Новинки Томаса Дэвенпорта

Ажиотаж вокруг искусственного интеллекта и его применения в классическом бизнесе не утихает, но многие компании до сих пор не понимают, какую реальную выгоду принесет им внедрение новых технологий в их бизнес-процессы. Эксперт в области аналитики и больших данных, преподаватель в Гарвардской школе бизнеса Томас Дэвенпорт в своей книге покажет, как можно эффективно интегрировать ИИ и когнитивные технологии в текущую бизнес-стратегию предприятия, чтобы сделать продукты привлекательнее, процессы совершеннее, а компанию успешнее. Он подробно рассматривает преимущества и сложности внедрения различных видов технологий: статистическое машинное обучение, нейронные сети, глубокое обучение, обработка естественного языка, экспертные системы на основе правил, роботы и роботизированная автоматизация процессов. И приводит примеры использования ИИ в разных компаниях: Amazon, Google, Facebook, GlaxoSmithKline, Uber, GE, цифровом банке DBS и др.Книга Томаса Дэвенпорта — дорожная карта для владельцев и руководителей компаний по внедрению решений на основе искусственного интеллекта и когнитивных технологий.

Ажиотаж вокруг искусственного интеллекта и его применения в классическом бизнесе не утихает, но многие компании до сих пор не понимают, какую реальную выгоду принесет им внедрение новых технологий в их бизнес-процессы. Эксперт в области аналитики и больших данных, преподаватель в Гарвардской школе бизнеса Томас Дэвенпорт в своей книге покажет, как можно эффективно интегрировать ИИ и когнитивные технологии в текущую бизнес-стратегию предприятия, чтобы сделать продукты привлекательнее, процессы совершеннее, а компанию успешнее. Он подробно рассматривает преимущества и сложности внедрения различных видов технологий: статистическое…

In The AI Advantage, Thomas Davenport offers a guide to using artificial intelligence in business. He describes what technologies are available and how companies can use them for business benefits and competitive advantage. He cuts through the hype of the AI craze—remember when it seemed plausible that IBM's Watson could cure cancer?—to explain how businesses can put artificial intelligence to work now, in the real world. His key recommendation: don't go for the “moonshot” (curing cancer, or synthesizing all investment knowledge); look for the “low-hanging fruit” to make your company more efficient.

Davenport explains that the business value AI offers is solid rather than sexy or splashy. AI will improve products and processes and make decisions better informed—important but largely invisible tasks. AI technologies won't replace human workers but augment their capabilities, with smart machines to work alongside smart people. AI can automate structured and repetitive work; provide extensive analysis of data through machine learning (“analytics on steroids”), and engage with customers and employees via chatbots and intelligent agents. Companies should experiment with these technologies and develop their own expertise.

Davenport describes the major AI technologies and explains how they are being used, reports on the AI work done by large commercial enterprises like Amazon and Google, and outlines strategies and steps to becoming a cognitive corporation. This book provides an invaluable guide to the real-world future of business AI.

A book in the Management on the Cutting Edge series, published in cooperation with MIT Sloan Management Review.

Умение работать с данными - реальное конкурентное преимущество в современном мире. Книга в доступной форме раскказывает о методах и терминах количественного анализа, учит формулировать гипотезы, интерпретировать данные и говорить на одном языке с профессиональными аналитиками.

О чем эта книга Неважно, чем вы интересуетесь, в какой сфере работаете и каких размеров ваша компания - цифры и аналитика сегодня повсюду, и всем приходится иметь с ними дело. Чтобы принимать эффективные решения, нужно уметь анализировать данные и извлекать из них смысл. В этом вам поможет данная книга, которая в доступной форме объясняет, как: - формулировать гипотезы и проверять их на основании данных; - интерпретировать и формулировать результаты анализа; - эффективно взаимодействовать с аналитиками в вашей компании; - развить количественное мышление. Цифровые данные и аналитика оказывают все большее влияние на…

