Data Governance

This content was originally featured in the March 19th, 2025 newsletter found here: INBOX INSIGHTS, March 19, 2025: Data Governance, Managing AI News

Data Governance: The Step You Can’t Skip

Picture this: Your demand gen team had just finished designing what you thought was the perfect ABM campaign. You’ve spent weeks aligning with sales on target accounts, creating personalized content journeys, and building out sophisticated trigger-based workflows in your marketing automation platform.

The day before launch, you are reviewing the final targeting parameters when you realize something concerning – you were planning to use firmographic data that had been appended by a third-party vendor six months ago, but nobody could tell you if your data processing agreement covered using that information for this specific type of outreach.

“No problem,” you thought. “Legal can give us a quick answer.”

Three weeks and seven email threads later, you discover that not only was your agreement insufficient for the planned usage, but half the data fields you had built your personalization strategy around were flagged as “questionable quality” in a data audit that nobody on the marketing team had seen.

You have to rebuild the entire campaign from scratch using only first-party data for which you have proper permissions. The delay cost you an entire quarter of pipeline generation.

Sound familiar? It happens to the best of us. So, how do we prevent this from happening? With data governance.

What Is Data Governance Anyway?

At its simplest, data governance answers three fundamental questions:

• Who owns and is responsible for the data?
• What exactly is the data (and what format is it in)?
• How can you properly access and use it?

These might seem like basic questions, but you’d be shocked at how many organizations – even sophisticated ones – struggle to answer them clearly.

The Painful Reality of Skipping This Step

Just recently, I watched a project get delayed by nearly four months because these questions weren’t addressed upfront. After extensive planning and statement of work development, the analytics team was ready to dive in—only to discover that the privacy team had concerns about customer data usage that completely contradicted the proposed approach.

Everyone had assumed someone else had checked these boxes. No one had.

The frustrating part? This was entirely preventable.

Why Does This Keep Happening?

I’ve noticed a few patterns that lead to these situations:

1. Siloed organizations: Data, analytics, privacy, and legal teams operating independently without clear communication channels
2. Excitement over results: Focusing on the exciting insights rather than the foundational elements needed to get there
3. Assumed knowledge: “Someone must have already figured this out” thinking
4. Pressure to move quickly: Skipping what seems like bureaucratic steps to show progress

Building Your Data Governance Foundation

Before you even think about that fancy machine learning model or dashboard, make sure you:

1. Identify your data stewards: Who has ultimate authority over each data source? Get them involved early.
2. Document your data inventory: What exactly do you have? Where does it live? How is it structured? What are the quality issues?
3. Establish access protocols: Who can see what data, under what circumstances, and with what approvals?
4. Clarify usage policies: What can this data be used for? Are there regulatory or privacy restrictions?
5. Create review processes: How will new data uses be evaluated and approved?

The Benefits of Getting This Right

When you invest in proper data governance upfront:

• Projects move faster overall (despite the initial time investment-trust me on this one)
• Teams avoid frustrating and expensive mid-project pivots
• Data quality and reliability improve
• Regulatory risks decrease substantially
• Cross-functional collaboration becomes smoother

Moving Forward

If you’re starting a new analytics initiative, I strongly recommend beginning with a data governance assessment. It might not be the most exciting kickoff activity, but I promise it will save you from that awful moment when someone asks, “Wait, are we even allowed to use this data?” after weeks or months of work.

And if you’re in the middle of a project that’s hitting roadblocks because of unclear data ownership or access issues? It’s never too late to pause and build that foundation properly.

Remember: the best analysis in the world is worthless if you can’t actually implement it because of governance issues that should have been addressed at the start.

Quick plug—if you want help navigating your data governance, give me a shout!

Have you experienced a project derailment due to overlooked data governance? I’d love to hear your stories and how you addressed them.

Reply to this email to tell me, or come join the conversation in our free Slack Group, Analytics for Marketers.

– Katie Robbert, CEO

Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.