Saâd AMRANI JOUTEY

Last week we took part in the third edition of McKinsey France's Tech Services Circle, which delved into the challenge of "Boosting Operating Margin Performance". This event has once again provided in-depth insights and actionable strategies to reshape the Tech Services Industry. The agenda for this third edition focused on: 🛡 Focus on Margin Protection: Strategies to protect your margins amidst changing market dynamics 📊 Pricing as a Game Changer: Leveraging pricing to drive operating margins higher 👥 Modernising People Supply Chain: Real-life case studies showing how modernisation can deliver a 3-5 point increase in margins On the stage, our CEO Jean-Philippe Couturier shared his insights with industry thought leaders: Charles-Henri Rannou, Marc-Antoine de La Chevasnerie and Pierre Watchi from McKinsey & Company. Each brought a unique perspective on using pricing strategies and modernising the people supply chain to deliver significant margin improvements. At Whoz, we are committed to turning these insights into action, setting new industry benchmarks and driving sustainable growth. 🔗 Want to dive deeper into how these winning strategies might help your business? Let’s connect! #TechServicesCircle #OperatingMargins #PeopleSupplyChain #BusinessStrategy

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Keen to discover how to harness Data Science and Machine Learning to Improve demand forecasting? 📈 Watch the replay of our latest webinar where we delve into this topic and unveil our solution FaaS4U, combining the robustness of AI with a fresh perspective to ensure effective stock management. 💡 Or reach out for a private session of knowledge sharing! 💬 Stay ahead with FaaS4U! #DataScience #MachineLearning #Forecasting #AI #StockManagement #axialyze #teamingforvalue #fromvisiontoreality

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🎯 VN1 Forecasting Competition report The VN1 forecasting competition, organised by Nicolas Vandeput, is now in full swing. The datasets are available to download, and the first phase ends on 3rd October. It is not too late to participate, see the first comment below for more detail. The challenge is to make accurate 13-week-ahead forecasts for sales volume across over 15,000 combinations of client, warehouse and product. I made a submission yesterday which pushed me up from 20th place up to 8th place (out of 41) on the leaderboard. I still have more ideas for improvement (as presumably the other competitors also do), so it will be interesting to see how things evolve over the coming days. My objectives for the competition are: - Enhance further my Python coding skills for data cleaning and processing - Deepen further my understanding of machine learning forecasting models - Enjoy the challenge of understanding patterns within a new dataset Here are some takeaways: 1. Benchmark comparison is crucial. For over 20 years, my go-to benchmark has been a 4-week weighted average with weights of 0.4, 0.3, 0.2 and 0.1. If a forecasting model doesn’t beat a simple benchmark, it’s time to try something else. 2. Beating the benchmark can be challenging. My initial model amendments performed worse than the benchmark. It was a relief once I had beaten the benchmark. Finding improvements is an iterative process, and it can be frustrating when trying something new makes the error larger. 3. Python’s power and efficiency are excellent for modelling a large number of time series. Although getting the code right is taking me longer than performing the analysis in Excel, I find that any subsequent tweaking and rerunning the Python code is much more convenient compared with managing an Excel workbook. I’ll share a full report of forecasting findings at the end of the competition. I’m looking forward to finding out how other competitors have approached the challenge. I regularly share my thoughts on #Forecasting, #ResourcePlanning, and #PerformanceImprovement in #CustomerOperations. Please connect with me, hit the 🔔 on my profile, and select “All” to stay updated.

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📣 👉 Amazon to invest $1.3 bln in France ! "Amazon Web Services (AWS) investment would increase cloud infrastructure in the Paris area to support France's flourishing #generativeAI opportunity" If you ever had a doubt of how much French business is embracing #hybridCloud and #GenAI, do not doubt any more ! As we've already demonstrated as a prime AWS partner, IBM Consulting is the right partner to support efficient and at scale #GenAI uses-cases in #France. https://lnkd.in/dPdsxZ6w

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New paper from myself and Anne Laure Thibaud (Thieullent) on the topic of how the rise of operational AI is going to fundamentally alter the way that organizations need to look at data. Key points: 1) GenAI (and Agentic) will enable digital employees at operational speeds 2) Digital Employees need data that reflects the operational reality 3) You need to establish a digital operating model 4) You'll need to plan for people managing AI as well as people 5) The Business needs to take control of its digital reality When we started writing this paper it felt like this world was still a while away, since then we've had an explosion in applications embedding GenAI and Agentic solutions. So now it more feels like this is how you need to plan for 2025 rather than a vision for the medium term. Myriam Chave, Mark Oost, Sergey P., Franck Greverie, Eric REICH, Alex Marandon https://lnkd.in/gFw2w9aJ

