Business Strategy

The latest reporting from the Financial Times highlights a point that energy analysts have been making for years: geopolitical shocks consistently strengthen the case for renewables, electrification and storage. Microsoft’s global vice-president for energy notes that oil and gas price spikes linked to the Middle East conflict reinforce the value of wind, solar and batteries in providing price stability. Once installed, renewables offer predictable cost profiles and reduce exposure to volatile global fuel markets. We saw this dynamic after Russia’s invasion of Ukraine. Europe accelerated solar deployment, heat pump uptake increased in several countries, and governments revisited questions of energy security through the lens of diversification and electrification. The underlying issue remains unchanged. Fossil fuels must continuously flow through complex global supply chains. When those flows are disrupted, prices spike and economies are exposed. Renewables, by contrast, are capital intensive upfront but deliver long term domestic supply and insulation from commodity shocks. There are short term risks. Inflation, higher interest rates and supply chain constraints can slow clean energy investment. Some governments may also respond by doubling down on gas infrastructure. The policy challenge is to avoid locking in further structural vulnerability. Energy security and climate policy are not competing objectives. In a world of recurrent geopolitical instability, they are increasingly aligned.

The disconnect between sales managers and reps in 2025 is wild. Manager: "Just pick up the phone!" Rep: *sends 47 emails, 12 texts, 3 LinkedIn messages, and a carrier pigeon* Sound familiar? 😅 After 20+ years in sales, I've watched this communication gap grow wider every year. But here's what both sides are missing: It's not about choosing ONE channel. It's about understanding WHICH channel works WHEN. The most successful reps I've seen? They've cracked the code: **First 24 hours:** • Email → Sets professional tone • LinkedIn → Shows you've done homework • Text → Only if they've given permission **Days 2-5:** • Phone call → NOW it's time (they know who you are) • Voice note → Personal touch that stands out • Video message → Shows real effort **The truth?** Your manager's right - calls DO convert better. You're also right - cold calling blind is dead. The magic happens when you warm them up FIRST. Think of it like dating: You wouldn't propose on the first date. So why are we calling strangers without context? **My top 3 strategies that actually work:** 1. The "Permission Play" End every email with: "Would a quick call tomorrow at 2pm work to discuss?" (They expect it now = higher answer rate) 2. The "Multi-Touch Warm-Up" Email → LinkedIn view → Call within 48 hours (They recognize your name = 3x more likely to answer) 3. The "Context Creator" Reference their LinkedIn post before calling "Saw your post about X, had a thought..." (You're not a stranger = conversation not pitch) Here's the brutal truth: Managers: Your reps aren't lazy. They're adapting to how buyers ACTUALLY buy in 2025. Reps: Your manager isn't wrong. The phone still closes more deals than any other channel. Bridge the gap. Use both. Win more. What's your take - Team Phone or Team Omnichannel? P.S I'm running a FREE 6-week LinkedIn Social Selling Bootcamp starting Monday 15th Sept, grab a free spot here https://lnkd.in/eVmxsMbM

