Recruitment & HR

The European Parliament has officially passed Extended Producer Responsibility (EPR) legislation that fundamentally shifts the responsibility for textile waste management to fashion brands and retailers – with far-reaching global implications. This new law requires all producers, including e-commerce platforms, to cover the full cost of collecting, sorting, and recycling textiles, regardless of whether they are based within or outside the EU. The financial burden of Europe's textile waste now falls squarely on the brands that create it. What are the critical business implications? UNIVERSAL SCOPE: The legislation applies to all producers selling in the EU market, including those of clothing, accessories, footwear, home textiles, and curtains. No company is exempt based on location. FAST FASHION PENALTY: Member states must specifically address ultra-fast and fast fashion practices when determining EPR financial contributions, creating cost penalties for unsustainable business models. GLOBAL SUPPLY CHAIN DISRUPTION: As the world's largest textile importer, the EU's new rules will ripple across global supply chains, particularly impacting exporters from Bangladesh, Vietnam, China, and India who supply much of Europe's fast fashion. TIMELINE PRESSURE: Officially adopted September 2025, this creates immediate operational and financial planning requirements. COMPETITIVE RESHAPING: Brands and retailers will inevitably pass increased costs down their supply chains, fundamentally altering supplier relationships and pricing structures globally. What are the implications for various stakeholders? For CEOs and board members: This represents more than regulatory compliance – it's a complete business model transformation. Companies must now integrate end-of-life costs into product pricing, rethink supplier partnerships, and accelerate circular design strategies. For sustainability and decarbonisation executives: This creates unprecedented opportunities for circular economy solutions, sustainable material innovation, and traceability system development across global supply chains. Link: https://lnkd.in/dTyHtHuD #sustainablefashion #circulareconomy #textilwaste #epr #fashionindustry #sustainability #supplychainmanagement #fastfashion #environmentalregulation #businessstrategy #decarbonisation #textilerecycling #fashionceos #boardgovernance #climateaction #wastemanagement #producerresponsibility #fashionsustainability #textileindustry #greenbusiness

How we talk about DEI is important. How we do the work of DEI, to actually achieve #diversity, #equity, and #inclusion, is far more important. As we head into 2025, I'm hearing a lot of buzz from well-meaning practitioners looking for ways they can rebrand the DEI status quo of one-off trainings, zero-budget lunch and learns, and volunteer burnout-inducing cultural celebrations so that they can continue with their workplace's business as usual under a new name. There is no rebrand in the world that can save ineffective practices. Long before this latest wave of backlash, practitioners leading this work have pushed for organizational DEI to become more accountable, measurable, and impactful. We've all seen organizations with rampant discrimination in promotion and hiring, with broadly inaccessible facilities, websites, products, and services, with toxic workplace cultures lacking respect, value, or safety for those in them, and with leadership teams leading with neither trust or transparency...boasting about their underfunded, poorly-attended, and undersupported DEI events to show their "commitment" to this work. If that's the status quo you're trying to save, forget about it. 🎯 Effective DEI work in 2024 was rigorous, measurable, and principled. It sought to identify problems before (not after) prescribing solutions, with the goal of improving diversity, equity, and inclusion outcomes. 💥 That same work in 2025 will look like strategic human-centered interventions with pre- and post-measurement to identify progress—or lack thereof—toward removing barriers to thriving in the workplace. 🎯 Effective DEI work in 2024 was systems-focused, not stopping at individual-level solutions like coaching or training, to root out systemic biases enabling homogeneity, inequity, and exclusion at scale. 💥 That same work in 2025 will look like organizational development and change management, to ensure that policies, processes, and practices across every workplace are enabling everyone to succeed. 🎯 Effective DEI work in 2024 was rooted in the collective, drawing on allyship between different identity groups to lend our collective power, influence, and resources to each other's causes. 💥 That same work in 2025 will look like coalition-building and organizing for mutual benefit, building trust between people from differing backgrounds to push for a better status quo that benefits everyone. When we give into fear and go on the defensive, we risk losing the creative edge we need to imagine a world better than the one we're familiar with. 2025 might be a hard year for DEI, yes. But the good, hard work behind it isn't going anywhere, not if practitioners stay focused on the impact we're working to achieve and continue honing our craft. Stay sharp, folks.

