Methods and Tools for Creative Competitive Intelligence - Stephane Goria - ebook

Methods and Tools for Creative Competitive Intelligence ebook

Stephane Goria

599,99 zł


"Creative competitive intelligence" is an information-seeking and monitoring activity of an information environment for the purpose of creativity and innovation. It involves the process leading up to the development of an informational supply adapted to the inspiration of creative or innovative personnel. This dynamic aims for the recognition of novelties (ideas, products, technologies, etc.), the identification of new players in the world of creation and innovation, and the identification of forgotten or neglected developmental paths. This book is aimed at readers who already have some experience of innovation and who are now looking for new ways to discover new products under development, anticipate the design of future products, identify unexplored tracks of inventions, develop and analyze innovation strategies, or recognize the emergence of budding artists.

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Table of Contents





1 Intelligence and Creative Competitive Intelligence

1.1. Supplying intelligence

1.2. Informational supply and creative competitive intelligence

1.3. Creative class and creative competitive intelligence

1.4. Creative competitive intelligence, objectives and means

2 Researching and Identifying Trends

2.1. Weak and strong signals and routine signals

2.2. Trends interpreted using graphs

2.3. Sources of information on trends

2.4. Algorithm of trend research

3 Formatting, Analysis and Inspiration Using Trends

3.1. Word clouds

3.2. Boards, cartograms and trend books

3.3. Note about researching images that relate to a trend

3.4. Trend funnel and cartogram of opportunities

3.5. Routine boards

4 Presenting and Analyzing Networks

4.1. Overview

4.2. Illustrating indirect links

4.3. Illustrating links between individuals

4.4. Demonstrating networks with multivariate entities

4.5. Invisible chessboards

4.6. Comparative analysis of networks using graphs

5 Visual Tools for Problem Solving

5.1. The great issues of problem solving

5.2. Maps to express questions and ideas

5.3. Window tools to change perspective

5.4. Business use cases and user stories

5.5. User experience maps

6 Investigating the Past and Present

6.1. Existing solutions

6.2. Lateral thinking of obsolete technologies

6.3. The C-K theory for design

6.4. Investigating blue oceans

6.5. Crossing of current trends

7 Inspiration Using TRIZ

7.1. A few general points about TRIZ

7.2. The innovation principles

7.3. Matrix of (technical) contradictions

7.4. Separation principles

7.5. Eras and laws of technical system evolution

7.6. Analyzing the technical system

7.7. The ideal final result (IFR)

8 Reasoning with the Aid of Operators

8.1. Search operators of expressions of avenues for innovation

8.2. The easy choice operators and their negation

8.3. Verbal operators

8.4. Operators using the imaginary

8.5. Combined techniques

8.6. The analogical operators

9 Use of Games for Serious Purposes

9.1. Some forms of games

9.2. The game for serious purposes

9.3. Information bingo to monitor speeches

9.4. The semantic brainball to find ideas

9.5. Keyword battleships

10 Diversion of Role-playing Games

10.1. Role-playing games

10.2. Knowledge acquisition through role-playing

10.3. The personas

10.4. The court of ideas

10.5. The seven creative families

10.6. Investigation trees

10.7. Complex route mapping

10.8. The investigation of possible futures

11 Tactical or Strategic Reflection and Wargames

11.1. Reasoning by military analogies

11.2. Free business wargames

11.3. Product clash maps

11.4. The strategic goban

12 Use of Objective-based Games

12.1. A small point about games with a purpose

12.2. The strategic and creative shoot (SCS)

12.3. The Rummy of attributes

12.4. The Small Horse Challenge

12.5. The informational and creative centipede

13 Creative Competitive Intelligence and Territorial Intelligence

13.1. Territory in question

13.2. Problems with creative competitive intelligence and territorial intelligence

13.3. Geo-strategic approach

13.4. Risk approach with

Clue Storming




End User License Agreement

List of Illustrations


Figure I.1.

Framework of strategic reflection

1 Intelligence and Creative Competitive Intelligence

Figure 1.1.

Difference in knowledge between the thoughts of the request-maker (A) and the final product (D)

Figure 1.2.

Different cases of informational provisions with regard to an identified need and an ideal provision

Figure 1.3.

Questioning and note-taking process when in the phase of understanding the intelligence problem (adapted from [DES 13])

Figure 1.4.

Positioning of different information supplies according to the time and the clarity of their request

2 Researching and Identifying Trends

Figure 2.1.

Product life cycle (according to [KIM 11])

Figure 2.2.

