If there were letter grades assigned to businesses based on how well they manage their data, most would get a failing grade.
The average business has a data governance score of roughly 1.65 on a scale of 1 to 5, according to GovernYourData.com, a data governance and best practices site sponsored by Informatica.
The average business is not just swimming in a sea of data, it is drowning in it.
Poor data governance results in a number of issues, including not knowing what data is available to support programs and other business functions, not being able to access relevant data, making decisions based on outdated data, and failing to secure data properly.
The retail chain, Target (News - Alert), can relate to that last challenge. The company recently disclosed in its Q4 2014 earnings that a data breach last year cost the company $162 million and affected 70 million people whose personal data and credit card information had been stolen. This could have been avoided with better data governance.
“The value of having a plan around data governance, no matter how big or small, is to have a set of processes and disciplines in place to help guide you towards the appropriate business priorities and optimal solutions with a clear identification of roles,” said Rob Karel of Informatica. “Once you know that, then you can focus on the critical few. Without data governance to facilitate this process, it’s pure luck whether you get to those critical few priorities or not.”
Foundational to having good data governance in place is answering three key questions: What are the top business imperatives as defined by your most senior leadership; what organizational business processes, decisions and stakeholder (e.g., citizen, partner, employee) interactions are most important in support of these top imperatives; and what data and applications are used to support those processes, decisions and interactions?
Businesses large and small need to be asking these questions and putting in place a proper plan for data governance. Data can be a competitive edge—or a way to ruin a company. Falling on the correct side of that dichotomy largely depends on how well a company manages its data.