What is the best way to integrate AI to proactively identify 'GWC' (Get It, Want It, Capacity to Do It) issues within an EOS framework, especially when preparing for exit?

Question

Tyler Smith · Accepted Answer

Proactively identifying 'GWC' issues is crucial for maintaining a high-performing organization and is particularly important when showcasing operational excellence during exit planning. AI integration offers a powerful method to move beyond reactive problem-solving. Leverage AI-powered HR analytics platforms that can analyze a combination of performance review data, 360-degree feedback, communication patterns (anonymized and aggregated), and project completion rates. These tools can identify subtle deviations from expected performance or engagement that might indicate a GWC gap.

For 'Get It,' AI can analyze task comprehension rates and recurring errors in specific roles. If a team member consistently misinterprets instructions or fails on tasks requiring certain understanding, the system can flag potential 'Get It' issues. For 'Want It,' AI can correlate employee satisfaction surveys with retention rates, promotion aspirations, and participation in voluntary professional development. A dip in engagement scores combined with a lack of initiative in skill development might signal a 'Want It' problem. Finally, for 'Capacity to Do It,' AI can assess workload distribution, project bottleneck analysis, and skills gap identification from internal training data. If an individual is consistently overloaded or lacks specific certifications required for their role, AI can highlight 'Capacity' constraints. These AI-driven insights provide objective, actionable data for leadership, allowing for targeted coaching, role adjustments, or training interventions well before these issues impact overall company performance or become apparent during a due diligence process.