Forty-two percent of data and analytics leaders do not assess, measure or monitor their data and analytics governance, according to a recent Gartner survey. Those who said they measured their governance activity mainly focused on achieving compliance-oriented goals.
Good data and analytics governance enables faster, smarter decisions. Organizations that want to improve the quality of their data often begin with data and analytics governance projects.
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Companies start data and analytics governance initiatives to drive better information behaviors through their policies. These policies help maximize the investment that organizations have not just in data and analytics, but also content (pictures, voice recordings, emails, etc.) coming from AI and IoT, for example. However, governance practices continue to be data-oriented rather than business-oriented.
CDOs and data and analytics leaders must ensure that their governance initiatives have concrete, measurable metrics that link data and analytics assets and initiatives to business and stakeholder value. For example, tie customer contact data quality to the percentage of customer retention in a specific market segment or percentage of revenue achieved via ecosystem partners.
Involve the broader organization in data governance
Data quality is not solely the job of the IT organization. Data governance work must rally stakeholders to the cause, and IT and the business must be clear on the roles they play. The business decides expectations for data quality, but the business also needs to understand that IT does not own data governance and is not responsible for data quality.
The key to resolving this challenge is for data and analytics leaders and CDOs to connect all governance activity specifically and directly with business outcomes and priorities.