Pranay Agrawal

Join me at the Smart Manufacturing Forum and the Data & AI summit in Canary Wharf London on the 14th of November. I will be doing a keynote detailing how AI is changing Smart Manufacturing and what the future looks like. In a fast moving but in-depth conversation, I'll be covering AI's impact on efficiency in manufacturing and supply chain, predictive maintenance and sustainability, while also diving into the fascinating topic of Digital Twins. We will discuss an amazing new technology approach that promises to re-do the landscape of Data and AI in manufacturing - you'll have to join us to see what I'm talking about! Join us - see you there. #SmartManufacturingForum #DataAndAI #Innovation #DigitalTransformation #CXOCircle #Leadership

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Shining a Light on the Unsung Hero of Advanced Analytics Thanks, #Cypher, for the opportunity to engage with such a forward-thinking community! While #AdvancedAnalytics, #AI, and now #GenAI often steal the spotlight, it's important to recognize the unsung hero behind their success: a strong #datafoundation. Without clean, reliable, and well-structured data, these advanced technologies can’t deliver their full potential. The real magic happens when the hard work of building and maintaining that foundation meets cutting-edge innovation. Let’s start glorifying the backbone of analytics success—the foundation that makes everything else possible! What’s your take on balancing innovation with foundational excellence? #DataFoundation #AI #GenAI #AnalyticsMaturity #DigitalTransformation #Innovation

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Team story: X is the smartest member of the team. Make sure to take care of him, Vivek! From 2015 to 2018, while working at ZS, my manager often said this about the "smartest" team members. He believed in giving them high-end tasks to keep them engaged. Over these three years, there were five such “smartest” resources at various time interval out of a 15-member team. Interestingly, these top performers left within 1 to 1.5 years, while "regular" stayed for three years or more. These “smartest” resources handled 20% of the revenue-generating ad-hoc analytics work, while the "regular" resources managed 80% of the revenue generating work, i.e. operational tasks. In 2018, with no “smartest” resources left, I advocated for a "regular" team member to take on an ad-hoc analytics project. My manager reluctantly agreed, and after working on the IC design project, he realized that this "regular" team member was also highly capable. I then explained to my manager that everyone at ZS is smart. Some are just more outspoken and quick to grasp things (termed by him as "smart"), but that doesn’t mean "regular" can’t rise to the challenge. It's just that the “smartest” resources kept getting ad-hoc work and work directly with the manager, which made them better at it and more valued in the manager’s eyes, while the "regular" resources were undervalued. This is a classic example of “perception bias” and how it led to a “self-fulfilling prophecy.” P.S. I was also considered a “regular” resource by him, and I was perfectly fine with that to avoid working with him directly! And honestly, I’m not that smart - my wife can vouch for it! 😃

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Looking forward towards sharing and learning best data practice,discuss insights and meet the best and like minded leaders in the industry . See you there ! #ETCIO #ETCIODSS #DataAnalytics #CIO #BusinessLeaders #DataStrategy #ITLeaders #ITSummit #TechInnovation #ETCIODSS #analytics #india #data

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📊 Excited to share insights from Prabhakant Sinha, Arun Shastri, and Sally E. Lorimer on the intersection of analytics and sales decisions! 💡 In a world inundated with #AI-driven recommendations, it's crucial to understand when #analytics should guide sales strategies, and when human intuition and expertise should take the lead. 🤝 Join the conversation to explore the balance between data-driven insights and human judgment in driving sales success. #Analytics #SalesStrategy #DataDrivenDecisionMaking #BusinessInsights Harvard Business Review https://lnkd.in/dJBgGRw5

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Consumer-facing businesses everywhere are using AI to elevate the customer experience with hyperpersonalization but are running into problems due to the lack of data centralization. In his latest Forbes article, EXL's Anand Logani shares valuable insights on how to use AI and centralized data to create a personalized omnichannel journey. Check out the article to learn how to build an effective omnichannel strategy that meets your customers’ expectations. #AI #Data #CX

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Audit Assistance is a solid area for #ReliableAI development. E.g. QC cycle times in Retail, CPG should boost shopper experience, in store ROI, and more. HT: Shravan Kumar A, Anand S, Lori Silverstein