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If you know an 18 yo who dream of creating a deep tech startup, they could go to a big natural sciences' university. Or… …go to a small(ish) stand alone business school🏫 Les Deeptech 🚀 from Bpifrance just released their latest analysis for #French #Deeptech, which gives us an interesting overview of the local higher education scene. Sure, HEC Paris - Innovation & Entrepreneurship Institute is ranked #4 in that list (and we are happy about it), but that’s not the really interesting part. What you should pay attention to is that we are not an anomaly. Among the top 15 listed universities, one-third are business schools! It does feel like getting a business education could bring value to science-based entrepreneurship… But what do I know? 🤷‍♂️ What we do know is that investing in research and education keeps paying dividends. And when in doubt between studying science and business, just get both degrees 😁 If you are interested, go check out the full ranking there: https://lnkd.in/eD-r8pDD PS: I know this is a list for ants, no need to call your optometrist 🔍 PPS: I will not complain about per capita measurements not being the global standard for ranking metrics

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🚀 Ekimetrics belongs to the 2% companies to be certified "Gold" from EcoVadis. It's a great achievement, rewarding Ekimetrics work on ESG strategy. EcoVadis ESG is based on 21 criteria, following international nroms on sustainable development. For Ekimetrics, it means: 1️⃣ Our strong internal commitment to sustainabilise our business 2️⃣ ESG is not just a buzz word (#greenwashing), it's a foundational value for us, that guides our actions and drives our ecosystem 3️⃣ Last but not least. ESG is not orthogonal to our AI practioner activities, quite the oppositive. We plan sustainable practices, among which ethics & carbon emissions reduction, at the core of our AI work. Big kuddos to all the teams. Caroline Milliotte Jean-Baptiste Bouzige Quentin Michard Laurent Félix Théo Alves Da Costa William NAIT MAZI 🐼

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Excellent article, comprehensive and detailed, perfect for getting familiar with linear regression in machine learning. Usefull for anyone looking to understand the basics and explore practical applications of this fundamental technique. 🚀 #MachineLearning #DataScience #AI #LinearRegression

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What is the common link between Generative AI and consulting? They both need a human-centric approach. 🤖 Today, Le Wagon for Business organized a workshop on Generative AI for consultants. Coming from various domains, 14 consultants gathered to participate in the intensive training led by •Guillaume VERDON• and Yannis Bouhamou. What did they learn in just one day? ↳ How to leverage Gen AI and LLMs with prompts tailored for consulting ↳ How to create automated workflows ↳ A deeper understanding of the ethical implications of Gen AI ↳ How to apply AI tools to better aid clients in real life scenarios 🛠️ Those who excel with AI stay ahead of the curve by continuously learning new ways to leverage the tool through training and practical application in their fields. Is your team staying at the forefront of innovation with AI? #GenAI #Consulting #Training #Learning

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Une Coupe de Cheveux en Provence (with help from GPT-4o and Claude 3.5 Sonnet) In days past, a classic consulting firm interview question involved quantitative estimation, such as asking how many gas stations there are in New York. I decided to test the quantitative reasoning skills of GPT-4o and Claude 3.5 Sonnet with a similar question: “What is the size of a town in Provence that might support 2-3 barbers or hair salons?” GPT-4o reasoned that a barber shop or salon might handle 15 clients a day, 5 days a week, and that potential clients might get a haircut every two months, resulting in an estimate of 600 clients per shop, and 1,200 to 1,800 clients for 2-3 shops. GPT-4o: “For instance, a town like Crestet, which has a population of around 400 (as of recent estimates), would likely not support 2-3 salons on its own, but nearby larger towns might.” “Given Crestet's small size, you might look for nearby towns such as: Vaison-la-Romaine: A larger town approximately 15 minutes away, with a population of around 6,000 people, which likely supports multiple barbers and hair salons. Carpentras: About 30 minutes away, with a population of around 30,000, offering many more options. Final Recommendation: For a reliable haircut experience, consider driving to Vaison-la-Romaine or Carpentras, where you will find several barbers and hair salons catering to a larger population. This ensures you have multiple options to choose from.” Finally, it produced the image below. Claude 3.5 Sonnet asserted that “[a] typical hair salon can serve about 100-200 regular clients” and assumed that “people get haircuts every 6-8 weeks on average.” Using the midpoints of those ranges, it got to 3,375 people to support 2-3 shops. It then noted that in “more rural areas like Provence, people might travel further for services. We should add a buffer to account for this: let's say 20%. 3,375 * 1.2 = 4,050 people” Finally, it rounded up for a conservative estimate: “To ensure the town can comfortably support 2-3 salons, let's round up. A town of about 4,500-5,000 people should be able to support 2-3 barbers or hair salons in a rural French setting like Provence.” It did an excellent job of identifying 5 nearby towns as options, based on population and driving distance, and concluded: “Among these options, Vaison-la-Romaine is likely your best bet, given its proximity and adequate size to support multiple hair salons. Orange and Carpentras, while slightly farther, offer more options due to their larger populations. Nyons is a good middle-ground option, while Buis-les-Baronnies might be worth checking if you prefer a smaller town setting.” My assessment: GPT-4o did a better job on the estimation portion of the problem and on the image, and Claude 3.5 Sonnet came up with a nice set of towns. Based on these analyses, I am heading to Vaison-la-Romaine and will report back in the comments. #technology #ai #innovation #france