В мире, где традиционные источники конкурентного преимущества уже во многом исчерпаны, трудно помочь своей компании выделиться из толпы конкурентов. Используйте аналитику, чтобы принимаемые вами решения были правильнее, а бизнес-процессы шли максимально эффективно. В книге "Аналитика как конкурентное преимущество. Новая наука побеждать" Том Дэвенпорт и Джоан Хар-рис утверждают, что рамки использования данных значительно расширились. Ведущие компании не просто собирают и складируют большие объемы информации. Они целиком выстраивают свою конкурентную стратегию на знаниях, получаемых благодаря данным, и эта стратегия, в свою очередь,…

You have more information at hand about your business environment than ever before. But are you using it to out-think” your rivals? If not, you may be missing out on a potent competitive tool.

In Competing on Analytics: The New Science of Winning, Thomas H. Davenport and Jeanne G. Harris argue that the frontier for using data to make decisions has shifted dramatically. Certain high-performing enterprises are now building their competitive strategies around data-driven insights that in turn generate impressive business results. Their secret weapon? Analytics: sophisticated quantitative and statistical analysis and predictive modeling.

Exemplars of analytics are using new tools to identify their most profitable customers and offer them the right price, to accelerate product innovation, to optimize supply chains, and to identify the true drivers of financial performance. A wealth of examples from organizations as diverse as Amazon, Barclay’s, Capital One, Harrah’s, Procter & Gamble, Wachovia, and the Boston Red Sox illuminate how to leverage the power of analytics.

Knowledge workers create the innovations and strategies that keep their firms competitive and the economy healthy. Yet, companies continue to manage this new breed of employee with techniques designed for the Industrial Age. As this critical sector of the workforce continues to increase in size and importance, that's a mistake that could cost companies their future. Thomas Davenport argues that knowledge workers are vastly different from other types of workers in their motivations, attitudes, and need for autonomy–and, so, they require different management techniques to improve their performance and productivity.Based on extensive research…

Knowledge workers create the innovations and strategies that keep their firms competitive and the economy healthy. Yet, companies continue to manage this new breed of employee with techniques designed for the Industrial Age. As this critical sector of the workforce continues to increase in size and importance, that's a mistake that could cost companies their future. Thomas Davenport argues that knowledge workers are vastly different from other types of workers in their motivations, attitudes, and need for autonomy--and, so, they require different management techniques to improve their performance and productivity. Based on extensive…

According to virtually every business writer, we are in the midst of a new "information age," one that will revolutionize how workers work, how companies compete, perhaps even how thinkers think. And it is certainly true that Information Technology has become a giant industry. In America, more that 50% of all capital spending goes into IT, accounting for more than a third of the growth of the entire American economy in the last four years. Over the last decade, IT spending in the U.S. is estimated at 3 trillion dollars. And yet, by almost all accounts, IT hasn't worked all that well. Why is it that so many of the companies that have invested in these costly new technologies never saw the returns they had hoped for? And why do workers, even CEOs, find it so hard to adjust to new IT systems?
In Information Ecology , Thomas Davenport proposes a revolutionary new way to look at information management, one that takes into account the total information environment within an organization. Arguing that the information that comes from computer systems may be considerably less valuable to managers than information that flows in from a variety of other sources, the author describes an approach that encompasses the company's entire information environment, the management of which he calls information ecology. Only when organizations are able to combine and integrate these diverse sources of information, and to take them to a higher level where information becomes knowledge, will they realize the full power of their information ecology. Thus, the author puts people, not technology, at the center of the information world. Information and knowledge are human creations, he points out, and we will never excel at managing them until we give people a primary role. Citing examples drawn
from his own extensive research and consulting including such major firms as A.T. & T., American Express, Ford, General Electric, Hallmark, Hoffman La Roche, IBM, Polaroid, Pacific Bell, and Toshiba Davenport illuminates the critical components of information ecology, and at every step along the way, he provides a quick assessment survey for managers to see how their organization measures up. He discusses the importance of developing an overall strategy for information use; explores the infighting, jealousy over resources, and political battles that can frustrate information sharing; underscores the importance of looking at how people really use information (how they search for it, modify it, share it, hoard it, and even ignore it) and the kinds of information they want; describes the ideal information staff, who not only store and retrive information, but also prune, provide context, enhance style, and choose the right presentation medium (in an age of work overload, vital
information must be presented compellingly so the appropriate people recognize and use it); examines how information management should be done on a day to day basis; and presents several alternatives to the machine engineering approach to structuring and modeling information. Davenport makes explicit what many managers already know in their that useful information flow depends on people, not equipment. In Information Ecology he paves the way for all managers to build a more competitive, creative, practical information environment for their companies.

