Demystifying Organizational Learning


Book Description

This book presents a solid, research-based conceptual framework that demystifies organizational learning and bridges the gap between theory and practice. Using an integrative approach, authors Raanan Lipshitz, Victor Friedman and Micha Popper provide practitioners and researchers with tools for understanding organizational learning under real-world conditions. Key Features: Tackles the problem of mystification: A clear message is presented that organizational learning and related concepts have been mystified in a way that is unnecessary and dysfunctional to both theory and practice. This book provides a unique set of tools for understanding, promoting, and studying organizational learning. Introduces an integrative theme that addresses three key questions: How can organizations actually learn? What is the key for productive organizational learning? When is productive organizational learning likely to occur? Answering these questions is the key to clarifying the conceptual confusion that plagues the related fields of organizational learning, learning organizations, and knowledge management. Illuminates organizational reality: All of the concepts presented in the book are illustrated through concrete case examples. Detailed analyses are provided of both successful and unsuccessful applications of organizational learning. In addition, examples of interventions to develop organizational learning are included to help managers and consultants. Intended Audience: This book is designed for advanced undergraduate and graduate courses such as Organizational Learning, Knowledge Management, and Organizational Behavior in the departments of Management, Organizational Behavior, Psychology, and Sociology.




Demystifying Organizational Learning


Book Description

This book presents a solid, research-based conceptual framework that demystifies organizational learning and bridges the gap between theory and practice. Using an integrative approach, authors Raanan Lipshitz, Victor Friedman and Micha Popper provide practitioners and researchers with tools for understanding organizational learning under real-world conditions.




Handbook of Organizational Learning and Knowledge


Book Description

This is an overview of how the concept of organisational learning emerged, how it has been used and debated, and where it may be going.




Demystifying Professional Learning Communities


Book Description

The purpose of this book is to clearly define an approach to school improvement that uses professional learning community (PLC) practices to achieve school improvement and success for every student. This book offers information, examples and case studies to clarify the concept of a PLC, to respond to critical issues in schools, and to support educational leaders in addressing the important mandates of accountability and school improvement. As school leaders proactively lead efforts to create learning communities, their schools, districts, and staff will incorporate knowledge, skills, and practices that focus on teaching and learning for all. The authors' findings will assist leaders, change agents, policy makers, and university faculty in guiding schools toward creating and maintaining PLCs as they sustain school improvement for student learning.




Demystifying Technical Training


Book Description

Praise for Demystifying Technical Training "Demystifying Technical Training is a must-read for CLOs, managers of training, instructors, and instructional designers. All who read it will gain critical insights into how to lower the cost and improve the efficiency and effectiveness of learning." —Wm. Douglas Harward, CEO and founder of Training Industry, Inc. "Individuals interested in and accountable for deriving significant value from technical training investments will gain great benefit from reading this book and applying its wisdom." —Karen Kocher, CLO at Cigna Healthcare "Demystifying Technical Training is an essential, complete guide for any learning organization. The overviews and concepts are clearly stated, while the case studies and sidebars provide practical examples you can apply in your situation." —Jean Barbazette, president of The Training Clinic and author of Managing the Training Function for Bottom-Line Results "Considering the cost of acquiring and developing talent, why wouldn't all CEO/COOs insist on investing in people to improve results and reduce risk? This book demystifies the process of developing technical experts to increase the return on investment in human capital. Bravo!" —Martin J. Menard, former group CIO at Intel Corporation "Technical training is a key to sustaining competitiveness in the new economy. Learn how to leverage and optimize its value in your organization through this wonderfully insightful and practical resource." —Dr. Arthur L. Jue, director of global organization and talent development at Oracle and co-author of Social Media at Work: How Networking Tools Propel Organizational Performance "Don't be misled by the title—this book—while focusing on the often segmented world of domain specific job skills—provides guidance valid for the full spectrum of workforce learning from soft-skills to 'technical' skills." —Ruth Clark, principal and president of Clark Training & Consulting and author of e-Learning and the Science of Instruction




