From bureaucracy to intelligent administration

 

Eva Bolfíková

 

UPJŠ in Košice, Faculty of Public Administration

Department of Social Sciences

E-mail: eva.bolfikova@upjs.sk

 

 

 

 

Abstract

 

     The paper is presenting some of the Weber's rational model of the bureaucracy functioning consequencies as a object of the critical analyses. It showes the possible way to the construction of the administration  alternative model, with respect to the chaos and complexity paradigm main attributes. The complex adaptive systems are explained as a very effective platform of the administration character change. The possibilities of the complexity' knowledge in the systems are discussed.

 

 

Introduction

 

     Discussions regarding the future of public administration lead by the effort to reach improving of its effectiveness can be followed in several study lines and analyses, altogether the tools (methodological as well as merits) enable to recognize two readable ways.

 

     One way uses classic scientific paradigm sources and is oriented towards the study of partial administrative attributes which despite slight movements (towards reduction of dysfunctional mechanisms) remains bureaucracy . Sources of criticism and basis for improvement of bureaucracy functioning are sought in essence of ideal model of M. Weber.

 

     Second way leads through change of the key paradigm, change of the essence of the thinking in relation to administrative systems when the basis is the understanding of administrative systems as complex adaptive systems which basic attributes emerges in relation to the essence of bureaucracy as an alternative.

 

     Findings to which lead the second way including solution of the question if it is actually possible to apply instruments of complex adaptive systems to administrative systems are in many contexts supported by knowledge within the first presented way (unintended conclusions of intended behaviour (Selznick), ritualism of bureaucracy (Merton), bureaucracy phenomenon, blocked society, zone of uncertainty (Crozier), contingent models (Lawrence, Lorche) ...).

 

 

 

1. Certainties and uncertainties of bureaucracy

 

                                                                   'When those subject to bureaucratic control seek to escape the influence of the existing bureaucratic apparatus, this is normally possible only by creating an organization of their own which is equally subject to the process of bureaucratization.

                                                                                                           M. Weber  (1968, s.224)

 

 

     Work of M. Weber on the bureaucracy model as an ideal type of behaviour was focused on intensive rationalization trend by which was characterized social life in the private as well as public sphere. According to M. Weber the bureaucratic coordination of human activities is an immanent sign (mark) of modern social structures (and organizations).

 

     In line of the organized world study in historical “repeat” as well as recently Weber has developed ideal type – bureaucracy – as a part of study and analyses of solution for continually historically lead  phenomenon of differentiation of positions and statuses of individuals and groups in the society. Such picture of the inequity of people statuses intends the need for solution of modification and regulation of mutual relationships with the respect to the current positions in the line of power and authority. Bureaucracy occurs as one of the solutions apprehended and explained as the most effective – through complex rationalization depersonalization (institutionalization), therefore perfect regulation of human nature in the interest of coordination amount of appropriately oriented activities and relationships.

 

     In Weber ideas is bureaucracy most effective way of administration. It is predetermined For this position is predetermined by generally known attributes of democracy which shall this system and its operation “to insure” in the sense of complete rationality of overall happening in organizations, absolute predictability of the development and results of decisions, maximal simplification of way of coordination (hierarchy, abstract rules and generalized algorithms), communication (only formal and preferably written), specialization etc.

 

     Even the first reactions and critics as well as other analyses showed that ideal model of bureaucracy is actually an abstraction which in real conditions can not work and doesn´t work with the assumed effectiveness. They highlight that these tools which are introduced as a guarantee (and certainty) of effectiveness actually produce enormous complexity, decrease organization effectiveness of organisation and means serious uncertainties of bureaucratic administration.

 

 

2. Sources of intelligent administration

 

     Behaviour (not only) of social systems is the subject of study of various scientific disciplines which by using of conventional tools submits their models, conceptions, theories. New models built on the platform of complexity offer behaviour of social systems as unpredictable with the attributes of self-reference and they are supported by the platform of so called new science, chaos theory, theory of complexity, research of complex adaptive systems, non-linear dynamics, theory of dynamic systems and synergy.

 

     Application of complexity theory in the study of human (social) systems is showed in two clearly separated categories. First is metaphoric and descriptive. It derives its language (reference system) from the new science and applies it to explanation of happening in complex human environment. These applications are focused on searching and explanation of examples of self-organization, emergency, butterfly effect and attractors in social systems (M. Wheatley, M. Kellner-Rogers, L. Fitzgerald). Models and metaphors of new science are used to description of social system outputs, not the processes as such. They don´t focus their attention to why and how it gets to emergency of complex models (models). It means that they work with complex system as it was a “black box”.

