book

The Decision Intelligence Handbook

by L. Y. Pratt, N. E. Malcolm

June 2023

Intermediate to advanced

267 pages

7h 54m

English

O'Reilly Media, Inc.

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Foreword
Preface
About This BookDecision Intelligence in a NutshellLLMs, OMGWho Is This Book For?What You Will LearnAssumptions This Book MakesContents of This BookConventions Used in This BookUsing Supplemental MaterialsO’Reilly Online LearningHow to Contact UsAcknowledgments
1. Introduction
Do You Need Decision Intelligence?What DI Does for You and Your OrganizationFrom Data to DecisionsThe Decision Complexity CeilingWhat Is DI?Build Your First CDD, Right Now!DI Is About Action-to-Outcome DecisionsDI Is About Human-in-the-Loop DecisionsWhy Data-Driven Decision Makers Need DIWhere DI Comes FromWhat DI Is NotThe DI Maturity ModelThe Shifting Meaning of “Decision Intelligence”Who Is Doing DI Today?The Nine DI ProcessesConclusion
2. Decision Requirements
Decision Requirements (Phase A): OverviewProcess A1: The Decision Objective StatementDecision Objective Statement: Net-Zero Emissions Program Use CaseInterlude: Convening the Decision TeamMaking Decisions at Multiple Organizational LevelsBalancing Information, Authority, and ResponsibilityProcess A2: Decision FramingDecision VerificationWhy Decision Framing Is ImportantFormal Process Description: Process A2, Decision FramingWhen the Decision Frame Is WrongVerifying and Framing: Net-Zero Emissions Program Use CaseTry It Yourself: Decision Requirements for a Telecom Use CaseFraming the DecisionAsking About Outcomes and GoalsCompleting the Decision Framing WorksheetConclusion
3. Decision Modeling: The Decision Design Process
The Decision Modeling Phase: OverviewDecision ElementsDecisions and TimeProcess B1: Decision DesignFormal Process Description: Process B1: Decision DesignDivergent and Convergent ThinkingThe CDD Elicitation MeetingDivergent Thinking: Eliciting Outcomes and ObjectivesCapturing Out-of-Context Decision Elements in a “Parking Lot”Convergent Thinking: Refining (“Cleaning Up”) Outcomes and ObjectivesDivergent Thinking: Eliciting LeversConvergent Thinking: Refining LeversDivergent Thinking: Eliciting Intermediates (Causal Chains)Convergent Thinking: Refining IntermediatesDivergent Thinking: Eliciting ExternalsConvergent Thinking: Refining ExternalsConvergent Thinking: Refining Decision ElementsRefining and Expanding Your CDDLevels of Modeling DetailHow Do You Know When to Stop Decision Modeling?Decision Design Use Case: Governmental Net-Zero ProjectTry It Yourself: Decision Design for a Telecom Use CaseBrainstorming OutcomesBrainstorming LeversWiring Known Dependencies TogetherInitial RefinementIterating On and Publishing the CDDConclusion
4. Decision Modeling: The Decision Asset Investigation Process
Deciding to Go DigitalIntroduction to Process B2: Decision Asset InvestigationFrom Simple to Sophisticated AssetsDocumenting Decision AssetsFormal Process Description: Process B2: Decision Asset InvestigationDecision Asset Investigation: A Sweet Potato CDD Drives Data Gathering and ResearchData for ExternalsThe Puzzle Toy Use Case: The Decision Asset ConversationTry It Yourself: Decision Asset Investigation for the Telecom Use CaseConclusion
5. Decision Reasoning: The Decision Simulation Process
Decision Reasoning: Phase OverviewDecision Simulation Process OverviewWhy Simulate Your CDD?Deciding Whether to Automate Your Decision SimulationDeveloping the Simulation IterativelyFormal Process Description: Decision SimulationCreating a Decision SimulationSimplifying the CDDLever ChoicesExternals and AssumptionsIntermediates and OutcomesDecision Simulation FidelityRunning the Simulation “Backward”: Decision Models for OptimizationTechnology OptionsSimulation Report: Identifying Patterns and Feedback LoopsNet-Zero Emissions Use Case: Simulating the Decision ModelVisualizing Emergent Patterns in the Puzzle Toy Use Case SimulationTry It Yourself: Decision Simulation for the Telecom Use CaseDeciding on a CDD to SimulateDesigning CDD Visual ElementsCoding the DependenciesTesting Your SimulationConclusion
6. Decision Reasoning: The Decision Assessment Process
Introduction to Process C2, Decision AssessmentFormal Process Description: Process C2, Decision AssessmentDecision Assessment LensesBaselineAccuracy of the Model, and of Its PartsBiasSensitivityUncertainty and RiskProvenanceFidelityConsensusTimingTry It Yourself: Decision Assessment for the Telecom Use CaseConclusion
7. Decision Action
Decision Action Phase OverviewProcess D1: Decision MonitoringFormal Process Description: Process D1, Decision MonitoringWhen Is a Monitored Value Wrong Enough to Matter?What to MonitorWhen Do You Need to Revisit Your Decision?Decision Monitoring RecordsSilos, Whack-a-Mole, and the Measurement EffectCase Study: Network Upgrade: When the Decision Is Already Off the RailsTry It Yourself: Decision Monitoring for the Unlimited Usage Plan Use CaseConclusion
8. Decision Review
The Decision Review Phase: OverviewProcess E1: Decision Artifacts RetentionLegal, Regulatory, and Policy IssuesWhen Should Decision Artifacts Retention Begin and End?Formal Process Description: Process E1, Decision Artifacts RetentionTry It Yourself: Decision Artifacts Retention for the Telecom Use CaseProcess E2: Decision RetrospectiveOne-Time Versus Repeated DecisionsMeasuring Decision QualityFormal Process Description: Process E2, Decision RetrospectiveContinuous Decision-Process ImprovementConclusion

Appendix. Framework for How Data Informs Decisions
Index
About the Authors

Content preview from The Decision Intelligence Handbook

About the Authors

L. Y. Pratt, PhD, Chief Scientist at Quantellia, has been delivering artificial intelligence and machine learning solutions for her clients for over 30 years. These include the Human Genome Project, the Colorado Bureau of Investigation, the US Department of Energy, SAP, and the Administrative Office of the US Courts. She is a machine learning pioneer, having led the teams that invented inductive transfer and decision intelligence (DI). Pratt received the CAREER award from the National Science Foundation, an innovation award from Microsoft, and the Exemplary Research Award from the Colorado Advanced Software Institute (CASI). Formerly a computer science professor at the Colorado School of Mines, Pratt has appeared multiple times on national television and NPR, has given two TEDx talks, and is a respected AI and DI speaker worldwide.

Recognized by the Women Innovators and Inventors Project, Pratt continues to push the boundaries of technology as one of the creators and evangelists for decision intelligence, which is the next phase of artificial intelligence, and which will define how AI is used in the 21st century.

N. E. Malcolm, COO at Quantellia, has over 25 years of experience managing and delivering enterprise software, data science, machine learning, and decision intelligence projects. Malcolm has spent five years on the Quantellia executive team with Dr. Pratt, continuously improving and developing best practices for both decision intelligence and Agile ...

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The Decision Intelligence Handbook

by L. Y. Pratt, N. E. Malcolm

About the Authors

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.