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It was a pleasure talking to CXO Digital Pulse. I hope the discussion helps the industry, as they work towards disruptive AI incubation and adoption. Cheers! #ai #adoption #standardization #sustainability https://lnkd.in/gXchrKj3

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Join this webinar to learn how to drive impactful insights for your organization with AI and Tableau Pulse. Register now to get expert help from leaders at CoEnterprise #Insurance #Insuretech #BFSI #Analytics #BI #Tableau

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As we are approaching the final quarter of the year, I’ll be sharing some of observations and fault lines with the genAI trend observed in retail. There are many nuances to this but here are three to start: 1) No Data strategy. Companies that did not take their data strategy seriously will struggle taking their genAI strategy seriously. This is a first principle. GenAI strategies will agonize without a centralized semantic layer and a clear meta data strategy (among other things). We are no longer data modeling exclusively for humans, we are enabling a level of semantic rigor for AI agent consumption. Disparate data sources will also lead to missing opportunities to unlock the power of unstructured data sources, and to release differentiating hyper-tailored customer experiences to name a few.   2) Resources: This could be either in internal skillsets both technical and business, partnerships or cash. Those new to the AI discipline, introduced to it via the openAI web platform, may now be finding themselves tackling complicated AI systems and strategies. And thus finding out quickly that it turns out moving useful AI products into production is not easy. For those who have been working in the areas of data science/ML/AI for years will tell you this is no surprise, it was never easy. Many are now realizing that it is much easier to describe reality than to approximate it. And that innovative ideas can come from places that might be least expected, and absent from the expected. As genAI allows for the democratization of innovative workflows, this leads to the insight that the way we work, what we might have traditionally valued, is changing. 3) Design: A common issue with enterprise design is the misapplication of traditional assumptions rooted in deterministic systems that do not learn in any meaningful way. Rather consider probabilistic systems that can handle uncertainty and scale the intelligence of the system. Considering a focus on peer to peer agent communication. This will potentially lead to AI agents negotiating their own communication protocols as the intelligence of the system scales. This in part allows for the emergent behavior of collective intelligence whereas the system potentially transforms from a clock-like system to a dynamic beehive-like network. Those are a few quick takes and there are many more, I’m curious to hear any other observations from those in the field.

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Understanding the full spectrum of Indian voices has always been a challenge in market research. Achieving true representativeness is crucial for ensuring greater empathy and better insights. I'm excited to share that Ipsos has acquired Crownit (GoldVIP), a mobile-first panel and data collection platform. This move helps us combine traditional methods with agile digital approaches, significantly enhancing our ability to capture diverse perspectives across India. This acquisition is a key step towards solving the representativeness issue, enabling us to gather more accurate and meaningful insights. It's an exciting time for market research in India! Read the press release: https://lnkd.in/eP5HnXaK #MarketResearch #DataCollection #MobileFirst #DigitalTransformation 

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✨ Data for AI Leaders Roadshow Abstractions ✨   One dynamic month of public speaking, client (CDAO) connects, learnings. Multiple forums - AWS DataCon, Informatica World Tour, HETT Show, Snowflake World Tour; 100+ client and prospect conversations.   My abstractions:   AI | GenAI reality check - After we get past the "How great my AI use case ('experiment' is what most mean) is" narrative, the real conversation and learning begins, when leaders face the brutal facts that there is work to be done.    Pre-requisite for Scaling AI - Health | Wealth | Consumers | Citizens - Whichever domain you belong to, if you don't have "ready" data for AI, forget about scaling AI use cases. No mind-blowing product can scale AI unless- you know where to look to start navigating this puzzle.    'Lego'fying the foundation - Often data becomes the blocker for AI scaling. Productised data can become the catalyst to scale.    Trust worthy data and AI - Transparent, responsible, explainable, fair structures, policies, which can be set and monitored are key to a healthy data + AI scale-worthy solution    AI for Data and Data for AI - Data needs AI to solve it's problem. AI needs Data to solve its problem. You separate both - you lose the plot.    Data + AI portfolio value - It is no longer data value assessment, or AI value assessment, but the vertical integration of the Data + AI portfolio value, to make CDAOs win the AI race.    Double click on each of these topics with us. Let's learn more from each other. #data for #genAI, #responsibleAI, #artificialintelligence Sriram Narasimhan, Pushpa Ramachandran, Ashish Sharma, Ajay Upadhyay, Balasubramani Harikrishnan, Bijoy C, Soumya Chowdhury, Prakash K., Sukhvinder Phalora, Hema Hariharan, Jayakumar Rajaretnam, Tushar Marathe, Antonio Sawaya, Nishant Jain, Varun Khanna, Sangeeta Kar, Debojit Biswas

