Workforce Performance Predictors

Elite performers don't work harder. They build sustainable energy systems. The most successful executives I work with track more than revenue metrics. They monitor the four biomarkers that actually predict sustainable performance: 💓 Heart Rate Variability (HRV) → Your nervous system's readiness for high-stakes decisions  → Elite executives maintain HRV above 50ms even during acquisition weeks  → Low HRV = 23% decrease in complex problem-solving ability 💤 Deep Sleep Percentage → Your brain's overnight consolidation of strategic insights  → Peak performers hit 20-25% deep sleep (most executives get 12%)  → Every 1% increase = 8% boost in next-day creative thinking 🫁 VO2 Max → Your cardiovascular engine for sustained mental performance  → Higher VO2 max = 31% better stress resilience during crisis management  → It's the strongest predictor of cognitive sharpness past 50 📈 Glucose Stability → Your energy system's ability to fuel consistent decision-making  → Stable glucose = steady focus through 12-hour board meeting marathons  → Blood sugar spikes trigger 40% more reactive leadership decisions The uncomfortable reality: These aren't health metrics. They're leading indicators of your business performance. Your HRV determines whether you'll read the room correctly in that crucial negotiation. Your deep sleep decides if you'll connect the dots others miss. Your VO2 max predicts whether you'll still have bandwidth for the make-or-break conversation at 8 PM. Most executives are stuck in the weekend recovery trap. They push through Monday to Friday, then collapse into Netflix and takeout, only to repeat the cycle. Elite performers don't work harder. They build sustainable energy systems. Track one metric starting Monday. Your executive presence depends on it. 💬 Which of these four would transform your performance most? ♻️ Share this with someone who's tired of the crash-and-burn cycle 👉 Follow Liz Bradford for insights on sustainable executive performance

Breaking the Frame: Is Cognitive Ability Losing Its Edge in Predicting Job Performance? For decades, general cognitive ability (GCA) has been hailed as the gold standard for predicting job performance. But recent research by Paul Sackett, and colleagues challenges this. A meta-analysis of 21st century data reveals that the relationship between GCA and job performance may be weaker than we thought. With a corrected correlation of just .22, particularly in combination with the it's time to reconsider our reliance on cognitive tests alone. They then update validity comparisons across methods. 🗝 Key insights: 1. The relationship between GCA and job performance is weaker than previously thought (corrected correlation of .22-.23 vs. .51). 2. Job-specific predictors like structured interviews, work samples, and job knowledge tests now show higher validity. 3. The validity-diversity tradeoff may have fundamentally changed. Equally valid selection systems can be created without heavy reliance on cognitive tests, potentially reducing adverse impact. 4. There's significant variability in predictor validity across settings. The field average may not apply to your specific context. 5. Cognitive ability remains valuable for predicting training performance and in jobs requiring substantial on-the-job learning. Why the change? The authors offer several reasons for why the findings about cognitive ability's relationship to job performance might have changed: 1. Changes in job criteria and the performance domain: Modern conceptualizations of job performance are broader, incorporating aspects like interpersonal skills, citizenship, and teamwork, which are less cognitively loaded than traditional task performance measures. 2. Shift in economy: There's been a reduction in manufacturing jobs (which dominated earlier data) and an increase in jobs with public-facing and teamwork components, changing the nature of task performance. 3. Measurement issues and range restriction: Prior meta-analyses often applied inappropriate range restriction corrections, leading to overestimation of validity. and job-specific applicant pools may be more restricted in range of cognitive ability now than in the past. 4. Older data: The data used as the basis for previous estimates (e.g., Schmidt & Hunter, 1998) was based exclusively on studies at least 50 years old. 5. Publication bias: There may have been a file drawer effect in earlier research, where studies with lower validity were less likely to be published. This research doesn't negate the value of cognitive ability, but it does suggest a more nuanced, multi-faceted approach to selection is needed. As jobs evolve and performance criteria broaden, we must adapt our hiring strategies accordingly. For me, this is a great example of continuing to test our assumptions -- even when they might challenge our own prior ideas and work. Links in the comments!

