Business Strategy

A Brooklyn developer just leased 25% faster than 7 competing projects in a 3-block radius. Rents 10-20% above market. With 18 more lease-ups in the pipeline, many backed by institutional developers with bigger budgets and stronger brands. The edge wasn't location or capital, but a design-oriented focus on the drivers of real rent premiums. Fve lessons from Charney Companies' development at Union Channel in Brooklyn, New York: 1/ Unit mix. Pulled architectural plans for every competing project in the market. 3-bedrooms were 3% of supply but demand pointed to 14%. Union Channel tripled the market average. They were the first unit type to fully lease. 2/ Studios. Market average was 500 sqft at $3,500/month. Too much space, too much rent. Union Channel built 400 sqft studios — 20% smaller, 10% cheaper. Leased 50% faster than the rest of the building. 3/ Living rooms. Of every layout variable tested across hundreds of units, living room width was the single strongest predictor of rent per sqft. Every other layout decision was calibrated to protect it. 4/ Amenities. Conventional wisdom says more amenities = more value. The data says the opposite. Quality of select amenities beats breadth. Fitness center quality had the strongest correlation with rent per sqft. They hired a gym consultant instead of designing in-house. 5/ Marketing. 20% of leases came directly from social media — 4x the rate on prior projects. Strategy built around the neighborhood, not the building. Murals on construction fencing. 3,000 organic Instagram followers before opening. These five decisions account for 73% of the value created at Union Channel. All made before the building opened. The data exists in every market. Most developers just aren't looking. Full case study from Andrew Steiker-Epstein in this week's Thesis Driven newsletter. Link in comments.

This is the most underrated way to use Claude: (and it has nothing to do with writing or coding) It's competitive intelligence. Using data that's free, public, and updated every single week. Here's my extract step by step guide: Step 1. Go to claude .ai. Step 2. Select the new Claude "Opus 4.6." Step 3. Turn on "Extended Thinking." Step 4. Pick a competitor. Go to their careers page. Step 5. Copy every open job listing into one doc. (Title. Team name. Location. Full description) Step 6. Save it as one .txt or .docx file. Step 7. Search the company at EDGAR (sec .gov) Step 8. Download its recent 10-K or 10-Q filing. (Official strategy, risks, and financials - all public.) Step 9. Upload both files to Claude Opus 4.6. Step 10. Paste this exact prompt: "You are a competitive intelligence analyst at a rival company. I've uploaded [Company]'s complete current job listings and their most recent SEC filing. Perform a strategic intelligence analysis: → Cluster these roles by what they suggest is being built. Don't use the team names they've listed. Infer the actual product initiatives from the skills, tools, and responsibilities described. → Identify capabilities or teams that appear entirely new — not mentioned anywhere in the SEC filing. These are unreleased bets. → Find roles where seniority is disproportionately high for a new team. This signals executive-level priority. → Cross-reference the SEC filing's Risk Factors and Strategy sections with hiring patterns. Where are they investing against a stated risk? Where did they flag a risk but have zero hiring to address it? → Predict 3 product launches or strategic moves this company will make in the next 6-12 months. State your confidence level and cite specific job titles and filing sections as evidence. Format this as a 1-page competitive intelligence briefing for a CMO." What you'll find: → Products that don't exist yet but will in 6 months. → Priorities that contradict what the CEO said. → Risks they told the SEC but aren't addressing. This is what consulting firms charge $200K for. It took me 10 minutes. I used the new Claude 'Opus 4.6' for a reason: ✦ It read 60 job listing & a 200-page filing together.  ✦ And connects dots across both. ✦ It is superior in thinking and context retrieval. That's why I didn't use ChatGPT for this.