Replenishment isn’t a side feature, it’s a force multiplier. This is a big mistake. We’ve seen replenishment flows outperform promos and win-back emails combined. They convert better every time with the right timing and zero customer effort. Brands overspend on ads to win new customers, then forget to win them again. They need to predict exactly when a customer needs to repurchase and trigger the message at the perfect moment. Not too soon, not too late. Just right. ++ 𝗪𝗵𝘆 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿𝘀 𝗗𝗼𝗻’𝘁 𝗥𝗲𝗼𝗿𝗱𝗲𝗿 – 𝗔𝗻𝗱 𝗛𝗼𝘄 𝘁𝗼 𝗙𝗶𝘅 𝗜𝘁 ++  𝗧𝗵𝗲𝘆 𝗙𝗼𝗿𝗴𝗲𝘁 ✅ Fix: Replenit’s AI triggers proactive reminders across channels exactly when customers are likely to run out, via the brand's own marketing automation vendors, without any migration. 𝗣𝗼𝗼𝗿 𝗧𝗶𝗺𝗶𝗻𝗴 𝗼𝗿 𝗖𝗵𝗮𝗻𝗻𝗲𝗹 ✅ Fix: Multichannel orchestration (SMS, push, email) with personalized timing based on consumption behavior. 𝗡𝗼 𝗖𝗹𝗲𝗮𝗿 𝗜𝗻𝗰𝗲𝗻𝘁𝗶𝘃𝗲 ✅ Fix: Smart upsell bundles, urgency messages (“running low?”), and loyalty integration improve reorder ROI.   • Food & Beverage, pet food and treats, wellness & beauty products hold the highest repeat purchase potential, being very high due to frequent, perishable-driven consumption patterns. • Online groceries and FMCG rank high in habitual/impulsive behavior, presenting a strong fit for mobile push and SMS-driven replenishment campaigns. Brands like Glosel turned a leaky bucket into a revenue engine with Replenit’s AI-powered multichannel replenishment flows. 🚀 53.75% more automation revenue 🛒 +28% higher AOV 📲 100% of the Multichannel approach, email, SMS & Push channel revenue -12X Higher Engagement Rate Why does it work? Because Replenit activates timely, no-effort reorders across email, SMS, push, and more. Most brands forget to remind customers. ++ 𝟯 𝗧𝗮𝗰𝘁𝗶𝗰𝗮𝗹 𝗥𝗲𝗰𝗼𝗺𝗺𝗲𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝘀 𝗳𝗼𝗿 𝗥𝗲𝘁𝗮𝗶𝗹𝗲𝗿𝘀 ++ 1️⃣ Make Replenishment an Always-On Growth Engine Don’t treat it as a postscript. Integrate replenishment flows as a core revenue pillar in your retention strategy. 2️⃣ Automate Across Channels With Smart Triggers Use AI-powered solutions to trigger SMS, email, and push notifications based on usage cycles, not guesswork. 3️⃣ Track and Optimize With First-Party Data Loops Leverage Replenit’s dashboards to identify top retention products, run experiments on timing, and iterate continuously. 𝗧𝗼 𝗮𝗰𝗰𝗲𝘀𝘀 𝗮𝗹𝗹 𝗼𝘂𝗿 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗳𝗼𝗹𝗹𝗼𝘄 ecommert® 𝗮𝗻𝗱 𝗷𝗼𝗶𝗻 𝟭𝟰,𝟮𝟬𝟬+ 𝗖𝗣𝗚, 𝗿𝗲𝘁𝗮𝗶𝗹, 𝗮𝗻𝗱 𝗠𝗮𝗿𝗧𝗲𝗰𝗵 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝘃𝗲𝘀 𝘄𝗵𝗼 𝘀𝘂𝗯𝘀𝗰𝗿𝗶𝗯𝗲𝗱 𝘁𝗼 𝗲𝗰𝗼𝗺𝗺𝗲𝗿𝘁® : 𝗖𝗣𝗚 𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗚𝗿𝗼𝘄𝘁𝗵 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿. About ecommert We partner with CPG businesses and leading technology companies of all sizes to accelerate growth through AI-driven digital commerce solutions. #CPG #ecommerce #Replenishment #AI #FMCG

A very easy way to improve your Amazon ads efficiency by at least 10% Let’s say you’re spending ₹4–5 lakhs/month on Amazon ads. Your ACoS looks okay. Conversion rate seems fine. But your gut tells you—you’re still wasting some money on irrelevant traffic You’re not wrong At Atomberg, we had found that some of our Amazon spend was going toward search terms that had no business seeing our ads: - “cheap fan” -“rechargeable fan” - “usb fan under 1000” None of these users were in-market for a ₹3,000+ BLDC ceiling fan. But we were still showing up. And paying for those clicks. And it’s not just us. I’ve seen 6–7 brands' Amazon ad accounts across categories over the last few years—same problem, every single time The fix? N-gram analysis Takes less than an hour. You don’t need to be a performance marketing expert. But the results compound What’s N-gram analysis? It’s breaking down every search term into its word components—1-grams, 2-grams, 3-grams—and then identifying patterns that consistently drive waste… or conversion. Example: “cheap rechargeable fan for hostel room” turns into: 1-grams: cheap, rechargeable, fan, hostel, room 2-grams: rechargeable fan, hostel room 3-grams: fan for hostel, etc. When you do this across all your search terms, you start seeing the real picture. Why this matters more than just checking your search term report: Search terms ≠ keywords a) One keyword can trigger 100s of different queries. Some convert. Most don’t. You need to find the patterns. b) Waste is diluted across low-volume terms. Maybe “rechargeable