03343nam a2200181   4500001000700000010001800007100004100025101000800066200010500074205001200179210003300191215001800224330281800242606003203060606001703092700002703109701002503136395495  a9781452241517  a20190530d2014       y0pory50      ba  aeng  aStructured analytic techniques for intelligence analysisfRichards J. Heuer Jr., Randolph H. Pherson  a2nd ed.  aWashington, D.C.cSaged2014  a361 p.d21 cm  aForeword. Preface.Chapter 1: Introduction and overview. 1.1 Our vision. 1.2 Two types of thinking. 1.3 Dealing with bias. 1.4 The role of structured analytic techniques. 1.5 the value of team analysis. 1.6 The history of structured analytic techniques. 1.7 Selection of techniques for this book. 1.8 Quick summary of chapters. Chapter 2: Building a system 2 taxonomy. 2.1 Taxonomy of system 2 methods. 2.2 Taxonomy of structured analytic techniques. Chapter 3: Choosing the right technique. 3.1 Core techniques. 3.2 Five habits every analyst should master. 3.3 One project, multiple techniques. 3.4 Common errors in selecting techniques. 3.5 Structured technique selection guide. Chapter 4: decomposition and visualization. 4.1 Getting started checklist. 4.2 AIMS (audience, issue, message, storyline). 4.3 Customer checklist. 4.4 Issue redefinition. 4.5 Chronologies and timelines. 4.6 Sorting. 4.7 Ranking, scoring, prioritizing. 4.8 Matrices. 4.9 Venn analysis. 4.10 Network analysis. 4.11 Mind maps and concept maps. 4.12 Process maps and Gantt charts. Chapter 5: Idea generation. 5.1 Structured brainstorming. 5.2 Virtual brainstorming. 5.3 Nominal group technique. 5.4 Starbursting. 5.5 Cross-impact matrix. 5.6 Morphological analysis. 5.7 Quadrant crunching (TM). Chapter 6: Scenarios and indicators. 6.1 Scenarios analysis. 6.2 Indicators. 6.3 Indicators validation. Chapter 7: hypothesis generation and testing. 7.1 Hypothesis generation. 7.2 Diagnostic reasoning. 7.3 Analysis of competing hypotheses. 7.4 Argument mapping. 7.5 Deception detection. Chapter 8: Assessment of cause and effect. 8.1 Key assumptions check. 8.2 Structured analogies. 8.3 Role playing. 8.4 Red hat analysis. 8.5 Outside-in thinking. Chapter 9: Challenge analysis. 9.1 Premortem analysis. 9.2 Structured self-critique. 9.3 What if? Analysis. 9.4 High impact/low probability analysis. 9.5 Devil's advocacy. 9.6 Red team analysis. 9.7 Delphi method. Chapter 10: Conflict management. 10.1 Adversarial collaboration. 10.2 Structured debate. Chapter 11: Decision support. 11.1 Decision trees. 11.2 Decision matrix. 11.3 Pros-cons-faults-and-fixes. 11.4 Force field analysis. 11.5 SWOT analysis. 11.6 Impact matrix. 11.7 Complexity manager. Chapter 12: Practitioner's guide to collaboration. 12.1 social networks and analytic teams. 12.2 Dividing the work. 12.3 Common pitfalls with small groups. 12.4 Benefiting from diversity. 12.5 Advocacy vs. Objective inquiry. 12.6 Leadership and training. Chapter 13: Validation of structured analytic techniques. 13.1 Limits of empirical analysis. 13.2 Establishing face validity. 13.3 A program for empirical validation. 13.4 Recommended research program. Chapter 14: The future of structured analytic techniques. 14.1 Structuring the data. 14.2 Key drivers. 14.3 Imagining the future: 2020.  aANÁLISE DA INFORMAÇÃO  aMETODOLOGIAS  aHEUER JR.bRichards J.  aPHERSONbRandolph H.