Data is your business. Have you unlocked its full potential? If you read nothing else on data strategy, read this book. We've combed through hundreds of Harvard Business Review articles and selected the most important ones to help you maximize your analytics capabilities; harness the power of data, algorithms, and AI; and gain competitive advantage in our hyperconnected world. This book will inspire you to: Reap the rewards of digital transformation Make better data-driven decisions Design breakout products that generate profitable insights Address vulnerabilities to cyberattacks and data breaches Reskill your workforce and build a culture of continuous learning Win with personalized customer experiences at scale This collection of articles includes "What's Your Data Strategy?," by Leandro DalleMule and Thomas H. Davenport; "Democratizing Transformation," by Marco Iansiti and Satya Nadella; "Why Companies Should Consolidate Tech Roles in the C-Suite," by Thomas H. Davenport, John Spens, and Saurabh Gupta; "Developing a Digital Mindset," by Tsedal Neeley and Paul Leonardi; "What Does It Actually Take to Build a Data-Driven Culture?," by Mai B. AlOwaish and Thomas C. Redman; "When Data Creates Competitive Advantage," by Andrei Hagiu and Julian Wright; "Building an Insights Engine," by Frank van den Driest, Stan Sthanunathan, and Keith Weed; "Personalization Done Right," by Mark Abraham and David C. Edelman; "Ensure High-Quality Data Powers Your AI," by Thomas C. Redman; "The Ethics of Managing People's Data," by Michael Segalla and Dominique Rouzies; "Where Data-Driven Decision-Making Can Go Wrong," by Michael Luca and Amy C. Edmondson; "Sizing Up Your Cyberrisks," by Thomas J. Parenty and Jack J. Domet; "A Better Way to Put Your Data to Work," Veeral Desai, Tim Fountaine, and Kayvaun Rowshankish; and "Heavy Machinery Meets AI," by Vijay Govindarajan and Venkat Venkatraman. HBR's 10 Must Reads are definitive collections of classic ideas, practical advice, and essential thinking from the pages of Harvard Business Review. Exploring topics like disruptive innovation, emotional intelligence, and new technology in our ever-evolving world, these books empower any leader to make bold decisions and inspire others.

Inscriptions ici : 🎟️ https://lu.ma/khtf9c9x

Ravi de vous retrouver demain 28 mai 19H00 pour notre meetup 🚀 Comptoir IA #23

Une rafale d’IA générative avant le pont : 👾 Ari – Vibe Fighter : jeu et avatars Street Fighter créés en temps réel 🧠 Olivier - HABS - Human Augmented Brain System – Le “Neuralink” made in France 📞 Thomas (YC W2025) – Dollyglot : nous passerons un appel à Donald Trump 😜 🎬 Gilles – Analyse créa & tech de sa campagne Meta 🎥 Alexandre – Première démo publique de VEO 3

🤩 Dans le cadre magnifique de La Maison by Motier Ventures

🎟️ 90 places · networking & apéro

​Un immense merci à notre dream team qui rend tout cela possible : John-Edwin, Caroline, Thierry, Marine, Sane, Gilles, Ghislain, Christian, Hedy, Edouard, Alexandre, Paul, Sylvain, Ari 🙏

Inscrivez-vous vite ! 🎟️ https://lu.ma/khtf9c9x

Merci pour vos RT 🔄

1️⃣5️⃣ème édition du meetup Comptoir IA ✨

🚀 Prêts pour le meetup Comptoir IA n°15 ? C'est parti ! Mercredi 24 prochain à 19H00.

🎟️ Inscrivez-vous vite, les places partent comme des petits pains ! https://lu.ma/comptoir-IA-15

📰 News IA et Open-Prompting comme d’habitude

📖 Alexandre dévoilera comment ChatGPT révolutionne la vie des dyslexiques 🗺️ Chloé vous présentera la cartographie des pépites françaises de l'IA 🇫🇷💎 💪 Paul-Louis mettra les LLM au défi dans un benchmark musclé et vous présentera phospho (YC W24) 🎨 Laissez-vous émerveiller par les créations de Mehdi 🦾 Haixuan Xavier viendra avec son robot IA open-source avec lequel il a fait sensation avec Thomas d’🤗 🌇 Hubert dévoilera son rapport sur les villes et l'IA générative

🙏 Un grand merci à MyConnecting IA, Stephane, John-Edwin, Sane et surtout PublicisLive Paris (Florence, François, Achille) pour leur soutien !

