Senior data strategy leaders gathered at Chicago’s Navy Pier for the Enterprise Data Strategy Board Meeting, where they participated in candid, behind-the-scenes chats about running data analytics, governance, and management at the nation’s largest brands.  

The two-day event included small-group discussions, case studies, and four rounds of unconferences — where members get to choose the most pressing topics and challenges they’re facing in real time and benchmark with their data strategy peers. 

The only thing missing from the Board Meeting was vendors, consultants, or agencies influencing the conversations. 

Here’s a look at what we covered:

Data Strategy Case Studies:

• AI and data mesh: Revolutionizing your data strategy with reliable data products – led by Joe DosSantos at Workday 
• Empowering data stewardship leveraging a data catalog – led by David Nyquist at McKesson 
• Unlocking the power of data: Inside American Express’ analytical data hub – led by Sahil Sabharwal at American Express  
• Best Buy’s journey to a visualization COE – led by Jeff Nieman at Best Buy    
• AI governance: McDonald’s path to responsible AI – led by Matt Sandler at McDonald’s 

Member-Led Small-Group Discussions: 

• Teaming up for data: Engaging stakeholders for data success – led by Heidi Perry at Prime Therapeutics  
• Data monetization: Strategies to unlock the value of data – led by Jen Fronzaglia at Walmart  
• Cracking the code: Overcoming barriers to effective data governance – led by Tijuana Willis, Zurich North America  
• Generative AI: Charting a path from strategy to success – led by Sanjay Sidhwani at Valley Bank 

Unconferences to Explore the Top Data Strategy Challenges:

On day two, Enterprise Data Strategy Board members set the meeting’s agenda themselves through our Unconferences, fast-paced, peer-to-peer discussions where members suggest discussion topics, vote for their favorites, and join the conversations that interest them most. 

It means members are spending the entire time talking about the topics that are most important to them. 

Here’s a look at some of the most pressing challenges data leaders are facing:

• Data strategy roadmaps for the next 2-3 years  
• Tools: Rationalizing to simplify your tech stack, moving from legacy to modern  
• MDM: What’s working (and what’s not)  
• Data stewards: Full-time roles, where they sit, how to identify, and what skills are required  
• Managing data personas and talent strategy: Skills critical for future   
• Data analytics value measurement: Frameworks, KPIs, and successes and challenges  
• Hub and spoke/centralized models: Development, what success looks like, and pros and cons  
• Holistic data quality: Identification, reporting, and resolution tools 

The best on-site discussions will grow as full community conversations in the coming weeks and months as we dig deeper together.