Thomas H. Davenport Bücher

Aus Informationen Gewinne machen; Verborgenes Potential entdecken; Von internationalen Organisationen lernen

This book offers a unique perspective on knowledge management at Siemens, showcasing the corporation's practical applications and experiences as a benchmark in the field. Tom Davenport and Gilbert Probst compile instructive case studies that reflect years of knowledge management practice, with most cases updated and new ones added in the second edition. It provides a comprehensive account of effectively managing organizational knowledge assets, emphasizing generic lessons from Siemens' experience. The text outlines a roadmap for building a "mature knowledge enterprise," enhancing understanding of the necessary steps to sustain competitive advantage in the knowledge economy. The practice-oriented approach distinguishes this work within KM literature. Notably, the cases reveal not just the analysis of knowledge management tools and processes, but also their development, commitment building, and implementation leadership. Esteemed figures in the field commend the book for its insights into how valuable resources drive these tools and for being a rare account of a single company's knowledge management journey. Siemens' impressive strides toward becoming a knowledge-driven firm are detailed, making this volume a valuable resource for practitioners seeking practical applications of knowledge management.

Elixir's pragmatic syntax and built-in support for metaprogramming will make you productive and keep you interested for the long haul. Maybe the time is right for the Next Big Thing. Maybe it's Elixir. This book is the introduction to Elixir for experienced programmers, completely updated for Elixir 1.3.

This book is the introduction to Elixir for experienced programmers, completely updated for Elixir 1.6 and beyond. Explore functional programming without the academic overtones (tell me about monads just one more time). Create concurrent applications, but get them right without all the locking and consistency headaches.

To really address the data concerns of today's enterprise, they wanted to find a way to help enterprises achieve the success they seek. Not as a prescriptive process-but a methodology to become agile and leverage data and analytics to drive a competitive advantage. You know, it's amazing what can happen when two people with very different perspectives get together to solve a big problem. This evolutionary guide resulted from the a-ha moment between these two influencers at the top of their fields - one, an academic researcher and consultant, and the other, a longtime analytics practitioner and chief product officer at Teradata. Together, they created a powerful framework every type of business can use to connect analytic power, business practices, and human dynamics in ways that can transform what is currently possible. -- Provided by publisher

"In Competing on Analytics: The New Science of Winning, Thomas H. Davenport and Jeanne G. Harris argue that the frontier for using data has shifted dramatically. Leading companies are doing more than just collecting and storing information in large quantities. They're now building their competitive strategies around data-driven insights that are, in turn, generating impressive business results. Their secret weapon? Analytics: sophisticated quantitative and statistical analysis and predictive modeling supported by data-savvy senior leaders and powerful information technology."--Jacket.

"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."--Jacket

This invigorating and thought-provoking exploration examines the rise of automation and its implications for sustainable careers across various industries. With nearly half of working Americans at risk of job loss due to technology, the threat extends beyond blue-collar roles to educated knowledge workers, including writers, paralegals, and medical technicians. The industrial revolution previously shifted workers from farms to factories, while the first era of automation relieved humans of manual labor. Now, we are entering Era Three, marked by the rise of artificial intelligence, where smart computers can outperform humans in decision-making, learning, and comprehension. This evolution raises questions about the future of professions such as law, nursing, teaching, and editing. The authors reframe the conversation around automation, suggesting that the future lies not in a competition between humans and machines, but in their collaboration. By embracing augmentation—using technology to enhance human capabilities—workers can achieve greater productivity and success. Rather than viewing machines as threats, we can see them as partners in creative problem-solving as we transition into this new era. The choice to adapt and thrive is ours.

In this rich, entertaining primer, former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction: What type of mortgage risk Chase Bank predicted before the recession. Predicting which people will drop out of school, cancel a subscription, or get divorced before they are even aware of it themselves. Why early retirement decreases life expectancy and vegetarians miss fewer flights. Five reasons why organizations predict death, including one health insurance company. A truly omnipresent science, predictive analytics affects everyone, every day. Although largely unseen, it drives millions of decisions, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate. Predictive analytics transcends human perception. This book's final chapter answers the riddle: What often happens to you that cannot be witnessed, and that you can't even be sure has happened afterward -- but that can be predicted in advance? Whether you are a consumer of it -- or consumed by it -- get a handle on the power of Predictive Analytics. This book is easily understood by all readers. Rather than a "how to" for hands-on techies, the book entices lay-readers and experts alike by covering new case studies and the latest state-of-the-art techniques.

"An exploration of the future of work featuring real-world profiles of changing jobs and work arrangements in light of human/AI interaction"-- Provided by publisher