Compliance with legal requirements is the most commonly cited driver for data governance initiatives according to new research from BARC. However, this varies somewhat between regions (Europe: 64 percent, North America: 48 percent, Asia-Pacific: 30 percent). This indicates that GDPR is likely a factor in driving adoption, especially for European companies.
However, Timm Grosser, co-author of the study, warns that setting up data governance exclusively to comply with regulations runs the risk of reducing it to a restrictive procedure.
“This underestimates the value data governance can have with regards to facilitating data quality. A well-defined data governance process can help bring the perspectives of data collectors and data consumers closer together. It also contributes to better overall data quality. We observe businesses frequently underestimating the true potential of data governance beyond regulation and compliance”, said Grosser.
Differing priorities in approaches to data governance
Best practices in data governance are still developing. However, there is widespread agreement on one point: technology is not the main limiting factor. Businesses currently planning their data governance endeavor tend to focus on administrative tasks: they favor the development of a data catalog as their top-rated measure, followed by the establishment of new roles and processes. On the other hand, existing practitioners concentrate more on practical execution, such as data quality monitoring and training.
“This way of working helps generate business demand”, said Grosser. “Challenging and developing users in data governance issues is a promising approach as it addresses the most widely identified challenges today and in the future.”
Benefits of data governance
A majority of respondents (53 percent) say they have enhanced their decision-making and accomplished a unified understanding of their data. Governance measures have also helped to create the conditions for data-driven work and becoming a digital company (47 percent).
“Creating a unified understanding of data can raise the effectiveness of targeted data governance to a higher, overall strategic enterprise level and help a company along its path to digitalization,” said Grosser. “However, if these actions are predominantly targeted at the data warehouse, their achievements will be of limited usefulness. Core business processes ultimately generate business value.”
Data quality is the greatest challenge to users of data
Inadequate data quality remains the foremost challenge users face with their data. BARC’s market research and data-centered projects have shown this repeatedly for many years now. Yet it appears that the reasons for the apparent inability of businesses to cope with this problem in order to achieve continuous improvement are largely organizational.
In spite of pressing data quality issues, there is a lack of acceptance and priority for data governance at executive level and in lines of business.