 

     Second category presents approach characterized as mechanical (not mechanistic). Its terms and conceptions derives also form the new science and mathematics of complex systems but its aim is to investigate what happens in social environment, how the complex system generate its surprising behaviour (R. Stacey, J. Goldstein, S. Guastello, K. Dooley.) – “open box”.

 

 

2.1. Essence and sources of complexity

 

     In social and natural sciences was the term “complex” traditionally used as a synonym for “difficult” and “complicated”, in organization science was connected in various ways with the problem of group size and extent of group relationships (Greicunas 1937), unknown causalities (Blau a McKinley 1979), technology (Coffey 1992), etc. After 20 years of much heterogeneous research was the problem of complexity emphasized when some of the researches directly refers to “complexity science” (Gleick 1987). Most of authors have focused on the question of non-linearity, self-organization, ´deterministic chaos. Key role in this development played „The Santa Fe Institute and its team of Nobel prize laureates, above all Waldrop (1992) and Kauffman (1993). In the field of management and organization science are for the transfer and spreading of new science application most important works of Merry(ho) (1995) and Stacey(ho) (1991, 1995, 1996), study of organizations as a communication nets and activity nets (Czarniawska-Joerges 1992, Weick 1995), especially – autonomous (Foerster 1984) and self-referring (Luhman 1984), for administrative systems field mainly D. Kiel (1994).

 

     Biggiero (2002) submitted differentiation of epistemological and traditional meaning of complexity with the use of means which enable to divide various resources of so called observed irreducible complexity (observed irreducible complexity – OIC) into two groups.

 

    First group is formed by sources which are connected with formal (mathematical) and physical theory of complexity, he calls them “bit perspective” because they understand the information only in computer meaning within the formal decisions. In this “simple” perspective can be observed understanding of organization as an automat (net of automats) where can be watched only inputs and outputs of decision and decision is analysed on the basis of quantitative (formal) perspective.

 

     Second group is formed by those OIC resources which are connected with philosophic, cognitive, linguistic and psychological aspects of information. Organization are here viewed as a “sense-maker” respecting emphasis of semiotic perspective of OIC.

 

     Biggiero (2002) differs further complexity sources – qualitative (logic, computed and chaotic) and quantitative (gnoseologic, semiotic and relational) which in application on organization conditions can be perceived in position of understanding sources, study and administration management as wholeness system with real behaviour in concrete internal and external conditions.

 

 

2.2. Administrative system as a complex adaptive system

 

     Complex adaptive systems are characterized by basic attributes which are identical for the natural systems as for the social systems. Their basics for understanding of administrative as a complex adaptive system and highlights the specifics of “new approach” to study and management of organization in application of above mentioned disciplines.

 

1.      Complex adaptive systems are not linear, there is no proportionality between cause and effects. It means that also the small causes can evoke extensive effects. Non-linearity is the rule, linearity is the exception. From this view, complex systems are intuitive and their behaviour surprising. For administrative systems is this rule important from the viewpoint of functionality assessment of all attributes which characterize them as linear system where each cause (rule, action) can resulted only in before generalized effect. Non-linear systems are not effective in maximal possibility of generalization but on the other hand in permissibility of existence of situations and actions as singularities which brings inevitably despite in basic parameters defined essence spectrum of indefinite and unique shapes in the real operation. Complex adaptive systems tell about non-linear character of cause and effect relation, it doesn´t mean that system is in the state of permanent, continual chaos, it just means that the system respects great variability and dynamic of elements and processes in the system and relations between them.

 

In linear systems (bureaucracy) are relations between variables stable. Maximal regulated bureaucracy system “do everything” to maintain stability in any circumstances, instability – even potential – is excluded. Despite this the reality of bureaucracy functioning based on the maximal reduction of complexity brings many deviations and unpredictable causalities.