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Le véhicule autonome ? Pour le DARPA, d'abord pour les missions de reconnaissance ou dangereuses, hors des routes et des chemins : https://lnkd.in/eDfDerrF "When it comes to automating off-road driving, the U.S. Army can be a great customer. After all, autonomous vehicles started as a DARPA project, says Jeff Peters, a partner at Ibex Investors. DARPA (Defense Advanced Research Projects Agency) is a U.S. Department of Defense agency focused on advancing technology for military use. “The hype around AV moved a lot of the industry toward bigger potential commercial applications, but DoD projects have persisted,” Peters told TechCrunch over email, noting that autonomous mining startup SafeAI and autonomous trucking startup Kodiak Robotics have also pursued defense grants. “I think AV companies (those still around) will chase DoD projects because it offers large, non-dilutive funding in the interim prior to commercial operations.”  Overland AI is the latest byproduct of the DARPA program. Boots, a professor of machine learning at the University of Washington and founder of the Robot Learning Laboratory at the university’s school of computer science and engineering, has a long history of collaborating with the U.S. Army Research Lab and DARPA.  Overland was spun out from Boots’ research and team involved in DARPA’s RACER (Robotic Autonomy in Complex Environments with Resiliency) program, the goal of which is to develop self-driving vehicles that can handle tough terrain. The program is still ongoing. Overland, which is stacked with deep tech veterans from Google, Nvidia, Apple, Waymo, Aurora, Embark and Argo, as well as software engineers who’ve worked on mission-critical solutions at SpaceX, RTX and the U.S. Army, was recently selected to continue on to the second phase."

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💥New investment – Industry 4.0💥 🎉 The Bpifrance French Tech Accélération team is delighted to announce its participation in the €8.5M fundraising of OSS Ventures, an #Industry40 #startupstudio, alongside Tikehau Capital and Etablissements Peugeot Frères. 🚀 OSS Ventures is the leading studio specializing in software for operations. Its mission is to help factories digitalize, become more efficient, and reduce their environmental impact. ⭐Since its establishment in 2019, the studio has demonstrated a strong track record: - Created more than 15 #startups. - OSS Ventures, one of Europe's most successful digital studios, generates over €25M in annual recurring revenue (ARR) from its startups. - The solutions are deployed at nearly 2 000 industrial sites. - OSS has also created a community: a network of industrial partners, industry operations managers and sector experts. 🔍OSS Ventures aims to identify the operational problems encountered by blue-collar workers and operators, and to map out the areas where digital technology can help. The company’s strength lies in co-constructing startups with manufacturers. 💡 They have created various companies, such as fabriq, a software for digital problem-solving in factories, and MyC, a solution for health management in complex environments (ships, oil rigs, mining, etc.). 🚀 With this latest round of financing, OSS Ventures has raised a total of €11M. This funding will enable the studio to scale up its model and create 5 startups per year. 🏆 The startup studio is an operational company, which relies on its 20-member team, with expertise in IT development, design, marketing and sales, operations, and communications. 👉 Find out more: press release link in comments Renan Devillieres Pierre Lavaux Aurore Lanchart Jean-Philippe Lorinquer Quentin Dubois Maroussia Houimli Pierre GILLET Océane Fleury Bpifrance #France2030 #Manufacturing #Innovation #DigitalTransformation

