The Wisdom of the Many: How to create Self-Organisation and how to use Collective Intelligence in Companies and in Society From Management to ManagemANT

2016

Chapter 1

From management to ManagemANT©

Surely you use a navigation device or tour planning programs. Then you already rely on the services of ants. Why so? Because the common route planners are programmed with the so-called ant algorithm, which shows you the best way from A to B, just like ants have been doing for more than 100 million years in their search for food. This is so efficient and effective that the biomass of ants on our planet is now larger than that of humans. Incredible, isn't it? One could now erroneously deduce from this that the individual ant is a particularly intelligent living being. But that’s not true. The ant has very limited cognitive abilities and a no less limited memory. The behaviour of ants today can be simulated almost equally by computers and robots, not only out of pure joy of playing, by the way, but also for the purpose of useful application in companies and organizations.

The intelligence of ants is based on a particularly impressive phenomenon, swarm intelligence . This means that the interaction of many individual ants in a community with a high division of labour – as in an ant colony - leads to remarkable achievements that cannot be deduced from the behaviour of the individual ant. This emergence of completely new characteristics in the collective is called emergent group performance. Equally remarkable is the fact that the term swarm intelligence was not first applied by biologists, as many of you might assume, but by engineers as an alternative to self-organisation in their treatise on "cellular robotic systems" (G. Beni & J. Wang, 1989). The robotic systems described by the two scientists are no longer controlled and organised from a central location, but control each other decentralised by communicating with each other. Numerous experiments from the interdisciplinary self-organisation research show impressively how a swarm works (also with the ant laboratories set up by the authors in the context of live experiments for the executive development of acquisition enterprises, non-profit organizations and activity networks). Transferred to the requirements of today's specialists and managers, inspired by the impressive achievements of swarms, some of the essential prerequisites for the generation of self-organisation can also be crystallised from animal and human swarms.

Self-organizing prerequisites

How can we create self-organisation for and in companies and organisations for the benefit of all concerned? Recent research from the most diverse scientific disciplines - biology, computer science, robotics, economics, social psychology, management theory, business administration, logistics and sociology - has brought to light numerous - success-critical - prerequisites, some of which - especially at the beginning of the study of swarm intelligence - are of particular interest.

Motivation: Self-organisation requires an incentive for the individual if the respective participant doesn’t happen to be intrinsically motivated. Participants can be not only employees, but all stakeholders of an organization. Thus, customers, suppliers, service providers, partners or subcontractors are to be counted among the stakeholders. As we know from our own professional experience, not all participants are endued with intrinsic motivation, and therefore extrinsic incentives are often needed, which need not only consist of monetary compensations. In practice, therefore, stimuli can arise from a wide variety of network advantages for the individual.

Independence: It is reflected in the opinions, considerations, assessments, judgements or decisions of those involved. Independence can be better described and understood by minimizing dependence on the opinions and decisions of others. Of course, we know how difficult it is that, for example, employees of a company can be independent of the behaviour of others. Therefore, if one wants to generate collective added value, it is precisely those rules that must be created that guarantee this to a large extent. Among other things, independence can also be expressed through non-conformism of the respective employee. On the other hand, excessive conformism of group and team members represents a real obstacle to the emergence of collective added value and thus to the success of swarm intelligence, knowing how much a minimum of conformism to cohesiveness (group cohesion ) is required. In particular, independence means that group pressure does not lead individuals to renounce their own opinions and judgements in order to live in harmony with the group.

Diversity: It is the diversity of individuals in terms of talents, experiences, knowledge, skills, perspectives, training, but also in many cases due to social background, age and gender. The diversity of the individuals in a system is one of the most important prerequisites for the emergence of collective intelligence, which we use - more or less - synonymously with swarm intelligence or self-organisation in this book. Countless empirical studies from management research confirm the power and wisdom of the diversity of collectives, groups and teams.

Decentralized knowledge: Particular knowledge of (only) those participants or employees that are actually working on site, i.e. that have local knowledge that cannot be stored or located anywhere in companies. The scattered knowledge is typically fragmented knowledge , which in many cases is only implicitly present in the minds of the individuals of an organisation. Implicit knowledge is basically present in the organisations, but the individual participants do not generally know that they have it at all. Implicit knowledge plays an eminent role in the collective performance of a company or a system such as the market economy. Decentralized knowledge is thus scattered local knowledge and often represents implicit partial knowledge of individuals of a larger whole.

