Training & Development

It takes one minute to damage a career you spent 30 years building. Because success isn’t about skill or intelligence. It’s about emotional regulation. Exercising restraint instead of: → Engaging in a heated debate with a client. → Exchanging a sharp word with a colleague. → Sending an angry email in the heat of the moment. The second you lose control, you’ve lost. Emotional regulation is the biggest marker of career success. The good news is it’s a muscle you can build. Here's how: 1. Know Your Triggers → Identify what sets you off. → Do you feel threatened when criticised? → Awareness is the first step to control. 2. Hit Pause → Before reacting, ask yourself: What are the consequences of my move? → Regret minimisation is critical. 3. Reframe the Experience → What else could this mean? → Maybe the person was having a bad day. → Chose an interpretation that serves you. 4. Create a Delay on Emails Sent → Set a 10-minute delay on all outgoing emails. → This in and of itself could save your career. 5. Breathe → When emotions rise, take three slow breaths. → It signals your nervous system to reset. → Simple, but powerful. 6. Speak With Emotional Intelligence → Once you’re ready to respond, choose your words carefully. → Ask: How can I create the right outcome in a calm way? Remember: → If you choose restraint, you win. → If you reframe, you grow. And every time you stay in control, you keep your power. How important do you think emotional regulation is for career success? ---- ☀️Follow Deena Priest for career, leadership and personal development insights.

It’s simple math 🧐 I use to think that motivation was the key to monumental success. Long story short, it’s not. It’s about the little things you do every day that will take you from reasonable to slightly unreasonable to completely unreasonable progress. Your future is not defined by how motivated you are, but by your daily routines and systems. I believe in this so much that we named our company Butterfly 3ffect to reflect the value of incremental gains. we believe that that’s how the best people and brands grow. Here’s how you grow the small way: 1. Start by setting achievable goals, like reading one chapter of a book each day or going for a short walk 2. Practice gratitude by writing down three things you're thankful for every night before bed 3. Engage in daily self-reflection, even if it's just for a few minutes, to assess your thoughts and actions 4. Incorporate small acts of kindness into your daily routine, like holding the door for someone or offering a genuine compliment 5. Learn something new every day, whether it's a fun fact, a new word, or a new skill 6. Prioritise self-care by getting enough sleep, staying hydrated, and taking breaks when needed 7. Surround yourself with positive influences, whether it's uplifting books, supportive friends, or inspiring podcasts 8. Embrace failure as a learning opportunity and a stepping stone to growth 9. Stay consistent and patient, knowing that small progress over time adds up to significant improvement 10. Celebrate your achievements, no matter how small, to stay motivated and encouraged along the way.

In 2008, Michael Phelps won Olympic GOLD - completely blind. The moment he dove in, his goggles filled with water. But he kept swimming. Most swimmers would’ve fallen apart. Phelps didn’t - because he had trained for chaos, hundreds of times. His coach, Bob Bowman, would break his goggles, remove clocks, exhaust him deliberately. Why? Because when you train under stress, performance becomes instinct. Psychologists call this stress inoculation. When you expose yourself to small, manageable stress: - Your amygdala (fear centre) becomes less reactive. - Your prefrontal cortex (logic centre) stays calmer under pressure. Phelps had rehearsed swimming blind so often that it felt normal. He knew the stroke count. He hit the wall without seeing it. And won GOLD by 0.01 seconds. The same science is why: - Navy SEALs tie their hands and practice underwater survival. - Astronauts simulate system failures in zero gravity. - Emergency responders train inside burning buildings. And you can build it too. Here’s how: ✅ Expose yourself to small discomforts. Take cold showers. Wake up 30 minutes earlier. Speak up in meetings. The goal is to build confidence that you can handle hard things. ✅ Use quick stress resets. Try cyclic sighing: Inhale deeply through your nose. Take a second small inhale. Exhale slowly through your mouth. Repeat 3-5 times to calm your system fast. ✅ Strengthen emotional endurance. Instead of avoiding difficult conversations, hard tasks, or feedback - lean into them. Facing small emotional challenges trains you for bigger ones later. ✅ Celebrate small victories. Every time you stay calm, adapt, or keep going under pressure - recognise it. These tiny wins are building your mental "muscle memory" for resilience. As a new parent, I know my son Krish will face his own "goggles-filled-with-water" moments someday. So the best I can do is model resilience myself. Because resilience isn’t gifted - it’s trained. And when you train your brain for chaos, you can survive anything. So I hope you do the same. If this made you pause, feel free to repost and share the thought. #healthandwellness #mentalhealth #stress

