STUDY FINDS COST PER WEAR INFORMATION SHIFTS SHOPPERS TO QUALITY: A new study published in Psychology & Marketing offers a fascinating look at what fashion drives fashion purchasing decisions. Researchers from the University of Bath and Cambridge University found that simply showing consumers the cost per wear (CPW) of garments (price divided by the number of times an item can be worn) can shift preferences away from cheap, low-quality clothing toward higher-priced, longer-lasting options. The findings draw on behavioural psychology to reveal that people respond more to perceived 'economic value' than to abstract sustainability messages. When shoppers could compare CPW between garments, and especially when figures were backed by trusted certification, they were far more likely to choose quality over quantity. The authors suggest CPW could be a powerful tool for brands and policymakers seeking to reframe sustainability as smart spending. Full story in comments.
Product Value Creation
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Few Lessons from Deploying and Using LLMs in Production Deploying LLMs can feel like hiring a hyperactive genius internâthey dazzle users while potentially draining your API budget. Here are some insights Iâve gathered: 1. âCheapâ is a Lie You Tell Yourself: Cloud costs per call may seem low, but the overall expense of an LLM-based system can skyrocket. Fixes: - Cache repetitive queries: Users ask the same thing at least 100x/day - Gatekeep: Use cheap classifiers (BERT) to filter âeasyâ requests. Let LLMs handle only the complex 10% and your current systems handle the remaining 90%. - Quantize your models: Shrink LLMs to run on cheaper hardware without massive accuracy drops - Asynchronously build your caches â Pre-generate common responses before theyâre requested or gracefully fail the first time a query comes and cache for the next time. 2. Guard Against Model Hallucinations: Sometimes, models express answers with such confidence that distinguishing fact from fiction becomes challenging, even for human reviewers. Fixes: - Use RAG - Just a fancy way of saying to provide your model the knowledge it requires in the prompt itself by querying some database based on semantic matches with the query. - Guardrails: Validate outputs using regex or cross-encoders to establish a clear decision boundary between the query and the LLMâs response. 3. The best LLM is often a discriminative model: You donât always need a full LLM. Consider knowledge distillation: use a large LLM to label your data and then train a smaller, discriminative model that performs similarly at a much lower cost. 4. It's not about the model, it is about the data on which it is trained: A smaller LLM might struggle with specialized domain dataâthatâs normal. Fine-tune your model on your specific data set by starting with parameter-efficient methods (like LoRA or Adapters) and using synthetic data generation to bootstrap training. 5. Prompts are the new Features: Prompts are the new features in your system. Version them, run A/B tests, and continuously refine using online experiments. Consider bandit algorithms to automatically promote the best-performing variants. What do you think? Have I missed anything? Iâd love to hear your âI survived LLM prodâ stories in the comments!
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Innovation isnât just about upgrading your toolsâitâs about reinventing how you create, deliver, and capture value. Digital business models are reshaping industries by creating value in ways unimaginable a decade ago. These aren't your grandparentâs business models with a digital veneerâthey're transformative, leveraging tech to disrupt markets, engage customers, and redefine competition. This revolution is captured brilliantly in the book: ð·ðððð¡ðð ðµð¢ð ðððð ð ðððððð ððð ð¼ððð¢ð ð¡ðð¦ 4.0: ð»ðð¤ ð¼ðððð£ðð¡ððð ððð ðððâðððððð¦ ðâððð ð¡âð ð¹ð¢ð¡ð¢ðð ðð ð¶ðððððððð . ð ð¨ð®ð« ðð¢ð¥ð¥ðð«ð¬ ð¨ð ðð¢ð ð¢ððð¥ ðð®ð¬ð¢ð§ðð¬ð¬ ðð¨ððð¥ð¬: â¢Â ðð¢ð ð¢ððð¥ð¥ð² ðð§ððð¥ðð ððð¥ð®ð ðð«ðððð¢ð¨ð§: Value driven by tech, not just supported by it. Think smart thermostats optimizing energy, not just controlling it. â¢Â ððð«ð¤ðð ðð¨ð¯ðð¥ðð²: New offerings or ways of doing businessâlike predictive maintenance or on-demand manufacturing. â¢Â ðð¢ð ð¢ððð¥ ðð®ð¬ðð¨ð¦ðð« ðð¨ð®ðð¡ð©ð¨ð¢ð§ðð¬: Customer relationships built through apps, IoT, and connected services. â¢Â ðð¢ð ð¢ððð¥ð¥ð² ððð«ð¢ð¯ðð ððð: Unique selling points rooted in data and digital capabilities. But how do we map the revenue streams emerging from these shifting dynamics? Iâve come to see it through three essential components: â¢Â ðð¨ð«ð ððð¥ð®ð ðð«ð¨ð©ð¨ð¬ð¢ðð¢ð¨ð§ (What is being offered?) â¢Â ððð¥ð®ð ðð«ðððð¢ð¨ð§ ðððð¡ðð§ð¢ð¬ð¦ð¬ (How is value created?) â¢Â ððð¯ðð§ð®ð ððð«ððð¦ð¬ (How is value captured?) ðððð ðð®ð¥ð¥ ðð«ðð¢ðð¥ð: https://lnkd.in/ewhRUM28 ******************************************* ⢠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 ð for notifications!
