The First Law of Data Quality explained the importance of understanding your Data Usage, which is essential to the proper preparation required before launching your data quality initiative.
The Second Law of Data Quality explained the need for maintaining your Data Quality Inertia, which means a successful data quality initiative requires a program—and not a one-time project.
The Third Law of Data Quality
“Data quality is everyone's responsibility.”
Data quality is neither a business issue nor a technical issue—because it is both.
Data quality initiatives require the collaborative effort of business and technical stakeholders working together. A true collaboration is built on accepting shared ownership of the challenge as well as shared responsibility for its success—or failure.
What happens when data quality is not viewed as a shared enterprise-wide responsibility and an incident occurs when poor quality information undermined a critical business decision?
In most organizations, the answer is a good old-fashioned blamestorming session.
Yes, blamestorming can feel very cathartic.
Sometimes, it seems like nothing brings a group closer together than when they are pointing their collective finger at another group, or at an individual stupid enough not to attend the blamestorming session—and sometimes the designated scapegoat is accidentally on purpose not invited to the meeting.
However, these sessions don’t help the organization move forward, don't help minimize the likelihood of similar incidents recurring in the near future, and don't foster any true sense of teamwork (except among those on Team Not Our Fault).
Many data quality issues are caused by a lack of data ownership and an absence of clear guidelines indicating who is responsible for ensuring that data is of sufficient quality to meet the daily business needs of the enterprise.
However, establishing data ownership and defining data quality standards and guidelines is not about predetermining who to blame if something goes wrong.
Blamestorming is all about the traditional definition of CYA. Forget that definition. Your organization needs to redefine CYA as Collaboration Yields Accountability.
Business stakeholders usually own the data because they are more closely aligned with its meaning and daily use within a business context.
Technical stakeholders usually own the data quality processes because they are more closely aligned with the daily management of the enterprise architecture.
However, everyone—regardless of their primary role or job function—must accept their personal responsibility in both preventing data quality issues and responding appropriately to mitigate the associated business risks when issues do occur.
Collaboration yields accountability for collective ownership of the current data quality issues as well as collective responsibility for resolving them.
It's NOT a cliché
Assuming that it is someone else's responsibility is a fundamental root case for your organization's data quality problems.
The need for collaboration among all business and technical stakeholders is so obvious that it has become a cliché.
Clichés are universal truths that have become universally ignored.
Data quality is everyone's responsibility.
It's NOT a cliché. It's NOT a slogan. It IS the law.
More specifically, it's The Third Law of Data Quality.