Categories of consumers (according to [ROG 03, p. 281])

Figure 2.3.

Curve of dissemination of an innovation (according to [RAY 10])

Figure 2.4.

Main categories for trend cycles (according to [BRA 07])

Figure 2.5.

Google searches for the expression “Tecktonik

Figure 2.6.

Short and long trend cycles (according to [BRA 07] and [KOT 12])

Figure 2.7.

The number of different interactive book titles in the French market between 1981 and 2013


Figure 2.8.

Extensive modeling of the forces that influence an organization

Figure 2.9.

Force fields that influence the nature of an object

Figure 2.10.

Spheres and elements of influence on the evolution of an object

Figure 2.11.

Questioning process for influential trends

3 Formatting, Analysis and Inspiration Using Trends

Figure 3.1.

Example of comparing two word clouds


Figure 3.2.

Illustration of a trend and new ideas board in three columns


. For a color version of the figure, see

Figure 3.3.

Diagram for carrying out a trend cartogram


Figure 3.4.

Example of a research table of images ready to be filled out


. For a color version of the figure, see

Figure 3.5.

Trend funnel (an adaptation of [MAR 10, p. 197])

Figure 3.6.

Mood board “Work at home” by Ashley Pahl [PEA 14]

Figure 3.7.

Routine boards of joysticks on videogame consoles in 2002

4 Presenting and Analyzing Networks

Figure 4.1.

Example of a network considered at level 1

Figure 4.2.

Example of a network considered at level 2

Figure 4.3.

Example of a network considered at level 2

Figure 4.4.

Example of a network constituted of weak, strong and angled links

Figure 4.5.

Example of a network considered in terms of clusters

Figure 4.6.

Some examples of variations of an eye for a Chernoff face

Figure 4.7.

Example of a Chernoff face representing 22 different measures

Figure 4.8.

Redrawing Figure 4.3 with the addition of Chernoff faces

Figure 4.9.

Invisible chessboard square. For a color version of the figure, see

5 Visual Tools for Problem Solving

Figure 5.1.

Heuristic map or mind map with a close-up about sources of information regarding drones. For a color version of the figure, see

Figure 5.2.

Concept map for different categories and elements of drones. For a color version of the figure, see

Figure 5.3.

Lotus flower map for 2 first levels of links for the previous heuristic map


Figure 5.4.

Example of developing a cause–effect diagram

Figure 5.5.

Example of a tree decomposing objectives (according to [LON 15])

Figure 5.6.

Multiscreen (according to [SAV 00])

Figure 5.7.

Hyperspective window building

Figure 5.8.

Customer experience corridor: general example and example of a hotel. For a color version of the figure, see

Figure 5.9.

Outline of business use case diagram [LON 15]

Figure 5.10.

UX map ready to be filled out. For a color version of the figure, see

6 Investigating the Past and Present

Figure 6.1.

Selection table for a sector of activity

Figure 6.2.

Table for selecting an animal or plant in order to investigate a solution inspired by nature

Figure 6.3.

Diagram of the process of lateral thinking for obsolete technologies. For a color version of the figure, see

Figure 6.4.

Concepts-knowledge diagram applied to the case of a flying boat

Figure 6.5.

Strategic canvas for yellow tail wines [Kim 08, p. 39]

Figure 6.6.

Investigation grid for forgotten customers. For a color version of the figure, see

Figure 6.7.

Example of semantic cartography for urban mobility (collective/individual * harmonious/aggressive) [CHR 08]

Figure 6.8.

Example of a mood board: Retro and Tech [CHR 08]

7 Inspiration Using TRIZ

Figure 7.1.

The 40 principles of TRIZ innovation

Figure 7.2.

The 39 features for TRIZ

Figure 7.3.

Illustration of the technical system

Figure 7.4.

Blank technical record

8 Reasoning with the Aid of Operators

Figure 8.1.

Lexical table for the search of new ideas and avenues for innovation

Figure 8.2.

WIFI REALM is NARROW matrix. For a color version of the figure, see

Figure 8.3.

General reasoning by analogy context selection table

9 Use of Games for Serious Purposes

Figure 9.1.

Diagram summarizing the main characteristics of a game

Figure 9.2.

Example of an information bingo grid on the topic: monitoring software

Figure 9.3.

Example of a rocket board in French


10 Diversion of Role-playing Games

Figure 10.1.

Role-playing game character sheet: Cyberpunk 3.0 [MOS 07]

Figure 10.2.

Example of a persona

Figure 10.3.

Examples of seven creative families cards [CHA 13]

Figure 10.4.