Et tous nos amis : Gilles, Hedy, Thierry, Christian, Léava, Lucie, Hanna, Caroline, Brian, Florian, Dov, Ghislain, Laurent, Julien, Jean-Charles…

📅 Rendez-vous mercredi chez Publicis Live pour vivre une expérience IA inoubliable ! 🤫👕 Pour ceux qui ont un T-Shirt Comptoir IA, vous êtes sur la liste ! 💬 Des questions ? Envie de participer ? DM moi (QR code requis à l’entrée) https://www.linkedin.com/in/nicoguyon/

Do you know what happens to your personal data when you are browsing, buying, or using apps? Discover how your data is harvested and exploited, and what you can do to access, delete, and monetize it. Data for All empowers everyone—from tech experts to the general public—to control how third parties use personal data. Read this eye-opening book to learn: The types of data you generate with every action, every day Where your data is stored, who controls it, and how much money they make from it How you can manage access and monetization of your own data Restricting data access to only companies and organizations you want to support The history of how we think about data, and why that is changing The new data ecosystem being built right now for your benefit The data you generate every day is the lifeblood of many large companies—and they make billions of dollars using it. In Data for All, bestselling author John K. Thompson outlines how this one-sided data economy is about to undergo a dramatic change. Thompson pulls back the curtain to reveal the true nature of data ownership, and how you can turn your data from a revenue stream for companies into a financial asset for your benefit. About the Technology Do you know what happens to your personal data when you’re browsing and buying? New global laws are turning the tide on companies who make billions from your clicks, searches, and likes. This eye-opening book provides an inspiring vision of how you can take back control of the data you generate every day. About the Book Data for All gives you a step-by-step plan to transform your relationship with data and start earning a “data dividend”—hundreds or thousands of dollars paid out simply for your online activities. You’ll learn how to oversee who accesses your data, how much different types of data are worth, and how to keep private details private. What's Inside The types of data you generate with every action, every day How you can manage access and monetization of your own data The history of how we think about data, and why that is changing The new data ecosystem being built right now for your benefit About the Reader For anyone who is curious or concerned about how their data is used. No technical knowledge required. About the Author John K. Thompson is an international technology executive with over 37 years of experience in the fields of data, advanced analytics, and artificial intelligence. Quotes An honest, direct, pull-no-punches source on one of the most important personal issues of our time....I changed some of my own behaviors after reading the book, and I suggest you do so as well. You have more to lose than you may think. - From the Foreword by Thomas H. Davenport, author of Competing on Analytics and The AI Advantage A must-read for anyone interested in the future of data. It helped me understand the reasons behind the current data ecosystem and the laws that are shaping its future. A great resource for both professionals and individuals. I highly recommend it. - Ravit Jain, Founder & Host of The Ravit Show, Data Science Evangelist

Today I’m chatting with returning guest Tom Davenport, who is a Distinguished Professor at Babson College, a Visiting Professor at Oxford, a Research Fellow at MIT, and a Senior Advisor to Deloitte’s AI practice. He is also the author of three new books (!) on AI and in this episode, we’re discussing the role of product orientation in enterprise data science teams, the skills required, what he’s seeing in the wild in terms of teams adopting this approach, and the value it can create. Back in episode 26, Tom was a guest on my show and he gave the data science/analytics industry an approximate “2 out of 10” rating in terms of its ability to generate value with data. So, naturally, I asked him for an update on that rating, and he kindly obliged. How are you all doing? Listen in to find out!