If you're learning SQL in 2025, this mindmap is your best friend. From beginners writing SELECT queries to advanced analysts optimizing joins and using window functions, this guide has it all: 1. 𝐒𝐐𝐋 𝐁𝐚𝐬𝐢𝐜𝐬 – SELECT, WHERE, ORDER BY, GROUP BY, and more. 2. 𝐅𝐢𝐥𝐭𝐞𝐫𝐢𝐧𝐠, 𝐒𝐨𝐫𝐭𝐢𝐧𝐠 & 𝐀𝐠𝐠𝐫𝐞𝐠𝐚𝐭𝐢𝐨𝐧s – Learn to slice data with conditions, BETWEEN, IN, and logical operators. 3. 𝐉𝐨𝐢𝐧𝐬 – Understand how to combine data from multiple tables with INNER, LEFT, RIGHT, and FULL OUTER joins. 4. 𝐖𝐢𝐧𝐝𝐨𝐰 𝐅𝐮𝐧𝐜𝐭𝐢𝐨ns – Use RANK(), LEAD(), LAG(), and ROW_NUMBER() for advanced analytics. 5. 𝐃𝐚𝐭𝐞 𝐅𝐮𝐧𝐜𝐭𝐢𝐨𝐧s – Work with time-based data using DATE_TRUNC(), EXTRACT(), NOW() etc. 6. 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 – Perform statistical analysis and integrate with ML tools like BigQuery ML and Snowflake ML. 7. 𝐂𝐓𝐄𝐬, 𝐓𝐞𝐦𝐩 𝐓𝐚𝐛𝐥𝐞𝐬 & 𝐒𝐮𝐛𝐪𝐮𝐞𝐫𝐢𝐞s – Reuse logic with WITH clauses, recursive queries, and subqueries. 8. 𝐏𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨n – Learn indexing, query planning, and writing efficient queries for dashboards. 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧 𝐓𝐢𝐩𝐬: - Use indexes on columns you frequently filter or join - Avoid SELECT * and only fetch the necessary columns - Use EXPLAIN or ANALYZE to understand query execution plans - Limit joins and subqueries when possible for better performance - Rewrite complex logic using CTEs or temp tables to improve readability 𝐇𝐨𝐰 𝐭𝐨 𝐋𝐞𝐚𝐫𝐧 𝐒𝐐𝐋 𝐄𝐟𝐟𝐞𝐜𝐭𝐢𝐯𝐞𝐥𝐲: – Practice simple SELECT, WHERE, and GROUP BY queries – Use sample datasets to understand INNER, LEFT, and FULL joins – Try window functions, date functions, and subqueries – Build dashboards or solve business problems using real-world data – Participate in SQL competitions or daily practice series Whether you're prepping for interviews, optimizing dashboards, or building data pipelines, this mindmap is your go-to reference. ♻️ Save it for later or share it with someone who might find it helpful! 𝐏.𝐒. I share job search tips and insights on data analytics & data science in my free newsletter. Join 15,000+ readers here → https://lnkd.in/dUfe4Ac6