Extract from the investigation tree representing the choices of the book The Caves of Kalte [DEV 84] and drawn using Graphviz software


. For a color version of the figure, see

11 Tactical or Strategic Reflection and Wargames

Figure 11.1.

Different combat tactics from the point of view of the black army

Figure 11.2.

Elements of business wargaming (inspired from [TRE 96])

Figure 11.3.

Breakthrough of Nespresso coffeemakers compared to Kraftwood

Figure 11.4.

Some examples of territories


Figure 11.5.

Distribution of variables in rows and columns (left) to obtain a grid interpretable in the manner of a goban (right). For a color version of the figure, see

Figure 11.6.

Sales of Wii games (white) compared to games PS3 and Xbox 360 (black) in 2009


12 Use of Objective-based Games

Figure 12.1.

SCS Strategic round for Yellow Tail wines


Figure 12.2.

Creative SCS round for Yellow Tail wines

Figure 12.3.

Flight plan and SCS counter-attack rounds

Figure 12.4.

Some examples of cards dedicated to

the search for routines concerning the design of joysticks

Figure 12.5.

Example of questions referring to the Small Horse Challenge squares


For a color version of the figure, see

Figure 12.6.

Centipede arcade version (1980)

Figure 12.7.

Informational and creative centipede board. For a color version of the figure, see

13 Creative Competitive Intelligence and Territorial Intelligence

Figure 13.1.

Table for territorial estimation of the originality of ideas. For a color version of the figure, see

Figure 13.2.

Interpretation of the circle of kings according to Kautilya [KAU 98]

Figure 13.3.

Information sheet for Clue Storming dedicated to security


Figure 1.

An example, with a transparency effect, of using a war-room



Table of Contents

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Series Editor Fabrice Papy

Methods and Tools for Creative Competitive Intelligence

Stéphane Goria

First published 2017 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.

Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:


27-37 St George’s Road

London SW19 4EU


John Wiley & Sons, Inc.

111 River Street

Hoboken, NJ 07030


© ISTE Ltd 2017

The rights of Stéphane Goria to be identified as the author of this work have been asserted by him in accordance with the Copyright, Designs and Patents Act 1988.

Library of Congress Control Number: 2017935630

British Library Cataloguing-in-Publication DataA CIP record for this book is available from the British LibraryISBN 978-1-78630-163-5


This book constitutes a summary of investigations, which I have carried out for years, surrounding collective creative intelligence. This form of intelligence is not the first that has been a particular interest of mine. The more my research has advanced, the more I have been able to identify the diverse relationships between intelligence and innovation, as well as between intelligence and creativity. All of this really began in 2002 when writing a business thesis concentrating on the improvements of intelligence processes in a context of competitive territorial intelligence. Like all doctoral students who are interested in competitive or competitor intelligence, it was necessary to start this work by creating a summary of the diverse information intelligence uses. I was soon to discover the most classic forms of information intelligence, namely technological, competitive, strategic, market or legislative intelligence. However, by observing and putting these intelligence practices into their professional framework, I noticed that numerous requests to investigate information have revealed the need to identify new solutions. Consequently, it is on this relationship, between information retrieval and identifying new solutions, that my investigative work will intensely focus on.

Throughout the years, I have explored the existing relationships between the functions of competitor intelligence and the requirements and functions of innovation, and then between design and processes of competitor intelligence and knowledge management. This led me to concentrate my investigation on the lines separating intelligence from creating information, in order to eventually link research activities for information and creativity within the same research objective. It is in this way that in 2007, I opted for the expression “creative intelligence” in order to give a name to a type of intelligence that has the objective of directly contributing to processes of innovation, invention and creation. On reflection, I quickly realized that I was far from being the first to employ this expression to link intelligence and creation. I then refined my readings and investigations to better understand the specificities of this intelligence explored previously by practitioners and theorists. Nowadays, I consider creative intelligence to be a process that links competitor intelligence and innovation. Like other forms of intelligence, it seeks to do this through various functions such as acquiring, processing, shaping and sharing information, and also two other functions, associated more with knowledge management and innovation, which are the creation of knowledge and identification of innovative spaces.