Highlights / Skip to:

Tom provides an updated rating (between 1-10) as to how well he thinks data science and analytics teams are doing these days at creating economic value (00:44) Why Tom believes that “motivation is not enough for data science work” (03:06) Tom provides his definition of what data products are and some opinions on other industry definitions (04:22) How Tom views the rise of taking a product approach to data roles and why data products must be tied to value (07:55) Tom explains why he feels top down executive support is needed to drive a product orientation (11:51) Brian and Tom discuss how they feel companies should prioritize true data products versus more informal AI efforts (16:26) The trends Tom sees in the companies and teams that are implementing a data product orientation (19:18) Brian and Tom discuss the models they typically see for data teams and their key components (23:18) Tom explains the value and necessity of data product management (34:49) Tom describes his three new books (39:00)

Quotes from Today’s Episode “Data science in general, I think has been focused heavily on motivation to fit lines and curves to data points, and that particular motivation certainly isn’t enough in that even if you create a good model that fits the data, it doesn’t mean at all that is going to produce any economic value.” – Tom Davenport  (03:05)

“If data scientists don’t worry about deployment, then they’re not going to be in their jobs for terribly long because they’re not providing any value to their organizations.” – Tom Davenport (13:25)

“Product also means you got to market this thing if it’s going to be successful. You just can’t assume because it’s a brilliant algorithm with capturing a lot of area under the curve that it’s somehow going to be great for your company.” – Tom Davenport (19:04)

“[PM is] a hard thing, even for people in non-technical roles, because product management has always been a sort of ‘minister without portfolio’ sort of job, and you know, influence without formal authority, where you are responsible for a lot of things happening, but the people don’t report to you, generally.” – Tom Davenport (22:03)

“This collaboration between a human being making a decision and an AI system that might in some cases come up with a different decision but can’t explain itself, that’s a really tough thing to do [well].” – Tom Davenport (28:04)

“This idea that we’re going to use externally-sourced systems for ML is not likely to succeed in many cases because, you know, those vendors didn’t work closely with everybody in your organization” – Tom Davenport (30:21)

“I think it’s unlikely that [organizational gaps] are going to be successfully addressed by merging everybody together in one organization. I think that’s what product managers do is they try to address those gaps in the organization and develop a process that makes coordination at least possible, if not true, all the time.” – Tom Davenport (36:49)

Links Tom’s LinkedIn: https://www.linkedin.com/in/davenporttom/ Tom’s Twitter: https://twitter.com/tdav All-in On AI by Thomas Davenport & Nitin Mittal, 2023 Working With AI by Thomas Davenport & Stephen Miller, 2022 Advanced Introduction to AI in Healthcare by Thomas Davenport, John Glaser, & Elizabeth Gardner, 2022 Competing On Analytics by Thomas Davenport & Jeanne G. Harris, 2007

Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.

Abstract Hosted by Al Martin, VP, IBM Expert Services Delivery, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts. This week on Making Data Simple, we have Kristen Summers and John Thomas. Kristen is a Distinguished Engineer in Cloud and Cognitive Expert Labs. Kristen has worked in Artificial Intelligence and Data Science, PHD in Computer Science, and leads Data Science within our Expert Labs. John is a Distinguished Engineer in Data and Expert Labs, John leads Services that helps clients establish the AI factory.

Show Notes 3:24 – What is the AI academy and how does it all fit together? 4:34 – AI Ladder and AI Maturity 8:32 – How does the AI Factory make it easier to accomplish the AI Ladder? 12:00 – Why does your team do it better? 17:03 – How do you know your data is ready? 21:22 – What is the most practical use case? 23:02 – What does it really mean to infuse AI? 25:15 – Definition of AI maturity curve 28:25 – How do you know it’s trustworthy? 29:14 – What the most important lesson you’ve learned with AI and what is AI not very good at? In the Dream House  Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter.  Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

In this podcast, Nathan Furr(@nathan_furr) talks about leading transformation. He shares some of the crucial ingredients of transformational leaders. He sheds some light on how businesses could improve their storytelling to get the transformation agenda across. He shares some cool tips and tricks that help leaders plan for a transformation across data-driven and disruptive times.

Timeline: 1:39 Nathan's journey. 4:49 Nathan's current role. 13:55 Transforming legacy old company. 21:52 The right moment for companies to think about data transformation. 26:38 Using comic books to share transformational stories. 34:32 Who's the most responsible person in an organization for transformation? 39:13 Qualities a leader must have for bringing in transformational change. 43:40 Nathan's success mantra. 47:57 Nathan's favorite reads. 50:29 Closing remarks.

