Weak Signals for Strategic Intelligence: Anticipation Tool for Managers / Edition 1

by Humbert Lesca, Nicolas Lesca

Overview

The expression: "We did not see it coming!" has often been heard in recent years from decision makers at the highest levels of responsibility in the private and public sectors. Yet there were actually early (warning) signals, but they were often ignored or not used due to a lack of appropriate methodology. To avoid such blind spots, this book provides answers to the question "how to anticipate".

The concept of a "weak signal" is at the heart of the proposed methods. After presenting examples of this concept, the authors provide original and validated answers to questions of feasibility: How to recognize a weak signal? How to exploit it? Numerous applications are presented.

Product Details

ISBN-13:	9781848213180
Publisher:	Wiley
Publication date:	10/31/2011
Series:	ISTE Series , #585
Pages:	230
Product dimensions:	6.00(w) x 9.30(h) x 1.10(d)

About the Author

Humbert Lesca is Emeritus Professor at Pierre Mendès France University, Grenoble, France and director of research at the CERAG-CNRS (center for studies and research applied to management) laboratory.

Nicolas Lesca is Professor at Claude Bernard University, Lyon, France, and a director of research at the CERAG-CNRS laboratory.

Table of Contents

Introduction xi

Chapter 1 Concepts, Issues and Hypotheses 1

1.1 Introduction: governance and radar 1

1.1.1 Steering the ship 1

1.1.2 Corporate governance and strategic decision-making 2

1.1.3 The ship's radar (radio detection and ranging) 6

1.1.4 The organization's "radar", a tool for its governability 6

1.2 The organization's environment and its governance through a "storm" 8

1.2.1 The ship, the ocean, and any danger to be faced 8

1.2.2 The enterprise, its environment, uncertainty, hazards, and opportunities 9

1.2.3 Scrutinizing and interpreting the environment 13

1.3 Anticipation (act of looking forward) 15

1.3.1 Anticipating: definition and examples 15

1.3.2 Do not confuse anticipation with forecasting 17

1.3.3 Anticipation and scenario-based prospective: possible complementarity 21

1.3.4 Anticipating odd events, discontinuities, anomalies, etc. 22

1.4 Anticipative information: two types 23

1.4.1 Definition 23

1.4.2 Difference between strategic information and day-to-day management information 23

1.4.3 Two types of anticipative information 24

1.5 Weak signals 25

1.5.1 Definition of a weak signal 26

1.5.2 An example of weak signal as the trigger to a warning 27

1.5.3 Should we prefer a "strong" but backward-looking signal, or a "weak" but forward-looking signal? 29

1.5.4 Conversion, transformation of a weak signal into an early warning signal 33

1.5.5 Should we refer to a "signal" or a "sign"? Intentionality of the sender 34

1.5.6 Weak signals… or decoys, deceptions, and information asymmetry 35

1.5.7 Characteristics of a weak signal: "stealthy information" 36

1.5.8 Sources emitting weak signals: examples 40

1.6 Detecting weak signals 43

1.6.1 Individual intelligence (in the Latin sense of the word): a definition 44

1.6.2 Cognitive style of a person 44

1.6.3 Individual cognitive biases 45

1.6.4 Fear 47

1.7 Interpreting, amplifying and exploiting weak signals to support strategic decision making 47

1.7.1 Need for collective intelligence (CI) for interpreting weak signals 48

1.7.2 CM: justification and definition of the process 50

1.7.3 Definition of CI as the emergence of CCM 57

1.7.4 From CCM to knowledge management 58

1.8 Puzzle® method for the operationalization of CCM 59

1.8.1 Issue: why the puzzle metaphor? 60

1.8.2 Definition of the Puzzle® method 62

1.8.3 Fundamental hypotheses of the Puzzle® method 67

1.8.4 Work group and CI 69

1.9 Global VASIC process for detecting, recognizing and utilizing weak signals 69

1.9.1 Targeting of anticipative scanning and information sources 72

1.9.2 Tracking and individual selection of weak signals 73

1.9.3 Escalating information, collective/centralized selection and storage 74

1.9.4 Dissemination and preparation of information for CCM sessions 75

1.9.5 Animation 75

1.9.6 Measurements: performance indicators of the VASIC process 76

1.10 Conclusion 79

1.10.1 Results on completion of Chapter 1 79

Chapter 2 Detecting, Recognizing and Corroborating a Weak Signal: Applications 81