Networking of many (communication): The greater the number of individuals, the greater the possibilities and opportunities for generating a powerful swarm result. This effect can be partly explained by the law of large numbers, among other things. The interaction of many is brought about and strengthened by interaction in the broad sense of the term. One of the most important tools for this is communication by means of modern information and communication technologies (ICT), whereby the respective technology does not necessarily have an initialising but only an amplifying effect. The most famous examples of this are certainly the internet and the associated possibilities of internet-based technologies.

No central control: If the processes are controlled centrally, this influences the participants. The initiators are not allowed to jump in again until the results have been evaluated. Swarm intelligence usually relies on heterarchic organization of the group members. Heterarchy stands for an organisational system in which the individual members of the organisation do not have a relationship of superiority or subordination, but are formally on an equal footing with one another. Heterarchy often stands for self-control and self-determination. The decisions are therefore not to be made from above, but bottom-up. The swarm members must act at eye level in their actions, interactions and communication. The swarm is not led hierarchically, but leads itself in the best sense of the word, decentrally and from below, mutually and reciprocally. Network organizations are also often heterarchically controlled.

Mining rights and now what?

The final aggregation of all motivated , independent , diverse , decentralised and communicating individual contributions to a total performance of the swarm is a special challenge in the context of the generation of swarm intelligence, since the respective applications cannot only be evaluated with different summaries. The concentration of many fragmented individual contributions in the form of partial knowledge ranges from sometimes simple averaging to very complex aggregation procedures, such as, in the authors' view, the free play of supply and demand on a free market such as the stock exchange: The market aggregates, as it were, the many individual pieces of information into a market price and communicates them back to the individuals, who in turn change their behaviour. The example of Goldcorp is cited as an example to underline the swarm prerequisites for the generation of swarm intelligent phenomena:

Goldcorp, a Canadian mining company, was facing a problem. Although it had the mining rights for a promising piece of land, it had no idea where to start digging. So, after a long time of searching and thinking Goldcorp put out a prize and made all the geodata about the land in question available online to the specialist community . More than 1000 scientists from all over the world came forward and networked and combined their own information and data with that of Goldcorp . The result: Within a few weeks and without any additional costs, almost 40 previously unknown gold finds were discovered. The challenge of the aggregation of the swarm of scientists for the mine operator shows quite clearly how swarm intelligence can work. The emphasis is on can, because the swarm intelligence does not guarantee one hundred per cent success. Of course, the swarm, in its modern version the crowd , does not always and immediately encounter a true gold mine. Even with the ants that live in colonies, the swarm intelligent performances are not necessarily successful with certainty. Typically, however, they provide good results, as is often the case with heuristics. They are rules of thumb that do not guarantee optimal results, but in many cases produce satisfactory or good results. In this non-fiction book, we want to devote more attention to this particular feature and ask ourselves: What are the prerequisites for us to be able to count on the most promising results possible, and when would we reach a dead end with the collective's achievements? What are the criteria that mark this crossroad? When is it worth trusting in the wisdom of the many and when not?

Crowdsourcing and Open Innovation

To make use of the wisdom of the many has meanwhile spread to renowned enterprises. With crowdsourcing and open innovation, completely new participants are called upon to contribute ideas when one’s own limits are reached through closed innovations . For example, the world-famous Danish toy brick company Lego operates its own ideas page, where anyone can contribute new ideas that are ultimately evaluated and selected by the community. And if your idea is one of the best, then you will also get a share of the successes. Thus, Lego offers ideal self-organising prerequisites. As many people as possible, with different ideas, with very different know-how backgrounds and knowledge are motivated (turnover share) to participate in the big idea search and idea generation. Finally, the entire knowledge of the many is aggregated and evaluated. And the results are new Lego products.

But what does crowdsourcing actually mean? What is behind it and are there tangible examples? Crowdsourcing means countless people from the global village working together on something via the internet: Wikipedia , Google Docs , company-Wikis & Co. are prime examples of successful crowdsourcing projects and, as already mentioned, they build their success on self-organising prerequisites. Crowdsourcing therefore means working globally and cross-linked. But what are the most important reasons why innovative companies like Lego trust the swarm performance of their customers?

For almost 100 years, Lego has been one of the world's best known and most successful toy manufacturers. Why should the company let customers interfere with product development? Do such innovative companies not have enough resourceful power within their own staff? We see the essential reasons for Open Innovation and Crowdsourcing , as a specific form of collective intelligence in the creative environment.