 

2.      Complex adaptive systems are fractal. All forms which show irregularities are on perception level (perception and observation) highly dependent on character of used measure. In fractal systems doesn´t exist measure which would provide generally truthful answer to the question regarding mode and character of its existence and operation. Every system submits own, very specific fractal structures which helps to make an idea about the character of the system as an unit. If the fractal is a fraction, a part of system which is explicit carrier of system marks as an unit then knowledge of system operation specifics on the one fragment level enables to think about the system operation specifics as an unit. Fractal structures in administrative systems present multidimensional spaces when study of operation (and management) of such spaces supposed in any circumstances possibility of differentiation to “even smaller” parts. In fractal administrative (social) systems are this way asserted indicator sets abstracted on various levels, in various fields of system operation as synoptic marks when each individual mark (indicators) suppose the possibility to act in position of synoptic mark including another individual marks. Fractal structures enable to study and manage the system as unique case different form the others even identical systems on the outside (every bureaucratic system has same attributes), presents study way oriented into the system and enable knowledge and management of system as an unit through knowledge and management of its parts. It means also that knowledge of systems with identical parameters (administrative organizational systems) when these parameters helps to distinguish these systems from other systems is insufficient tool for understanding of mechanisms of operation of each one real system in concrete circumstances – knowledge of uniqueness enables respect of fractal structure of system and its character.

 

3.      Complex adaptive systems show repeated symmetries – they tend to repeat basic structure on several levels. Repeating of basic structure ( for organizational systems – of basic mechanisms) in complex systems is provided just by fractal structure of these systems. It means that if we know basic mechanism of operation of some system part on the fractal level we can expect that this mechanism will be vital also on the other system levels (example from the top to the bottom:. “the rule” that “the fish always stinks from the head downwards” that means if the head stinks, all other parts of the fish stinks too, example from the bottom to the top: if the motivation system on the individuals level in organization is strongly influenced by personally oriented preferences it means that also motivation systems on higher coordination levels will not miss this characteristic and probably mechanism of effective coordination of organizational and individual goals has failed what means that if mechanism of strong individual interests orientation is one of working mechanism of organization systems and if fractal is the carrier of the mark and vice versa organisation is becoming tool for reaching other than organizational goals and de facto lose justification of its own existence, in first stages diagnosed as low organization effectiveness.

 

4.      Complex systems are sensitive to input conditions. These quality of complex systems finds effects in huge dynamic of the system and broad variability of possibilities in the way of its functioning – showed in the form of trajectory as a symbol of through alternatives subsidized freedom in the system development. For study and management is this quality important mainly in the phase of information processing bounded to input conditions when at the moment of information processing process are input conditions (processed information) changed. Decision phase is therefore necessary dependent on involving of intuitive processes and possibility to predict system development escapes usually used rational procedures. Effect of system high sensitivity to input conditions is inability of perfect prediction of future system development. Part of respecting this attribute is using of so called small steps method when soon diagnostic of possible deviations enable flexibly modify accepted decisions according to current development of conditions (or information) with regard to reached goal.

 

5.      Complex systems are saturated feedback loops. System behaviour is output of multi – interactions. When the level of organization raises, complex systems tend to start new way of behaviour which is not possible to describe similarly as previous behaviour. This mark of complex systems is related to previous, when organization growth (organizing – and complexity) introduced serious change on the level of input conditions of study and system management. It shows also that with the growth of system complexity proportionally with the organizing level raises also level of uncertainty which is necessary to “arrange“ (coordinate, limit by rules and stereotypes in decision). The more complicated are the schemes of mutual interactions between system parts the bigger is space for uncertainty and vagueness and less effective are functioning mechanisms appointed for its regulation, mainly if they are concentrated in the form of rational procedures and reached the form of institutionalized widely approved mental models.

 

 

2.3. Knowledge of organizational complexity

 

     Sources of complexity may be in strongly simplified sense searched everywhere where it comes to any form of reduction of human being character (natural sources) in any measure. According to this the environment of formal organization and bureaucratically managed organization is presented as a space characterized by the high level of uncertainty despite the enormous effort to arrange and control it within the frame of regulation. Strong emphasis put on rationality (absolutization of rationalization) implies sources on its providing, subsidized by supposed maximal regulation:

 

-         high level of generalization – abstract rules, stereotypes, algorithms

 

-         maximal formalization of communication and relationships – ignored expressive relations

 

-         highly stable structure (hierarchical) with determined communication direction – without respect to multi-interactive character of organizational environment

 

-         high level of specialization – without ability of flexibility with regard to contexts

 

-         etc.

 

    First sign of complexity in organizations is so called imperfect generalization. Rules are generalized in relation to type of participant behaviour, situation. To confirm existence of the rule it is necessary to generalize (and categorize). Rules are applied “locally” in the context in which appeared the need for their existence, in style which wasn´t specified within the prediction. Impact of the rule can be limited but can not be eliminated. Circumstance have however shape of uniqueness which is not and can not be specified by the rule. Generalization implanted into the rule is necessary selective.

