Building Dashboards to Spotlight Leakage and Friction

Your AI model just hallucinated in production, costing $50K in customer refunds. Now, imagine the fallout if that same model is used to screen candidates and inadvertently accepts fraudulent applications. This scenario isn’t just a tech failure; it exposes your organization to compliance risks, brand damage, and wasted

interview hours. As engineering leaders, the stakes are high. You must ensure your hiring processes are both secure and efficient, or risk losing top talent and incurring significant costs. It's time to take a hard look at your dashboards, not just for performance metrics but for identifying leakage (false accepts) and

friction (false rejects). This article will guide you through implementing actionable dashboards that spotlight these critical issues.

For engineering leaders, understanding the importance of telemetry in hiring is crucial. Leading indicators can predict not just candidate drop-off but also potential fraud attempts. By leveraging data, you can proactively address issues before they escalate into costly mistakes. Moreover, aligning your reviewer

staffing with real-time data insights allows for a more agile response to fraud patterns and candidate behavior. This is not just about avoiding risks; it's about creating a hiring process that candidates trust and feel confident in.

To effectively implement a dashboard strategy, follow these steps: Step 1: Integrate telemetry tools that collect data on candidate interactions and outcomes. Tools like Google Analytics and your ATS can provide valuable insights. Step 2: Set up dashboards that specifically track metrics related to false accepts and

false rejects. Use visualizations to highlight trends over time. Step 3: Conduct regular reviews of these dashboards to identify patterns that indicate potential fraud or bottlenecks in the hiring process. Step 4: Adjust your reviewer staffing and policies based on the insights you gather. For instance, if a spike in”,