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Optimizing Data-to-Learning-to-Action

The Modern Approach to Continuous Performance Improvement for Businesses

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Apply a powerful new approach to ensure continuous performance improvement for your business. Learn to determine and value the people, processes, and technology-based solutions that optimize your organization's data-to-learning-to-action processes. This book details how to holistically enhance the activities that span from data to learning to decisions to actions, essential for achieving outstanding performance in today's business landscape. By integrating insights from decision science, constraint theory, and process improvement, it offers a clear and effective method applicable across various business functions and sectors. You will discover how to systematically work backwards from decisions to data, estimate the flow of value along the chain, and identify value bottlenecks. Additionally, you will learn techniques for quantifying the value attainable by addressing these bottlenecks, providing credible support for making timely investments. In a dynamic environment filled with disruptive technologies like cloud computing, AI, and big data, this comprehensive approach equips executives to make informed decisions underpinned by quantifiable value. Key takeaways include understanding the fundamental elements of data-to-learning-to-action processes, identifying high-leverage processes, evaluating solution options, and continuously improving by addressing value constraints.

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Optimizing Data-to-Learning-to-Action, Steven Flinn

Langue
Année de publication
2018
Reliure
(souple)
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Titre
Optimizing Data-to-Learning-to-Action
Sous-titre
The Modern Approach to Continuous Performance Improvement for Businesses
Langue
Anglais
Éditeur
Apress
Publié
2018
Format
souple
Pages
216
ISBN10
1484235304
ISBN13
9781484235300
Séries
Description
Apply a powerful new approach to ensure continuous performance improvement for your business. Learn to determine and value the people, processes, and technology-based solutions that optimize your organization's data-to-learning-to-action processes. This book details how to holistically enhance the activities that span from data to learning to decisions to actions, essential for achieving outstanding performance in today's business landscape. By integrating insights from decision science, constraint theory, and process improvement, it offers a clear and effective method applicable across various business functions and sectors. You will discover how to systematically work backwards from decisions to data, estimate the flow of value along the chain, and identify value bottlenecks. Additionally, you will learn techniques for quantifying the value attainable by addressing these bottlenecks, providing credible support for making timely investments. In a dynamic environment filled with disruptive technologies like cloud computing, AI, and big data, this comprehensive approach equips executives to make informed decisions underpinned by quantifiable value. Key takeaways include understanding the fundamental elements of data-to-learning-to-action processes, identifying high-leverage processes, evaluating solution options, and continuously improving by addressing value constraints.