fan for hostel” spent ₹300. You ignore it. But what if 12 other queries with “rechargeable” spent ₹6,000 in total with zero conversions? c) Long-tail is infinite. N-grams are finite. You can’t negate every bad search. But you can block the core terms—“cheap”, “usb”, “mini”—once and be done with it. d) It helps you scale campaigns too. You can find goldmine phrases like “white ceiling fan”, “silent BLDC fan”, “fan for living room”—with 5x+ ROAS. Those became exact match campaigns What you should do: a) Pull last 3 months of search term data b) Break them into unigrams, bigrams, trigrams c) Create a pivot with spend, orders, ROAS by N-gram d) Negate high-spend, low-conversion N-grams (e.g., “cheap”, “rechargeable”) e) Boost high-ROAS ones (e.g., “bldc”, “ceiling fan white”) f) Add exact match campaigns g) Rinse and repeat monthly Try it. Guaranteed to improve efficiency at whatever scale you are operating If you want to read an expanded version of the post, link is in the first comment

Scaling from 50 to 100 employees almost killed our company. Until we discovered a simple org structure that unlocked $100M+ in annual revenue. In my 10+ years of experience as a founder, one of the biggest challenges I faced in scaling was bridging the organizational gap between startup and enterprise. We hit that wall at around 100~ employees. What worked beautifully with a small team suddenly became our biggest obstacle to growth. The problem was our functional org structure: Engineers reporting to engineering, product to product, business to business. This created a complex dependency web: • Planning took weeks • No clear ownership  • Business threw Jira tickets over the fence and prayed for them to get completed • Engineers didn’t understand priorities and worked on problems that didn’t align with customer needs That was when I studied Amazon's Single-Threaded Owner (STO) model, in which dedicated GMs run independent business units with their own cross-functional teams and manage P&L It looked great for Amazon's scale but felt impossible for growing companies like ours. These 2 critical barriers made it impractical for our scale: 1. Engineering Squad Requirements: True STO demands complete engineering teams (including managers) reporting to a single owner. At our size, we couldn't justify full engineering squads for each business unit. To make it work, we would have to quadruple our engineering headcount. 2. P&L Owner Complexity: STO leaders need unicorn-level skills: deep business acumen and P&L management experience. Not only are these leaders rare and expensive, but requiring all these skills in one person would have limited our talent pool and slowed our ability to launch new initiatives. What we needed was a model that captured STO's focus and accountability but worked for our size and growth needs. That's when we created Mission-Aligned Teams (MATs), a hybrid model that changed our execution (for good) Key principles: • Each team owns a specific mission (e.g., improving customer service, optimizing payment flow) • Teams are cross-functional and self-sufficient,  • Leaders can be anyone (engineer, PM, marketer) who's good at execution • People still report functionally for career development • Leaders focus on execution, not people management The results exceeded our highest expectations: New MAT leads launched new products, each generating $5-10M in revenue within a year with under 10 person teams. Planning became streamlined. Ownership became clear. But it's NOT for everyone (like STO wasn’t for us) If you're under 50 people, the overhead probably isn't worth it. If you're Amazon-scale, pure STO might be better. MAT works best in the messy middle: when you're too big for everyone to be in one room but too small for a full enterprise structure. image courtesy of Manu Cornet ------ If you liked this, follow me Henry Shi as I share insights from my journey of building and scaling a  $1B/year business.

