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How to Achieve Cross-Functional Collaboration in Data Governance

Last updated: October 7, 2024

Wondering how to unlock the full potential of your audience data? Are you struggling to institute the organizational culture you need to keep your audience data safe?

To help you address these issues, Bettina Lindner Lippisch, Omeda’s VP of Privacy and Data Governance, has created a multi-post series on how to create a data governance program that protects your business and helps drive results.

In Part 1 of this series, Bettina discussed the relationship between privacy, data governance and CDPs and how each of these elements contribute to a solid strategy.  

Part 2 focuses on the importance of collaboration in building your data governance program. Data governance cannot thrive in isolation. It requires active participation from every corner of your organization. In this article, we’ll delve into actionable steps to create a cross-functional data governance program that serves your company and clients effectively.

Upgrade your privacy game: Watch the webinar with our VP who shares crucial security insights:

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Step 1: Assess Your Current Data Literacy and Data Governance Maturity

Before you begin, take some time to understand your organization’s current data governance landscape. Even if you currently do not have a formal data governance program in place, having a baseline grasp of your data assets, ownership, access, and existing policies is essential to tailor your future actions effectively.

Identify Business Goals and Challenges

Engage with business leaders, executives, and the board to document your company’s primary data-related goals and challenges. Recognize areas of concern such as risk of data breaches, data inaccuracy, outdated customer data, or missing insights in the sales pipeline. Also, explore hidden data assets that might hold untapped potential.

Take Inventory of Your Data

A good starting point is for your IT or Data Team to identify the systems and repositories handling data. But don’t forget that data might reside in unexpected locations, like historical HR records stored on a local drive, or paper invoices received by finance filed away in a locked cabinet awaiting digitalization. There are many templates available online to guide your data assessment.

Data assessments should encompass at least these essential elements:

1. Data Type (e.g., Public, Private, Confidential, Restricted)
2. Data Access (who can view and edit the data)
3. Data Location (where the data is stored, e.g., U.S., Canada)
4. Data Repository (system where the data resides)
5. Data Processes and Integrations (how data is updated, appended, or moved, and the flow across repositories)

Assess Your Current State/Maturity

Evaluate your organization’s maturity in various data governance areas, including:

1. Policies: Determine if you have sufficient policies guiding data handling, privacy and security practices.
2. Training & Knowledge: Assess your understanding of data-related rules and responsibilities, as well as stakeholder knowledge of leveraging data for business success.
3. Data Quality: Analyze if your data is trustworthy, accurate, and standardized. Evaluate processes for addressing data quality issues
4. Data Processes: Review your data processes related to privacy, security and compliance, including any automated data transfers between systems that alter or consolidate data.
5. Data Intelligence: Consider how data is used for decision-making across the organization and whether it is reliable.

Identify Immediate Gaps and Opportunities

Cross-reference your baseline findings with your business goals. Using the above assessments, identify and document immediate opportunities and risks related to your data governance strategy.

Step 2: Kick-Start Collaboration

Now that you have a comprehensive understanding of your data landscape and organization’s goals, it’s time to initiate cross-functional collaboration around data governance.

Identify Champions within Each Department/Practice Area’

Recruit Allies and Advisers: Recognize individuals within each department or practice area who are passionate about data quality and compliance. 

These champions will bridge the gap between your data governance priorities and the practical needs of their teams. Share your baseline findings with them for valuable insights and validation of any assumptions you make about their area,

Create a Knowledge Base and Training Program

Provide Education on Data-Handling Best Practices: Develop a comprehensive knowledge base and training program that covers data-handling best practices. Ensure that everyone in your organization has access to this resource and uses it. Not only does this promote a shared understanding of data governance, but it also empowers employees to make informed and consistent decisions about data. Based on your maturity assessment around policy and training, prioritize high-risk policy gaps related to security, privacy and compliance — and focus on opportunities to improve data usage through training.

Treat Data Governance as a Product

• R&D Activities: Invest in research and development activities to continually improve your data governance framework. Did you learn about any data that might have been missed in providing new insights? Did you discover data that could be used to better serve your customers? Also keep an eye out for data quality issues that require fixing.
• Testing: Regularly assess and test your data governance policies and procedures to identify weaknesses and areas for improvement. Monitoring data quality should be an ongoing task for the data governance team so you can continuously improve your data integrity and quality.
• Marketing Across the Organization: Promote the value of your data and data governance program across all parts of your organization. This can be achieved by showcasing data success stories, highlighting the benefits of data governance, and demonstrating how data is enhancing decision-making or process efficiencies.
• Listen to Your Data “Users”: Treat everyone as “users” of data. Take the time to understand how each department and team uses data, what challenges they face with it, and whether they have confidence in the data for their decision-making. This insight is invaluable in tailoring your data governance efforts to meet specific needs, and also will aid you in maturing your data governance program as a whole by understanding where improvements are needed.

Partner with Technology Teams

• Catalog and Document Data: Collaborate closely with technology teams responsible for data management. Catalog and document the data and its related processes comprehensively. This documentation is the foundation of effective data governance. This should be an ongoing effort to have an up-to-date snapshot of your data inventory.
• Identify Gaps and Opportunities: Use the documentation and assessments to engage with end-users of data and their ideas and concerns. Setting up regular meetings or roundtables with data stakeholders. By involving both technical and non-technical stakeholders, data governance aligns with the broader organizational and business objectives.

Step 3: Continuous Learning and Collaboration

Don’t hesitate to seek external help and remain open to new knowledge in this ever-evolving data landscape.

Establish a Network of Resources and Partners

Extend collaboration beyond your organization by involving vendors and partners specializing in data governance and analytics platforms. It truly does take a village to build and mature a solid data governance program.

Stay Curious

In today’s dynamic data world, data governance is never truly finished. Continue educating yourself and your collaborators on emerging technologies, such as Artificial Intelligence (AI) and Machine Learning (ML), which can revolutionize how data is utilized. Don’t stop learning and listening!

Summary

Achieving cross-functional collaboration in data governance is imperative for unlocking the full potential of your data assets. By following the above actionable steps, you can cultivate a culture of collaboration, accountability, and data-driven decision-making. Remember, data governance is not a one-time project, but an ongoing journey that requires active involvement from all stakeholders. Embrace it as a collective effort to reap the benefits of effective data governance. Together, you can build a data-driven future where data governance is everyone’s responsibility, enriching your entire organization.

In the upcoming Part 3 of this series, we will explore how to measure the progress and success of your data governance so you can track your progress and impact on your organization. Stay tuned!

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