In a conversation with one of my technology clients on launching a Master Data Management (MDM) program, we discussed why the failure rate for such initiatives is so high. One of the reasons is that companies often ignore data governance, or it is almost always an afterthought in any customer data integration project.
It made me think that if data governance is so important—but often ignored—companies may not really understand the need for data governance.
In the face of cutthroat competition in the technology industry, deriving insights out of customer data gives companies the edge to understand and serve their customers better. But customer data is only as good as our ability to govern it. How do we define data governance, why is it valuable and what activities are carried out in a data governance process?
Let me first try to define data governance, while differentiating it from MDM, which is more tactical in nature. Simply put, data governance is a set of rules, policies and processes that maximize the value of enterprise data as an asset. Why do we need customer data governance? Some reasons are clear:
- Increased revenue. Data governance enables us to become more customer-centric. A unified definition of a customer across different parts of the company enables account managers to understand customer needs better and garner trust, thereby allowing them to introduce additional solutions and increase revenue.
- Improved customer selection and retention. Data governance allows for a more contextual and holistic view of customers, enabling marketers to improve their targeting efforts and create more efficient retention programs that improve customer experiences.
- Better risk management. A good data governance framework makes it easier to audit customer data, mitigating risks like violating customer privacy, failing to meet contractual and regulatory requirements or even dealing with high-risk customers.
- Operational Cost Reduction. Strong governance can reduce sales and marketing operational costs, in addition to lowering system costs. Companies can eliminate duplicate entries, which prevents multiple mailings or calls made to the same account. Decreased data redundancy also eliminates extraneous data systems, reducing operational cost and generating greater fiscal control.
Data governance can be enforced through data stewardship, a critical component that ensures that our decision-making capabilities are not jeopardized due to inaccurate and inconsistent data. What are data stewards’ key activities?
- Enforce data governance policies on data usage, decision rights and accountability.
- Enforce data quality processes that deal with initial data capture and ongoing data maintenance, while ensuring agreed-upon data quality metrics are regularly monitored.
- Represent and support stakeholders’ information needs in a consultative and timely manner.
- Review potential issues before they affect existing data processes and track their resolution within required time frames.
- Govern organizational relationships in the data, such as managing customer hierarchies that allow marketers and account managers to understand who their customers really are in the context of their overall organization.