Organizational Culture

Does becoming a parent affect academic trajectories? Yes, and particularly so for women: 🔹University employment drops by almost 30 percent for women, much less so for men. 🔹Probability of being tenured is about 35 percent lower for women, no change for men. 🔹Number of publications is 31 to 35 percent lower for women, no change for men. These are among the key results of a new study by Sofie Cairo, Ria Ivandic, Anne Sophie Lassen, and Valentina Tartari using rich Danish admin data. Why do women’s and men’s career trajectories diverge sharply after parenthood? The paper studies a series of candidate explanations and finds that the gap in childcare load seems mainly responsible: "women academics do almost five times more childcare than their male academic counterparts. For example, 55% of female researchers get up at night to take care of the child most or all the time, in comparison to 11% of men". Read the full paper here: Sofie Cairo, Ria Ivandic, Anne Sophie Lassen, and Valentina Tartari (2026), Parenthood and the career ladder: evidence from academia, Centre for Economic Performance discussion paper: https://lnkd.in/eK2gWzSb

A learning culture is not built by offering more training. It emerges where curiosity, connection, and purpose intersect. Andrew Barry, in The Curious Lion, describes learning culture as a lotus where several forces overlap. I find this framing helpful because it moves the conversation beyond HR programs and into the fabric of the organization. At the individual level, there is curiosity. People must feel invited to ask questions, challenge assumptions, and explore. Without individual curiosity, learning remains compliance. At the organizational level, there is mission. Learning needs direction. When people understand what the company stands for and where it is going, their curiosity becomes focused rather than scattered. At the relational level, there is human connection. Learning accelerates in environments where people feel safe to speak, experiment, and reflect together. The fourth circle is continuous learning. Learning must be ongoing, not episodic. Not a workshop, but a way of operating. Continuous learning ensures that curiosity, mission, and connection reinforce each other over time rather than fading after the latest initiative. When these circles overlap, deeper elements emerge: Shared vision aligns effort. Shared experiences create collective memory. Shared assumptions shape how reality is interpreted. Shared stories transmit meaning across generations. At the center sits what we call learning culture. Not an initiative, but a pattern of how people think, relate, and evolve together. The question for leaders is not, “Do we offer learning opportunities?” It is, “Do curiosity, mission, and connection truly reinforce each other continuously in our organization?” That is where learning becomes cultural rather than occasional.

Readers responded with both surprise and agreement last week when I wrote that the single biggest predictor of how rapidly a team makes progress building an AI agent lay in their ability to drive a disciplined process for evals (measuring the system’s performance) and error analysis (identifying the causes of errors). It’s tempting to shortcut these processes and to quickly attempt fixes to mistakes rather than slowing down to identify the root causes. But evals and error analysis can lead to much faster progress. In this first of a two-part letter, I’ll share some best practices for finding and addressing issues in agentic systems. Even though error analysis has long been an important part of building supervised learning systems, it is still underappreciated compared to, say, using the latest and buzziest tools. Identifying the root causes of particular kinds of errors might seem “boring,” but it pays off! If you are not yet persuaded that error analysis is important, permit me to point out:  - To master a composition on a musical instrument, you don’t only play the same piece from start to end. Instead, you identify where you’re stumbling and practice those parts more. - To be healthy, you don’t just build your diet around the latest nutrition fads. You also ask your doctor about your bloodwork to see if anything is amiss. (I did this last month and am happy to report I’m in good health! 😃) - To improve your sports team’s performance, you don’t just practice trick shots. Instead, you review game films to spot gaps and then address them. To improve your agentic AI system, don’t just stack up the latest buzzy techniques that just went viral on social media (though I find it fun to experiment with buzzy AI techniques as much as the next person!). Instead, use error analysis to figure out where it’s falling short, and focus on that. Before analyzing errors, we first have to decide what is an error. So the first step is to put in evals. I’ll focus on that for the remainder of this letter and discuss error analysis next week. If you are using supervised learning to train a binary classifier, the number of ways the algorithm could make a mistake is limited. It could output 0 instead of 1, or vice versa. There is also a handful of standard metrics like accuracy, precision, recall, F1, ROC, etc. that apply to many problems. So as long as you know the test distribution, evals are relatively straightforward, and much of the work of error analysis lies in identifying what types of input an algorithm fails on, which also leads to data-centric AI techniques for acquiring more data to augment the algorithm in areas where it’s weak. With generative AI, a lot of intuitions from evals and error analysis of supervised learning carry over — history doesn’t repeat itself, but it rhymes. [Truncated due to length limit. Full text: https://lnkd.in/gjqv6VeA ]

