Milan Zeleny

THE APPLICATION OF AUTOPOIESIS IN SYSTEMS ANALYSIS: ARE AUTOPOIETIC SYSTEMS ALSO SOCIAL SYSTEMS?

Autopoietic systems are “self-producing” systems. The concepts of the autopoietic nature of a system were developed by Varela et al 8 based upon a living, biological, system. To illustrate the diversity of autopoiesis in its application to systems analysis, three systems (a eukaryotic cell, an osmotic precipitation membrane, and the human family) have been defined and analyzed using the six-point key, criteria, of Varela et al. Conclusions have been drawn as to the autopoietic nature of each system. Varela et al.s criteria as they have been applied to a biological (living) system can be applied to other systems (e.g.. chemical, spontaneous social) that are not currently considered as “living” and this may have a profound effect on the way “living organization” is defined and/or viewed. The very question of autopoiesis in spontaneous social systems is irrelevant. Not only are spontaneous social systems autopoietic but a stronger relation exists where “All autopoietic, and therefore all biological (living)...

Optimal system design with multiple criteria: De Novo programming approach

Abstract Modern production is increasingly characterized by no-waste, no-buffer, just-in-time operations, full utilization of scarce resources, multiple objectives (quality, worker satisfaction, profits, etc.), and continuous flexibility of design and redesign of systems. De Novo programming is intended to pursue these new requirements explicitly. Using practical examples, the difference is demonstrated between “optimizing a given system” and “designing an optimal system”. New concepts of optimality, new ways of resolving Multiple-Criteria Decision-Making (MCDM) conflicts, and new conditions for optimal and continuous system improvement, are called for and proposed.

Optimizing given systems vs. designing optimal systems : the de novo programming approach

The purpose of “system optimization” cannot be just to improve the performance of a given, pre-configured system (search for efficiency) but rather to find the best system configuration, itself, i.e., design an optimal system (search for effectiveness). System boundaries, especially in socio-economic and engineering systems, are not conveniently given and fixed a priori, but are themselves to be determined in an optimal way. We present theory and methodology of optimal system design (or configuration), as it is embodied in de novo programming. The message is clear and simple: optimizing “badly” configured system is ineffective and wasteful while optimally designed systems hardly need any further “optimization”.

SPONTANEOUS SOCIAL ORDERS

Abstract As the results of man-engineered experiments with social design, social “revolution”, socialist “architectures”, and other feats of “social engineering”, are crumbling down, they are causing large-scale human suffering through their failures. There is a renewed awareness that self-organizing and spontaneous properties of complex social systems are much too powerful (and much too vulnerable at the same lime) to respond or be exposed to the endless, reductionistic “tinkering” of policy “makers”, “scientists” of the artificial, and “engineers of human souls”.‡ The mankind is again ready to learn how to “trigger”, “catalyze”, “sustain” and “lead-manage” a spontaneous process of social self-organization; it is becoming less inclined to design another “central super-controller”, “information-processing command system”, or “World Brain”. The purpose of this paper is to show: (1) that theories dealing with “spontaneous social orders” have deep historical roots and (2) that systems sciences are in a good ...

Gestalt system of holistic graphics: new management support view of MCDM

We present a holistic system of unaggregated multidimensional “profiles”, avoiding the information-destroying reduction of multicriterion dimensionality to a single “number”. Visualization of system information is proposed, transforming numerical data into graphical images. This respects and enhances human ability (and preference) to reason directly on the basis of a graphical Gestalt.

An essay into a philosophy of MCDM: a way of thinking or another algorithm?