The aim of this book is to push you to discover creative intelligence through different methods that I have tested or developed. This is why I have chosen above all to prioritize the questions that are relevant for understanding the problem, the collection and arrangement of information regarding creative intelligence. The concept of creative intelligence addressed in this work is mostly considered as a type of intelligence, which allows us to make discoveries in development stages, to identify creation paths which have not previously been dealt with, to develop original strategies, to anticipate innovation strategies and to form new points of reference. All of these methods presented have to be considered as advanced intelligence methods. I thus presume that the reader is at least already familiarized with the concept of intelligence, questioning the problems inherent in information retrieval, challenging search engines, using social media or creating alerts. If this is not the case, I advise you to read works like those completed by G. Balmisse [BAL 14], P.-Y. Debliquy [DE 14], J. Deiss [DEI 15], C. Dupin [DUP 14], D. Rouach [ROU 10], etc. It must be clarified that I will not address the practices of systematic and automatic intelligence. At most, I will cite some of them and put forward their main principles in order to tackle a method or a means to increase their relevance using a “push” approach based on the automation of a digital intelligence process.

As already mentioned, I did not create the expression “creative competitive intelligence”. In fact, it seems that it had been awaiting recognition since at least the start of the 1990s. I no longer remember the precise moment I discovered it and I cannot tell you if I ended up employing the expression after a lecture or an exchange with an intelligence specialist, or even if the idea came to me naturally when reflecting on a term which could express the idea of intelligence that is directly related to innovation. If you try this terminological investigation yourself, you will realize that when you are searching for an expression inspired by intelligence and which expresses a strong link to innovation or creation, the expression creative intelligence naturally emerges and, consequently, it is very difficult to forget about it. Nevertheless, other expressions such as “innovation intelligence” and “inventive intelligence” appear. Since 2012, these two expressions are increasingly used in job offers that require a similar skill.

My definition of creative intelligence includes both aspects of intelligence as well as “creation intelligence” or “creative intelligence”, “creative trends intelligence”, “design intelligence”, “stylistic intelligence” and “artistic intelligence”, this last expression being linked with activities of artistic creation or the organization of artistic displays. Creative intelligence as a generic expression used to define a type of intelligence focusing on creative and innovative activities can also be combined with other forms of intelligence to create more plural expressions like “creative and technological competitive intelligence”/“technological competitive and creative intelligence”, “creative and strategic intelligence”/“strategic and creative intelligence”, “creative and competitor intelligence”/“competitor and creative intelligence” or “territorial and creative intelligence” which I will tackle at the end of this work. These combinations of different forms of intelligence simply illustrate that resulting forms of intelligence can be defined and put into place according to certain specificities of two initial intelligence systems which are joined together.

Now that I have given you an insight into what could define creative intelligence, I think that it is time to explore creative intelligence to a greater extent. In order to do this, I will make use of a diagram that I call a “reflective strategic framework” (Figure I.1) that I apply to all forms of intelligence and especially creative intelligence. This framework can also help to prepare the groundwork for problem-solving, whether this be in a context of innovation or not. It is made up of five frames which bring together the elements that strongly interact and that are relevant for resolving a problem from its initial emergence (resolution request) up to its identification (the resolution request is thus implicit). I encourage you to use this framework as a basis to resolve a problem that you are faced with. The order in which you will tackle the fields that compose this framework does not matter; the important aspect is to try to fully find out about them before starting to solve a complex problem. This framework summarizes numerous points which must be examined when we carry out an intelligence process. It also serves as a basis through which the chapters of this book have been organized. First, I will handle the request (expressed or not) in terms of digital provision it implies and interpretative problems that it may produce. If there is a request, it is essential to try to satisfy it by providing the information that is most suitable for their need, their expectations, preferences and availabilities. Then, you may concentrate on the informational problem that needs to be resolved by employing, for example, well-known questioning methods such as 5W&1H and Why Why Why (Chapter 5). As you will come to notice, certain tools and methods presented in this work are tips tricks, while others are more complex, some can be used by a single individual and others require the work of a group of people. It is perhaps convenient to remember that intelligence is not only the responsibility of those in charge of it or of the strategist, but also the responsibility of all of the members of the organization.

Figure I.1.Framework of strategic reflection

The intelligence expert is an expert in identifying, acquiring, treating, analyzing and disseminating important information which is often strategic for the organization, but it is also impossible for them to know everything about a problem or a particular product when working alone. Furthermore, in a creative intelligence framework, the link between information and strategic decisions is very weak. If you look for innovation paths, for example, once certain opportunities have been identified and discussed, a decision can quite easily be reached which will then have a great impact on the future of the organization. This potential impact and the rapidity of the discussed decision, according to the profile of the strategist(s), must then also be considered in terms of the form that the provision of creative intelligence will take. If you keep in mind this potentially important aspect of decision-making, the techniques and tools of intelligence that I put forward must allow you to identify the needs to fulfill them correctly, as well as the initial objectives and the usefulness of the information or other solutions which are to be provided from the work carried out to resolve the problem. In theory, these elements must resonate with the ideal final result that the person who made the request imagined was possible and that which the intelligence expert would feel capable of carrying out.