I Can Spot a Great Candidate in 30 Seconds - Without Looking at Their Resume. At Vicco Laboratories, the first few interview rounds are handled by our HR and leadership team. They assess skills, experience, performance history - all the standard checkboxes. But when someone reaches my room, I’m not evaluating capability. I’m evaluating character. Because skills can be trained. Character can’t. So in the final round, I deliberately observe three things before we even get into formal questions: 𝐓𝐫𝐚𝐢𝐭 1: 𝐇𝐨𝐰 𝐓𝐡𝐞𝐲 𝐓𝐫𝐞𝐚𝐭 𝐭𝐡𝐞 𝐒𝐦𝐚𝐥𝐥𝐞𝐬𝐭 𝐏𝐞𝐫𝐬𝐨𝐧 𝐢𝐧 𝐭𝐡𝐞 𝐑𝐨𝐨𝐦 Before they enter, I always ask our receptionist to make them wait for a few minutes. Not to trouble them — but to observe: Do they greet her or ignore her? Do they show gratitude or entitlement? Do they smile or stay blank? Do they thank her when being called in? If someone is only respectful upwards, they’re not fit for leadership. 𝐓𝐫𝐚𝐢𝐭 2: 𝐇𝐨𝐰 𝐓𝐡𝐞𝐲 𝐇𝐚𝐧𝐝𝐥𝐞 𝐒𝐢𝐥𝐞𝐧𝐜𝐞 During the conversation, I pause intentionally. A great candidate: Doesn’t panic when things go quiet Holds eye contact without overcompensating Thinks before responding, instead of rushing to impress Silence is a pressure test.  Silence exposes a person’s comfort with themselves. And self-assured people make better decisions under pressure. 𝐓𝐫𝐚𝐢𝐭 3: 𝐖𝐡𝐞𝐭𝐡𝐞𝐫 𝐓𝐡𝐞𝐲 𝐀𝐬𝐤 “𝐖𝐡𝐚𝐭 𝐂𝐚𝐧 𝐈 𝐆𝐢𝐯𝐞 𝐭𝐨 𝐕𝐢𝐜𝐜𝐨”, 𝐍𝐨𝐭 𝐉𝐮𝐬𝐭 “𝐖𝐡𝐚𝐭 𝐖𝐢𝐥𝐥 𝐈 𝐆𝐞𝐭?” I watch closely when compensation and responsibilities are discussed. If the questions are only about salary, perks and timings, they’re employees. If they ask about learning culture, values, decision-making structure…they are already thinking as an owner. I’ll always choose alignment over achievement. So if you’re ever preparing for your final round anywhere — don’t just prepare your resume. Prepare your presence. Because long after your words fade, your character stays in the room. Sanjeev Pendharkar  Just sharing what I’ve learnt #values #business #hiring #hr #decisionmaking #cv #leadership #skills