Essential reasons for Open Innovation and Crowdsourcing

innovative products and services,

high acceptance as a result of the participation factor,

viral distribution in social networks that increase brand awareness and brand value,

cost-effective solution of creative problems,

positive feedback on the further innovative strength of the company

ManagemANT - All are needed

Of course, the mentioned self-organising prerequisites , which are often based on the personal characteristics of the individuals of the swarm, are only a limited selection to explain the emergence of swarm intelligence. For the time being, however, in order to approach the phenomenon of collective intelligence - often used by respective researchers and scientists as a synonym for swarm intelligence - a sensible - didactic - self-limitation is needed. At this stage it can be anticipated that the term ManagemANT© created by the authors means the systematic generation of the mentioned prerequisites for the profitable use of self-organisation by specialists and executives in companies, organisations and supply networks. ManagemANT not only stands for ant management, but is also representative of all forms of generating and using the services of collectives by specialists and managers.

The authors of ManagemANT see the creation of the necessary conditions as one of the essential future challenges for management and leadership. If the potential of the collective is to be raised, then the aforementioned - personnel - prerequisites must be systematically facilitated and specifically generated. This gives employee leadership a meaningful realignment. Organisational and personnel development are required to support employees, for example in their independence and sometimes also in their non-conformism, not out of humanism or selfless charity, but for the purpose of raising collective potential. Before the application and profitable use of the services of swarms, there comes the planned creation of success-critical framework conditions . These not only consist of personnel requirements, but also include complex phenomena such as corporate culture . This cannot - as we will see - be generated on command, but is often already the cause and result of processes that we cannot adapt and influence directly - like a craftsman does his workpiece (F. von Hayek, 1945).

This therefore is the first step of the new management, the ManagemANT. As will become apparent in the course of this book, this realignment of tasks for managers contains an enormous amount of explosive material for the current self-image of management and leadership. The term specialist is also given a relevant reorientation: in ManagemANT, all are needed. Everyone can, for example, contribute much more through his or her fragmented , implicit and local on-site knowledge than is ever recognised and used by conventional management. This means that all parties involved in a company or a supply network , not only employees, but in many cases customers, suppliers, subcontractors, service providers and other partners, are required. In the context of our own professional field - business consulting - we know, of course, that there sometimes exists a seemingly insurmountable gap between theory and practice. We also know that the path to the targeted use of successes and achievements in practice is a long one. But: The way there is not only worthwhile, it can constitute the question of to be or not to be for companies and their stakeholders.

But what about the fields of application of self-organisation in the broad field of management and leadership of organizations? In practice, these organisations and their systems appear as economically and legally independent enterprises, non-profit organisations or, increasingly, forms of cooperation in the form of supply chains . Where are promising and profitable areas of application for specialists and managers? Where are the beneficial advantages to be reckoned with that go beyond the tightly defined business objectives such as efficiency and effectiveness and what if management relies on ManagemANT? Will the managers become superfluous at some point, or even soon? Are today's managers - as the saying is - sawing at their own branch on which they sit? This non-fiction book is intended to clarify this.

Of oxen and swarms of people

A classic piece of literature of swarm intelligence that has lit the worldwide preoccupation of diversified groups with the phenomenon of the swarm is the 2004 world bestseller The Wisdom of Crowds, published by the American economic journalist James Surowiecki. From our point of view, however, the meaningful subtitle " Why the Many Are Smarter Than the Few and How Collective Wisdom Shapes Business, Economies, Societies and Nations", triggers an expectation that is not as easily and not as unrestrictedly feasible within and by groups. The phenomenon of swarm intelligence is more complex not only from a scientific point of view. Particularly concerning the implementation into operational practice, diverse and sometimes untoward details have to be taken into account in order to generate collective added value. Nevertheless, The Wisdom of Crowds is certainly inspiring and motivating for the reader. In the book, Surowiecki describes, among other things, the practical problem of estimating the weight of a disembowelled ox as accurately as possible by about 900 visitors to a livestock market, who consisted of a wide variety of people; and for the person with the best estimate, a small prize was waiting as a motivation for serious participation. So, apart from many possible experts like butchers, farmers, cattle breeders, also numerous real laymen like you and me. It turned out that the collective on average (arithmetic mean of all individual estimates) came to an estimate that almost accurately reflected the weight of the dismembered ox and that despite the numerous individual estimates deviating almost bizarrely from the actual value. The best single estimate was even worse than the average (aggregated) estimate of all participants.

And the surprising thing about it is that everyone contributes to a result that is, on average, better than most individual estimates due to their independence and diversity of individual estimates as well as their particular decentralised