Demystifying Big Data and Machine Learning for Healthcare


Book Description

Healthcare transformation requires us to continually look at new and better ways to manage insights – both within and outside the organization today. Increasingly, the ability to glean and operationalize new insights efficiently as a byproduct of an organization’s day-to-day operations is becoming vital to hospitals and health systems ability to survive and prosper. One of the long-standing challenges in healthcare informatics has been the ability to deal with the sheer variety and volume of disparate healthcare data and the increasing need to derive veracity and value out of it. Demystifying Big Data and Machine Learning for Healthcare investigates how healthcare organizations can leverage this tapestry of big data to discover new business value, use cases, and knowledge as well as how big data can be woven into pre-existing business intelligence and analytics efforts. This book focuses on teaching you how to: Develop skills needed to identify and demolish big-data myths Become an expert in separating hype from reality Understand the V’s that matter in healthcare and why Harmonize the 4 C’s across little and big data Choose data fi delity over data quality Learn how to apply the NRF Framework Master applied machine learning for healthcare Conduct a guided tour of learning algorithms Recognize and be prepared for the future of artificial intelligence in healthcare via best practices, feedback loops, and contextually intelligent agents (CIAs) The variety of data in healthcare spans multiple business workflows, formats (structured, un-, and semi-structured), integration at point of care/need, and integration with existing knowledge. In order to deal with these realities, the authors propose new approaches to creating a knowledge-driven learning organization-based on new and existing strategies, methods and technologies. This book will address the long-standing challenges in healthcare informatics and provide pragmatic recommendations on how to deal with them.




Demystifying AI for the Enterprise


Book Description

Artificial intelligence (AI) in its various forms –– machine learning, chatbots, robots, agents, etc. –– is increasingly being seen as a core component of enterprise business workflow and information management systems. The current promise and hype around AI are being driven by software vendors, academic research projects, and startups. However, we posit that the greatest promise and potential for AI lies in the enterprise with its applications touching all organizational facets. With increasing business process and workflow maturity, coupled with recent trends in cloud computing, datafication, IoT, cybersecurity, and advanced analytics, there is an understanding that the challenges of tomorrow cannot be solely addressed by today’s people, processes, and products. There is still considerable mystery, hype, and fear about AI in today’s world. A considerable amount of current discourse focuses on a dystopian future that could adversely affect humanity. Such opinions, with understandable fear of the unknown, don’t consider the history of human innovation, the current state of business and technology, or the primarily augmentative nature of tomorrow’s AI. This book demystifies AI for the enterprise. It takes readers from the basics (definitions, state-of-the-art, etc.) to a multi-industry journey, and concludes with expert advice on everything an organization must do to succeed. Along the way, we debunk myths, provide practical pointers, and include best practices with applicable vignettes. AI brings to enterprise the capabilities that promise new ways by which professionals can address both mundane and interesting challenges more efficiently, effectively, and collaboratively (with humans). The opportunity for tomorrow’s enterprise is to augment existing teams and resources with the power of AI in order to gain competitive advantage, discover new business models, establish or optimize new revenues, and achieve better customer and user satisfaction.




Demystifying Six Sigma


Book Description

When an entire organization is reaching the highest quality standards, the result is a Six Sigma culture.




Organizational Learning


Book Description

Why do some organizations learn at faster rates than others? Why do organizations "forget"? Could productivity gains acquired in one part of an organization be transferred to another? These are among the questions addressed in Organizational Learning: Creating, Retaining and Transferring Knowledge. Since its original publication in 1999, this book has set the standard for research and analysis in the field. This fully updated and expanded edition showcases the most current research and insights, featuring a new chapter that provides a theoretical framework for analyzing organizational learning and presents evidence about how the organizational context affects learning processes and outcomes. Drawing from a wide array of studies across the spectrum of management, economics, sociology, and psychology, Organizational Learning explores the dynamics of learning curves in organizations, with particular emphasis on how individuals and groups generate, share, reinforce, and sometimes forget knowledge. With an increased emphasis on service organizations, including healthcare, Linda Argote demonstrates that organizations vary dramatically in the rates at which they learn—with profound implications for productivity, performance, and managerial and strategic decision making.




Demystifying Talent Management


Book Description

Demystifying Talent Management offers practical advice for all managers, HR professionals, senior leaders, and other employees on how to work together to build a talented and motivated workforce. The book addresses performance, development, coaching, feedback, compensation, and other elements of people management. Using simple, straightforward language, Kim Janson tells you how you can avoid confusion and conflicts when engaging in talent management. You'll learn: What performance is needed and expected: how to translate your company's strategy into individual performance; What it means to measure and track progress, simply and clearly; What you can and should do to help an individual's development; How to narrow your focus to improve a skill, knowledge, or experience; How to take both an individual's profile and the direction of the organization into account in career development and succession planning; How to make compensation (cash, public accolades, feedback, etc.) a true driver of results; How coaching and feedback are essential in bringing all the elements of talent management together. This book will guide you to a deeper understanding of the mechanics of talent management and development success so that all the stakeholders can come together in a win-win-win-win scenario.