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The most expensive mistake in business is assuming your customers will never change. Last year, something shifted in Indian retail. Gen Z (377 million) overtook millennials (356 million) to become our largest consumer group, influencing $40-45 billion worth of apparel and footwear purchases. But they're not shopping at the stores we built for them. [Et Retail] Brands watched their growth collapse in just 12 months. â ZARA fell from 40% to 8% growth, [Et Retail] â Levi Strauss & Co. crashed from 54% to 4% growth [Et Retail] â H&M dropped from 40% to 11% growth [Et Retail] Here's why the growth has slowed down: ð Gen Z discovered new brands like Freakins and Bonkers Corner, offering trendy clothes at â¹500-800 ð They chose self-expression over brand loyalty ð 70% of their shopping moved online, heavily influenced by Instagram ð They demanded inclusive sizing (XS to XXL) and unisex options that legacy brands ignored Take FREAKINS, which clocked â¹25 crore in FY2023, or Bonkers.corner, clocked â¹100 crore. [The Economic Times] [Et Retail] These brands understood what Gen Z wanted: crop tops, baggy clothes, Korean pants, and oversized tees at prices that let them experiment with three different outfits daily. Body positivity isn't a marketing campaign for this generation. It's how they think. When they couldn't find the sizes or styles they wanted at premium stores priced at â¹1,200-1,500, they simply went elsewhere. Myntra saw the shift and launched FWD with â¹500 price points. The result was explosive: 100% year-on-year growth and 16 million Gen Z users, who now represent one in three e-lifestyle shoppers. [Et Retail] Legacy brands bet that Gen Z would "grow up" and pay premium prices. Instead, 377 million young Indians chose values over logos. The most expensive mistake in business? Assuming your customers will never change. What changes in your customer base have surprised you recently?
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We spent the last 3 months researching how PE firms create value ð± The result: âThe Private Equity Value Creation Reportâ â one of the most in-depth studies on the topic, based on the data from over 10,000 PE entries and exits globally. ð³ ð¸ð²ð ðð®ð¸ð²ð®ðð®ðð: 1ï¸â£ Revenue growth is the largest driver of PE value creation On average, it contributes to 54% of value creation. Recently, revenue growth has become an even more critical driver of success (as multiples have come down), contributing to ~65-70% of value creation in the last 2 years. 2ï¸â£ Margin expansion plays a smaller role at 15% Margin expansion is most impactful when PE firms target operationally challenged businesses rather than already-efficient businesses. 78% of deals with negative EBITDA margins achieved margin expansion (median +1250bps), while businesses with high EBITDA margins (>30%) typically saw margin contraction. 3ï¸â£ Multiple expansion contributes significantly at 32% For the top quartile deals, its contribution is even higher at 40%. By sector, TMT, Science & Health, and Services see the largest multiple expansion. Consumer and Industrials see the least. By size, multiple expansion is the highest for smaller deals under $100M EV. 4ï¸â£ Growth amplifies all other PE value creation drivers Growing companies benefit from operating leverage and are more likely to achieve margin expansion. 58% of growing firms expand margins compared to 44% of those with negative growth. Higher-growth companies also typically command 30â50% higher multiples at exit. 5ï¸â£ Top and bottom-performing deals are held the longest Investors hold onto the best-performing assets for greater upside but also hold the worst, trying to fix the business. Assets held in the 3-6 year range tend to cluster around more predictable, moderate returns. 