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Building a Career Around Data Products: Using Product Mindset with Analytics Today, I had the pleasure of catching up with Vineet Batra from Chubb, who heads their analytics team. Vineet is a passionate leader in building intelligent data products with his strong background leading products and data teams at OYO and BNY. We discussed the future of analytics and products, focusing on the creation of data products and noting that awareness around this topic is still quite limited. Many might wonder, what are data products, and why do we need them? Simply put, data products represent the next level in analytics, embedding data insights into core products and daily lives. While, traditional analytics often involves ad hoc analyses presented in PPTs, Excel sheets, or dashboards. In contrast, data products leverage these insights on a larger scale, integrating them into everyday tools and processes with strong use of cloud technology. But it requires a strong product approach. Here are some examples of how data products touch our lives: •⁠ ⁠Credit Bureaus: Organizations like CIBIL, Transunion use data from our payment and credit histories and transactions to create credit scores, providing a snapshot of our creditworthiness. •⁠ ⁠Payment Networks: Companies such as Visa and MasterCard utilize vast amounts of transaction data to build data insights solutions and indexes to help network banks and merchant. •⁠ ⁠Health Apps: Applications like Fitbit and Apple Health collect and analyze data from our daily activities, offering insights into our fitness levels and health trends. Personally I had the opportunity to build some very useful data products during my career, including the automation of audits, marketing automation and global procurement to drive supply chain synergies. These experiences have shown me firsthand the transformative power of data products. The next big thing in AI and products will be embedding AI and analytics into everything, building very cool data-driven products. Google Maps is a prime example of how data and AI help us navigate our world efficiently, which has also enabled innovative solutions like Uber. What are some data products that have touched your life? Share your experiences and thoughts in the comments below ! If you are someone who would like to explore learning about building data products, do comment or DM either of us. #dataproducts #career #analytics #product

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While most dashboards expect the user to explore and find their own insights, data stories come with a preset storyline presented in an engaging manner. As Nobel laureate Daniel Kahneman famously said, “No one ever made a decision because of a number. They need a story.” #datastorytelling #datavisualization #analytics #businessintelligence

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Meet with ZS at #InformaticaWorld24 to learn how we are enhancing enterprise data management and leveraging gen AI. Book a meeting here: https://bit.ly/3Ub3x0P #datagovernance #datamanagement #artificialintelligence #AI

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Honored to be recognized by AIM Research as one of the 100 Most Influential AI Leaders. Truly humbled and honored by this great gesture. It has been a long journey though but with ever changing analytics it is truly just a start. Thank you to AIM Research and Congratulations to all my fellow AI and analytics practitioners and contributors who has been part of this journey. Let’s keep pushing the boundaries of what’s possible! https://lnkd.in/ggyykX44 #AI #Innovation #Leadership #Recognition #AIMResearch #AMPBA #IIDS #Analytics #AIM #ArtificialIntelligence #ISB Feel free to connect with me for any discussions on Analytics and Digital Transformation. Preksha Jain Sejuti Das