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

Apartment operators are nervous. You can see it in the latest rent data. After six straight months of increased rent momentum nationally, year-over-year rent growth has backtracked a bit in each of the past two months -- coinciding with prime leasing season. Nationally, YoY effective rent growth eased from 1.05% in March to 0.74% in May. The modest backtracking comes DESPITE strong absorption, steady occupancy rates, and improved affordability (declining rent-to-income ratios). We talk a lot about weak consumer sentiment. But it's not just consumers. Sentiment is a powerful variable -- even if one hard to measure -- among operators setting rents. When operators are nervous, they'll likely sacrifice on rents (or ramp up concessions) to protect occupancy. It's happening most clearly in the high-supplied markets across the Sun Belt and Mountain regions, BUT we're also seeing stalled momentum in the lower-supplied Midwest and Coastal markets. So while it was the 40+ year high in supply that pushed rents down in the last two years (even amidst strong demand), it's not just about supply anymore. Washington, D.C., is a prime example of this trend. There's been a lot of nervousness about the D.C. market due to DOGE cuts and federal layoffs. And yet apartment occupancy rates have held strong, improving 50 bps since January and now topping 96%. Rent-to-income ratios among new lease signers (in professionally managed, market-rate apartments) have fallen to 23.1%, according to RealPage data. The REITs with D.C. exposure have all reported solid demand and healthy collections there, too. And yet: Rent growth in D.C. is backtracking more than most of the country. Year-over-year effective rent growth eased from 3.45% in March to 2.35% in May. In most lower-supplied Coastal and Midwest markets, we're seeing operators just hold steady on rents rather than continue the steady upward push we saw previously. And remember: This is the time of year we typically see rents accelerate. In the higher-supplied Mountain and Sun Belt markets, reduced effective rent momentum is primarily driven by increased concessions. Among stabilized apartments (non lease-ups) here utilizing concessions, the average discount increased from 8.9% of asking rent in March to 10.1% in May. That's more than one month "free" on a 12-month lease. Markets with the most deceleration in effective rent change over the past two months include a mix of lower-supply and higher-supply markets: Las Vegas, Riverside, Baltimore, Austin, Memphis, Milwaukee, Kansas City, Washington DC, Denver and Orlando. Markets immune to the trend (with continued momentum) include San Francisco, where sentiment was previously so low it could only go up. There's no other reasonable explanation for slowing rent momentum than nervous operators worried about weak consumer confidence and the parade of headlines warning of a potential recession. Where do rents go from here? Thoughts? #apartments #rents

Sustainability Services Ecosystem Map 🌎 This diagram, developed by Giki, offers a structured view of the growing ecosystem of organizations and platforms supporting sustainability. Its relevance today is undeniable, particularly as regulatory pressure, investor scrutiny, and stakeholder expectations accelerate. The sustainability landscape is growing increasingly complex. Companies are no longer relying on a single advisor or platform but are engaging with a wide range of actors, from disclosure bodies to emissions software providers, capacity-building networks, and global initiatives. This map organizes the ecosystem into five service categories: Measurement and Disclosure, Capacity Building and Engagement, Strategy and Net Zero Transition, and External Stakeholder Relationships. Each plays a distinct role in supporting the design, implementation, and tracking of sustainability strategies. In the measurement space, frameworks, standards, rating systems, and software tools coexist to support robust disclosure practices. Understanding their scope and interconnections is critical for building consistent and reliable reporting processes. In the consulting and advisory realm, various firms provide strategy development and transition planning, often acting as integrators across tools, frameworks, and data systems. Their role is central in operationalizing sustainability commitments. The capacity-building and engagement segment includes platforms focused on employee activation, public education, and behavioral change. These initiatives help embed sustainability into organizational culture and broader stakeholder engagement. Global initiatives and offset providers help align ambition across sectors while offering access to shared methodologies, benchmarks, and mechanisms for emissions reduction or removal. Their influence extends across policy, market signaling, and credibility. As sustainability becomes a core business function, it is essential to map out the ecosystem of support available. Knowing the distinct role of each actor allows organizations to build the right partnerships and infrastructure to deliver credible, impactful outcomes. #sustainability #sustainable #business #esg

In the U.S., you can grab coffee with a CEO in two weeks. In Europe, it might take two years to get that meeting. I ’ve spent years building relationships across both U.S. and European markets, and if there’s one thing I’ve learned, it’s this: networking looks completely different depending on where you are. The way people connect, build trust, and create opportunities is shaped by culture-and if you don’t adapt your approach, you’ll hit walls fast. So, if you're an executive expanding globally, a leader hiring across regions, or a professional trying to break into a new market-this post is for you. The U.S.: Fast, Open, and High-Volume Americans love to network. Connections are made quickly, introductions flow freely, and saying "let's grab coffee" isn’t just polite—it’s expected. - Cold outreach is normal—you can message a top executive on LinkedIn, and they just might say yes. - Speed matters. Business moves fast, so meetings, interviews, and hiring decisions happen quickly. But here’s the catch: Just because you had a great chat doesn’t mean you’ve built a deep relationship. Trust takes follow-ups, consistency, and results. I’ve seen European executives struggle with this—mistaking initial enthusiasm for long-term commitment. In the U.S., networking is about momentum—you have to keep showing up, adding value, and staying top of mind. In Europe, networking is a long game. If you don’t have an introduction, it’s much harder to get in the door. - Warm introductions matter. Cold outreach? Much tougher. Senior leaders prefer to meet through trusted referrals—someone who can vouch for you. - Fewer, deeper relationships. Once trust is built, it’s strong and lasting—but it takes time to get there. - Decisions take longer. Whether it’s hiring, partnerships, or leadership moves, things don’t happen overnight—expect a longer courtship period. I’ve seen U.S. executives enter the European market and get frustrated fast—wondering why it’s taking months (or years!) to break into leadership circles. But that’s how the market works. The key to winning in Europe? Patience, credibility, and long-term thinking. So, What Does This Mean for Global Leaders? If you’re an American executive expanding into Europe… 📌 Be patient. One meeting won’t seal the deal—you have to earn trust over time. 📌 Get introductions. A warm referral is worth more than 100 cold emails. 📌 Don’t push too hard. European business culture favors depth over speed—respect the process. If you’re a European leader entering the U.S. market… 📌 Don’t wait for permission—reach out. People expect direct outreach and initiative. 📌 Follow up fast. If you’re slow to respond, the opportunity moves on without you. 📌 Be ready to show value quickly. Americans won’t wait months to see if you’re a fit. Networking isn’t just about who you know—it’s about how you build relationships. #Networking #Leadership #ExecutiveSearch #CareerGrowth #GlobalBusiness #US #Europe

