Trends in Performance Reviews and Feedback

Most performance reviews try to do two jobs at once: 1️⃣ Pick between people for pay, promotion, and roles. 2️⃣ Develop people by finding strengths and gaps. These goals pull in opposite directions. Why this clash happens (brain + math): 🧠 Brain: When a review affects your pay or job, your brain reads it as a threat. Stress goes up. Learning shuts down. Feedback feels like a warning, not help. 🔢 Math: If you focus on ranking people clearly, everyone’s profile looks the same and you lose detail about strengths and weaknesses. If you focus on rich, detailed feedback, clear rankings get fuzzy. You can’t optimize both at the same time. The fix isn’t “blend them better.” You need a third way. Build two separate tracks with different goals, timing, and rules. Track A — Allocate (between people) - Purpose: pay, promotion, role, and staffing decisions. - Timing: set times (e.g., twice a year). - Evidence: common criteria and comparisons across people. - Norms: fairness, consistency, clear documentation. Track B — Develop (within people) - Purpose: growth, new skills, behavior change. - Timing: ongoing, low‑stakes coaching in regular 1:1s. - Evidence: specific behaviors and goals; focus on the future (“feedforward”). - Norms: psychological safety, curiosity, experimentation. Design moves that make it work: 👉 Separate the moments: Never mix ratings or money talks with coaching time. 👉 Separate the artifacts: Use different forms and language for each track. 👉 Separate the roles: Talent review leaders handle Track A; managers/peers coach in Track B. 👉 Give employees a voice: Enable upward feedback and self‑nominations for growth or promotion. 👉 Aim at behavior and the future: Be specific about what to try next, not who someone “is.” Employee gut‑check: “Is this feedback or a warning?” If people can’t tell, the system isn’t truly separate yet. When we honor the polarity—allocate separately, develop safely—performance management can actually serve both business goals. #EmployeeExperience #PerformanceManagement #Leadership #HR

Six-month performance reviews are broken. ❌ By the time feedback lands, it’s outdated. Managers can’t recall details. Employees leave frustrated. And in the AI era, six months is a lifetime. ⏳ That’s why Thomas Forstner (VP of People & Talent at Juro) rewired performance management with AI. The tipping point - believing that talent density was too important for the business to rely on "best practices" that weren't generating results. Instead of clunky review cycles and dreaded PIPs, Juro now runs: 🛢️ OILSmith → a custom GPT guiding managers through Juro’s OILS feedback framework (Observation, Impact, Listen, Suggestion). 🛠️ FutureSmith → AI-powered “futurespectives” that help managers and employees design roles for the next 6 months. ⚡ Slack nudges, Humaans automations, Zapier flows → performance as a continuous data stream. 📚 Notion as Org Brain → the living hub connecting all of it. The results? ✅ 300+ feedback conversations logged in 2 months ✅ Near 100% completion rate | 100+ hours saved ✅ 4.8 (out of 5) ChatGPT rating for OILSmith ✅ Early signals that PIPs can be eliminated entirely The bold takeaway: not every build has to be a super technical, vibe-coded platform! Sometimes, simple agentic workflows powered by GPT and first-principles thinking unlock the biggest wins. That’s why I’m thrilled to feature Thomas in the latest edition of How I Built It. 👉Read the full HIBI post in my Field Notes newsletter (link in comments) 👉Join our AMA with Thomas on Wed, Sept 10 (details below) Hope you can join us! Thomas will be sharing his full playbook. 🔥 #HowIBuiltIt #Huertanomics #AIforHR #PeopleOps #FutureOfWork

