Workforce Performance Predictors

𝗕𝗶𝗴 𝗙𝗶𝘃𝗲 𝘃𝘀. 𝗛𝗘𝗫𝗔𝗖𝗢: 𝗪𝗵𝗶𝗰𝗵 𝗱𝗼𝗲𝘀 𝗮 𝗯𝗲𝘁𝘁𝗲𝗿 𝗷𝗼𝗯 𝗮𝘁 𝗽𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝗻𝗴 𝘄𝗼𝗿𝗸 𝗯𝗲𝗵𝗮𝘃𝗶𝗼𝗿? 🤔 One of my old work friends asked me recently whether I’d recommend a Big Five– or HEXACO-based psychometric tool for employee selection, with predictive validity as the main criterion. Not being a super-expert on this topic, I told her that AFAIK they’re more or less equivalent, with HEXACO having that extra Honesty–Humility dimension, so if counterproductive work behavior (CWB) is a big deal for them, HEXACO might have a slight edge over the Big Five. 🧑🎓 To double-check my reasoning and advice, I dug into the available evidence and luckily came across a solid meta-analytic review by Pletzer & Abrahams (2025) that compares the predictive validity of these two models for task performance and CWB, among other things. 📊 Interestingly, when you look at the overlapping dimensions one by one, the Big Five seems to have a slight edge in predicting both task performance and CWB (see attached charts based on the paper’s data). But when you combine inter-correlations from the sample-size–weighted meta-analytic correlation matrix and estimate explained variance, the conclusion flips: HEXACO outperforms the Big Five in predicting both CWB (20.1% vs. 14.9%) and task performance (6.7% vs. 4.3%). ⚙️ The reason seems to be that HEXACO includes the extra Honesty–Humility trait (which captures ethical variance and is a decent predictor of negative workplace behaviors), shows higher predictive validity for the generally most predictive trait (Conscientiousness), and has less inter-correlation between traits (so their predictive power overlaps less). ❓ Curious if anyone in my network has experience switching from Big Five to HEXACO. What were the main reasons for you, and did it pay off? Asking for a friend (and myself) 🙏🙂 Note: The attached charts aren’t from the paper itself—I made them using the paper’s data, so any discrepancies are on me. Link to the original paper: https://lnkd.in/eyzK-s5i #personality #bigfive #hexaco #validity #performance #cwb #iopsychology

Most organisations still believe this... 👉 “If we spend more on training, performance will improve.” A new meta-analysis of 75,000+ employees (Kim et al., 2025) shows that’s only partly true. Yes...training helps...But the effect is modest (ρ = .13). 🚨 Experience beats expenditure The strongest performance gains came from... ✅ How employees experience training...Not: ⏳ Hours delivered 💰 Budget spent 🧮 Number of courses Effect size when training is perceived as useful?... 🤯 ρ = .23 → nearly double the average effect. Psychology > PowerPoint. 💥 The winning combo: Generic + firm-specific skills 😐 Generic skills alone → moderate impact 😐 Firm-specific alone → weak impact 😁 Both together → ρ = .29 (strongest effect) This aligns perfectly with strategic human capital theory...It’s not what people know, it's how different capabilities combine in your system. Training doesn’t just affect HR metrics...Surprisingly, training had a stronger effect on: ✅ Productivity ✅ Quality ✅ Financial performance Than on: ❌ Engagement ❌ Retention ❌Motivation Systems > sentiment. The uncomfortable truth: Most organisations still measure: ❌ Hours ❌ Attendance ❌ Spend But what actually predicts performance is: ✔ Perceived relevance ✔ Application ✔ Behavioural transfer ✔ System readiness My takeaway... Performance is not a training problem...It’s a readiness problem. If the system isn’t ready…No amount of learning will activate behaviour. If you're still measuring training like it's 2005...You’re optimising the wrong variable.

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.