We have become accustomed to viewing MCDM as another OR/MS algorithm, characterized by a mere shift from k = 1 to k = n with respect to number k of objective functions or criteria. MCDM research and applications has therefore neglected the search for organizational embedding of MCDM: what types of organizations and under what conditions have the propensity to operate under multiple and which under single criteria? Organizations which derive their structure, strategy and motivation from the singleness of purpose will not and can not be conducive to the notions of multiple critera, no matter how skillfully or forcefully presented, or mathematically complete and computationally user-friendly. The organization, its structure and motivational culture have to change first. In short, traditional hierarchy of command, based on extreme specialization and little autonomy of employees and their departments will not be as open to the multiplicity of criteria as the self-managing teams of non-hierarchical companies which integrate task, labor and knowledge and which are only now starting to dominate certain business and management cultures.

Knowledge-information autopoietic cycle: towards the wisdom systems

Decision-making processes are characterised by purposeful coordination of interrelated activities of pre-decision, decision and post-decision stages. In this sense, human decision-making processes require explicit knowledge generation, enhancement and renewal. So far the areas of decision-making have remained mostly free of knowledge and knowledge management, process orientation and autopoiesis and self-producing cycles in general. Yet, in this paper we move further ahead. The transition from information to knowledge is still going on and much remains to be accomplished, but the next transition - from knowledge to wisdom - is already taking shape. We formulate clear, unambiguous and pragmatic definitions and distinctions of knowledge and information, establish simple and natural measures of the value of knowledge and describe the knowledge-Information autopoietic cycle A-C-I-S and its circulatory nature in managing knowledge of the enterprise. Then we elaborate on the future evolution of knowledge management by discussing the outlines of wisdom, wisdom systems and the contours of the Wise Enterprise.

The evolution of optimality: de novo programming

Evolutionary algorithms have been quite effective in dealing with single-objective “optimization” while the area of Evolutionary Multiobjective Optimization (EMOO) has extended its efficiency to Multiple Criteria Decision Making (MCDM) as well. The number of technical publications in EMOO is impressive and indicative of a rather explosive growth in recent years. It is fair to say however that most of the progress has been in applying and evolving algorithms and their convergence properties, not in evolving the optimality concept itself, nor in expanding the notions of true optimization. Yet, the conceptual constructs based on evolution and Darwinian selection have probably most to contribute – at least in theory – to the evolution of optimality. They should be least dependent on a priori fixation of anything in problem formulation: constraints, objectives or alternatives. Modern systems and problems are typical for their flexibility, not for their fixation. In this paper we draw attention to the impossibility of optimization when crucial variables are given and present Eight basic concepts of optimality. In the second part of this contribution we choose a more realistic problem of linear programming where constraints are not “given” but flexible and to be optimized and objective functions are multiple: De novo programming.

FROM KNOWLEDGE TO WISDOM: ON BEING INFORMED AND KNOWLEDGEABLE, BECOMING WISE AND ETHICAL

In this paper from the Xiangshang Forum 2006, we propose the Wisdom project, an international network initiative on developing the next generation of management and entrepreneurial systems based on knowledge and wisdom rather than data and information. This is a major challenge especially for China which must aspire to become wise and ethical rather than just efficient or effective. Major topics of the project include knowledge management, wisdom systems, added value measures, entrepreneurial university, and management as a profession. These topics are the key ones for developing sustainable competitive advantage of any globally aspiring economy or enterprise.

Strategy as Action: from Porter to Anti-Porter

In the post-crisis era, new concepts are emerging, while some old and dysfunctional ones are being discarded. Strategy is about making series of decisions that drive corporate action under specific coupling with company’s environment and context. Because decisions are actions, the strategy itself is action, not just a description of action. In the world of traditional strategy, descriptions (information) have replaced action (knowledge), and talk has replaced walk. We start from the premise that strategy is what company does, and what company does is its strategy. One cannot run a company just on descriptions and framed mission statements. The role of customers is crucial: the customer shapes strategy and triggers corporate action. Without respecting the customer, there is no viable strategy. This is why we label the action-based strategic thinking as “Anti-Porter†: consumers do not want tradeoffs and thus truly effective strategy cannot be rooted in Porter’s tradeoffs.