They asked me to present my "diversity strategy" to the board. I brought a mirror. Set it right in the middle of their mahogany table. Watched them shift in their leather chairs as they stared at their own reflection. "This is your diversity problem," I said. Twelve faces. Same color. Same gender. Same golf club. They wanted me to solve what they refused to see: You can't fix diversity from the outside when the rot starts at the top. I'd spent six months building a framework that would've transformed their pipeline. Created pathways for Black talent they claimed they "couldn't find." Designed retention strategies for the ones who kept leaving. My research showed they'd lost 47 Black employees in 18 months. Exit interviews all said the same thing: "No path to leadership." Hard to see a path when every road leads to a room that looks like a country club board meeting from 1952. The CFO cleared his throat. "This feels... aggressive." Aggressive? Showing you a mirror is aggressive? But excluding us from every decision isn't? Paying us 63 cents to your dollar isn't? Having our faces on your website but not in your C-suite isn't? I picked up my mirror. My $75K framework. My 200-slide deck. "You don't need a diversity strategy. You need diverse leadership. And that starts with looking at why this mirror makes you so uncomfortable." They hired a different consultant. Someone who wouldn't hold up mirrors. Someone who'd make them feel good about their 2% improvement metrics. That company? Still bleeding Black talent. Stock down 30%. Getting roasted on Glassdoor. Me? I only work with boards ready to shatter their mirrors and rebuild their tables. With seats for people who don't look like them. With budgets that match their press releases. With leadership that leads by example, not excuses. Your diversity strategy isn't about finding us. We're right here. It's about finding the courage to look in the mirror and admit why we're not in your boardroom. Some reflections are meant to be broken. Thank You; It's True.™ #ExecutivePresence #BlackWomenInBusiness #ThankYouItsTrue

Rick Rubin went on stage in Helsinki the day after my talk. Someone asked how he resolves creative differences with artists. His answer was simple: change the conversation from "I disagree" to "let's build it." Then he shared a story: An artist played him a song. The transition didn't work. Rubin told him so. The artist said, "We'll just cut that part in half." Rubin thought to himself: What a dumb idea. But he didn't say that. He said, "Let's try it." The artist played it. It worked. Rubin is a legend. He's produced everyone from Johnny Cash to Jay-Z. Instead, he bit his tongue and let the artist prove him wrong. The principle: when you make an idea tangible, it stops being the person's idea. It becomes something you can both look at objectively and improve together. Once you build it, the truth is obvious. Here's what this looks like in practice: Your designer wants to change the entire homepage layout. You think it's too risky. Instead of three meetings debating it, you say: "Let's build a prototype and test it with 50 users this week." Your sales team wants to restructure the pricing page. Instead of blocking it because you're worried about conversions, you say: "Let's run it as an A/B test on 20% of traffic for two weeks." Your engineer wants to rebuild a core feature from scratch. You think it's overengineered. But instead of killing it in the planning phase, you say: "Spike it out in three days and show me if the performance gain is real." You're not saying yes to everything. You're saying, "Let's find out." Rubin also said something that stuck with me: "If there's disagreement, I always side with the artist's vision. Because to them, it's their career. To me, it's just one piece of my portfolio." Most leaders think backing down makes them look weak. Rubin knows that siding with the person who has the most at stake makes better work happen. Your job isn't to be right. It's to create the conditions where the best idea wins. Stop debating. Start building. P.S. This insight is from this week's newsletter where I break down why Yamaha dominates while Steinway got sold to private equity: https://lnkd.in/efSqP_9K P.P.S. Access additional research links, the podcast, and the full archive in the first comment 👇 Thank you to Nordic Business Forum!

In the early years of Marico, I made a decision that shaped everything that followed. I gave young people serious responsibility. Not after years of proving themselves. Right at the start. Real roles. Real ownership. Real consequences. Some of them made mistakes. That was expected. But they learned fast. They asked for feedback. They iterated. They took initiative. Many of them went on to become some of the best leaders in the organisation. My view is simple. If someone makes an error, but they take ownership, improve, and do not repeat it, they have earned the right to grow. If someone avoids responsibility or hides from mistakes, they are not ready. Empowerment is not about handing out titles. It is about giving people the room to fail safely and the support to recover intelligently. You cannot build a high-performance organisation if every decision needs your approval. The real test of leadership is not in how well you control outcomes. It is in how confidently you let others lead. #leadership #hiring #talent #growth #future #team #success