🌟 𝐒𝐭𝐨𝐩 𝐓𝐡𝐢𝐧𝐤𝐢𝐧𝐠 𝐁𝐢𝐠 - 𝐒𝐭𝐚𝐫𝐭 𝐓𝐡𝐢𝐧𝐤𝐢𝐧𝐠 𝐖𝐢𝐝𝐞! The biggest breakthroughs don’t happen by digging deeper into one area - they happen when ideas, industries, and technologies collide. Think about it: AI combined with IoT has transformed healthcare. Sustainability powered by cloud solutions is opening new markets. The magic lies at the 𝐢𝐧𝐭𝐞𝐫𝐬𝐞𝐜𝐭𝐢𝐨𝐧𝐬 - where fresh opportunities emerge. 🚀 𝐖𝐡𝐲 𝐓𝐡𝐢𝐬 𝐌𝐚𝐭𝐭𝐞𝐫𝐬 1️⃣ 𝐅𝐚𝐬𝐭𝐞𝐫 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐨𝐧: Combining technologies like AI and cloud accelerates growth. 2️⃣ 𝐍𝐞𝐰 𝐌𝐚𝐫𝐤𝐞𝐭 𝐑𝐞𝐚𝐜𝐡: Partnerships across industries unlock untapped customers. 3️⃣ 𝐒𝐡𝐚𝐫𝐞𝐝 𝐕𝐚𝐥𝐮𝐞: Cross-industry collaboration lowers costs and drives new value. At Deloitte, I’ve seen the power of collaboration. By partnering with organizations like #Celonis, #Schaeffler, #HumboldtInnovation, and #GermanEntrepreneurship, we’ve established the European non-profit AI ecosystem, #KIPark. This initiative brings together players from different industries to unlock innovation. For example, we’ve developed an ESG platform, marking a significant step toward sustainable solutions that are robust and business-relevant. 🛠️ 𝐓𝐡𝐫𝐞𝐞 𝐖𝐚𝐲𝐬 𝐭𝐨 𝐒𝐭𝐚𝐲 𝐀𝐡𝐞𝐚𝐝 1️⃣ 𝐋𝐨𝐨𝐤 𝐎𝐮𝐭𝐬𝐢𝐝𝐞 𝐘𝐨𝐮𝐫 𝐈𝐧𝐝𝐮𝐬𝐭𝐫𝐲: Who could you partner with to create something new? 2️⃣ 𝐁𝐮𝐢𝐥𝐝 𝐌𝐢𝐱𝐞𝐝 𝐓𝐞𝐚𝐦𝐬: Pair data scientists with operations or customer-facing teams. 3️⃣ 𝐄𝐱𝐩𝐞𝐫𝐢𝐦𝐞𝐧𝐭 𝐁𝐨𝐥𝐝𝐥𝐲: Start small pilots that combine tech and business ideas. 🌍 𝐓𝐡𝐞 𝐁𝐨𝐭𝐭𝐨𝐦 𝐋𝐢𝐧𝐞 The future belongs to businesses that connect the dots others don’t see. Breadth - not just depth - is the key to growth and resilience. 💬 𝐘𝐨𝐮𝐫 𝐓𝐮𝐫𝐧 What’s one unexpected partnership or idea you’ve seen recently that sparked innovation? Let’s exchange ideas. Who knows what new intersections we might uncover together? #Deloitte #AI #Innovation #Leadership #BusinessStrategy #Partnerships 𝐴𝑟𝑡𝐵𝑎𝑠𝑒𝑙. 𝐶ℎ𝑎𝑛𝑔𝑒𝑂𝑓𝑃𝑒𝑟𝑠𝑝𝑒𝑐𝑡𝑖𝑣𝑒. 𝐹𝑜𝑢𝑛𝑑 𝑎𝑡 @𝑔𝑎𝑏𝑟𝑖𝑒𝑙𝑙𝑒𝑒𝑒𝑟𝑢𝑡ℎ

As Industry 4.0 reshapes our business landscape, it’s critical to grasp its diverse aspects. The "Periodic Table of Industry 4.0 Elements" serves as a high-level guide, focusing on crucial areas for companies to consider in their strategic planning. 𝐁𝐫𝐞𝐚𝐤𝐢𝐧𝐠 𝐃𝐨𝐰𝐧 𝐭𝐡𝐞 𝐂𝐚𝐭𝐞𝐠𝐨𝐫𝐢𝐞𝐬: 𝟏. 𝐄𝐧𝐚𝐛𝐥𝐢𝐧𝐠 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬: The major technological innovations that serve as the engine for Industry 4.0. Invest in upskilling your workforce with the proper digital literacy to effectively leverage these technologies for innovation and competitive advantage. 𝟐. 𝐕𝐚𝐥𝐮𝐞 𝐃𝐫𝐢𝐯𝐞𝐫𝐬: The primary benefits and objectives that Industry 4.0 aims to deliver. Prioritize and measure your initiatives based on their potential to drive value in these specific areas. 𝟑. 𝐎𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐔𝐬𝐞 𝐂𝐚𝐬𝐞𝐬: The most common use cases where enabling Industry 4.0 technologies change how companies operate and how employees work. 𝟒. 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐔𝐬𝐞 𝐂𝐚𝐬𝐞𝐬: The most common use cases where products are being reimaged and improved with enabling Industry 4.0 technologies. Products are not only being designed differently, but designed with intelligence built in and customer experiences as part of the sale. 𝟓. 𝐍𝐞𝐰 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐌𝐨𝐝𝐞𝐥𝐬: Industry 4.0 introduces new ways of conducting business and providing value. Explore partnerships and platforms that could enable you to adopt new business models and expand your market reach. 𝟔. 