https://lnkd.in/eXQit86M   Deep Dive podcast: How to improve leadership and organizational effectiveness with deeper insights into work effort. Four Takeaways from our meta-analysis: 1️⃣Understanding Effort: Effort in the workplace encompasses the intensity and persistence of work and the direction of what employees work on. Understanding these dimensions can help #leaders better assess how employee effort impacts performance and align it with organizational goals. 2️⃣Effort as a Performance Predictor: This meta-analysis shows that effort is a significant predictor of #job #performance, which is more directly controllable by employees and management than traits like intelligence or personality. Leaders should focus more on facilitating and recognizing effort, which closely correlates with immediate and long-term performance outcomes. 3️⃣Strategic Implications for Workforce Management: Since effort is influenced by both intrinsic motivation and the organizational environment, leaders should create a work atmosphere that enhances motivation and effectively aligns employee efforts with firm objectives. This involves recognizing and cultivating the conditions that encourage sustained effort. 4️⃣Future Research Directions: The article calls for a more precise operationalization of effort and a deeper understanding of its relationship with related constructs like engagement and grit. For practical application, strategies to enhance intrinsic motivation could significantly improve sustained employee effort. Get open-access article: Van Iddekinge, C. H., Arnold, J., Aguinis, H., Lang, J. W. B., & Lievens, F. 2023. Work effort: A conceptual and meta-analytic review. Journal of Management, 49(1): 125–157. https://lnkd.in/dnQtsQNU Academy of International Business (AIB) Academy of International Business (AIB) Latin America & the Caribbean Chapter AOM ENT Division HR Division - Academy of Management AOM Organizational Behavior Division Administrative Sciences Association of Canada Africa Academy of Management ANPAD ACEDE (Spanish Academy of Management) British Academy of Management Eastern Academy of Management EUROPEAN ACADEMY OF MANAGEMENT EGOS (European Group for Organizational Studies) GW Business Alumni GW Latino Alumni Network Christopher Bracey Ellen Granberg Iberoamerican Academy of Management Indian Academy of Management International Association for Chinese Management Research Management Faculty of Color Association (MFCA) MIDWEST ACADEMY OF MANAGEMENT INC Società Italiana di Management The George Washington University The George Washington University School of Business The PhD Project The Strategic Management Society Western Academy of Management (Official Site) Yönetim Akademisi Derneği - Turkish Academy of Management

Kia ora e te LinkedIn whānau! A great story here by Chereè Kinnear and New Zealand Herald around hybrid work and spaces. I was asked about my NZ data on working from home options, but here are the details you might be interested in. This paper is "in progress" and not published (yet!). The study looks at panel data (twice yearly) from the New Zealand workforce from November 2021 to April 2024, with six waves of data and over 6,000 employee respondents. The differences are tested across WFH options of (1) only office, (2) only home, and (3) hybrid work (being a mix of options 1 and 2).  Rates: Sample size Date All Office. All Home. Hybrid. 1070 Nov 2021 39.0% 13.0% 48.0% 1031 May 2022 43.0% 7.9% 49.1% 1135 Dec 2022 60.7% 7.0% 32.3% 1037 June 2023 63.3% 8.3% 28.4% 1000 Dec 2023 52.6% 5.7% 41.7% 1081 April 2024 32.0% 3.6% 64.4% You can see flexible work like hybrid has fluctuated and currently is quite high. The good news is the effects are consistent across ALL the waves of data including the highs and lows of hybrid work adoption. Hybrid working results in the highest levels of performance and does not differ by type of performance: (1) organizational citizenship behaviours - helping behaviours (e.g., co-workers with their work, representing the organization after hours), or (2) innovative work behaviours - creating new ideas, championing them, and helping them become integrated. Research shows these two behaviours enable firms to perform better than their competitors with workforces doing less of these behaviours (increased bottom line). Finally, gender differences were explored with findings suggesting females’ performance might be greater via hybrid work, although this is not consistent across the waves, but was found for the past year. For those worried about trusting workers to allow for hybrid work - well, that trust issue is likely holding you back! And as a reminder - if you think a worker/s are not doing their mahi at home, well, sorry to tell you: it ain't happening in the office either! Set performance expectations and follow through. Simple! Those who get less done at home than the office need a reminder that hybrid work is a previlage but those 'knocking it out of the park' - well, let them keep doing it! Leaders and SLT: beware of managers wanting the return to the 'old days'. They are likely gone!! Managers will need to adapt. Simple as that. Kia kaha all. Ngā mihi, Prof Jarrod Haar, PhD, FRSNZ, CFHRNZ #hybrid #workingfromhome #performance #productivity #innovation #helping #orgclimate #trust #gender

Your Team Just Took DISC. Now What? Four letters. Some communication insights. Maybe a workshop. Cool. But you still can't predict who'll crush that open role. Or why your top performer just quit. Or which "culture fit" hire will flame out in 90 days. DISC wasn't built for that. And that's fine – it does what it does. Team bonding. Self-awareness. "I'm a high D, so I'm direct." But it stops at the surface. Here's what actually predicts performance: Hardwired motivational drives. Not how someone prefers to communicate. How they're wired to operate when the pressure's on. That's what Aptive Index measures. One assessment. Your entire talent lifecycle. ✅ Pre-hire screening ✅ Team dynamics ✅ Conflict resolution ✅ Leadership development ✅ AI coaching that scales Your hiring data informs development. Your team insights shape succession planning. Your conflict patterns reveal blind spots. Everything connects because it's all one system. The difference: DISC = workshop Aptive = infrastructure DISC helps teams understand each other a little better. Aptive helps you build the right team in the first place. Which matters more right now: Understanding communication styles or predicting who'll actually deliver? #Leadership #TalentStrategy #HiringRight #PeopleAnalytics #OrganizationalDevelopment