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What is the biggest mistake leaders make when trying to use data? According to Texas data expert Derek Ryan, it’s letting "gut feelings" override what the numbers say. In this episode of Winning on Issues, former RPT Chairman James Dickey sits down with Derek Ryan, founder of Ryan Data and Research, to unpack the rigorous discipline required to manage and utilize massive, complex datasets for success in government and politics. Derek shares best practices he developed while managing the Republican Party of Texas's master voter file for a decade, discussing everything from data hygiene to integrating AI, all while ensuring voter privacy and public transparency. 00:01:18 | Data Management Masterclass: Hygiene and Standardization 00:02:11 | Best Practices: Getting Reliable Data from State Agencies 00:03:25 | The Biggest Mistake: Why Leaders Choose Emotion Over Data 00:05:01 | Data as a Driver of Change: The Shift to Real-Time Responsiveness 00:06:40 | Telling the Story: Presenting Data with Graphics Over Numbers 00:08:28 | The AI Impact: Streamlining Queries and Finding Hidden Trends 00:10:02 | Avoiding Vanity Metrics: The "Why" Question in Decision Making 00:11:39 | Untapped Opportunity: Using Data to Optimize Resource Allocation 00:14:01 | Predicting Problems: Using Licensing Data to Prevent Issues 00:16:39 | Transparency vs. Privacy: Balancing Public Data and PII Protection 00:21:14 | Systemic Rollout: Why Redundant Backups Are Essential (Floppy Disks to Cloud) 00:24:34 | TexStats and Fraud: Using Data to Ensure Good Stewardship 00:28:21 | Measuring Policy: Setting Goals to Prove Implementation Success 00:29:52 | Building a Data Culture: Advice for Agency Heads ✅ Key Takeaways: The Biggest Mistake is Emotional: Leaders often make the mistake of following a gut feeling over what the data is actually reporting. You must be willing to accept results, even if they contradict your initial expectations. Data as a Driver: Data is moving beyond measurement to become a driver of change through real-time responsiveness, allowing governments to instantly allocate resources, like sending ballots to busy locations. Standardization is Crucial: For multi-million record datasets, standardization of data is crucial for keeping it fresh and accurate. Untapped Opportunities for Agencies: Agencies can use their internal data to predict problems, such as identifying overworked offices or cross-referencing licensing data with new movers to find potential employees (e.g., matching licensed teachers to new mover addresses). Redundancy is King: To avoid systemic failure (like a cloud outage or a hacker attack), all critical systems require redundant backups, spanning cloud servers, physical drives, and multiple transfer methods