Key Takeaways
- DATAVERSITY’s Women in Data Management and Governance (WDMG) community recently hosted The Data Governance Challenge, an interactive online workshop where attendees tackled realistic governance issues.
- Participants in the challenge proved that success comes from applying data governance principles to real-world business constraints rather than pursuing theoretical perfection.
- Winning teams built their data governance strategies on existing operations rather than proposing new systems.
- To win data governance buy-in, attendees emphasized the importance of speaking to stakeholders and other audiences in their language.
What Is the Data Governance Challenge?
Organizations have access to abundant data governance best practices and theory, yet implementation remains a persistent challenge. The gap isn’t knowledge; it’s application. What appears effective in data governance frameworks often falters when confronted with scarce resources, competing business priorities, and organizationally change-resistant teams.
The critical need is not more best practices, but the ability to translate data governance principles into actionable strategies that deliver data quality within real business constraints.
To start bridging this gap, DATAVERSITY and its Women in Data Management and Governance (WDMG) community recently hosted an interactive online workshop called The Data Governance Challenge. The half-day event brought data professionals of all levels together, challenging them to move beyond theoretical frameworks and develop practical solutions that could win executive buy-in and drive enterprise engagement.
A Workshop to Spur Action
The Data Governance Challenge emerged from conversations about what data professionals actually need: opportunities to practice advocacy and problem-solving in realistic scenarios. Shannon Kempe, chief digital officer of DATAVERSITY, structured the event to combine collaborative problem-solving with practical skill development. Based on feedback from webinar attendees and WDMG advisory board members, Kempe focused on two common struggles: how to convince executives to support data governance initiatives and encourage team members to embrace them. With this framework, DATAVERSITY put the event together.
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Advancing Expertise with Two Messy Real-World Scenarios
The event started with an opening keynote, “From Overlooked to Indispensable: How to Get Buy-In on Data Quality.” Here, Renee Colwell, global data quality lead at Revantage, encouraged participants to “pick something and zero in on it” and to “move fast and fix things.” This advice set the tone for the challenge: practical and action oriented.
During the event, attendees teamed up to tackle one of two scenarios:
Executive Advocacy Scenario: Teams competed to secure executive buy-in for a foundational data governance program at a struggling retail business. The company had difficulty with:
- Decreased customer satisfaction
- Increased returns
- Audit flags on data quality
- A floundering AI initiative
Groups had to present a one-page investment brief and a five-minute pitch that addressed each executive’s priority, while using existing tools and staying within a $450,000 budget and 90-day time frame.
Enterprise Engagement Scenario: In the second scenario, a healthcare organization needed to increase engagement to improve data literacy and quality while facing:
- Change fatigue
- Overloaded workers
- An imperative to demonstrate measurable results
Once again, teams collaborated to deliver a one-page blueprint for a 90-day campaign and a five-minute pitch to engage cross-functional frontline staff and multiple business units. The challenge: total learner time could not exceed five hours per employee, and all activities had to use existing channels, such as Microsoft Teams/Slack, town halls, the learning management system, and manager huddles.
The winning teams would have a chance to deepen and formalize their applied problem-solving skills through their choice of the following prizes:
- Applied Data Governance Practitioner (ADGP) or Certified Data Management Professional (CDMP) certification training program
- Professional subscription to the DATAVERSITY Training Center
A panel of judges got to work evaluating the solutions.
A Creative Solution to Address Multiple Stakeholder Concerns
The winning team of the Executive Advocacy challenge demonstrated how to translate data governance principles into language that resonates with C-suite executives. The judges noted that the combination of customer focus, executive-specific milestones, and proactive risk mitigation distinguished their approach.
The team’s blueprint included outstanding elements:
Customer Validation Pilot: The team wanted to fully understand customer feedback and capture their voice. It proposed a pilot, within the budget and deadlines, that would conduct customer surveys, pay attention to the data quality collected, and analyze the data to understand why the returns had increased. This innovative solution linked data quality to address a critical business problem.
Executive-Specific Milestones: The group was specific and spoke to each executive’s concern in their 12-month program, built from the customer validation pilot. They mapped concrete outcomes to individual executive priorities.
Risk Mitigation: The team’s risk assessment and mitigation strategies stood out. They established a cross-functional working group, consisting of domain data experts across the organization, that audited product information and identified data issues. To handle these experts’ exhaustion and change fatigue, the team requested temporary staff to cover their operational duties. That way, the subject matter experts could focus on data governance without the stress of their existing workload.
These three tactics, combined with a clear pitch and communications, made this team stand out from other solutions competing in the Executive Advocacy challenge.
Engagement That Reduces Rework
The winning team of the Enterprise Engagement challenge demonstrated how to drive data quality improvements without overwhelming already-stretched teams. Judges commended their clearly articulated solution, realistic week-by-week plan, and messaging tailored to multiple audiences.
Three tactics stood out:
Messaging That Resonated with Multiple Audiences: The team tailored its messaging to multiple audiences, such as executives, clinicians, finance and revenue, and analytics and data teams. This team addressed their data quality needs by drawing from common experiences. For example, team members used the analogy of routine car maintenance to make data quality tangible and relevant across diverse roles.
Practical Weekly Plan: Instead of trying to boil the ocean by covering multiple data literacy topics for everyone in 90 days, the team constructed a phased, week-by-week approach that thoughtfully balanced the constraints and outcomes.
- Concentrated training efforts and support on the data leads, chosen by each department
- Launched general training in 10-minute increments over six sessions
- Developed and established KPIs – such as a >75% participation rate and reduced rework tickets – to assess improvements in data quality
Identification of Problems and Their Outcomes: The winning team targeted their outcomes to a mission-driven, patient-first, and change-weary healthcare culture. This group recognized clinician burnout and addressed it by embedding trainings into the existing workflow and limited the general training to a total of one hour. They added some fun data quality quizzes and challenges where business units could win a free lunch.
The team’s approach succeeded because it respected the reality of healthcare operations: overworked staff, limited time, and deep change fatigue. Rather than adding to the burden, their campaign worked within existing workflows to create sustainable behavior change.
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Conclusion: Building a Resilient Data Governance Program
As the winning teams demonstrated, getting executive buy-in for and engaging the enterprise is a tricky endeavor. But, they succeeded by meeting the business where it was and applying data governance principles there. They piggybacked on business goals and requirements, acknowledged all the different needs, and tailored their messaging to each stakeholder segment.
The challenge required teams to deliver a five-minute pitch and blueprint showing impact within 90 days. But what does sustained data governance look like beyond those initial wins?
Cindy Hoffman, director of enterprise AI at Xcel Energy, discussed the ins and outs of sustaining a successful program in her closing keynote, “From Vision to Value – Building a Resilient Data Governance Program.” Xcel Energy started a data governance program to support an enterprise resource planning (ERP) implementation. She emphasized that implementing governance frameworks “really does take a bit of time, but it has to be something that you adopt and adapt along the way.”
Her team’s recent AI-enabled metadata classification project cut a two-to-three-year data migration timeline to roughly one year – a 90% time reduction that proved governance principles drive measurable results.
The key takeaway from both Hoffman’s journey and the WDMG challenge: Data governance knowledge matters most when applied to the chaos of actual business constraints. Whether you’re advocating to executives or engaging across the enterprise, that’s how data governance moves from PowerPoint to practice.
Want to take The Data Governance Challenge? Join us at DGIQ + EDW 2026 in San Diego for the next installment, a full-day interactive workshop.
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