Louder for the people at the back 🎤 Many organisations today seem to have shifted from being institutions that develop great talent to those that primarily seek ready-made talent. This trend overlooks the immense value of individuals who, despite lacking experience, possess a great attitude, commitment, and a team-oriented mindset. These qualities often outweigh the drawbacks of hiring experienced individuals with a fixed and toxic mindset. The best organisations attract talent with their best years ahead of them, focusing on potential rather than past achievements. Let’s be clear this is more about mindset and willingness to learn and unlearn as apposed to age. To realise the incredible potential return, organisations must commit to creating an environment where continuous development is possible. This requires a multi-faceted approach: 1. Robust Training Programmes: Employers should invest in comprehensive training programmes that equip employees with the necessary skills for their roles. This includes on-the-job training, mentorship programmes, online courses, and workshops. 2. Redefining Hiring Criteria: Organisations should revise their hiring criteria to focus more on candidates’ potential and willingness to learn rather than solely on prior experience or formal qualifications. Behavioural interviews, aptitude tests, and probationary periods can help assess a candidate's ability to learn and adapt. 3. Partnerships with Educational Institutions: Companies can collaborate with educational institutions to design curricula that align with industry needs. Apprenticeship programmes, internships, and cooperative education can bridge the gap between academic learning and practical job skills. 4. Lifelong Learning Culture: Encouraging a culture of lifelong learning within organisations is crucial. Employers should provide ongoing education opportunities and support for professional development. This includes continuous skills assessment and access to resources for upskilling and reskilling. 5. Inclusive Recruitment Practices: Employers should implement inclusive recruitment practices that remove biases and barriers. Blind recruitment, diversity quotas, and targeted outreach programmes can help ensure that diverse candidates are given a fair chance. By implementing these measures, organisations can develop a workforce that is adaptable, innovative, and resilient, ensuring sustainable success and growth.

Most companies think they need AI experts. What they actually need is a data pit crew. Data Scientists, Engineers, Analysts, these roles are exploding, with data science jobs projected to 𝐠𝐫𝐨𝐰 𝟑𝟔% 𝐛𝐲 𝟐𝟎𝟑𝟏, according to BLS, one of the fastest-growing professions. Meanwhile, according to Gartner 𝟔𝟏% 𝐨𝐟 𝐨𝐫𝐠𝐚𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧𝐬 are evolving their data strategies to keep up with AI-driven disruption. Job titles don’t tell the full story. Here’s what these roles actually do: • 𝐃𝐚𝐭𝐚 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐬 – 𝐓𝐡𝐞 𝐁𝐥𝐮𝐞𝐩𝐫𝐢𝐧𝐭 𝐃𝐞𝐬𝐢𝐠𝐧𝐞𝐫𝐬 They design the structure that makes everything else possible: data lakes, warehouses, and pipelines that ensure information moves efficiently and securely. Without them, data would be a tangled mess. • 𝐃𝐚𝐭𝐚 𝐀𝐥𝐜𝐡𝐞𝐦𝐢𝐬𝐭𝐬 – 𝐓𝐡𝐞 𝐈𝐧𝐬𝐢𝐠𝐡𝐭 𝐂𝐫𝐞𝐚𝐭𝐨𝐫𝐬  They don’t just analyze data; they extract value from it. Using machine learning, statistical modeling, and predictive analytics, they turn raw data into business-changing insights. • 𝐈𝐧𝐬𝐢𝐠𝐡𝐭 𝐃𝐞𝐭𝐞𝐜𝐭𝐢𝐯𝐞𝐬 – 𝐓𝐡𝐞 𝐏𝐚𝐭𝐭𝐞𝐫𝐧 𝐅𝐢𝐧𝐝𝐞𝐫𝐬 They specialize in uncovering trends, correlations, and anomalies. Whether it’s identifying fraud, optimizing operations, or finding revenue opportunities, their job is to make sense of the noise. • 𝐃𝐚𝐭𝐚 𝐖𝐡𝐢𝐬𝐩𝐞𝐫𝐞𝐫𝐬 – 𝐓𝐡𝐞 𝐀𝐈 𝐇𝐚𝐧𝐝𝐥𝐞𝐫𝐬  They prepare data for AI, ensuring it’s clean, structured, and optimized for machine learning models. Because feeding bad data into AI is like training a GPS with a 10-year-old map. • 𝐃𝐚𝐭𝐚 𝐎𝐫𝐚𝐜𝐥𝐞𝐬 – 𝐓𝐡𝐞 𝐅𝐨𝐫𝐞𝐜𝐚𝐬𝐭 𝐒𝐩𝐞𝐜𝐢𝐚𝐥𝐢𝐬𝐭𝐬  They predict what’s coming next: market trends, customer behavior, risk factors. Using historical data and predictive models, they help businesses make proactive decisions. • 𝐃𝐚𝐭𝐚 𝐒𝐮𝐫𝐠𝐞𝐨𝐧𝐬 – 𝐓𝐡𝐞 𝐂𝐥𝐞𝐚𝐧-𝐔𝐩 𝐂𝐫𝐞𝐰  They fix bad data, remove errors, and ensure consistency. Because even the best algorithms are useless if they’re working with garbage. • 𝐃𝐚𝐭𝐚 𝐏𝐡𝐢𝐥𝐨𝐬𝐨𝐩𝐡𝐞𝐫𝐬 – 𝐓𝐡𝐞 𝐄𝐭𝐡𝐢𝐜𝐬 & 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲 𝐆𝐮𝐢𝐝𝐞𝐬  They ask the big questions: Should we use this data? Is it biased? Does it comply with privacy laws? They ensure data-driven decisions are also responsible ones. With Chief Data Officers now overseeing AI strategy at 58% of organizations, the importance of these roles is only growing. So, which one best describes what you do? Or do you have a better title for your role? Drop it in the comments! 𝐅𝐨𝐫 𝐬𝐨𝐮𝐫𝐜𝐞𝐬 𝐚𝐧𝐝 𝐝𝐞𝐞𝐩𝐞𝐫 𝐝𝐢𝐯𝐞: https://lnkd.in/eawvf8Rx ******************************************* • Visit www.jeffwinterinsights.com for access to all my content and to stay current on Industry 4.0 and other cool tech trends • Ring the 🔔 for notifications!