𝐃𝐞𝐬𝐢𝐠𝐧 𝐏𝐫𝐢𝐧𝐜𝐢𝐩𝐥𝐞𝐬: The foundational guidelines that enable the seamless integration and efficient functioning of advanced digital technologies and processes within the industrial ecosystem. This table is not exhaustive, but rather a focused lens to view the critical elements that can help drive strategic decisions during these transformative times. And just like the elements in nature, the elements of Industry 4.0 are vast and continuously expanding as we learn and discover new things! 💬 I'd love to hear your thoughts: How are you leveraging these elements in your Industry 4.0 strategy? 𝐅𝐮𝐥𝐥 𝐚𝐫𝐭𝐢𝐜𝐥𝐞: https://lnkd.in/eCFwNzJg ******************************************* • 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!

Tesco’s share price is up almost 50% in the last two years. The business is on a roll, reporting strong financial performance in the latest update which I recently discussed with BBC News. ➡ Strong Financial Performance: 💠Retail like-for-like sales up 2.9%, with UK (+4.0%), ROI (+4.7%), and Central Europe (+0.6%) 💠Adjusted operating profit increased 10.0% to £1,555m 💠Market share reaches 27.8% - highest since January 2022 ➡ Omnichannel Excellence: 💠Large stores leading with 4.2% growth 💠Digital sales surging - online up 9.3%, now 13.5% of UK sales 💠Whoosh rapid delivery expanding to 1,460 stores 💠1.3M online orders per week ➡ Digital & Loyalty Innovation: 💠Clubcard penetration reaching new heights: UK 82%, ROI 85%, CE 87% 💠4.9M customers receiving personalised 'Clubcard Challenges' 💠Growing retail media platform showing strong advertiser engagement What's fascinating about Tesco's performance isn't just the numbers - it's the sophisticated ecosystem play that's emerging. Here's why I believe Tesco are in such a commanding position: 📲 Data Monetisation Tesco isn't just running a retail media network; they're orchestrating the UK's largest closed-loop retail ecosystem. With 23M Clubcard households, they've created a virtuous cycle: customer data drives personalisation, which increases engagement, which generates more data. Their partnership with dunnhumby transforms this into a powerful advertiser proposition - true closed-loop measurement across online and offline touchpoints. This is retail media 2.0. What's more, retail media typically delivers 60-70% margins, compared to traditional grocery retail's 2-5%. By building this high-margin revenue stream, built on strong tech underpinnings, their media tech proposition has become a key strategic asset boosting their valuation. It's a page out of the Amazon/Walmart's media businesses playbook where this part of the business is valued at multiples of their retail operations. 🎯 Core Business Focus The 4.0% like-for-like growth tells a deeper story about strategic discipline. Over the past decade, Tesco has systematically simplified its business model - exiting non-core markets and doubling down on what they do best: food retail with a magic sprinkle of data. It’s been fascinating to see how sometimes doing less allows businesses to achieve more. 🤖 AI-Powered Customer Centricity The deployment of AI to analyse shopping patterns isn't just about efficiency - it's about reimagining the customer relationship. By using predictive analytics to anticipate customer needs and suggest relevant products, Tesco is moving from reactive to predictive retail. In my view, the next stage of personalisation. These results showcase Tesco's ability to balance traditional retail strength with digital innovation while maintaining strong market leadership.