In order to do this, you must know what you want to do with the certain number of resources at your disposal. Moreover, this book aims to put forward a range of techniques and solutions to provide you with the keys to solve problems regarding information investigation, strategic reflection and encouraging a creative group in particular. As you will see, the essential point of the book is to present diverse means through which to organize information in order to identify, reflect on and communicate elements relating to changes to a sector-specific environment, associated threats or risks, new opportunities and other paths of innovation. You will also notice that many techniques which come from problem-solving involve some form of game. I thus believe that a specific source of inspiration conceives methods or techniques which are still ignored and which allow us to otherwise to solve numerous solutions.

Now, as already mentioned above, before developing all of these points, I will start by presenting in a conventional manner the most important notions handled in the context of this work. I will start with a history of creative intelligence which I will then associate with some of these practices.

1Intelligence and Creative Competitive Intelligence

1.1. Supplying intelligence

Carrying out intelligence requires the employment of several technologies, such as but not limited to those linked to the Web. There are also situations in which we may bypass technology in order to go back to basics: the purely human capacities to understand, investigate, collect, treat, analyze, format and disseminate information. Even if nowadays there are tools that are highly efficient and despite the fact that a great quantity of interesting information can be found on the Internet, the fact remains that the individual and their abilities are at the heart of creating an adapted and relevant intelligence system. I would also add that from the point of view of an expert in charge of collecting information, intellectual capacities are sought after without really relying on technologies when in the phase of understanding the problem posed as well as that of identifying the relevant sources of information. In this way, the first problem with which the intelligence expert is often confronted concerns identifying the informational supply to search for, in order to produce a satisfying response for their partner.

In fact, information investigation generally at least implies searching on the Web. Or in simpler terms, searching for information or for sources of information on the Web, which points to the problem of creating a series of queries to be entered into a search engine. However, before launching into a search engine blindly, it is definitely preferable to reflect on the question and to carefully create one or several queries which will then be adapted and entered into one or several search engines. Consequently, it is necessary to have already selected the search engine(s) that will be used. As you already know, a rigorous intelligence expert cannot be satisfied with a search engine chosen by way of default. In the same way, before embarking upon investigations which will take a long time, we must have fully understood what was initially asked. This corresponds first to the specifications, which must be met in order to satisfy the request-maker. In order to do this, like every list of specifications, it must be created equally between the two parties: that of the request-maker(s) or receiver(s) and that of the creator(s) of the intelligence or intelligence system. Nevertheless, in terms of intelligence, a perfect list of specifications is impossible to establish. There will always be some ambiguities and different ways of interpreting the request which are left at the discretion of the intelligence expert. This is why, in order to fully understand the informational need to which we must respond, an intelligence expert must identify and explore the informational need hidden behind the informational request that was transferred to them. To do this, the intelligence expert must first have an explicit and reasonable informational needs document at their disposal.

Concerning the explicit part, it is about having a list of needs which does not cover a specific theme (competition, technologies, trends, legislation, etc.), but which instead targets responses to apply or a series of questions which the informational provision must clarify or bring an adequate response to [BUL 14, p. 53]. Thanks to this type of document, the intelligence expert reduces interpretation ambiguities which are inevitably linked to requests which use generic terms such as “put a strategic intelligence system into place”, “carry out competitive intelligence”, “undertake technological and sector-specific intelligence”, etc. By focusing on provision and its usefulness, the intelligence expert can easily realize if they do not understand what is expected of them or if a suitable response will be put forward. To get there, it is convenient to question the receiver by asking them questions such as “why are you doing this?”, “what objectives are you aiming to fulfill?”, “in order to respond to what questions, for example?” In fact, in the majority of cases, making examples of provisions to produce or employing information for more explicitness can prove to be of great use in order to better discern the needs of an intelligence system.

