Today many organizations face challenges when developing a realistic plan or schedule that provides the best possible balance between customer service and revenue goals. Optimization technology has long been used to find the best solutions to complex planning and scheduling problems. A decision-support environment that enables the flexible exploration of all the trade-offs and sensitivities needs to provide the following capabilities: Flexibility to develop and compare realistic planning and scheduling scenarios Quality sensitivity analysis and explanations Collaborative planning and scenario sharing Decision recommendations This IBM® Redbooks® publication introduces you to the IBM ILOG® Optimization Decision Manager (ODM) Enterprise. This decision-support application provides the capabilities you need to take full advantage of optimization technology. Applications built with IBM ILOG ODM Enterprise can help users create, compare, and understand planning or scheduling scenarios. They can also adjust any of the model inputs or goals, and fully understanding the binding constraints, trade-offs, sensitivities, and business options. This book enables business analysts, architects, and administrators to design and use their own operational decision management solution.

Revealing the limitations of human decision-making, this book explores how Artificial Intelligence (AI) can be used to optimize decisions for improved business outcomes and efficiency, as well as looking ahead to the significant contributions Decision Intelligence (DI) can make to society and the ethical challenges it may raise. From the theories and concepts used to design autonomous intelligent agents to the technologies that power DI systems and the ways in which companies use decision-making building blocks to build DI solutions that enable businesses to democratize AI, this book presents an impressive framework to integrate artificial and human intelligence for the success of different types of business decisions. Replete with case studies on DI applications, as well as wider discussions on the social implications of the technology, Decision Intelligence: Human–Machine Integration for Decision Making appeals to both students of AI and data sciences and businesses considering DI adoption.

Analytics systematically informs human judgment with data-driven insight, improving decision-making and enabling greater innovation and creativity in support of strategy. This book hows how IBM has successfully leveraged analytics across the enterprise, worldwide. Through 31 case studies, the book shares real-world perspectives on what does and doesn't work and how to start or accelerate the business transformation. Coverage includes: creating a smarter workforce through big data and analytics; more effectively optimizing supply chain processes; systematically improving financial forecasting; managing financial risk, increasing operational efficiency, and creating business value; reaching more B2B or B2C customers and deepening their engagement; optimizing manufacturing and product management processes; deploying your sales organization to increase revenue and effectiveness; achieving new levels of excellence in services delivery and reducing risk; transforming IT to enable wider use of analytics; and "measuring the immeasurable" and filling gaps in imperfect data.

"A very rich book sprinkled with real-life examples as well as battle-tested advice.” —Pierre Haren, VP ILOG, IBM "James does a thorough job of explaining Decision Management Systems as enablers of a formidable business transformation.” —Deepak Advani, Vice President, Business Analytics Products and SPSS, IBM Build Systems That Work Actively to Help You Maximize Growth and Profits Most companies rely on operational systems that are largely passive. But what if you could make your systems active participants in optimizing your business? What if your systems could act intelligently on their own? Learn, not just report? Empower users to take action instead of simply escalating their problems? Evolve without massive IT investments? Decision Management Systems can do all that and more. In this book, the field’s leading expert demonstrates how to use them to drive unprecedented levels of business value. James Taylor shows how to integrate operational and analytic technologies to create systems that are more agile, more analytic, and more adaptive. Through actual case studies, you’ll learn how to combine technologies such as predictive analytics, optimization, and business rules—improving customer service, reducing fraud, managing risk, increasing agility, and driving growth. Both a practical how-to guide and a framework for planning, Decision Management Systems focuses on mainstream business challenges. Coverage includes Understanding how Decision Management Systems can transform your business Planning your systems “with the decision in mind” Identifying, modeling, and prioritizing the decisions you need to optimize Designing and implementing robust decision services Monitoring your ongoing decision-making and learning how to improve it Proven enablers of effective Decision Management Systems: people, process, and technology Identifying and overcoming obstacles that can derail your Decision Management Systems initiative

IBM® Operational Decision Management (ODM) is a family of products used by IT and business users to create and manage business decision logic throughout their organization. This IBM RedpaperTM publication offers advice on all aspects of performance, including hardware, architecture, authoring, quality of service, monitoring, and tuning. The advice is based upon preferred practices and experience gained from real customer situations. This paper is aimed at a wide ODM audience, including IBM employees and customers, and provides useful information to both new and experienced users. Although the product family is known as IBM WebSphere® Operational Decision Management (WODM), at V8.0, with V8.0.1 the the name is now simply IBM Operational Decision Manager (ODM). The performance information in this paper is based on V8.0 of this product family and differences introduced with V8.0.1 are pointed out.