Teams with continuous feedback programs show 23% higher profitability and 18% greater productivity than those relying on outdated annual performance reviews. AI ALPI research has uncovered a critical shift in top-performing HR departments. While 76% of organizations still rely on annual reviews, market leaders are leveraging technology-enabled continuous feedback loops that drive real business outcomes. → Weekly micro-feedback sessions are replacing quarterly or annual reviews, creating psychological safety and real-time course correction ↳ This approach reduces employee anxiety and creates 3x more actionable insights than traditional methods → AI-powered tools now enable performance tracking without the administrative burden ↳ HR leaders implementing these systems report 42% reduction in management time spent on performance administration → Human-centered leadership training has become a critical enabler ↳ Organizations investing in empathy-driven feedback skills see 37% higher retention rates among high performers Companies that implemented continuous feedback systems initially saw a temporary 15% drop in satisfaction as managers adjusted to more frequent, meaningful conversations. By month three, both engagement and productivity metrics surpassed previous levels by significant margins. 🔥 Want more breakdowns like this? Follow along for insights on: → Getting started with AI in HR teams → Scaling AI adoption across HR functions → Building AI competency in HR departments → Taking HR AI platforms to enterprise market → Developing HR AI products that solve real problems #ContinuousFeedback #HRTech #FutureOfWork #LeadershipDevelopment #PerformanceManagement

𝐄𝐯𝐞𝐫𝐲𝐨𝐧𝐞 𝐬𝐚𝐲𝐬 𝐭𝐡𝐞𝐲 𝐰𝐚𝐧𝐭 𝐭𝐨 𝐛𝐮𝐢𝐥𝐝 𝐚 𝐬𝐮𝐬𝐭𝐚𝐢𝐧𝐚𝐛𝐥𝐞 𝐡𝐢𝐠𝐡-𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞 𝐜𝐮𝐥𝐭𝐮𝐫𝐞. But if that’s the goal… it’s not going well. We analyzed performance data from employees across 3 years: 👉 83% of employees never received a high-performance rating across 6 review cycles. 👉 5% received a high-performance rating twice. 👉 But only 2% sustained it across two consecutive cycles. That drop-off is telling. Performance isn’t a personality trait. It’s not something you either have or don’t. 🔄 𝐈𝐭’𝐬 𝐜𝐲𝐜𝐥𝐢𝐜𝐚𝐥—𝐩𝐞𝐨𝐩𝐥𝐞 𝐦𝐨𝐯𝐞 𝐢𝐧 𝐚𝐧𝐝 𝐨𝐮𝐭 𝐨𝐟 𝐡𝐢𝐠𝐡 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞 𝐛𝐚𝐬𝐞𝐝 𝐨𝐧 𝐭𝐡𝐞 𝐜𝐨𝐧𝐝𝐢𝐭𝐢𝐨𝐧𝐬 𝐚𝐫𝐨𝐮𝐧𝐝 𝐭𝐡𝐞𝐦. So what does work? The data points to three key levers: 🆕 Onboarding: Companies with a larger proportion of high-performing employees have higher onboarding scores, and employees who feel early alignment with their role are 48% more likely to become high-performing. 🎯 Goal-setting: Before even being rated high performing, those employees are 21% more likely to create goals, and 26% more likely to align them to company objectives. 💬 Feedback: High-performing employees are much more likely to say their manager gives them useful feedback on their performance. We found in 1 company that an employee's response to the question about 𝐭𝐡𝐞𝐢𝐫 𝐦𝐚𝐧𝐚𝐠𝐞𝐫 𝐩𝐫𝐨𝐯𝐢𝐝𝐢𝐧𝐠 𝐟𝐞𝐞𝐝𝐛𝐚𝐜𝐤 𝐰𝐚𝐬 𝐦𝐨𝐫𝐞 𝐩𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐯𝐞 𝐨𝐟 𝐟𝐮𝐭𝐮𝐫𝐞 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞 𝐫𝐚𝐭𝐢𝐧𝐠 𝐭𝐡𝐚𝐧 𝐩𝐚𝐬𝐭 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞 𝐫𝐚𝐭𝐢𝐧𝐠. Showing that feedback is a leading indicator of performance and creates the environment for high performance. Bottom line: If you’re not seeing high performance, don’t assume it’s a talent issue. It’s likely a design issue. You don’t need mythical talent. You need to do the basics - equip people, get clear goals, and provide feedback along the way.