In terms of the reasonable aspect of the document of need, it must allow the intelligence expert to signal and to conclude, according to the amount of time that they are given as well as their abilities and means at their disposal, whether or not they can respond to the request effectively. This may be the case for a cartography request with competitive principles for a company, which includes their profile and a monitoring of their actions. In general, this type of work cannot be reasonably carried out by a single person in a single day, unless part of a type of pre-programmed package which the intelligence expert already has more or less at their disposal. If the request is above all that concerns theme, for example, “put a technological competitive intelligence system into place which responds to the needs of a R&D service”, the intelligence expert must link this request with an explicit and reasonable formulation of informational needs to be fulfilled. Even if they are granted full rein as an intelligence specialist, they must be able to take the time to locate the recipients of their work, understand their needs and formulate with each one of them explicit documents of specific provisions as well as numerous other criteria such as quantity, frequency and the form of information to provide. It is unimaginable to carry out this work without locating the recipients of the information, obtaining the technical information and preliminary knowledge about what is created using the R&D service, or spending a few weeks to properly establish the needs and adjust the provisions.

As stated earlier, this process of making the informational needs more explicit is as relevant to requests for information and intelligence investigation which will exploit the Web as to the others, that is to say those which do not target the Web or are not limited to information found on the Web. Whatever the details of the request, every reflection that aims to make the useful response more explicit stays the same. The use or non-use of search engines, the use of an original flux RSS aggregator, the exploration of a database with the use of a data mining software system or its use at trade shows are only a few of the possible applications. Every element is needed in order to collect information effectively, to fully understand the need that these actions are meant to respond to. In this way, every information researcher or intelligence expert must be capable of putting strategies in place to better understand the demand and informational need of their request-maker.

Unfortunately, as it has been expressed notably by M. Mugur-Schächter [MUG 07] and B. Simonnot [SIM 13], information is an ambiguous and complex notion which in the framework of intelligence too often provokes misunderstandings and provision errors. Making the request more explicit is thus absolutely necessary and must pass through clearly identifying the needs of the real request-maker while avoiding intermediaries. When the request is complex, the needs must be put into an explicit hierarchy. By default, it is up to the intelligence expert to propose ideal responses to their request-maker that they will be able to produce. Generally, a discussion surrounding these provision propositions will have the advantage of refocusing, rendering the need more explicit making it more about the practical usage of information to look out for and the likely responses that they could bring. It may also shed light on the context of the informational request which is made and predict, in an ideal situation, what would be the best result to propose. The strategic reflection framework presented in the introduction (Figure 1.1) can serve as a model to follow in order to automate this very delicate first part of understanding an informational problem which the intelligence expect is responsible for solving.

Obviously, these problems can also be posed in the context of putting creative competitive intelligence into place, even if this form of intelligence most regularly imposes an additional process. In order to further explore the problems posed by understanding an informational need, whether it be linked to a more traditional intelligence framework (strategic, competitive, technological, legislative, etc.) or creative competitive intelligence, I will call upon two series of illustrations, starting with those in Figure 1.1. In this way, as already mentioned, the first problem to be dealt with when we try to understand an informational need in order to create an adequate response consists of limiting the difference in understanding the problem between the recipient on one side and the intelligence expert on the other.

Figure 1.1.Difference in knowledge between the thoughts of the request-maker (A) and the final product (D)

In the series of illustrations shown in Figure 1.1, A represents the field of informational investigation that the request-maker thinks about. They have identified the need themselves. B shows what is eventually expressed as the informational need to the intelligence expert. C demonstrates what the intelligence expert has understood (of course, another intelligence expert would have interpreted this differently) and in D, we see what the intelligence expert has been able to produce after the information retrieval, verification, treatments and formatting. In contrast, E presents the different areas of investigation identified by the request-maker which are not found in the response that was created. In order to avoid this type of problem, an intelligence expert must be able to have discussions with the request-maker, asking additional questions and if necessary, leaving them the chance to adjust their response so that they can better understand the needs of the request-maker during the project. Intermediaries, which separate the two sides, must also be kept to a minimum since the gap between real informational need and the request eventually created will increase with the number of people for whom the request will pass through. If the intelligence expert has the time to improve their bank of information, through repetitions and regular feedback with their recipients, it is obvious that their understanding of the needs will look more and more like illustration A in Figure 1.1. But not everyone has the luxury of several months to refine their understanding of each one of the intelligence requests.

With this taken into consideration, there is another problem which emerges in terms of the collection of information. This problem corresponds, on the one hand, to the gap that will separate what we wish to provide from what we successfully provide with regard to the needs of the request-maker and, on the other hand, to the gap that will separate the proposed informational provision from the ideal informational provision that would have been provided. Figure 1.2 illustrates some cases of intelligence provision which can be carried out by linking them with the wishes of the request-maker, the understanding of the intelligence expert and the ideal provision that can be carried out.