Most people think having a human approve an AI decision means the decision is safe. It does not. 👀 There is a term for what actually happens when humans rubber stamp AI outputs under time pressure. Automation bias. It is one of the most documented and underreported risks in enterprise AI right now. After 13 years and 200+ deployments, here is what I have learned about building genuine oversight into AI systems. The human reviewing an output needs three things to actually be in the loop. They need to understand what they are reviewing. They need the context to catch what the model gets wrong. And they need to be genuinely empowered to say no without institutional pressure to simply keep moving. Most organisations have none of those three in place. They have a signature process. That is not the same thing. Before any high-stakes AI output reaches a decision point in your organisation, ask these questions. ➡️ Does the person approving this understand the underlying data well enough to catch an error? ➡️ Is there time built in for genuine review or just enough time to click approve? ➡️ What happens if someone says no? Is that genuinely supported? If the answer to any of those is no… you do not have human oversight. You have automation bias with a human signature attached. What does genuine human oversight look like in your organisation right now? #ai #leadership #futureofwork #artificialintelligence #aistrategy #teamhuman #intellectualatrophy #criticalthinking

India’s green economy is growing fast but LinkedIn data suggests green talent is growing even faster. The LinkedIn Hiring Rate (LHR) for green talent — defined as professionals with green skills, green job titles, or both — is now 59.7% higher than for the overall workforce. This means green-skilled professionals are significantly more likely to be hired than their peers, underscoring the growing demand for sustainability-focused roles. “The prioritisation of green talent by Indian companies is being fuelled by an interplay of policy reforms, rising consumer consciousness, and the need for deep business transformation,” says Neelima Burra, Chief Strategy, Transformation, and Marketing Officer at Luminous Power Technologies. “Government initiatives like the PM Suryaghar Yojna, National Solar Mission, and Smart City Mission, combined with the growing mandate for ESG reporting — are also pushing companies to recruit sustainability experts, carbon auditors, and ESG strategists to meet regulatory and investor expectations,” she adds further. Operational efficiency has emerged as the top skill across the top five industries increasingly hiring for green skills, as per LinkedIn data. In contrast, precision agriculture skills lead in farming, ranching, and forestry — highlighting how sector-specific green skills are evolving. “Operational efficiency offers the fastest route to tangible returns. It moves the conversation beyond regulatory compliance to net profitability, ensuring we can do more with less energy and fewer materials,” says Venu Nuguri Managing Director and CEO at Hitachi Energy. This surge in demand aligns with broader economic trends. Green jobs in India have grown over 10 times in the past five years, with Gen Z accounting for 63% of applicants, reports The Economic Times, citing a report by WeNaturalists. The projections are equally ambitious. India’s green economy will generate 7.29 million jobs by FY28 and 35 million by 2047, as the sector scales toward a $1 trillion valuation by 2030 and $15 trillion by 2070, suggests another report by The Economic Times, citing a report by NLB Services. The message is clear: green skills aren’t just good for the planet — they’re becoming essential for employability. As India accelerates its climate and economic goals, the workforce is already adapting. The question now is whether education, training, and policy can keep pace. Read the full report here: https://lnkd.in/g873CzHT #COP30 #GreenerTogether Source: The Economic Times: https://lnkd.in/d-3bShQP  The Economic Times: https://lnkd.in/dSUMFS58 

