عنوان

Optimizing data-to-learning-to-action :

شابک

1484235312

شابک

1484235320

شابک

1484246659

شابک

9781484235317

شابک

9781484235324

شابک

9781484246658

شابک اشتباه

1484235304

شابک اشتباه

9781484235300

عنوان اصلي

Optimizing data-to-learning-to-action :

نام عام مواد

[Book]

ساير اطلاعات عنواني

the modern approach to continuous performance improvement for businesses /

نام نخستين پديدآور

Steven Flinn.

محل نشرو پخش و غیره

[United States] :

محل نشرو پخش و غیره

New York, NY :

نام ناشر، پخش کننده و غيره

Apress,

نام ناشر، پخش کننده و غيره

Distributed to the Book trade worldwide by Springer

تاریخ نشرو بخش و غیره

2018.

تاریخ نشرو بخش و غیره

©2018

نام خاص و کميت اثر

1 online resource

متن يادداشت

Includes bibliographical references and index.

متن يادداشت

Intro; Contents; About the Author; About the Technical Reviewer; Acknowledgments; Introduction; Chapter 1: Case for Action; The Economic Imperative; Disruptive Technologies; Cloud Computing; Internet of Things; Big Data and Business Intelligence; Machine Learning/AI; Enterprise Collaboration; The Combinatorial Effect; The Confusion; Why Have Legacy Approaches Come up Short?; The Case for Data-to-Learning-to-Action; Summary; Chapter 2: Roots of a New Approach; Root 1: Process Improvement; Root II: Theory of Constraints; Root III: Decision Science; The Emergence of the New Approach; Summary.

متن يادداشت

Alternative Modeling PerspectivesThe Bayesian Approach; Summary; Chapter 7: Total Value; Total Value; Business-Renewal Lifecycle; Optimizing Total Value; Retrospective Value; Summary; Chapter 8: Optimizing Learning Throughput; Additional Strategies; Parallel Versus Sequential Debottlenecking; Learning Synergies; Constraint Look-ahead; Anticipated Capabilities; Rationalizing to the Limiting Constraint; Full Method Overview; Summary; Chapter 9: Patterns of Learning Constraints and Solutions; Determining the Value; Process and Collaborate Constraints; Predictive Analytics Constraints.

متن يادداشت

Chapter 3: Data-to-Learning-to-ActionElements of the Chain; Data Acquisition; Data Filtering; Information Management; The Architecture of Learning; Anticipatory Computing; Neural Networks; Information, Knowledge, and Learning; Search and Discovery; Predictive Analytics; Process and Collaborate; Decide and Act; Summary; Chapter 4: Tech Stuff and Where It Fits; General-Purpose Applications; Document and Content Management; Business Intelligence; Enterprise Social Networks; Function-Specific Applications; R & D: High-Throughput Experimentation Technologies.

متن يادداشت

Sales and Marketing: Marketing AnalyticsSales and Marketing: Customer Relationship Management; Supply and Manufacturing: Supply Chain Management; Human Resources: Talent Management; Summary; Chapter 5: Reversing the Flow: Decision-to-Data; Value Drivers; Decisions, Decisions; Working Backward; Constraints on Value; Resolving Constraints; Summary; Chapter 6: Quantifying the Value; Value of Learning; Calculating Learning Value; Encoding Uncertainties; Value of Learning with Perfect Predictability; Value of Learning with Imperfect Predictability; Modeling Refinements; Learning Value Modeling.

متن يادداشت

Search and Discovery ConstraintsInformation Management Constraints; Data Filtering Constraints; Data Acquisition Constraints; Summary; Chapter 10: Organizing for Data-to-Learning-to-Action Success; Scoping the Project; Gaining Executive Buy-in; Organizing the Initiative; Dedicated Resources; Phasing an Individual Project; Change Management: What's in It for Me?; Measuring Success; Skeptics to Champions; We already do that . . .; It's too much work . . .; It doesn't apply to the creative parts of the organization ...

بدون عنوان

0

بدون عنوان

8

بدون عنوان

8

بدون عنوان

8

بدون عنوان

8

متن يادداشت

Apply a powerful new approach and method that ensures continuous performance improvement for your business. You will learn how to determine and value the people, process, and technology-based solutions that will optimize your organization's data-to-learning-to-action processes. This book describes in detail how to holistically optimize the chain of activities that span from data to learning to decisions to actions, an imperative for achieving outstanding performance in today's business environment. Adapting and integrating insights from decision science, constraint theory, and process improvement, the book provides a method that is clear, effective, and can be applied to nearly every business function and sector. You will learn how to systematically work backwards from decisions to data, estimate the flow of value along the chain, and identify the inevitable value bottlenecks. And, importantly, you will learn techniques for quantifying the value that can be attained by successfully addressing the bottlenecks, providing the credible support needed to make the right level of investments at the right place and at just the right time. In today's dynamic environment, with its never-ending stream of new, disruptive technologies that executives must consider (e.g., cloud computing, Internet of Things, AI/machine learning, business intelligence, enterprise social, etc., along with the associated big data generated), author Steven Flinn provides the comprehensive approach that is needed for making effective decisions about these technologies, underpinned by credibly quantified value. What You'll Learn: Understand data-to-learning-to-action processes and their fundamental elements Discover the highest leverage data-to-learning-to-action processes in your organization Identify the key decisions that are associated with a data-to-learning-to-action process Know why it's NOT all about data, but it IS all about decisions and learning Determine the value upside of enhanced learning that can improve decisions Work backwards from the decisions to determine the value constraints in data-to-learning-to-action processes Evaluate people, process, and technology-based solution options to address the constraints Quantify the expected value of each of the solution options and prioritize accordingly Implement, measure, and continuously improve by addressing the next constraints on value.

منبع سفارش / آدرس اشتراک

Springer Nature

شماره انبار

com.springer.onix.9781484235317

عنوان

Optimizing data-to-learning-to-action.

شماره استاندارد بين المللي کتاب و موسيقي

9781484235300

موضوع مستند نشده

Decision making-- Data processing.

موضوع مستند نشده

Machine learning.

موضوع مستند نشده

Management information systems.

موضوع مستند نشده

BUSINESS & ECONOMICS-- Industrial Management.

موضوع مستند نشده

BUSINESS & ECONOMICS-- Management Science.

موضوع مستند نشده

BUSINESS & ECONOMICS-- Management.

موضوع مستند نشده

BUSINESS & ECONOMICS-- Organizational Behavior.

موضوع مستند نشده

Databases.

موضوع مستند نشده

Decision making-- Data processing.

موضوع مستند نشده

Machine learning.

موضوع مستند نشده

Management information systems.

موضوع مستند نشده

Software Engineering.

موضوع مستند نشده

BUS-- 041000

موضوع مستند نشده

BUS-- 042000

موضوع مستند نشده

BUS-- 082000

موضوع مستند نشده

BUS-- 085000

موضوع مستند نشده

UN

موضوع مستند نشده

UN

شماره

ويراست

شماره رده

مستند نام اشخاص تاييد نشده

Flinn, Steven

تاريخ عمليات

20200823032052.0

قواعد فهرست نويسي ( بخش توصيفي )

pn

نام الکترونيکي

نوع ماده

[Book]

تكميل شده

Y