Your leadership team is underperforming. (And cracking the whip harder won't fix it.) Here's what nobody tells you about accountability: The harder you push, the less they deliver. I've watched CEOs destroy their executive teams this way: 🔥 Public callouts in meetings 🔥 Micromanaging every decision   🔥 Threats disguised as "motivation" 🔥 Fear-based deadline pressure Result: Your best leaders become corporate zombies. They show up. They comply. They stop caring. The expensive truth: Fear creates compliance. Clarity creates commitment. And you need commitment to win. Real story from last month: → CEO constantly berated his team for missing targets → 3 VPs quit in 6 months → Company lost $2M in transition costs alone Different CEO, different approach: → Created radical clarity around expectations → Listened without judgment → Built safety to admit mistakes early → Revenue up 40% in 12 months The difference? One used accountability as a weapon. The other used it as a framework for excellence. The 4 frameworks that create compassionate accountability: 1. RACI Matrix - Ends the "whose job is this?" chaos (Everyone knows their lane AND their value) 2. OKRs - Aligns hearts and minds (Shared goals create shared ownership) 3. EOS Accountability Chart - One person, one seat (Clear ownership without overlapping egos) 4. OGSM - Strategy meets reality (No more "I thought you meant..." conversations) But here's the key: These aren't hammers to hit people with. They're maps to help people win. The paradox of leadership: High standards + High support = High performance High standards + Low support = High turnover Your leadership team doesn't need more pressure. They need more clarity. Because when accountability comes from compassion, not control: → Problems get solved, not hidden → Leaders take ownership, not cover → Teams push forward, not back Stop managing through fear. Start leading through frameworks. Your leadership team is capable of greatness. But only if you create the conditions for it. Save this. Share it with your team. Because the best leaders don't create followers. They create owners. And ownership starts with clarity. P.S. Want a PDF of my Accountability Cheat Sheet? Get it free: https://lnkd.in/dpWsuT4b ♻️ Repost to help a CEO in your network. Follow Eric Partaker for more leadership insights. — 📢 Want to lead like a world-class CEO? Join my FREE TRAINING: "How to Work with Your Board to Accelerate Your Company’s Growth" Thu Jul 10th, 12 noon Eastern / 5pm UK time https://lnkd.in/dCJ-nCxM 📌 The CEO Accelerator starts July 23rd. 20+ Founders & CEOs have already enrolled. Learn more and apply: https://lnkd.in/dgRr89bM

McKinsey & Company 𝗯𝗹𝘂𝗲𝗽𝗿𝗶𝗻𝘁 𝗳𝗼𝗿 𝗵𝗼𝘄 𝗯𝗮𝗻𝗸𝘀 𝗰𝗮𝗻 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗲𝘅𝘁𝗿𝗮𝗰𝘁 𝗿𝗲𝗮𝗹 𝘃𝗮𝗹𝘂𝗲 𝗳𝗿𝗼𝗺 𝗔𝗜: ⬇️ This is a full-stack, enterprise-grade architecture — built on agents, orchestration, and rewired workflows. The AI bank stack consists out of 4 key layers: ⬇️ 𝟭. 𝗘𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗟𝗮𝘆𝗲𝗿 This is the user layer — customers and employees. McKinsey calls for fully reimagined, intelligent, personalized experiences across all channels. → Multimodal chat (text, voice, image) → Omnichannel UX across mobile, contact center, branch → Digital twins for customer simulation and workforce training It’s all about a UI refresh and UX overhaul grounded in real AI. 𝟮. 𝗔𝗜-𝗣𝗼𝘄𝗲𝗿𝗲𝗱 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗠𝗮𝗸𝗶𝗻𝗴 This is the brain of the AI-first bank. And it’s not just predictive models anymore — it’s orchestrated agent ecosystems. → AI Orchestrators: Plan, reason, delegate across workflows → Domain Agents: Specialize in credit policy, fraud, risk, legal → Copilots: Embedded in workflows to guide users and automate decisions McKinsey reports 20–60% productivity gains in decision-making with this approach. 𝟯. 𝗖𝗼𝗿𝗲 𝗧𝗲𝗰𝗵 & 𝗗𝗮𝘁𝗮 The foundation layer most banks underestimate — until GenAI models stall in production. → Vector databases → LLM orchestration and FinOps → Search and retrieval engines → ML pipelines → Secure data architecture → API infrastructure The goal: make data accessible, tools reusable, and infra invisible to the business. Without this, nothing scales. 𝟰. 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗻𝗴 𝗠𝗼𝗱𝗲𝗹 This is where the transformation wins or fails. Without rewiring the org, the tech doesn’t matter. → AI control towers to track value and set guardrails → Cross-functional teams across business, tech, and AI → Platform operating model for speed and alignment → Enterprise-wide reuse of AI capabilities If you're building isolated projects without shared assets or central coordination, you’re not transforming — you’re experimenting. 𝗪𝗵𝗮𝘁 𝘁𝗵𝗶𝘀 𝗮𝗹𝗹 𝗮𝗱𝗱𝘀 𝘂𝗽 𝘁𝗼? The banks that win won’t be the ones with the most pilots. They’ll be the ones that industrialize agents, orchestration, and rewired workflows, with full-stack coordination. Full McKinsey article: https://lnkd.in/dPaJzVK4 𝗜 𝗲𝘅𝗽𝗹𝗼𝗿𝗲 𝘁𝗵𝗲𝘀𝗲 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁𝘀 — 𝗮𝗻𝗱 𝘄𝗵𝗮𝘁 𝘁𝗵𝗲𝘆 𝗺𝗲𝗮𝗻 𝗳𝗼𝗿 𝗿𝗲𝗮𝗹-𝘄𝗼𝗿𝗹𝗱 𝘂𝘀𝗲 𝗰𝗮𝘀𝗲𝘀 — 𝗶𝗻 𝗺𝘆 𝘄𝗲𝗲𝗸𝗹𝘆 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿. 𝗬𝗼𝘂 𝗰𝗮𝗻 𝘀𝘂𝗯𝘀𝗰𝗿𝗶𝗯𝗲 𝗵𝗲𝗿𝗲 𝗳𝗼𝗿 𝗳𝗿𝗲𝗲: https://lnkd.in/dbf74Y9E