You don’t just marry a person. You marry a potential career advantage. A Washington University study tracked 4,500+ couples for 5 years—and found your spouse’s personality can influence your job satisfaction, income, and promotions. 🧵 1. The Big Idea: Disciplined and dependable partners don’t just make good spouses. They quietly help their partner succeed at work. And the effect holds for both men and women. 2. The study tracked: ✅ Job satisfaction ✅ Income ✅ Likelihood of promotion ...and matched it against each spouse’s personality traits. One trait consistently stood out. 3. The secret sauce? Being disciplined and dependable. Partners with these qualities predicted: -Higher income -Greater job satisfaction -More frequent promotions Even after controlling for the worker’s own personality traits. 4. How does it work? The researchers found 3 key ways this plays out: -Outsourcing – They take on more of the home load, freeing up mental space. -Emulation – You start mimicking their good habits. -Stability – A calm, organized home improves your focus at work. 5. What about other traits? Being nice (agreeable) or emotionally stable had less impact on career outcomes. It wasn’t about charm—it was about consistency. 6. And this wasn’t just for traditional households. Dual-income couples showed the same benefits. Even when both partners worked full-time, having a steady, structured spouse made a difference. 7. Bottom line: You bring yourself to work. But your partner shapes how well you show up. If you’ve got someone who’s steady, reliable, and disciplined—thank them. They’re helping you win behind the scenes.

The $100M mistake to avoid when establishing compensation bands for your global office locations A mistake I sometimes see when companies set up their global compensation practices is to take one, and only one, pay differential for that new country/region and then apply it against the HQ-location compensation bands. On the one hand, this is a simple way to establish the pay practices for a global office location. However, it is an oversimplification that leads to either overpaying or underpaying talent requisite with a company’s target compensation philosophy. In particular, the global pay differentials for sales reps tend to be markedly more compressed than for other job functions such as engineering. I find this very interesting. Let’s take a look. ___________ Example: Your HQ is in SF. You decide to open an office in London. The average pay differential between SF and London in Pave is 66%. Your P4 SWEs in SF make $200k. And your ENT sales reps make $250k. (These are the band midpoints for argument's sake here.) Given the 66% average SF<>London pay differential, you decide to pay your UK P4 SWEs $132k (£99.9k GBP) and your UK ENT sales reps $165k USD (£124.9 GBP). Seems simple and easy, right? Not quite. Turns out, the pay differential for SF<>London SWEs is 63%. Meanwhile, the pay differential for SF<>London sales reps is 87% (!). Instead of £99.9k GBP, your London P4 SWEs should make closer to £95.4k GBP. And instead of £124.9 GBP, your London ENT sales reps should make closer to £164.6k GBP. If you do not take job function into account when setting your London compensation bands, you will likely be overpaying your SWEs and substantially underpaying your sales reps in that office. By the way, this simple example doesn’t take other variables such as job level into account. Often (but not always), pay differentials get more compressed at senior levels. Bottom line–pay differentials are a useful starting point for designing global compensation bands. But it is vital to go deeper on the dimensions of job function, job level, and more when setting up global comp bands. And yes, sales tends to have more compressed pay differentials in most global regions in Pave’s dataset versus the USA. This is likely driven by the nature of how sales comp is so tightly linked to revenue outcomes, meaning that it is a bit more “bottoms up” in nature versus other job families which are more subject to localized labor market forces. ___________ To zoom out a bit, let’s suppose your company has 4,000 employees and the average all-in cost (cash, equity, benefits) per employee is $250,000. This means you are spending roughly $1B (with a b) per year on headcount. A bil! 10% of $1B is $100M. Seemingly small percentage errors–10%, for argument’s sake–in your compensation bands have massive financial and/or employee retention impact at scale. Precision matters. Pay with confidence. #pave #benchmarks #global #compensation