Figure 1.2.Different cases of informational provisions with regard to an identified need and an ideal provision

In Figure 1.2, A1 illustrates what the request-maker has identified as the informational need and wants to be the provision of information, even if there may be certain difficulties in expressing this request (as in the case used above). F1 shows the ideal provision of information, which would allow us to respond to all of the informational needs of the request-maker included in their request or hidden by it. As it has probably already been noted, there are many cases where the intelligence expert can provide very relevant informational elements which the request-maker would not even dream of. As a general rule, the request-maker is not considered an expert in information retrieval, as they can demand things that cannot be realized, but they may also underestimate the ability of the intelligence expert.

In A2, illustrations A1 and F1 overlap to effectively show their similarities and differences. When we ask an intelligence expert for information, we must try to be as close to A1 as possible, and if possible approach F1. B1 and C2 represent the informational responses in terms of intelligence provision, which does not respond to the request. The advantage of this type of provision is that the request-maker will be disappointed very quickly. B2 to C2 represent their position in relation to the request as well as the ideal informational supply. Response B1 is too limited (B2) and must be more detailed while that of C1 is moved (useless information have been provided and others have been ignored) and so must be redefined (C2). Responses D1 and E1 must satisfy both, but response D1 brings forward a lot of useless information, even though it has allowed us to find one or two pieces of information that were not requested, which satisfy and positively surprise the request-maker. However, this work can be improved, because it requires too much time (investigation and sorting for the intelligence expert, reading and assimilation for the request-maker). This process comes up with too much superfluous information. We may also see from this figure that some requested information has not been provided. In E1 and E2 alike, we note an effective intelligence process that corresponds nearly perfectly to the request. This is a classic example of professional intelligence. Finally, F2 shows, through the dotted line, what a truly effective intelligence process should look like, even if it has to be carried out in two stages. First, a classic intelligence process (E1), and then, in order to clearly present things, an additional supply going towards F1. Extending the field of investigation of a traditional intelligence process is what should allow us to come to a strategy for creative competitive intelligence. Information must be proposed in order to fully satisfy the request (E2) and then extend this supply to approach the ideal informational supply, which is very difficult to define. A creative competitive intelligence process thus must be aimed in the right direction to avoid ending up in the case of D2. Nevertheless, to get there, a creative competitive intelligence process systematically takes more time and will inevitably produce more superfluous information and then a classic intelligence process. A creative competitive intelligence process thus takes place with a well-framed intelligence process (E2) when the working conditions allow it or need it. On the contrary, creative competitive intelligence does not overcome the problems posed by expression and understanding informational request (Figure 1.1). The creative part of the request must also use additional pieces of information to ensure that it does not distance itself too much from the assigned objective.

Lastly, as evoked above, there is one remaining dimension to take into account when putting an intelligence system into place: linking the provided information with the decisional process. In a certain way, it is about providing the means to improve or at least maintain the level of relevance of the information provided by the intelligence processes carried out throughout the period. It is a quality approach applied to the intelligence system which must be put into place. The contribution of the provided information in the decisional process must be estimated on a scale that goes from “useless” to “decisive”. In fact, when we wish to put an effective intelligence system into place, we should start using the definition of the system, examining the contribution of its information that will be put forward for the decisions of the organization. However, when we have little time or even when we find ourselves among a rather small structure, we generally tackle analysis of the informational contribution only once since the intelligence information has already been collected. The advantage of this type of planning is that it allows for empirical adjustments of the intelligence already in place.

In order to estimate whether some elements must be changed in the intelligence system, a few questions should be asked such as:

– Which information has helped and why?

– Which information has not been useful and why?

– Can you improve the relevance of the information already provided?

– Among the information provided, has there been anything that has proved useless?

– Is the information that was deemed useless a year ago still useless?

– Which information provided has had a crucial impact on the strategy or the working of the organization?

- What is the nature of this impact (positive, negative, other)?

- What are the reasons that allow us to explain this impact?

In order to avoid certain problems like those illustrated above, it is important for the intelligence expert to benefit in the best way possible from interviews with their request-maker and recipient of the bank of information. It is thus necessary for them to be well prepared for this type of interview that includes taking notes, which is one of the fundamental elements. In order to present a guide to manage this phase of information retrieval, I have been highly inspired by a diagram proposed by G. Desmaretz [DES 13] about taking notes (Figure 1.3). This diagram allows me to put forward in a single drawing the most important elements of note-taking during a discussion between an intelligence expert and their request-maker aiming to reach a good understanding of the informational need expressed.