6ï¸â£ Buy-and-build is central to PE value creation When done right, buy-and-build bolsters all three value creation drivers: revenue growth, margin expansion, and multiple expansion. Buy-and-build works at any size, but the uplift is strongest in small platforms. The multiple arbitrage strategy still works with add-ons trading at a 20% discount to platforms. 7ï¸â£ Larger deals drive more margin expansion Large businesses ($1bn+ EV) and public-to-private deals, on average, deliver more margin expansion. Smaller businesses, on the other hand, rely more on growth and multiple expansion to drive returns. Given the smaller size, returns on average, are also higher for family-to-sponsor deals. _______ ððð¹ð¹ ð¥ð²ð½ð¼ð¿ð Donât miss out on insights: ð¡ By Sector ð¡ By Deal Type and Size ð¡ MOICs and Loss rates + 5 case studies and 43 charts. Get it here â¡ï¸ https://lnkd.in/d9Z3kubU (E-mail required) #ValueCreation #Growth #PrivateEquity
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Itâs easy as a PM to only focus on the upside. But you'll notice: more experienced PMs actually spend more time on the downside. The reason is simple: the more time youâve spent in Product Management, the more times youâve been burned. The team releases âtheâ feature that was supposed to change everything for the product - and everything remains the same. When you reach this stage, product management becomes less about figuring out what new feature could deliver great value, and more about de-risking the choices you have made to deliver the needed impact. -- To do this systematically, I recommend considering Marty Cagan's classical 4 Risks. ð. ð©ð®ð¹ðð² ð¥ð¶ðð¸: ð§ðµð² ð¦ð¼ðð¹ ð¼ð³ ððµð² ð£ð¿ð¼ð±ðð°ð Remember Juicero? They built a $400 Wi-Fi-enabled juicer, only to discover that their value proposition wasnât compelling. Customers could just as easily squeeze the juice packs with their hands. A hard lesson in value risk. Value Risk asks whether customers care enough to open their wallets or devote their time. Itâs the soul of your product. If you canât be match how much they value their money or time, youâre toast. ð®. ð¨ðð®ð¯ð¶ð¹ð¶ðð ð¥ð¶ðð¸: ð§ðµð² ð¨ðð²ð¿âð ðð²ð»ð Usability Risk isn't about if customers find value; it's about whether they can even get to that value. Can they navigate your product without wanting to throw their device out the window? Google Glass failed not because of value but usability. People didnât want to wear something perceived as geeky, or that invaded privacy. Google Glass was a usability nightmare that never got its day in the sun. ð¯. ðð²ð®ðð¶ð¯ð¶ð¹ð¶ðð ð¥ð¶ðð¸: ð§ðµð² ðð¿ð ð¼ð³ ððµð² ð£ð¼ððð¶ð¯ð¹ð² Feasibility Risk takes a different angle. It's not about the market or the user; it's about you. Can you and your team actually build what youâve dreamed up? Theranos promised the moon but couldn't deliver. It claimed its technology could run extensive tests with a single drop of blood. The reality? It was scientifically impossible with their tech. They ignored feasibility risk and paid the price. ð°. ð©ð¶ð®ð¯ð¶ð¹ð¶ðð ð¥ð¶ðð¸: ð§ðµð² ð ðð¹ðð¶-ðð¶ðºð²ð»ðð¶ð¼ð»ð®ð¹ ððµð²ðð ðð®ðºð² (Business) Viability Risk is the "grandmaster" of risks. It asks: Does this product make sense within the broader context of your business? Take Kodak for example. They actually invented the digital camera but failed to adapt their business model to this disruptive technology. They held back due to fear it would cannibalize their film business. -- This systematic approach is the best way I have found to help de-risk big launches. How do you like to de-risk?