🥊 “Jingjin, have you ever considered that women are just inferior to men?” That was her opening line. The lady who challenged me was not a traditionalist in pearls. She was one of the top investment bankers of her time, closed billion-dollar deals, led global teams, the kind of woman whose voice dropped ten degrees when money was on the line. And she meant it. “Back in my day, if I had to hire, I’d always go for the man. No pregnancy leave. No PMS. No emotional volatility. Just less… liability.” And she doesn’t believe in what I do. Helping women lead from a place of wholeness. Because to her, wholeness is a luxury. Winning requires neutrality. And neutrality means: be less female and suck it up! I’ve heard versions of this many times, and too often, from high-performing women who "made it" by suppressing. But facts are: 🧠 There are no consistent brain differences between men and women that explain men’s “logic” or women’s “emotions.” 💥 Hormones impact everyone. Men’s testosterone drops when they nurture. Women’s cortisol rises in toxic workplaces, not because they’re weak, but because they’re sane. 📉 What we call “meritocracy” is often a reward system for those who can perform like they have no body, no children, no cycles. None of those are biologically male traits. They’re artifacts of a system built around male lives. So, if you're a woman who's bought into this logic, here are some counter-strategies: 🛠 1. Study Systems Like You Studied Deals Dissect the incentives, norms, and bias loops of your workplace the same way you’d break down a P&L. Don’t internalize what’s structural. 🧭 2. Redefine Strategic Strengths Stop mirroring alpha aggression to prove you belong. Deep listening, self-regulation, and nuance reading, these are leadership assets, not soft skills. Use them ruthlessly. 💬 3. Name It, Don’t Numb It If your hormones impact you one day a month, say so, but also say what it doesn’t mean: It doesn’t cancel out 29 days of clarity, strategy, and execution. 🪩 4. Build Your Own Meritocracy Start investing in spaces, networks, and cultures where your wholeness isn’t penalized. If none exist, build them. 🧱 5. Deconstruct Before You Self-Doubt When you catch yourself thinking “maybe I’m not built for this,” pause. Ask: Whose rules am I trying to win by? Who benefits when I question myself? This post isn’t about defending women. We don’t need defending. It’s about calling out the internalised metrics we still use to measure ourselves. 👊 And choosing to rewrite them. What’s the most 'rational' reason you’ve heard for why women are a liability?