Figure 1.3.Questioning and note-taking process when in the phase of understanding the intelligence problem (adapted from [DES 13])

If you find yourself in an unlucky situation where you cannot or can hardly benefit from an interview with the recipient(s) of your information or even the initial request-maker, there is still a method that could help you a little: establish a profile of recipients or request-makers. Profile sheets (section 10.3), which help to record interesting information relevant to the profile of a general request-maker or recipient, allow you to put yourself in their shoes to better understand how they work, a part of their experience and, above all, their probable expectations.

1.2. Informational supply and creative competitive intelligence

As we have just seen, a proper competitive intelligence project consists of a questioning stage as well as a stage in which hypotheses are made and released in regard to what must be carried out. This stage which is part of understanding informational need requires the person in charge of the competitive intelligence project (the intelligence expert) to suppose that there is, in theory, a gap between what is understood and what is requested. In other terms, the intelligence expert must ensure that there is a real correlation between the informational need expressed and the need that is understood. Moreover, the intelligence expert must also be able to identify the need that is not expressed, using the expressed need and the ideal informational supply which can be proposed in order to respond to the need that was initially recognized. There are thus different ways to tackle the supply of information and these can allow us to classify creative competitive intelligence in relation to other forms of intelligence.

One of the methods that we can employ for questioning objectives consists of placing informational supply on an axis, which allows us to recognize what is expressed by the request and what is implied. If we depart from the principle that the intelligence expert has not misunderstood, another axis may also interest us to understand the intelligence system more clearly: that is to say the temporal aims of informational supply. I can in this way construct a plane where an axis points to a type of intelligence according to when a request is expressed: at the extremes, we see the requests that have been expressed and not expressed with the more vague requests in the middle. If you are asked to investigate innovations and new ideas, you have to use a clearly expressed request associated with an enormous quantity of unspoken words, implicit knowledge, and supposed expectations and often of surprising and exploitable hopes for information (that are not defined). The other additional axis consists of placing into time the type of information to be investigated. Innovation points towards the future, while investigations regarding experiences, past results points towards the past. In the center, we see investigations for temporary information. There are thus six informational categories presented in Figure 1.4.

Figure 1.4.Positioning of different information supplies according to the time and the clarity of their request

From top to bottom, in other words, starting with information retrieval pointing towards the past, we see classic documentation that responds to clearly expressed requests (I1) and informative research that needs to be made more explicit (it can enter a process of knowledge capitalization that we must thus define then research) or even investigation surrounding historical cases which appear throughout the years, throughout implication, digitalization or case identification processes. Then, we can tackle the specific information that is more short term. With this aspect, we erase documentation in order to come to the most widespread intelligence case. We try to follow the information week by week, day by day and minute by minute in order to be informed of everything that may interest us in order to make a decision or to respond quickly. We find, in this context in particular, competitive intelligence systems, product and image, which according to the sector of activity and the spectrum that has to be considered, can constitute a clear informational request (observation of direct competitors, competitive products, opinions of consumers), a vague request (monitoring of positive and negative perceptions of current or potential customers, trends and methods of indirect competitors) or which require explanation or a creativity period (monitoring of potential replacement products, future new players, future customer expectations). Finally, we turn towards the future with explicit informational requests, at least perceptible at that moment. I propose placing prospective informational supplies there as well as anticipatory intelligence systems (I3) which bring clearly defined elements forward (technologies, regulations, new markets, etc.). When the objective of the research points towards the future when it is very ambiguous and rather generalized (find new ways to innovate for example), we find ourselves in the context of creative competitive intelligence (I4).

This figure also allows us to define creative competitive intelligence without calling upon the terms creation and innovation. With the help of this diagram, creative competitive intelligence can be understood as a form of intelligence which distinguishes itself from other forms of intelligence, due to the fact that it concentrated on needs that have not been expressed, or badly identified and which will allow us to be able to reach information, which will tell us things about the near future, from 1 to 7 years away according to the situation and the fields of application. The methods used for creative competitive intelligence can also be employed to carry out intelligence which is more short term or anticipatory. Nevertheless, it should be brought to our attention that creative competitive intelligence can also be assimilated to short-term intelligence, or even historical intelligence, when the qualitative word “creative”, which is associated with it, is used to characterize the sector of activities that it follows or in which it draws information. These are the creative sectors which are generally associated with part of the population which is called the creative class.

1.3. Creative class and creative competitive intelligence

Since the 1990s, with the arrival of the Internet, competitive intelligence and knowledge management, our society has become a society of information and knowledge. Since then, different analyses have brought transformations resulting from this type of society to light which has ended