product Management

Emily Washington, Senior Vice President of Product Management at Precisely, said, “Data quality and data governance, key pieces of data integrity, work together to enable businesses to understand and trust their data for confident decision-making.

“This report with LeBow uncovers how data governance strengthens data quality. It also provides fascinating insight into the choices that organizations are making today and assesses which ones are the most effective in charting a path to data governance maturity and, ultimately, to achieving data integrity.”

Some key findings from the report

The key findings from the report show that there is a recognition of the need for better data quality. It also shows that the biggest inhibitor is cultural awareness within business. The findings also found that while an increasing number of organizations have data governance, not all are actively investing in it.

Some of the key numbers are:

  • 75% say improving data quality/trust is the leading goal of data programs
  • 83% with mature data governance programs see value in improved data quality
  • 65% are looking to data programs for better decision-making
  • 64% of responding organizations have an ongoing data governance program
  • 82% agree that data governance requires a framework of policies, people, & processes
  • 49% say their data governance programs are jointly led by business and IT
  • 63% say cultural awareness and adoption are the leading obstacles to data governance
  • 57% of organizations represented have a dedicated data governance budget

What do organizations mean by data governance?

One of the big points of this report is the breadth of understanding of what data governance needs. It shows there is widespread acceptance around the need for both policies and a framework in addition to other measures. Those include:

  • Building a set of policies that govern the organization around data (81%)
  • Building a framework of people and processes responsible for data (82%)
  • Ensuring data usage follows detailed rules (72%)
  • Understanding data quality (70%)
  • Understanding data flows across the organization (68%)
  • Building a business glossary (57%)

The creation of a set of policies ensures that data governance and regulatory compliance are looked at in tandem. While they are separate functions managed by different groups, they impact each other. It is also important that the two operate separately, with the heads of both (CDO and CISO) being equivalent to each other. That may mean representation at the c-suite or reporting to different individuals on the board.

Who is responsible for data governance?

63% of respondents say they have a dedicated data governance office. Does that mean they have a Chief Data Officer (CD) heading up that team? No, and it seems that it was not asked in this report. Having a CDO shows a level of maturity for organizations. It means they already see data as an asset rather than a by-product of IT, something that Amy O’Connor, Chief Data and Information Officer at Precisely, called out in this podcast.

While the data governance office has lead responsibility for data governance (63%), IT (45%) also plays a role. What is not clear is if that role is primarily in the technical implementation of policies and processes. That is likely the case for many organizations, but smaller organizations may see this differently.

Interesting, other teams also believe they have a role to play. Analytics/BI teams (38%), risk and compliance (31%), as well as operations (19%) and finance (16%), also claim some responsibility.

For each of these teams, data quality is important in their decision-making. Among the business benefits this report calls out are:

  • optimizing data for operational efficiency (66%)
  • Using data and analytics to drive new business models (63%)
  • Mitigating regulatory and compliance risks (53%)
  • reducing costs (50%)

Data governance is not the same as regulatory compliance

It is good to see this report split out data governance and regulatory compliance. They are not the same thing even if both seem to be an IT function and impact each other.

The report shows that responsibility for regulatory compliance sits mainly with IT. However, different sizes of organizations involve other teams in the compliance discussion. Analytics/BI (small), data governance office (midsize) and risk and compliance (large) all have a part to play.

Having a risk and compliance team and not giving it control over regulatory compliance makes little sense. As with data governance, the role of IT should be to implement policies and processes, not to interpret compliance rules. In many organizations, however, it is the role of the CISO that creates a challenge. The CISO is seen as responsible for compliance and in charge of IT. As such, the two get conflated. But is this right? It is being increasingly challenged at large organizations and is beginning to change.

Measuring your data governance

To know how effective you are, you need a way to measure and monitor. In the case of data governance, 39% of organizations do not measure data governance. The question is, why?

The report attempts to address this from a tools perspective. For example, it finds that of the 64% that have deployed data governance programmes, only 43% have data governance software. Part of the issue here is cost. Larger organizations are more likely to have the right software. Is this an industry failing? Are data governance tools vendors failing to address the wider market? Where are the open-source tools that we would expect to fill such a gap?

Data governance is not the only problem. Software tools for data quality, catalogue and preparation are even less likely to be deployed. It seems that there is more talk than delivery happening here.

This is even more confusing because 66% of respondents say improved data quality is a major benefit from data governance programmes. It is the number one gain from organizations of all sizes. It’s hard to see, therefore, why organizations are not investing.

Of interest here is that 51% of c-suite respondents cited a lack of effective management tools as an obstacle. Given this, why is the c-suite not providing more money for investment in tools? It cannot be because the c-suite doesn’t see the value of data governance, because all the evidence from this report is that it does. It is something worth investigating in any future report.

Dealing with the culture clash

Like cybersecurity, the biggest internal challenge for data governance is culture (63%). The question is, where does this cultural problem come from? It appears that there is plenty of executive support, with just 18% citing its lack as an issue. For its part, none of the respondents from the c-suite saw a lack of support as an issue.

Does that mean the problem is in widespread training? There will certainly be an element to that. But organizations have invested heavily into cybersecurity and compliance, areas that overlap data governance. If training and staff awareness are still a problem, organizations need to rethink their training processes.

Two things do jump out from this report, and they are not about training or the c-suite. Understanding the right organizational approach (45%) and organization support (39%) are about middle management and engagement. It is about getting managers to understand how this will impact them and the benefits it brings for their departments.

Yet, as already stated, the report shows that organizations are aware of the benefits they get from data governance. So why are there organizational issues? Unfortunately, there is no detail on this, which is disappointing. Perhaps a set of qualitative interviews would have given greater insight.

Enterprise Times: What does this mean?

There is a lot more in this report than we’ve covered here, and it is worth a read. What it does show is that data governance is now being taken seriously and delivering where it is allowed. The report also shows that there is more to be done, and this is much more than just having a mature approach.

Organizations are continuing to acquire data faster than at any point in history. Getting anything, let alone the most, out of the data takes the right approach and processes. This report shows that the best performing organizations have established data governance offices and likely have a CDO. It gives them someone to drive the need for data governance forward at all levels of the business.

The big takeaway from this report is that the biggest benefit from data governance is data quality. If businesses are going to get the most value from their data, they need to start with data governance and use that to drive new business cases.


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