When the term “big data” first came on the scene, bestselling author Tom Davenport ( Competing on Analytics , Analytics at Work ) thought it was just another example of technology hype. But his research in the years that followed changed his mind.

Now, in clear, conversational language, Davenport explains what big data means—and why everyone in business needs to know about it. Big Data at Work covers all the bases: what big data means from a technical, consumer, and management perspective; what its opportunities and costs are; where it can have real business impact; and which aspects of this hot topic have been oversold.

This book will help you understand:
• Why big data is important to you and your organization
• What technology you need to manage it
• How big data could change your job, your company, and your industry
• How to hire, rent, or develop the kinds of people who make big data work
• The key success factors in implementing any big data project
• How big data is leading to a new approach to managing analytics

With dozens of company examples, including UPS, GE, Amazon, United Healthcare, Citigroup, and many others, this book will help you seize all opportunities—from improving decisions, products, and services to strengthening customer relationships. It will show you how to put big data to work in your own organization so that you too can harness the power of this ever-evolving new resource.

Why Everyone Needs Analytical SkillsWelcome to the age of data. No matter your interests (sports, movies, politics), your industry (finance, marketing, technology, manufacturing), or the type of organization you work for (big company, nonprofit, small start-up)—your world is awash with data.As a successful manager today, you must be able to make sense of all this information. You need to be conversant with analytical terminology and methods and able to work with quantitative information. This book promises to become your “quantitative literacy" guide—helping you develop the analytical skills you need right now in order to summarize data, find the meaning in it, and extract its value.In Keeping Up with the Quants, authors, professors, and analytics experts Thomas Davenport and Jinho Kim offer practical tools to improve your understanding of data analytics and enhance your thinking and decision making. You’ll gain crucial skills, including:• How to formulate a hypothesis• How to gather and analyze relevant data• How to interpret and communicate analytical results• How to develop habits of quantitative thinking• How to deal effectively with the “quants” in your organizationBig data and the analytics based on it promise to change virtually every industry and business function over the next decade. If you don’t have a business degree or if you aren’t comfortable with statistics and quantitative methods, this book is for you. Keeping Up with the Quants will give you the skills you need to master this new challenge—and gain a significant competitive edge.

Ажиотаж вокруг искусственного интеллекта и его применения в классическом бизнесе не утихает, но многие компании до сих пор не понимают, какую реальную выгоду принесет им внедрение новых технологий в их бизнес-процессы. Эксперт в области аналитики и больших данных, преподаватель в Гарвардской школе бизнеса Томас Дэвенпорт в своей книге покажет, как можно эффективно интегрировать ИИ и когнитивные технологии в текущую бизнес-стратегию предприятия, чтобы сделать продукты привлекательнее, процессы совершеннее, а компанию успешнее. Он подробно рассматривает преимущества и сложности внедрения различных видов технологий: статистическое машинное обучение, нейронные сети, глубокое обучение, обработку естественного языка, экспертные системы на основе правил, роботов и роботизированную автоматизацию процессов. И приводит примеры как успешного, так и неудачного использования ИИ в разных компаниях: Amazon, Google, Facebook, GlaxoSmithKline, Uber, GE, цифровом банке DBS и др.