I just read about a study I can’t stop thinking about… Say-do framework is the best predictor of employee’s performance (according to Harvard). Conventional wisdom suggests that the best indicators of employee performance are: • Educational background • Years of experience • Interview performance These factors are favored in hiring decisions and are seen as more reliable. And 72% of HR professionals rely heavily on resumes to predict job success. Look at most companies' hiring practices, the bias is clear: 85% of recruiters say the resume is the most important part of the hiring process. Is conventional wisdom correct? A study from Harvard says otherwise… Quiet power exists in alignment between words and actions. And in certain situations, say-do consistency makes the better employee. Here's why: Traditional metrics have their place. But they often fail to capture an employee's potential and work ethic. Enter the Say-Do Framework. It's elegantly simple: Compare what people say they'll do with what they actually do. This is especially true in dynamic, unpredictable environments. It's most effective when the stakes are high. The science backs it up. Work studies show a strong correlation between Say-Do consistency and Key Performance Indicators. Employees with high Say-Do alignment are: • 37% more productive • 42% better at team collaboration • 28% increased innovation But societal understanding needs to catch up with this research. It's time we debunk these myths about employee performance: 1. Past Performance ≠ Future Results The Say-Do Framework focuses on current actions and commitments. It provides a real-time measure of an employee's reliability and effectiveness. Understand this metric and help employees align their words with their actions. 2. High Performers Always Stand Out Just because someone isn't the loudest in meetings doesn't mean they're not delivering. The Say-Do Framework measures quiet consistency. Actions speak louder than words – literally. 3. Personality Tests Predict Success 76% of companies with 100+ employees use personality tests. But the Say-Do Framework outperforms them by focusing on: • Actual behavior • Commitment fulfillment • Consistency over time Many top performers excel in Say-Do alignment, regardless of personality type. If you're a manager, embrace this strategic advantage. Here's how: 1. Implement Say-Do Tracking Monitor commitments and their fulfillment. You can't improve what you don't measure. Take time to record what employees promise and what they deliver. Balance accountability with support. 2. Foster a Say-Do Culture Use this framework to build a culture of reliability and trust. Your team's ability to depend on each other can unlock unprecedented productivity. 3. Recognize Say-Do Champions If you identify employees with high Say-Do alignment, empower them. They're your hidden gems, driving performance through consistency and reliability.

Trust: The Hidden Performance Multiplier Your Team Needs Did you know that teams with high psychological safety are: 50% more productive 27% less likely to experience high turnover 76% more engaged at work Google's landmark Project Aristotle revealed that psychological safety is the #1 predictor of team success. Research from Harvard Business Review shows that teams with high trust are 2.5x more likely to achieve breakthrough performance. When team members feel safe to speak up, take risks, and be vulnerable, something magical happens: innovation accelerates, collaboration deepens, and performance soars. Top performers like Four Seasons and Pixar don't just get lucky. They've systematically built cultures where every voice matters and mistakes are seen as learning opportunities. Want to transform your team? Start by creating an environment of genuine trust and psychological safety. Trust is your most powerful competitive advantage.

Most HR analytics focus on the past when they should be predicting the future. Predictive culture analytics combines traditional engagement data with operational metrics, external benchmarks, and unstructured data sources to forecast potential issues before they manifest. The key components of an effective predictive system include: • Multi-source data integration (HR metrics + operational data + communication patterns) • Pattern recognition algorithms (identifying correlations between culture and outcomes) • Threshold-based alerting (signaling potential issues requiring intervention) • Scenario modeling (simulating how cultural changes might impact performance) • Continuous learning mechanisms (refining models based on actual outcomes) This isn't just better measurement—it's competitive intelligence. When you can predict which teams are likely to experience performance issues 4-6 weeks before traditional metrics show problems, you've moved from reactive to proactive management. The future of HR isn't better reporting. It's predictive intelligence. ♻ Repost if you found this insightful 📣 Follow me, Anthony Calleo, for EX insights 🌐 Contact Calleo EX for a free consultation #EmployeeExperience #EX #CalleoEX #WorkplaceCulture #HumanResources #EmployeeEngagement #DataDrivenCulture