Digital Decisioning

Using Decision Management to Deliver Business Impact from AI

By: James Taylor

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Paperback | 30 August 2026 | Edition Number 3

At a Glance

Paperback
206 Pages

Dimensions(cm)
22.86 x 15.24 x 1.12

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"I've worked as a C-level executive in multiple insurance companies and engaged countless strategy consultants, IT consultants and technology vendors over the past two decades. This book describes the only approach that has actually allowed me to operationalize predictive models and deliver real ROI!"

Digital Decisioning ensures your systems act intelligently on your behalf, making precise, consistent, real-time decisions at every touch point. It operationalizes machine learning and artificial intelligence, so you can make the best possible decision, every time. It uses business rules to guarantee the agility, transparency and compliance that established companies and regulated industries demand. Focusing only on decision-making, it supports continuous learning and improvement. Digital Decisioning applies machine learning and artificial intelligence at scale to automate the decisions essential for more profitable, more customer-centric and more digital business operations.

"Essential reading for COOs looking to rigorously improve automation through AI."

Based on dozens of successful projects around the word, this book lays out the basic elements of the approach in a practical how-to guide. Aimed at managers, not technical teams, this book will focus your efforts to apply machine learning, artificial intelligence and predictive analytics. It emphasizes practical "do this next" advice delivered in non-technical terms, describing the business value and impact of critical technologies without diving into technical detail. Stories of real implementations, real companies, show what can be done.

A completely updated version of an established and popular book on Decision Management, this second edition has forewords by leading analytic experts, Tom Davenport and Eric Siegel.

"James has been at the forefront of decision management techniques for years. Anyone trying to automate and embed analytics to support decisions should read this book."

--Bill Franks, Chief Analytics Officer, International Institute for Analytics, speaker, and author.

"An absolute masterclass in analytics from one of the great masters himself. Nothing but solid knowledge, sage advice, and great examples without an ounce of hyperbole or fluff."

--Doug Laney, Principal Data Strategist with Caserta, and best-selling author of 'Infonomics'.

Industry Reviews

"We are early in using AI in the decision cycle for signal/pattern recognition, understanding data/decisions in multiple contexts, assisting to select the decision models/algorithms, take appropriate actions within the guard rails of goals and constraints, and learning from the decision process to become better decision-makers over time. While there are inherent risks in allowing AI to do all this in an unsupervised manner, having AI assist in decision management is the prudent and successful way today. This book nicely ties the theory of decision management with real-world examples where organizations can make traction today leading them into a better decision management process in the future."

-Jim Sinur, Former VP and Distinguished Analyst, Gartner Group; Now Independent Analyst

"This book provides a clear and practical blueprint for implementing Digital Decisioning in your organization. If you are struggling to move from promise to practice in implementing AI solutions, then this is the must have guide. From overarching principles to real-world examples, this book shines a light on the best approach to unlocking value from your organization's AI, machine learning and decision management investments."

-Ben Collinge, Senior Director, Infrastructure Strategy, Royal Bank of Canada

"Historically, organizations have codified their best practices in rules. Now they are hungry to take advantage of the possibilities of AI to leverage the wealth of information in their historical data and take even better decisions. They are struggling to do so. James Taylor makes it clear how to succeed: By combining business rules and machine learning in a single digital decisioning framework. With clear explanations and examples based on years of practice, this book lays out what can be accomplished with digital decisioning platforms - and how to go about it successfully."

- Harley Davis, VP, Automation Intelligence/France Lab, IBM

"Do you wonder what all this fuss around AI, Machine Learning, Big Data, Business Rules, etc. is about from a practical business perspective? Then this book is a must for you! I wondered myself and reading this book clarified many things. It boils down to fusing AI, business rules, and optimization into digital decisioning to manage and automatically take business decisions in processes and workflows. The author uses his extensive knowledge and experience from many different real-world projects to show and explain this integration and why it is so important in today's business world. I highly recommend this book to anyone who is interested in AI, BR, ML, etc. with a business focus and wants to know how it all goes together to produce real business value."

-Odd Stein, Associate Professor of Information Systems, Department of Informatics, Lund University, Sweden

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