2.1 Recognition of a weak signal: examples 82

2.1.1 A lady heading up the purchasing function at a car equipment manufacturer? How bizarre! 82

2.1.2 When a weak signal is displayed on a sign in the street! 88

2.1.3 A research center at EADS: why Singapore? 90

2.1.4 Danone 93

2.2 Making a new weak signal reliable 95

2.2.1 Reliability of the information source 95

2.2.2 Comparing the weak signal with other information obtained previously 95

2.2.3 Consulting with an "expert" 98

2.2.4 Feedback from the animator to the gatekeeper who provided the weak signal 99

2.3 Conclusion 101

2.3.1 Result 101

Chapter 3 Utilization of Weak Signals, Collective Creation of Meaning: Applications 105

3.1 The Roger case: should we fear this new entrant to our industry? (the banking sector) 105

3.1.1 Issues for Roger as a company 105

3.1.2 Context 106

3.1.3 Codexi 106

3.1.4 Information to be used 107

3.1.5 Conduct of the collective work session 107

3.1.6 Results 115

3.2 The case for "valorizing CO₂ as a commodity": a preliminary study for the selection of a new strategic direction 119

3.2.1 The main problem: how to "give birth to an idea" within the Board of Directors (BoD)? 119

3.2.2 Challenge: arousing the interest of the BoD 120

3.2.3 Preparing for the session (which will prove to be the first session) 120

3.2.4 Background of the experiment (first session) 121

3.2.5 Conduct of the session (first session) 123

3.2.6 Second session, three months later 127

3.2.7 Conclusion and post-scriptum 131

3.3 The Danone case. The ministry is worried: are there signs showing that companies will destroy jobs over the next two years? Could Danone leave France? 132

3.3.1 The issue at hand 132

3.3.2 Fresh interest in weak signals 133

3.3.3 Background: lack of cross-disciplinarity 133

3.3.4 Organization and conduct of the experiment 134

3.3.5 Targeting of a field of study 134

3.3.6 Selection of Danone as an agent 135

3.3.7 Conduct of the CCM experiment 135

3.3.8 Conclusion at the close of the last session: huge plausible risk on the horizon! 144

3.4 The Opel case: initiating collective transversal intelligence to aid strategic decision-making 147

3.4.1 Issues and background 147

3.4.2 CI 148

3.4.3 Organizational context 148

3.4.4 Preparatory step upstream of the first CCM session 149

3.4.5 Conduct of the CCM session 151

3.4.6 Conclusions 161

3.5 Conclusion 163

3.5.1 Results 164

Chapter 4 Preparation of Weak Signals for Sessions in Collective Creation of Meaning: Applications 169

4.1 Introduction: two starting situations 169

4.2 The Roger case (continued): how are the news briefs used in the Roger CCM session prepared? 170

4.2.1 Preparation of the news briefs used in the CCM 170

4.2.2 The search for raw data: a substantial task 171

4.2.3 Extraction of news briefs: a time-consuming, delicate task 171

4.2.4 The Internet trap 172

4.3 CO₂ valorization case: automatic search for "news briefs" 174

4.3.1 Guiding idea: "FULL text" distillation 174

4.3.2 Steps in the search for "possible weak signal" news briefs 175

4.4 The Danone case: preparation of the weak signals 181

4.4.1 "Manual" search 181

4.4.2 "Manual" extraction 182

4.4.3 Automatic news briefs search and extraction 183

4.4.4 Conclusions on the "CO₂ valorization" and "Danone" cases using the Approxima prototype 184

4.5 Software modules for assisting in the automatic search for news briefs 185

4.5.1 Lookup table of characteristic words for the field being explored. Continuation of the "CO₂ valorization" case 185

4.5.2 Enhancing the anticipative- and characteristic-word bases 188

4.5.3 Semantics problems: synonyms, polysemes and related matters 190

4.5.4 Software enabling "event searches" 194

4.5.5 Integration platform for commercially available software modules 196

4.6 Conclusion 196

4.6.1 Result 196

Conclusion 199

Glossary 203

Bibliography 217

Index 227