We're moving away from charging for *access* to software and toward a model of charging for the *work delivered* by a combination of software and AI agents. Let’s dive into what’s happening and what it means for you ⤵️ 1. The rise of disruptive AI pricing models Tech companies are realizing they can't solely rely on seat-based subscriptions in an age of AI, automation and APIs where value is disconnected with how many people are logging in. Perhaps Salesforce going all-in on Agentforce (and charging $2 per conversation) was the push the industry needed. Each product category has its own flavor of disruptive pricing. - Legal AI products might charge for a demand package generated by AI or an AI-generated summary. - Creator AI products might charge for the content that gets produced such as a video generation or amount of video created. - GTM products might charge for specific tasks completed or workflows executed by the AI. 2. Selling work, not necessarily success As a customer, I wish I only had to pay for software when it delivered results. But the reality is that true success-based billing won’t work for the vast majority of today’s products. Most products should charge for work output instead. The issue is attribution. You want the customer to get a fantastic outcome — and you want them to recognize that your product powered that outcome. As soon as you start charging for success, the customer begins to rethink the results. 3. Goodbye ARR as we know it? Shifting to these newer value-based pricing models isn't a simple pricing change you can just announce in a press release. It's a business model evolution that looks a lot like the shift from on-prem to SaaS in the first place. These new AI pricing models might mean greater volatility in both usage and spend. Variable margin profiles across products and customers. Seasonal revenue fluctuations. The potential for project-based, non-recurring use cases. Put simply, annual recurring revenue (ARR) continues to get dethroned. — Full post in today’s Growth Unhinged newsletter: https://lnkd.in/ea5eTrVD Things are about to get interesting 🍿 #ai #pricing #saas

Bollywood’s biggest disruptor may not be Netflix or Hotstar but quiet 1,000 Cr money-making machine Maddock Films YRF and Dharma are legendary legacy. Maddock started when DDLJ was 20 years old. Maddock’s founder was a investment banker, not a Kapoor. Maddock’s first film Finding Fanny barely returned money. Far from being a disruptor, Maddock looks like a tiny, artsy production not to care But looking at the screen reveals a blockbuster machine having generated 1,300 Cr in 2024 Dinesh Vijan grew up in Punjabi, Partition afflicted family. In 2004, at 23, the i-banker left his job, crazily to make films. With no connections, Dinesh had to grapple. Starting with Being Cyrus in 2005, it barely broke even. With no films for 3 years, the struggle began. Teaming up with Being Cyrus’ Saif Ali Khan, Dinesh started Illuminati in 2008 In 2009 Love Aaj Kal landed, delivering a 100 Cr hit 5 years after Vijan’s start Indian cinema began to transform with 3 Idiots, Wake Up Sid, and ZNMD by 2010. Vijan’s focus was on telling unconventional stories. But Agent Vinod’s 2012 flop almost killed Illuminati. Movie production, like VC, is a hits business. Without another hit, Vijan would be out. As 2012’s Cocktail ended with 130 Cr, Vijan knew he was onto something By 2014, Vijan would start Maddock, debuting with Finding Fanny Maddock had built a formula, in an industry that didn’t seem to have any. Find unconventional stories. Work with similar group of actors. Blend two different disparate genres. Don’t depend on big stars. Maddock would soon churn out Badlapur, Hindi Medium, Raabta. Churning almost 90 Cr each, Maddock was staring into the 120,000 Cr media market By 2018, just 23% of box office collections were with star-driven movies, a huge shift Movies were a hits business. Box office collections drove 70% rev, digital 15-20%. Distributors, theaters, stars, creating ate up costs. Production houses would end with ~10% PAT. But Maddock became a hit factory. Merging horror/comedy, Stree would be a massive success in 2019. Generating 180 Cr on 20 Cr, it would be 10x gross on budget Maddock’s own revenue would cross 100 Cr, with a huge PAT of 35% Maddock diversified genres. Bala, Lukka Chupi, Made in China, would create a portfolio of “investments”. As the pandemic hit, theatricals got killed. Helped by OTT, the industry crept back in 2021. Driven by Sooryavanshi’s success, stars charged huge fees. Maddock lack of star reliance helped Maddock was soon about to use a new formula - the Stree horror universe By 23, it delivered more hits like ZHZB. But ’24 would be its announcement to the world. Stree 2 would hit 900 Cr. Maddock would deliver 2 more 100 Cr+ hits. Turning almost 1,300 Cr on 150 Cr budget, Maddock had become a money making machine. Star production houses like YRF, Dharma had been left in the dust by the outsider, i-banker with filmy dreams With details here (https://bit.ly/4gKxwpr), Maddock could create a 5,000 Cr empire disrupting Bollywood