Data governance programs are becoming more popular and important, but how do you know if your program is delivering the business value that it promises?
Why do companies implement data governance programs?
Data governance programs are implemented to ensure that the right data is being used in the right place at the right time. This means that the business can make better decisions, increase efficiency and improve customer experience.
Data governance programs also help organizations improve their ability to analyze and use data for competitive advantage by ensuring:
Data is accurate, complete and consistent.
Data isn't duplicated or lost from one system or process to another.
Data is secure and properly protected against threats to privacy (including accidental disclosure).
What is needed to create a successful data governance program?
Data governance programs need to be driven by business requirements and not by technology needs.
A data governance program needs the right people and processes in place to be successful, including:
The program sponsor
A steering committee or governance council, which may include representatives from business functions like finance, legal, and IT as well as other key stakeholders such as the data steward community (e.g., data stewards) or a Data Governance Office (DGO). The DGO would also have responsibility for leading overall strategy development related to data lifecycle management initiatives.
The roadmap should have clear deliverables so that everyone knows what the goals are and how they will be achieved over time. There should be regular communication around progress made on each deliverable so that others can understand what’s being worked on and why it matters for them personally/to their organization to everyone else participating in this overall effort going forward.
Despite its importance for businesses today, many organizations still struggle with implementing effective data governance programs due to various reasons. Here are some examples:
Political impediments:
Political impediments are the most common and challenging type of roadblock. They arise from a lack of understanding, a lack of consensus and support, or an outright disagreement between groups.
Aversion to change:
One of the most common reasons why data governance programs fail is resistance to change. As anyone who's ever tried to organize a closet, declutter their email inbox or start a new workout routine knows, people are often resistant to change.
Lack of accountability:
Lack of accountability is another common problem with data governance programs. When you have a big project, you need people to take responsibility for their parts of it. If they don't, the whole project can fall apart or not work as well as it should.
Wavering organizational priorities:
As the business environment changes, so do organizational priorities. This means that data governance programs may get abandoned or not delivered in a timely fashion.
Immature issue and risk management capability:
Lack of training for both IT and business users on how to use the tools needed to support DG programs, for example, data governance dashboards.
Dearth of skilled DG resources
Data Governance teams should have a mix of skills and experience. In addition to data management, data analytics, business and domain knowledge, you’ll also need people with project management skills who can lead the development of tools and processes that help your organization make better use of its data.
Inability to communicate tangible business value
One of the reasons data governance programs fail is an inability to communicate tangible business value. Data Governance is important because it helps the business be more efficient and effective, make better decisions and avoid costly mistakes. Yet many organizations struggle with getting buy-in from senior management when it comes to investing in these programs.
We have developed a proprietary framework and methodology to help you understand how your data governance effort is performing, and where you can improve.
Our methodology is based on the best practices of data governance as well as our experience with several clients across all industries. Our framework is based on the best practices of data governance, which were identified by analyzing thousands of projects across multiple industries.
Our approach was developed in partnership with leading academics and practitioners in this field to ensure we are leading edge while being grounded in solid research.
Our approach provides a repeatable, effective way to measure the business value of your data governance program, understand the ROI for your efforts, and compare the effectiveness of different organizations.
The following steps will help you determine whether your organization is getting a good return on investment from its data governance program:
Define success criteria (e.g., increase market share by 10%).
Compare this to current performance levels, or where they want to be in 3 years time (e.g., increase market share by 10% within 3 years).
Use these metrics to identify areas where there might be improvement opportunities (such as improving processes or policies).
Conclusion
We believe that data governance is a critical component of an organization's data strategy. Our approach provides a repeatable, effective way to measure the business value of your data governance program, understand the ROI for your efforts, and compare the effectiveness of different organizations.
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