You can’t afford a silent personal brand. Doubts cost you freedom, daily. An external force isn't stopping you… It’s the internal illusions you let consume you. ☑ Identify the self-sabotaging behaviors: Spotlight Effect Cringe: Overestimating how many see your posts and judging every word you write. Distraction: Mindless scrolling instead of meaningful engagement. Comparison Trap: Measuring likes, views, and connections against others, fueling insecurity. ☑ Understand the real obstacles: Decision Paralysis: Believing success requires perfect data and strategies before taking action. Personal vs. Useful: Focusing on personal opinions over genuine value for your audience. Vanity Metrics Addiction: Chasing impressions instead of true community-building. ☑ Implement these strategies to combat sabotage: Reality Check: Recognize that not everyone reads (or judges) your every post. Intentional Engagement: Dedicate time to comment, connect, and converse with your network. Self-Comparison: Track your own progress rather than obsessing over others. ☑ Develop a mindset for success: Embrace Imperfection: Learn in public and grow by sharing, not by hiding. Prioritize Value: Offer expertise that genuinely helps others instead of just voicing personal rants. Focus on Connection: Relationships over chasing larger and larger impression counts. ☑ Tools to help you stay on track: Time-Blocking: Schedule engagement sessions so distractions don’t derail you. Confidence Boosters: Keep reminders of past wins visible to fight impostor syndrome. Analytics with Purpose: Measure what matters—impact, relationships, and progress. ☑ Optimize your environment for growth: Supportive Circles: Join groups or masterminds that encourage your LinkedIn journey. Clear Your Feed: Mute, unfollow, or reduce content that triggers comparisons or doubt Structured Routines: Create consistent posting habits to overcome hesitation. ☑ Top tips for maintaining momentum: Post Consistently: Overcome the cringe feeling by taking action repeatedly. Reward Incremental Wins: Celebrate every milestone to keep motivation high. Keep Learning: Seek feedback, refine your approach, and always move forward. ☑ Ensure every action aligns with your goals. Adopt a strategy that includes: Clarity of Purpose: Know whom you serve. Consistent Execution: Show up every day. Resilient Mindset: Obstacles are part of the process. Act despite the illusions. The real villain isn’t out there. It’s within.

The most important skills today and in the next years will be human capabilities: critical and analytic thinking, resilience, leadership and influence, overlaid with technological literacy and AI skills to amplify these human capacities. World Economic Forum's new Future of Jobs Report provides a deep and broad analysis of the drivers of labour market transformation, the outlook for jobs and skills, and workforce strategies across industries and nations. It's a really worthwhile deep dive if you're interested in the topic (link in comments). Here are some of the highlights from the Skills section, which to my mind is at the heart of it. 🧠 Analytical Thinking Leads Core Skills. Skills like analytical thinking (70%), resilience (66%), and creative thinking (64%) top the list of core abilities for 2025. By 2030, the emphasis shifts even more towards AI and big data proficiency (85%), technological literacy (76%), and curiosity-driven lifelong learning (79%). This shift underscores the critical role of technology and adaptability in future workplaces. 📉 Skill Stability Declines but at a Slower Rate. Employers predict that 39% of workers' core skills will change by 2030, slightly lower than 44% in 2023. This reflects a stabilization in the pace of skill disruption due to increased emphasis on upskilling and reskilling programs. Half of the workforce now engages in training as part of long-term learning strategies compared to 41% in 2023, showcasing the growing adaptation to technological changes . 🌍 Economic Disparities in Skill Disruption. Middle-income economies anticipate higher skill disruption compared to high-income ones. This disparity highlights the uneven challenges of transitioning labor forces across global regions, particularly in economies still grappling with structural changes. 🚀 Tech-Savvy Skills in High Demand. The adoption of frontier technologies, including generative AI and machine learning, is increasing the demand for skills like big data analysis, cybersecurity, and technological literacy. These trends indicate that businesses are aligning workforce strategies to integrate these advancements effectively. 📚 Upskilling Is the Norm, Not the Exception. By 2030, 73% of organizations aim to prioritize workforce upskilling as a response to ongoing disruptions. This reflects a shift in corporate investment priorities towards human capital enhancement to maintain competitiveness.