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CIOs are leading a transformation focused on strategic, long-term value rather than just adopting the latest tech. ð Lenovoâs Global CIO Study shows 96% of CIOs plan to boost tech investments, focusing on AI and security. From my conversations, itâs clear theyâre also thinking about sustainability and future-proofing in a rapidly evolving tech landscape. ð¡ However, 61% of CIOs face challenges in proving ROI from these investments, highlighting the need to not only innovate but to deliver measurable outcomes. Here are four strategies to tackle this challenge: 1ï¸â£ Align Tech Investments with Business Goals Tie each technology decision directly to business outcomes. Whether itâs enhancing customer experience, increasing revenue, or improving operational efficiency, measurable goals make the case for ROI clearer. 2ï¸â£ Build Cross-functional Alignment Involve key business leaders in the early stages of technology planning. Demonstrating how investments benefit various departments, from marketing to operations, builds stronger support for technology initiatives and ensures alignment with broader company objectives. 3ï¸â£ Prioritize Long-term Value Creation While short-term wins are important, CIOs must invest in technology that continues to deliver value over time. AI, for instance, plays a pivotal role in future-proofing organizations in a rapidly changing digital landscape. 4ï¸â£ Leverage Sustainability and Future-of-Work Strategies New growth areas, like sustainability and adapting to the future of work, are top-of-mind for CIOs. AI is central to addressing these trends, from optimizing energy use to enabling more productive environments - key factors in demonstrating ROI over the long term. For me, leading through this transformation isnât just about adopting AI or new tools. Itâs about building a roadmap that is thoughtful and strategic, building a solid foundation today for tomorrowâs growth. How are you navigating your businessâs tech transformation to demonstrate ROI? Iâd love to hear your insights on the challenges and opportunities. ð¤ #WeAreLenovo #TechTransformation #AI
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Thereâs a fine line between saying ânoâ because of attitude and saying ânoâ because you understand the value of what you bring to the table. Early on, I realized it wasnât about followers, views, or appearances. It was about attention to detail, the process and the standards I had set for myself and my team. When clients asked to lower rates or push budgets, the response was simple: Thatâs my price. No over-explaining, no defending, no justifying. Confidence in the value you create is often more persuasive than any argument about experience or past projects. This mindset helps attract the right clients as well. The people who value your approach and respect your standards naturally gravitate toward working with you. And sometimes, it allows you to say ânoâ to opportunities that donât align, preserving focus, quality and integrity. Itâs also about presence. In client interactions, nothing replaces direct engagement. Even with a capable team, certain conversations, especially first calls or high-stakes projects, benefit from your direct involvement. People want to feel the commitment, the clarity, & the vision firsthand. That connection often determines whether a client signs on or walks away. At the end of the day, value is in how you position it, how you communicate it & how you stand by it. The right clients recognize that and the wrong ones fade away. And thatâs exactly how you build sustainable, meaningful work that makes a real impact. #graphicdesign
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ð AI is making services sexy again. ð The core promise of AI is the elimination of barriers to creation. Text, audio, video, code... all become easier to generate. When creation becomes that simple, it doesnât just empowerâit commoditizes. What once required deep expertise and high barriers to entry can now be built by many, intensifying competition in software. Meanwhile, service businessesâthe ones weâve all ignored because, letâs be honest, their margins werenât greatâhave a shot at massive value creation. Here's the math: ð©ð Average professional services margin: 15-25% ð¨ð» Average software margin: 70-80% ð¤ AI-powered services margin: Approaching software territory AI fundamentally alters the unit economics of human labor by scaling a single personâs productivity exponentially. It can convert a 5-person team into a 50-person productivity powerhouse. Services that traditionally lived in the low-margin corner are now knocking on the door of software-like profitability. In a commoditized software world, the moat shifts. Itâs not about the codeâitâs about who owns the customer relationship. Itâs in trust. Itâs in delivery. Services businesses that leverage AI effectively are on the verge of tremendous value creation. ð ð° The ultimate irony is that the technology thatâs supposed to take over the world, might actually put the power back in human hands. As software commoditizes, the intangible stuffârelationships, service, trustâbecomes the differentiator.
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In a post earlier this week, we discussed how value is created and sustained on factors wider than price. It is interesting to visualize this via data. The diagram below shows the position of retailers with at least something of a focus on price. Their consumer rated scores for price are on the x axis. The further to the right, the better the score. The y axis shows each retailerâs top non-price strength - design for IKEA, style for Primark, convenience for Walmart and Amazon, and so on. Higher is better rated. There are some interesting positions on the chart. The strongest area is the upper right. These retailers are highly regarded on price and are also great at delivering something else alongside. This makes their value proposition incredibly strong. The weakest area is the lower left. Here, retailers like Family Dollar and Big Lots have lackluster price scores - a big problem as this is supposed to be their point of differentiation. They don't score well on other factors either. Note, that these scores are from last year so before Big Lots went bankrupt. Itâs fine to be middling on price if you excel elsewhere. Amazon and Costco are in this bucket: they're competitive, but they donât solely focus on the lowest possible prices; however, they really deliver on other factors. TJX's brands are also present: by design, they offer great bargains, which is a little different to low prices. The bottom right, where Shein and Temu are placed, is interesting. Both are really strong on price but are relatively weak on secondary factors. This creates very one-dimensional loyalty, which is an issue now their low-price operating model has been disrupted. I have not included every retailer on this chart and there is a bit more noise in some of the data. But the creation of a thoughtful and differentiated value proposition, aligned to consumer desires, is one of the most critical things in retail. #retail #retailnews #value #price #retailers #strategy #consumers