I just watched a brilliant young mind quit after his first performance review.  The system didn't fail, it worked exactly as designed. And that's the problem. A close friend's son called me yesterday asking for advice. This kid has always been exceptional - top of his class, and one of the most hardworking young minds I know. He joined a company last year, excited to prove himself. His first performance review just happened. They put him on a PIP for "team collaboration issues." Here's what actually happened that past year: + On-time, flawless project delivery. + Zero complaints from stakeholders. + Often stayed late to get things right. But he wasn’t loud. He didn’t hang around in Slack threads and coffee chats or networked just for the sake of being visible. He focused on the work. And that somehow became a problem. When he called me, his voice was shaking. "I keep questioning myself. Maybe I really am terrible at my job." Just imagine an A-player, now doubting his entire future because our review systems punish introverts, misfit metrics, and non-traditional brilliance. I told him what I'm telling you: You're not the problem, kid. The system is. Four decades in this industry, and this still breaks my heart every time.  We're crushing exceptional talent with processes designed for a different era. We measure yesterday's activities instead of tomorrow's potential. The best leaders understand that real performance happens in real-time, not annual reviews. They coach continuously, celebrate wins immediately, and address challenges before they destroy confidence. ✅ Netflix eliminated performance reviews entirely.  ✅ Adobe replaced them with ongoing conversations.  ✅ Google shifted to quarterly goals with continuous feedback. These aren't experiments, they're competitive advantages. While traditional companies waste months on review documents nobody reads, smart organisations invest that time in actual development conversations that drive results. We need to replace annual reviews with monthly check-ins that matter. And most importantly, replace the assumption that people need to be "reviewed" like products with the understanding they need to be supported, challenged, and trusted to grow. That young man will find a company that values his work ethic over his small talk skills. His former employer will keep wondering why they can't retain talent while using the same broken processes. The difference will transform one organisation and devastate the other. So, stop managing performance like it's a quarterly report. Start enabling it like it's a human being's career and dreams. #performancereviews #thoughtleadership

Sustainability in Supply Chains A guide for private markets investors 🌍 Private markets investors face increasing pressure to integrate sustainability into supply chain management. This guide by PRI explains why supply chain due diligence is essential and how investors can embed it across the investment cycle to safeguard assets, reduce risks, and capture value. Supply chain risks, ranging from human rights abuses to environmental violations, have become financially material issues with direct implications for investor performance, regulatory compliance, and reputation. Human rights concerns are significant. Forced labour affects an estimated 28 million people worldwide, with rising risks in major sourcing countries such as India, Vietnam, China, Mexico and the United States. Migrant workers are particularly vulnerable, while child labour remains prevalent in high-risk industries and regions. Working conditions also present serious challenges. Excessive hours, unsafe workplaces and poor wages undermine the stability of global supply chains. These issues are concentrated in industries such as apparel, electronics, food and agriculture, construction materials and mining where oversight is often limited. Environmental risks add complexity. Nearly half of global sourcing markets face high or extreme risk of violations related to waste management, emissions and hazardous materials. Biodiversity loss and deforestation linked to commodities such as palm oil, soy and timber increase exposure to both regulatory and operational disruptions. Regulatory requirements are tightening worldwide. The EU Corporate Sustainability Due Diligence Directive, the US Uyghur Forced Labor Prevention Act and the EU Deforestation Regulation compel companies and investors to identify, mitigate and report risks throughout their supply chains. Failure to comply carries financial consequences. Volkswagen shipments were detained at US ports, Shein faced delays in listing plans due to sourcing concerns and companies in Germany were investigated and fined for breaches of the Supply Chain Act. These examples show how supply chain management is now a strategic necessity. Proactive due diligence creates opportunities. Companies with strong supply chain transparency and risk management can secure contracts, improve resilience, reduce costs and strengthen their brand. Investors can leverage these practices to enhance portfolio performance and protect value at exit. The guide explains that due diligence should be present at every stage of the investment cycle. This includes governance and policies, early screening, detailed risk assessments, legal agreements, active engagement, monitoring and exit planning. Clear roles, data systems and training are critical. Integrating sustainability into supply chain due diligence strengthens both risk management and value creation. #sustainability #business #sustainable #esg

Thousands of studies. Dozens of leading psychology researchers. Decades of experiments on why some people keep going when others quit… and I’ve boiled it down to the 7 biggest takeaways: 1. Action before motivation. Peter Gollwitzer’s work on implementation intentions shows that taking even the smallest step kickstarts a psychological commitment loop. Action fuels motivation more reliably than waiting to “feel ready.” 2. Make your goals specific. Locke & Latham’s Goal Setting Theory (over 1,000 studies) found that specific, challenging goals (“Run 3 times this week”) consistently lead to higher performance than vague ones (“Get fitter”). 3. Progress fuels persistence. According to the goal‐gradient hypothesis, motivation increases as we get closer to a goal. Studies in both animals and people show that small wins, like filling in progress bars or checking off steps, supercharge persistence. 4. Meaning beats willpower. Roy Baumeister found that willpower is finite, but Victor Frankl’s work on meaning and Kashdan & McKnight’s research on purpose show that a deep “why” sustains effort far beyond raw self-control. 5. Shape your environment. Wendy Wood’s research on habits shows that high self-control people don’t rely on willpower alone; they design their surroundings so the desired action is easy and temptations are out of reach. 6. Use social accountability. Harkins & Szymanski demonstrated the audience effect: people persist longer when others can see or expect their effort. More recently, Gollwitzer & Sheeran’s meta-analysis found that public commitments increase follow-through rates significantly. 7. Expect setbacks. Motivation oscillates; it’s not a flat line. Dörnyei’s process-oriented model outlines how motivation ebbs, flows, and needs recalibration. That shifting energy gives you data. And through it all, there’s one big takeaway: Stop waiting for motivation. Take action. Which one is most relevant for you?