Nathan's Recommended Read: East of Eden (Penguin Twentieth-Century Classics) by John Steinbeck, David Wyatt https://amzn.to/2S9MHA0

Nathan's Books The Innovator's Method: Bringing the Lean Start-up into Your Organization by Nathan Furr, Jeff Dyer, Clayton M. Christensen https://amzn.to/2TeadJE Leading Transformation: How to Take Charge of Your Company's Future by Nathan Furr, Kyle Nel, Thomas Zoega Ramsey https://amzn.to/2CTw16z Nail It then Scale It: The Entrepreneur's Guide to Creating and Managing Breakthrough Innovation: The lean startup book to help entrepreneurs launch a high-growth business by Nathan Furr, Paul Ahlstrom https://amzn.to/2UfTpSC

Podcast Link: https://futureofdata.org/leading-transformation-through-data-driven-times-nathan_furr-insead-futureofdata-podcast/

Nathan's BIO: Nathan Furr is a professor of strategy and innovation at INSEAD in Paris and a recognized expert in innovation and technology strategy. He has multiple books and articles published by outlets such as Harvard Business Review and MIT Sloan Management Review, including his most recent best-selling book, “The Innovator’s Method” (Harvard Business Review Press, September 2014), which won multiple awards from the business press. He has two forthcoming books from Harvard Business Review Press addressing 1) how companies lead transformation and 2) how innovators win support for their ideas.

Professor Furr has worked with leading companies to study and implement innovation strategies, including Google, Amazon, Citi, Deutsche Bank, Philips, Kimberly Clark, Solvay, and others. Professor Furr earned his Ph.D. from the Stanford Technology Ventures Program at Stanford University.

About #Podcast:

FutureOfData podcast is a conversation starter to bring leaders, influencers, and lead practitioners to discuss their journey in creating the data-driven future.

Wanna Join? If you or any you know wants to join in, Register your interest by emailing us @ [email protected]

Want to sponsor? Email us @ [email protected]

Keywords: FutureOfData,

DataAnalytics,

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Podcast,

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Send us a text Host Al Martin looks back on his top 5 favourite clips from episodes published in 2018. These conversations range from explaining the importance of data visualization, to discussing the differences between A.I. and deep learning. Thanks to all of our listeners for an incredible 2018, and prepare yourself for Season 3 of the Making Data Simple podcast!

Show Notes

00:00 - Check us out on YouTube and SoundCloud!  00:10 - Connect with producer Liam Seston on LinkedIn and Twitter.   00:15 - Connect with producer Steve Moore on LinkedIn and Twitter.  00:24 - Connect with host Al Martin on LinkedIn and Twitter.   00:55 - Listen to the full conversation with Lisa Seacat DeLuca here. 05:45 - Listen to the full conversation with John Thomas here. 09:59 - Listen to the full conversation with Jillian Lellis here.   13:39 - Listen to the full conversation with Adam Storm here. 18:36 - Listen to the full conversation with Jean Francois Puget here. Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

How to make simple sense of complex statistics--from the author of Numbers Rule Your World We live in a world of Big Data--and it's getting bigger every day. Virtually every choice we make hinges on how someone generates data . . . and how someone else interprets it--whether we realize it or not. Where do you send your child for the best education? Big Data. Which airline should you choose to ensure a timely arrival? Big Data. Who will you vote for in the next election? Big Data. The problem is, the more data we have, the more difficult it is to interpret it. From world leaders to average citizens, everyone is prone to making critical decisions based on poor data interpretations. In Numbersense, expert statistician Kaiser Fung explains when you should accept the conclusions of the Big Data "experts"--and when you should say, "Wait . . . what?" He delves deeply into a wide range of topics, offering the answers to important questions, such as: How does the college ranking system really work? Can an obesity measure solve America's biggest healthcare crisis? Should you trust current unemployment data issued by the government? How do you improve your fantasy sports team? Should you worry about businesses that track your data? Don't take for granted statements made in the media, by our leaders, or even by your best friend. We're on information overload today, and there's a lot of bad information out there. Numbersense gives you the insight into how Big Data interpretation works--and how it too often doesn't work. You won't come away with the skills of a professional statistician. But you will have a keen understanding of the data traps even the best statisticians can fall into, and you'll trust the mental alarm that goes off in your head when something just doesn't seem to add up. Praise for Numbersense " Numbersense correctly puts the emphasis not on the size of big data, but on the analysis of it. Lots of fun stories, plenty of lessons learned—in short, a great way to acquire your own sense of numbers!" Thomas H. Davenport, coauthor of Competing on Analytics and President’s Distinguished Professor of IT and Management, Babson College "Kaiser’s accessible business book will blow your mind like no other. You’ll be smarter, and you won’t even realize it. Buy. It. Now." Avinash Kaushik, Digital Marketing Evangelist, Google, and author, Web Analytics 2.0 "Each story in Numbersense goes deep into what you have to think about before you trust the numbers. Kaiser Fung ably demonstrates that it takes skill and resourcefulness to make the numbers confess their meaning." John Sall, Executive Vice President, SAS Institute "Kaiser Fung breaks the bad news—a ton more data is no panacea—but then has got your back, revealing the pitfalls of analysis with stimulating stories from the front lines of business, politics, health care, government, and education. The remedy isn’t an advanced degree, nor is it common sense. You need Numbersense." Eric Siegel, founder, Predictive Analytics World, and author, Predictive Analytics "I laughed my way through this superb-useful-fun book and learned and relearned a lot. Highly recommended!" Tom Peters, author of In Search of Excellence

