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Index
Title Page
Copyright
Dedication
Table of Contents
Chapter 1 Introduction
1.1 Introduction
1.2 Data, information, knowledge and intelligence
1.3 Knowledge generation processes
1.4 Explicit versus tacit knowledge
1.5 Principles of knowledge management
1.6 Business environment monitoring processes
1.7 Individual analysis projects
1.8 The analysis cycle
Chapter 2 Briefing and project brief
2.1 Introduction
2.2 The management brief
2.3 Why would a principal want to start a project
2.4 When to start a project
2.5 What is the scope of a project
2.6 Final checks with management
2.7 Checklist for a project brief
Chapter 3 Attributes of sources and the collection plan
3.1 Introduction
3.2 Segmentation of sources
3.3 Valuation of sources
3.4 Subject terminology
3.5 Data collection plan
Chapter 4 People: collection from friendly or neutral sources
4.1 Introduction
4.2 Anatomy of HUMINT
4.3 Free-flow
4.4 Interviewing
4.5 Interviewing colleagues who are former competitor staff
4.6 Sampling
4.7 Networking
4.8 Source protection
4.9 HUMINT collection across cultural barriers
Chapter 5 People: collection from unsuspecting sources
5.1 Introduction
5.2 Elicitation
Intermezzo: elicitation – examples collected as warnings
5.3 Elicitor
Chapter 6 Papers: collection from public domain sources
6.1 Introduction
Intermezzo: on the value of applying internet search
6.2 Anatomy of OSINT
Intermezzo: elementary set theory for analysts
Intermezzo: successive fractions
6.3 Applications of OSINT
6.4 Attention points when using OSINT as a collection method
Chapter 7 Pictures: collection of data from images
7.1 Introduction
7.2 Why analyse pictures
7.3 Who and where to should intelligence collection from pictures be applied
7.4 When to apply intelligence collection from pictures
7.5 How to apply intelligence collection from pictures
7.6 Attention points when using imagery intelligence output
Chapter 8 Products: collection of data from things
8.1 Introduction
8.2 Why to back-engineer and analyse products
8.3 Who and where to apply product back-engineering
8.4 When to apply back-engineering
8.5 How to apply back-engineering
8.6 Applications of back-engineering
8.7 Attention points when using back-engineering output
Chapter 9 Analysis
9.1 Introduction
9.2 Anatomy of analysis
9.3 Data and metadata
9.4 Attributes of strategic (business environment) analysis
9.5 Collector – analyst relationship
Chapter 10 Input data quality assurance
10.1 Introduction
10.2 Individual data correctness and data completeness
10.3 Individual data correctness assessment
Intermezzo: deception and strategic analysis
10.4 Who am I as an analyst?
10.5 Synthesis on individual data correctness assessment
10.6 Data set completeness assessment
10.7 Synthesis of data set completeness factors
Chapter 11 Data-set preparation
11.1 Introduction
11.2 Managing incomplete data sets
Intermezzo: on foxes and hedgehogs
11.3 Managing conflicting data in a data set
Chapter 12 Common issues in data set processing
12.1 Introduction
12.2 Weighing data on vividness of data reception
12.3 Weighing data on the source
12.4 Weighing data on actuality
12.5 Weighing data on sequence of data reception
12.6 Challenges of working with experts
12.7 Mixing up data quantity and data quality
12.8 Confusing quantitative data with quality data
12.9 Misperceiving events that together form a story
12.10 Premature closing
Intermezzo: premature closing – an example from World War II
12.11 Confusing causality and correlation in a data set
12.12 Underestimating sample size requirements
12.13 Using flawed analogies
Chapter 13 Hypothesis formulation and testing
13.1 Introduction
13.2 On analysis, theories, predictions and hypotheses
13.3 Testing predictions and hypotheses
Chapter 14 Analytical pitfalls
14.1 Introduction
14.2 Common pitfalls in intelligence analysis
14.3 Ethnocentric bias
14.4 Wishful thinking
14.5 Status quo bias
14.6 Herding instinct
14.7 Over-reliance on previous judgments
14.8 Conventional wisdom
14.9 Synthesis
Chapter 15 Reporting
15.1 Introduction
15.2 The process of reporting
Intermezzo: the pyramid principle for generating storylines
15.3 Defining the aim of the report
15.4 Formats of reporting
15.5 Requirements of reporting
15.6 Reporting as lifelong learning
Intermezzo: hints on slide writing
Chapter 16 Analyst decision-maker interaction
16.1 Introduction
16.2 On uncertainty
16.3 On decision-making strategies
Intermezzo: activities attributed to brain systems I and II
16.4 Strategic analysts and uncertainty
16.5 Decision-makers and uncertainty
16.6 Challenges in analyst/individual decision-maker interaction
16.7 Towards trusted advisor
Chapter 17 Social biases in decision-making
17.1 Introduction
17.2 Cherry picking from a dataset
17.3 Yesmanship
17.4 Groupthink
Chapter 18 Ethics and compliance in data collection
18.1 Introduction
18.2 Compliance is mandatory, ethics is a question of identity
18.3 Relevant legislation
18.4 Scope of compliance and ethics in strategic analysis
18.5 Ethically unacceptable methods in data collection
18.6 Defining and implementing a code of ethics for strategic analysis
18.7 Conclusions
Chapter 19 Data management and retrieval
19.1 Introduction
19.2 Why to organize data management
19.3 What data to manage
19.4 How to organize data management
19.5 When to operate a data management system
19.6 Who is to run the data management system
19.7 Who should be provided with administration rights
19.8 Who to admit entry
Chapter 20 Organizing a strategic analysis function
20.1 Introduction
20.2 How to get started
20.3 Structure follows strategy
20.4 Organizing for a good strategic analysis team
20.5 Functional and behavioral analytic competency building
20.6 Towards a world-class strategic analysis organization
Chapter 21 Profile of a strategy analyst
21.1 Introduction
21.2 Functional competencies
21.3 Behavioural competencies
21.4 Strategic analysis as a profession of lifelong learning
Intermezzo: skills and accountabilities of strategic analysts
Acknowledgements
Appendices
Notes
Literature
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