Precisely: Trends in Data Governance and Data Quality

Conducted by Precisely and Drexel University’s LeBow Center for Business Analytics (LeBow), this report affords organisations without data governance, and those at the earliest stages of implementation, with reliable, data-driven reasons to invest in building or maturing a data governance program. The payoff is real and substantiated in the survey’s findings. Eight hundred and twenty-five data and analytics professionals responded to the survey.

For the purposes of this survey, maturity stages for data governance were defined as:

• Performed – Performed as part of projects, with little consistency across projects
• Managed – Performed consistently across projects within a business unit or line of business
• Defined – Performed consistently across the enterprise using established formalisms and tools
• Measured – Metrics and dashboards are used to communicate and ensure consistency across the enterprise
• Optimised – A continuous improvement program is in place

Methodology and demographics

Top three industries that responded:

• Financial services (17%)
• Healthcare (16%)
• Media & Comms (14%)

Functional roles:

• Data Manager/Steward/Architect/Analyst (40%)
• VP/Director/Manager-Line of Business (24%)
• VP/Director/Manager-IT (16%)
• C-Suite (8%)
• Other (12%

Key findings

75% said that improving data quality/trust is the leading goal of data programs and 83% with mature data governance programs see value in improved data quality.

Only 57% of organisations represented have a dedicated governance budget and 63% say cultural awareness and adoption are the leading obstacles to data governance.

The study found that responsibility for data governance was generally spread across functions.

Why organisations are investing in data programs

The most important goal for respondents' data programs was improving quality and trust, with 75% surveyed saying so.

While IT was predominantly the main function looking after data regulations, In the mid-range size of companies (500-1000), a massive 74% of IT departments were responsible for data regulations.

While 64% of organisations have deployed data governance programs, only 43% of organisations say they have deployed data governance software — meaning that 19% have a program without data governance-specific software to support it.

Adding value

Of companies over 5000 in size, 52% have a data governance programme and 27% say they are without one, as it leads to better decision making.

Across all company sizes, improved data quality emerged as the key business benefit.

in terms of the C-suite, 51% of respondents cited lack of effective management tools as an obstacle, but 0% cited a lack of executive support.

Data Governance structure

Jointly led data governance programs reported higher added value across all value drivers.

65% of organisations with 5,000+ employees have dedicated budgets for data governance.

• Centralised (34%)
• Decentralised (13%)
• Hybrid (46%)
• Don't know (7%)

Obstacles

21% of respondents report a formal training program is in place.

63% say cultural awareness and adoption are the leading obstacles to data governance.

Overall, giving business users easy access to data and integration with data quality tools lead the qualities that respondents want to see in data governance software tools.