We analyzed over 13,600 investor portfolios and ranked the largest 250 PE investors in Europe (300+ hours of research) Congratulations to all the leaders: 🥇 CVC (managing a total enterprise value of €70bn across Europe) 🥈 KKR (€66bn) 🥉 EQT Group (€61bn) Other investors in the top 10 include Blackstone (€58bn), Cinven (€45bn), Ardian (€41bn), The Carlyle Group (€33bn), TDR Capital (€32bn), Advent (€32bn) and Bain Capital (€31bn). Collectively, the top 250 private equity firms manage an EV of €1.7tn in Europe. A few other insights from the data: 1. Investors established in the 1990s or before manage 77% of the total EV 2. The top 25 investors manage roughly the same EV as the next 225 combined 3. Europe 250 investors have an avg. EBITDA of €94m and manage 26 companies each 4. German HQ’d investors are underrepresented in the ranking with just 3% of total EV 5. London is home to 50 of the top 250 investors, followed by Paris (32) and New York (21) 𝗦𝗲𝗰𝘁𝗼𝗿 𝗟𝗲𝗮𝗱𝗲𝗿𝘀 - Hg (TMT) - CVC (Services and Industrials) - EQT Group (Science & Health) - KKR (Energy & Materials)  - Cinven (Financial Services) - TDR Capital (Consumer) Services, Consumer, and TMT are the largest PE markets by sector. Notably, Hg in TMT and TDR Capital in Consumer predominantly target those sectors, representing 71% and 69% of their portfolio, respectively. Compared to European investors, North American investors overweight TMT, Financial Services and Energy & Materials. They underallocate to Services, Industrials and Healthcare. 𝗚𝗿𝗼𝘄𝘁𝗵 𝗟𝗲𝗮𝗱𝗲𝗿𝘀 Hg, Cinven and Astorg stand out with high-growth, high-margin portfolios. CD&R, TDR Capital and PAI Partners rank among the largest employers in Europe given their large retail/consumer portfolio. Waterland Private Equity stands out as a big buyer of family-owned businesses. ________ 𝗙𝘂𝗹𝗹 𝗥𝗲𝗽𝗼𝗿𝘁 Tons of more insights and charts in the full analysis: 💡List of top 250 investors 💡Sector and Regional rankings 💡Portfolio insights (Growth, holding periods, and more) 💡Detailed methodology Get it here ➡️ https://lnkd.in/ezekm4MJ #investors #pe #europe #insights

Marketing Ops is the most underrated growth lever. Period. Companies that invest in MOps early scale faster, execute better, and improve revenue efficiency. I created this team structure guide for marketing ops teams. NOTE: THESE ARE JUST GUIDELINES. Actual teams will vary based on product, GTM motion, industry, etc. Here’s what happens at each stage: 📍 $1M - $9M ARR → 1-person team, wearing all the hats One Marketing Ops Manager does it all—campaigns, tech, reporting, and lead routing. Some part-time campaign support (or agency help). 📍 $10M - $99M ARR → Starting to scale, but still lean A Marketing Ops & AI Lead plus specialists in data, campaigns, and martech. Part-time data & Martech support. 📍 $100M - $999M ARR → Fully operational MOps function Director of Marketing Ops leading a team across campaign execution, analytics, enablement, and AI. Engineering support emerges as a need for heavier technology lifts. 📍 $1B+ ARR → Enterprise-grade MOps, deeply embedded into the business A VP/Head of Marketing Operations leading specialized teams for strategy, analytics, finance, governance, and AI. MOps is now a strategic function, influencing revenue and customer experience. Takeaways: 🚀 If your company is growing, your MOps team should be growing too. 💡 If you’re a CMO, invest in MOps early—before you feel the pain. 📊 If you’re in MOps, this is how you advocate for the right resources at the right time. Do these structures resonate with you? What would you change? PS: I'm writing more about this in my weekly newsletter, search "The Marketing Operations Leader" on Google and subscribe for free to stay updated. #marketing #martech #marketingoperations #growth

