to refine and optimize them. Concurrently, operations are being internationalized. There, known and unknown risks increase. For instance:
– outsourcing implies an improvement in productivity, a reduction in costs, as well as higher logistics costs (costs of delays, costs of risks related to stock shortages, etc.);
– the creation of subsidiaries abroad leads to higher transition costs as well as to more difficulty in control of strategy and operations;
– no longer being hesitant to relocate a growing part of the value chain. Outsourcing is based on often fragile networks: we are in an unstable and unpredictable mode, higher organizational costs, etc.
Some economists note that the notion of cost or productivity alone is no longer sufficient: certainly, manufacturing and technological costs have been reduced, but changing context and culture leads to an increase in social cost.
Thus, given that studies are generally not conducted in a comprehensive manner, it is difficult to measure the impact of changes and the new complexity of our systems. In which direction should we go? Realizing that you cannot understand everything, you have to change your paradigm and focus on two points:
– Strategic Risk Management. Without going into detail, this method implies that it is necessary to identify high value-added processes, key infrastructures and assess their vulnerability.
– Strategic Opportunity. The world is characterized by rapid change, it is volatile: customers change, so do their aspirations, tastes, preferences, wants and needs. Choice is not allowed because gaps between countries are widening and, if one does not respond to new needs and challenges, one will be overtaken by its competition. It is therefore a question of seizing opportunities and “conditioning” oneself in this sense.
I.4.2. The role of intelligence
Within the complexity maelstrom of systems, the interactions and the autonomy of agents are involved, which help create new orders. We are often confronted with the consistency of these orders with respect to the expectations of managers, consumers, clients or owners of the system. The only problem here is related to the fact that we only take into account analytical intelligence, and we model and integrate it into the programs we develop. Of course, as already mentioned, improvements have been made with the inclusion of “common sense” knowledge (e.g. à la CYC – Cycorp (society)), but this is far from enough. Indeed, this form of intelligence is too systematic and cannot by itself account for an individual’s profound satisfaction, the adequacy of a solution, a social, professional or sentimental success, etc.
In fact, in our brain, with regard to Gardner’s works [GAR 06], intelligence is considered as an ability or aptitude to manage some human being functions. Thus, human beings possess nine different kinds of intelligence, in addition to the logico-mathematics (here above mentioned). Here, we will note nine of them:
1 1) musical-rhythmic (harmony, rhythm, equilibria, etc.);
2 2) visual-spatial (organization, geometry, hierarchy, architecture, etc.);
3 3) verbal-linguistic (manipulation of words and languages, concepts and semantics);
4 4) logical-mathematical (modeling, cognition, reasoning, etc.);
5 5) bodily-kinesthetic (control of motion, of physical expressions and actions);
6 6) interpersonal (emotional intelligence, psychological);
7 7) intrapersonal (empathy, ability of understanding the self; global and social strengths, interactions and weaknesses around us);
8 8) naturalistic (ecology and sustainable receptiveness, including ethical and holistic understanding of the world);
9 9) existential intelligence (related to consciousness and resilience: spiritual, moral, of deontology, ethics, etc., related to the concept of inclusivity and over-mind constructs).
All these types of intelligences lead to considering the so-called “smart” devices, oftentimes based on artificial intelligence programs. This book does not address artificial intelligence per se, as AI is but an enabling technology made to implement and automatize the different concepts and abilities relative to intelligence.
The example hereafter will introduce emotional (interpersonal) and social (intrapersonal) intelligence. It is indeed necessary to take into account a form of intelligence called “emotional intelligence”. It allows us to recognize, interpret, process and manage emotions, an essential concept for modeling and understanding the relationships between reason and passion, as well as the development of social relationships. As essential steps in a decision-making process [GRE 05b, DAM 05], emotion, reflection and reason are inseparable and it has often been shown that decisions taken “coldly”, in an “objective” manner and in the absence of emotion, sometimes turn out to be biased in relation to the objective pursued. In any decision-making process, it is important to be able to detect the profound feelings of partners, to discriminate against them and to anticipate events or consequences of actions to be taken according to their sensitivity, character and psychological state. This conditions the partner’s potential acceptance and adherence to the final choice or proposal for a decision.
With analytical intelligence, we manage information by bringing in knowledge and know-how while remaining in the objective field. With emotional intelligence, we rather manage emotions and feelings, by putting into play the notions of accomplishment and recognition: here we are in the subjective field.
Finally, and for the sake of completeness, it is necessary to mention social intelligence, which is the ability to perceive one’s inner motivations and behavior as well as those of others and to act accordingly. This should help us to become what we have chosen to become and it also allows us, in a group or network, to have access to agents where everyone is in harmony. Social intelligence is the ability of an individual or group of individuals to work in a group, to share values and to integrate into a common project. It is an indispensable criterion and a prerequisite for what we have discussed in the previous chapters, namely cooperation, from which collective intelligence emerges. Much work still needs to be done to take all these concepts into account in current decision support systems.
I.4.3. The role of public institutions
This section defines a new role and mission for public institutions and administrations.
Since the Industrial Revolution, institutions and administrations have been abused by technology and much more recently by the mass liberation of consumer power. It is important that they regain their true mission, probably to preserve the integrity of all kinds of networks. Indeed, network law, “netiquette” and exchange protocols are all focal points for 21st Century administrations. Until the last century, an administration was mainly concerned with activities related to the passage of human action: the law of blood (transmission of inheritances, etc.), soil (management of borders and space at the level of individuals, commercial goods, etc.) and time (administrative cycles, etc.). Now, it must restructure itself to integrate the advances and challenges facing our information society. These new focal points are left relatively vacant, only to see the private use that is sometimes made of models and practices of general interest. For example, a company filing a patent for a general business model, a type of technology transfer, a good practice, all elements of the knowledge society that would probably benefit from being infiltrated into the public domain in order to promote the emergence