One skill separates great communicators from average ones: Perspective-taking. The ability to see things from someone else’s point of view. But most people do it wrong. Here’s how to do it right, especially when you’re leading or being led: When you’re the boss, persuading down: You’re trying to convince Maria on your team to do something different. She’s pushing back. Your instinct might be to assert your authority. But that’s a mistake. Here’s why… Research shows: The more powerful you feel, the worse your perspective-taking becomes. More power = less understanding. So if you want to persuade Maria, don’t lean into your title. Do the opposite: dial your power down, just briefly. Try this: Before the next conversation, remind yourself: Maria has power too. I need her buy-in. Maybe she sees something I don’t. Lower your feelings of power to raise your perspective. From that place, ask: → What does she see that I’m missing? → What might be in her way? → What’s a win-win outcome? That shift changes the entire dynamic. Instead of steamrolling, you’re collaborating. And that’s how you earn trust and results. Now flip it. You’re the employee persuading your boss. It’s a high-stakes moment. You’re nervous. So do you appeal to emotion? No. Drop the feelings. Focus on interests. Here’s the key question: “What’s in it for them?” Not how you feel. Not your big dream. → Will it save time? → Improve performance? → Help them hit their goals? Make it about their world, not yours. Why? Because every boss has a mental shortcut: → Does this employee make my life easier or harder? Be the person who brings clarity, ideas, and upside. Not complaints, drama, or friction. In summary: → Persuading down? Dial down your power to see clearer. → Persuading up? Focus on their interests, not your emotions. Perspective-taking is a superpower, if you learn how to use it. Now practice, practice, practice.

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.

I want to show you a clever trick you didn't know before. Imagine you have six months' worth of data. You want to build a model, so you take the first five months to train it. Then, you use the last month to test it. This is a common approach for building machine learning models. Unfortunately, you may find out your model works well with the train data but sucks on the test data. Overfitting is not weird. We've all been there. But often, the worst you can do is try and fix it before understanding why it’s happening. Ask anyone about this, and they will give you their favorite step-by-step guide on regularizing a model. They will jump right in and try to fix overfitting. Don’t do this. There's a different way. A better way. Here is the question I want you to answer before you start racking your brain trying to fix a model: Do your test and training data come from the same distribution? When building a model, we assume the train and test come from the same place. Unfortunately, this is not always the case. Here is where the trick I promised comes in: 1. Put your train and test set together. 2. Get rid of the target column. 3. Create a new binary feature, and set every sample from your train set to 0 and every sample from the test set to 1. This feature will be the new target. Now, train a simple binary classification model on this new dataset. The goal of this model is to predict whether a sample comes from the train or the test split. The intuition behind this idea is simple: If all your data comes from the same distribution, this model won't work. But if the data comes from different distributions, the model will learn to separate it. After you build a model, you can use the ROC-AUC to evaluate it. If the AUC is close to 0.5, your model can't separate the samples. This means your training and test data come from the same distribution. If the AUC is closer to 1.0, your model learned to differentiate the samples. Your training and test data come from different distributions. This technique is called Adversarial Validation. It's a clever, fast way to determine whether two datasets come from the same source. If your splits come from different distributions, you won't get anywhere. You can't out-train bad data. But there's more! You can also use Adversarial Validation to identify where the problem is coming from: 1. Compute the importance of each feature. 2. Remove the most important one from the data. 3. Rebuild the adversarial model. 4. Recompute the ROC-AUC again. You can repeat this process until the ROC-AUC is close to 0.5 and the model can’t differentiate between training and test samples. Adversarial Validation is especially useful in production applications to identify distribution shifts. Low investment with a high return.