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Founded in 2000 by🌟 Srikanth Velamakanni ,🔥 Pranay Agrawal and 🌟Ashwath Bhat ,🚀 Fractal offers artificial intelligence and advanced analytics solutions to Fortune 500 companies. 🚀🌟Fractal To File DRHP By September For $600 Mn IPO, Eyes $3 Bn Valuation🚀🌟 🌟Fractal's IPO Ambition: Fractal is set to file its Draft Red Herring Prospectus (DRHP) by September for a $600 million Initial Public Offering (IPO), targeting a $3 billion valuation. This bold move showcases the company's growth and vision for the future. 🌟Visionary Founders: Founded in 2000 by Srikanth Velamakanni, Pranay Agrawal, and Ashwath Bhat, Fractal has been at the forefront of artificial intelligence and advanced analytics solutions. Their dedication and foresight have propelled the company to serve Fortune 500 companies worldwide. 🌟AI and Analytics Leadership: Fractal's commitment to leveraging artificial intelligence and advanced analytics demonstrates its leadership in the tech industry. Their solutions empower businesses to make data-driven decisions, driving innovation and efficiency. 🌟Global Impact: With clients among the Fortune 500, Fractal's influence extends across various industries, proving the universal applicability and necessity of their cutting-edge solutions. Their journey inspires others to think big and strive for global impact. 🌟Perseverance and Growth: The founders' journey from starting Fractal in 2000 to preparing for a major IPO is a testament to their perseverance, strategic vision, and ability to navigate the evolving tech landscape. Their story encourages aspiring entrepreneurs to remain resilient and adaptable. 🌟Empowering Businesses: Fractal's advanced analytics solutions enable companies to unlock the full potential of their data, leading to smarter decision-making and enhanced business outcomes. This empowerment is a key driver of their success and a source of inspiration for other tech innovators. 🌟Strategic Milestone: The upcoming IPO is not just a financial milestone but a strategic move that will allow Fractal to scale further, innovate faster, and expand its market presence. It highlights the importance of strategic planning and execution in achieving long-term goals. 🌟Inspiring Future Entrepreneurs: Srikanth Velamakanni, Pranay Agrawal, and Ashwath Bhat's journey with Fractal serves as a powerful example for future entrepreneurs. Their success story demonstrates that with vision, dedication, and a focus on innovation, it's possible to achieve remarkable heights. ✅️Share Your Startup Story 🚀📲 https://lnkd.in/ggir3Qap ✅️visite our website🌐 https://lnkd.in/dad4nHP4 #Fractal #AI #AdvancedAnalytics #IPO #TechInnovation #SrikanthVelamakanni #PranayAgrawal #AshwathBhat #StartupSuccess #GlobalImpact #BusinessGrowth #Entrepreneurship #DataDriven #Fortune500 #Inspiration #Motivation #scoopearth

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#Take2 Why the Market May Be Overestimating Quick Commerce's Future Despite Damodaran's Optimism As a genuine admirer of #AswathDamodaran and his insightful #valuation frameworks, it's fascinating to see how his evaluations cut to the core of a business's #financial #health. However, with #quickcommerce, it’s possible that the broader market has overestimated the long-term potential of these businesses. Quick commerce is undeniably enticing in terms of #growth and #marketshare grabs, but as Damodaran himself has noted, the sector faces headwinds like narrow #margins and dependency on high-frequency, low-value transactions. Quick commerce relies heavily on the temporary advantage of local #logistics and #labor #arbitrage, but as cities become more congested and labor markets tighten, these operational “advantages” could quickly erode. Furthermore, the political landscape may not always be welcoming, especially given the impact on local #kirana stores, which are integral to India’s #retail fabric. While Damodaran’s framework rightly emphasizes lifecycle positioning, it may not fully capture the #political and #inflationary risks that quick commerce facilitates and faces as it scales. This could mean that valuations, even if optimistic now, might not reflect the long-term stability or profitability the street expects. One critical factor that quick commerce models often overlook is India's regional #diversity —it's anything but a #homogenous market. Local preferences, purchasing behaviors, and infrastructure vary widely from city to city. Quick commerce platforms will need to adapt to these variations, constantly refining and expanding their product categories to cater to local demands. This could mean shifting beyond the basic groceries and essentials model and embracing more regional product mixes, which further adds to complexity and costs. The sector's reliance on ultra-fast delivery and inventory optimization only intensifies these challenges, as what works in a metro city like Delhi or Mumbai may fail in smaller towns where consumer habits and logistical networks differ significantly. This makes scaling in India particularly #complex, and could limit the profitability of the "one-size-fits-all" model that quick commerce often tries to implement. All things considered, I’m confident that these companies have the talent needed to evolve. Just look at how Zomato transformed from its early days to what it is now. The real question is: what will they evolve into, and will that future model justify the premium they currently command? For now, I’ll take advantage of my exclusive offer on Coke Zero from quick commerce and enjoy it while it lasts.

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