The shift from seats to agents pressures SaaS margins. At the same time, the longstanding practice of getting enterprise customers to pre-commit and also prepay for functionality they may never deploy will get harder as CIOs look to free budget for their own LLM costs. To weather the storm, some SaaS companies have increased prices. This boosts revenue and margins in the short-term but can't be done repeatedly and creates even greater scrutiny over shelfware as procurement teams right-size and shift contracts to "pay as you go." To achieve sustainable growth, SaaS companies need to become hyperefficient at sales and marketing. Here are common ways to do so and who's doing it well: 1. PLG. Shopify and Atlassian exemplify efficient go-to-market based on product-led growth with free trials, low-friction upgrades and upsells. Their sales teams only need to get involved in the biggest opportunities at the largest accounts; every other step in acquisition, commercial transaction, activation, onboarding, and growth is self-service and automated. 2. Vertical SaaS. Guidewire Software and Veeva Systems are laser-focused on insurance and life sciences, respectively. Rather than casting a wide net, they spear-fish with deep domain knowledge and purpose-built solutions for that industry's specific workflows and regulatory requirements. Guidewire doesn't need to buy Super Bowl ads– their annual customer conference is the Super Bowl for property & casualty insurance executives. Nearly zero GTM effort is wasted– unsurprisingly they're the two most efficient on the list. We modeled Hearsay Systems after both these companies, and this focus allowed us to win incredible market share among Fortune 500 banks & insurers despite only raising $60M in totality. 3. Relocate operations to lower-cost regions and AI. This is private equity's favorite playbook to take costs out of companies they buy. Field sales continues to shift more to Zoom, which means you can hire AEs anywhere. Inside sales contributes a greater % of revenue as PLG motions are established. AI handles top-of-funnel leads qualification and generating marketing content and campaigns. 4. Focus on gross revenue retention. Because of high customer acquisition costs in #SaaS, leaky buckets are margin killers. Use LLMs to help customer success teams analyze product usage, segment cohorts, and identify opportunities to increase value realization. Put in guardrails to prevent sales reps from overselling an account, as doing so only creates churn in the next renewal cycle. 5. Introduce another product line. This only works if your new product has the same buyer as your existing products. Many SaaS acquisition pro formas fail to actualize for this reason, as it's not actually feasible to have the same AE sell both old and new products. Every SaaS company right now needs to double down on one or more of these levers in the AI era.

I’ve had 5 different people ask me about their early stage startup offer and each time I have told them: DO NOT TAKE IT. Here’s why: These were strong, tenured candidates with at least 10+ years of experience at name-brand mid-stage startups. They were allured by the opportunity to “go earlier and have a bigger impact”. If that is your only motivation, go for it. However, most of the time, you’re also motivated by the equity. Let me tell you plainly: 95% of the time, the equity offered is built on a lie. It is based on the idea that all startups are created equal and they aren’t even close. You get the same equity offer for joining the next Stripe or Facebook as you do if you’re joining a random GovTech company, even though the exit potential is 1/100th in GovTech. This creates a serious issue. Most people just think “early stage startup” implies a $10B+ outcome opportunity. They don’t question it. They ask their friends what equity they got, and they assume the company can be the next Notion, Ramp, or Airbnb. In reality, the best case, home run scenario for your startup might be $1B or even $500M. The founders either delude themselves into thinking this isn’t true, or they know it but of course they won’t admit it. The founders / investors will never give you the equity that would actually be fair, because they structurally can’t. If you are an up-and-comer in your career, going early stage (pre-$1M ARR) can be a great deal. You get paid in learning, and you can easily jump to another more successful company in 3-5 years. But if you are in the prime of your career, with a decade of experience under your belt, beware. Don’t join unless the startup has multiple $10B comps in the public markets, or the founders have a philosophy of offering 2-5x the market standard in equity (to compensate for the lower potential exit value). Some founders are wise enough to do this, but most will just give you the standard offer and expect you to not ask too many questions. P.S. Some founders will just compensate for this by offering strong cash offers. That is totally fine too, as long as you are eyes wide open about it.