Praise for Successful Business Intelligence "If you want to be an analytical competitor, you've got to go well beyond business intelligence technology. Cindi Howson has wrapped up the needed advice on technology, organization, strategy, and even culture in a neat package. It's required reading for quantitatively oriented strategists and the technologists who support them." --Thomas H. Davenport, President's Distinguished Professor, Babson College and co-author, Competing on Analytics "When used strategically, business intelligence can help companies transform their organization to be more agile, more competitive, and more profitable. Successful Business Intelligence offers valuable guidance for companies looking to embark upon their first BI project as well as those hoping to maximize their current deployments." --John Schwarz, CEO, Business Objects "A thoughtful, clearly written, and carefully researched examination of all facets of business intelligence that your organization needs to know to run its business more intelligently and exploit information to its fullest extent." --Wayne Eckerson, Director, TDWI Research "Using real-world examples, Cindi Howson shows you how to use business intelligence to improve the performance, and the quality, of your company." --Bill Baker, Distinguished Engineer & GM, Business Intelligence Applications, Microsoft Corporation "This book outlines the key steps to make BI an integral part of your company's culture and demonstrates how your company can use BI as a competitive differentiator." --Robert VanHees, CFO, Corporate Express "Given the trend to expand the business analytics user base, organizations are faced with a number of challenges that affect the success rate of these projects. This insightful book provides practical advice on improving that success rate." --Dan Vesset, Vice President, Business Analytics Solution Research, IDC

“Automated decisions systems are probably already being used in your industry, and they will undoubtedly grow in importance. If your business needs to make quick, accurate decisions on an industrialized scale, you need to read this book.” Thomas H. Davenport, Professor, Babson College, Author of Competing on Analytics The computer-based systems most organizations rely on to support their businesses are not very smart. Many of the business decisions these companies make tend to be hidden in systems that make poor decisions, or don’t make them at all. Further, most systems struggle to keep up with the pace of change. The answer is not to implement newer, “intelligent” systems. The fact is that much of today’s existing technology has the potential to be “smart enough” to make a big difference to an organization’s business. This book tells you how. Although the business context and underlying principles are explained in a nontechnical manner, the book also contains how-to guidance for more technical readers. The book’s companion site, www.smartenoughsystems.com, has additional information and references for practitioners as well as news and updates. Additional Praise for Smart (Enough) Systems “James Taylor and Neil Raden are on to something important in this book–the tremendous value of improving the large number of routine decisions that are made in organizations every day.” Dr. Hugh J. Watson, Chair of Business Administration, University of Georgia “This is a very important book. It lays out the agenda for business technology in the new century–nothing less than how to reorganize every aspect of how a company treats its customers.” David Raab, President, ClientXClient “This book is an important contribution to business productivity because it covers the opportunity from both the business executive’s and technologist’s perspective. This should be on every operational executive’s and every CIO’s list of essential reading.” John Parkinson, Former CTO, Capgemini, North American Region “This book shows how to use proven technology to make business processes smarter. It clearly makes the case that organizations need to optimize their operational decisions. It is a must-have reference for process professionals throughout your organization.” Jim Sinur, Chief Strategy Officer, Global 360, Inc.