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‘Le Chat’ ‘la platform’ Mistral AI artificial intelligence, France’s Startup Darling, Takes Aim at the US Market : Mistral's edge could come from customers that want to avoid being locked into particular cloud companies “Customers are even saying ‘Le Chat’ and ‘la platform’ It seems that the French touch is having an effect.” opportunity is huge — Bloomberg Intelligence estimated that the software and cloud market in generative AI market could reach $350 billion by 2032 : Mistral is going after OpenAI’s home turf “They do not want to be forced into an AI stack” “They want choices” Mistral released a series of AI models, which power generative AI services, and a ChatGPT-like feature called Le Chat : US manager says businesses are looking for alternatives to Big Tech : will find customers through these partners as well as via direct deals with companies using its open-source models. Open source is one of Mistral’s main selling points : the approach — where the underlying computer code is openly shared and tweakable — as a safer, more versatile method than closed systems offered by OpenAI and others : Mistral’s open-source models on-premises, with data stored in local servers instead of with public cloud providers ---- generative artificial intelligence ---

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⚡️ May the force be with you, Adobe Wan Kenobi 🤣 As the digital world whirls forward, a new contestant steps into the ring of trustworthiness – Adobe's AI assistant. 🚀 Using rigor to navigate the information labyrinth, it doesn't just answer; it illuminates with precision. Imagine you're sifting through a mountain of documents, seeking that golden nugget of information. Adobe's AI doesn't just find it; it hands you a map with an 'X' marking the spot. 🗺️✨ With the ability to handle up to 600 pages per document and tackle ten at a time, this assistant transforms daunting data deluges into digestible insights. For businesses, the implications are game-changing. From crafting detailed presentations to whipping up a sharp social media post – all backed by accurate, sourced content – it's an ally in the armory of every professional aiming for accuracy over ambiguity. As we pursue transformational growth at Accenture Song, we recognize that tools like Adobe's AI create a new benchmark in reliability, a beacon for those navigating the stormy seas of digital data. ⛵️🌊 Let's champion this blend of technological might with methodical precision! #DigitalTransformation #ArtificialIntelligence #Innovation #DataAccuracy #AdobeAI #ProfessionalExcellence Gabriel CREA Johan Knijtijzer Mehmet Olmez

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We're thrilled to share an insightful article featuring Jérémy Crevoisier, co-founder of Fasterion Consulting. From his background in astrophysics 🌠 and data analysis to the creation of Fasterion, this article explores his journey and the innovative services the company offers in technological and strategic intelligence. 📖 Jérémy’s story reflects the passion behind Fasterion, built on the belief that "the world is a database." 🙏 Special thanks to Stéphanie Robert and the University of Strasbourg for highlighting this story! 📖 Read the full article here: https://lnkd.in/eYpT9_Cv #Fasterion #Innovation #DataScience #TechnologicalIntelligence #Entrepreneurship

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➿ #AI / #LLM / #GenAI & environmental concerns: the history often repeats itself.. A few years ago, talks around AI where mainly focused on performance, metrics, #data volume, optimal architecture design. Then other questions hijacked the spotlight: how energy-efficient are those models? What's the cost of a relatively small increment in terms of performance? Is that increment necessary? This great article from Benoit Raphael brings a comprehensive point of view on Generative AI's appetite in terms on energy and water, and associated CO2 emission. Personal key takeaways : 1️⃣ It makes little sense to focus only on one aspect, eg model trainings. GenAI full lifecycle should be considered: from servers' and smartphones' design and consumption up to individual prompts' impacts 2️⃣ GenAI's impact on the planet needs to be compared to how much energy humans would need to produce the same output: for instance, LLMs generate illustration with a relatively small cost when compared to the time and energy a professional graphic designer would need to generate the same output. 3️⃣ Some interesting rough figures to quizz your friends: 🛩 Training GPT-3 model emitted approximately as much CO2 as 550 Paris - NYC round trips / passenger 📱With the most "greedy" models, generating one image uses (roughly) as much energy as you need to fully charge one cellphone 🚗 You can find in the article figures and proxies to approximate CO2 emission equivalence between model prompting and distance covered in a classic thermal car Etienne Grass | Alex Marandon | Nicolas Gaudilliere | Hugo Cascarigny | Philippe Cordier | Alexandre Lapene | Valentin Millery | Simon Gosset https://lnkd.in/eZKdjzZR

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Un projet ERP qui finit par ruiner l'un des plus grands conseils municipaux d'Europe 👇 https://lnkd.in/d2dYRxuH Many leaders pride themselves on setting the high-level direction and staying out of the details. But big picture, hands off leadership isn’t likely to work in a change situation, because the hardest part of change—the paralyzing part—is in the details. Any successful change requires a translation of ambiguous goals into concrete behaviors. To make a switch, you need to script the critical moves.

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