 

     While for bureaucratic (linear) systems are characterized by high level of generalization – existence of abstract rules as generally binding ways of action (in case of violation follows the sanction) without the regard to specifics of the task or situation, complex adaptive systems respect uniqueness of each situation – and possibility of deviation form the rule even they don´t exclude their existence – generalization on some level (but generalization is not perfect). Imperfection of generalization lays in potential or real existence of minimally one situation for which generalized rules doesn´t present functional way of solution (with regard to specifics of situation). If such situation appears in organization it can be considered for complex adaptive system.

     Second sign of organization complexity is so called “silent apology”. The underlining of the sense of rules implementation in organization is reaching of the goal, “fulfilment of apology” for existence and operation of organization (as a space “unnatural” for the human, regulated by formal rules). Example can be the rule: “except the working hours we don´t serve the customers”– the rule is developed because we suppose behaviour of clients – customers, request of people on their comfort and organization goals and we try to regulate applicable situations. This knowledge is causally related to apology of the rule.   

 

     Why is the silent apology requested? Because the environment of formal organizations is for human unnatural, artificially regulated. Only legitimate measure for apology of existence and operation of organization is its goal. Goal excuses everything that happens in organization (including existence of rules of its organization). Important moment arises when is for the apology (of organization operation) necessary to break the rule – in such case the rule as an instrument diverges with the apology. In extreme cases it is possible to break the rule without its normative generalization stops to be valid (clerk serves the client after the business hours – he doesn´t cancel the business hours – he breaks the rule because he wants to help increase the level of trust and satisfaction of clients – and organization effectiveness). Besides “official apology” – for application of rule exists also so called “silent apology” – for breaking the rule or possible deviations. If such case appears in the organization it can be considered for complex adaptive system.

 

     Causality, logic, paradoxes is the third sign of organizational complexity when in organized context of management according to rules leads to paradoxes. Reason often lays in absence of time dimension in system of rules and propositions. Causality of implication “if…then“ includes time but logic version “if...then“ doesn´t include time. For example: statement “if water temperature falls below zero it will freeze” differs from the statement “Euclid sentence is valid if the sum of angles in triangle is 180 degrees”. Paradox arise if the causal statement becomes practical rule, its description in terms of logic becomes contradictive – generates the paradox.

 

     For example:  the agency which wants to provide financial aid for single mothers requests to state the name of the father in application – they want to register irresponsible fathers. If mother states the name of the father she will obtain the financial sum. This amount however will be reduced in the case if the mother won´t state name of the father. Primary goal is to help single mothers but at the same time they reduce its aid if the mother won´t satisfy its request. That is paradox. Moreover, consequences of this rule and its breaking cannot bear the person to which is mainly related – a child. Logic connection: “if mother satisfy the request for the aid – she is single mother (and doesn´t state the name of father), she will not receive the aid (or only reduced)”. In final version shall the logic be like this „if YES than YES“. But if the mother states the name of father it means that she is not absolutely alone (she doesn´t fulfil the main condition) – so she doesn´t have the right even for the reduced aid – but she will obtain it. So in final conclusion statement is: “if No then YES”.

 

 

Conclusion

 

     Aim of the report was to show the possibilities of intelligent administrative building arising from sources, respecting character of complex adaptive systems which offers effective base for alternative study and management of administrative in non-bureaucratic sense. In effort to release from the ghost of bureaucracy - as it is introduced by M. Weber and his critics – as a relevant appears those tools which aims to study and management of administrative in the sense of learning organizations in which application means for the spehere of public administration not only the big challenge but mainly big, by many authors respected chance. Similarly as the bureaucracy cannot be understood as “phenomenon for itself” also the intelligent administrative can arise and function only in the space – social and individual – which is “ready” and “wishful” for release of maximal regulation and rationalization towards bigger tolerance, flexibility, freedom – but also natural (not only formal) responsibility. In such way becomes the problem of intelligent administrative interesting not only for those who are part of it but also for the broad civil public.

 

 

References:

 

  1. Biggiero, L. (2003): Complexity and Organization: Epistemological Aspects and Managerial Consequences. http./www.dis.uniromal.it/pub/EM/biggiero/page.html
  2. Blau, J., McKinley, W. (1979): Ideas, Complexity, and Innovation. Administrative Science Quarterly, 24, pp.200-219
  3. Czarniawska-Joerges, B. (1995): Rhetoric in Modern Organizations. Studies in Cultures, Organizations and Societies, 1, pp.147-152
  4. Foerster von Heinz (1984): Principles of Self-Organization in Socio-Managerial Context. In: Ulrich, H., Probst, G.J.B. (Eds.): Self-Organization and Management of Social Systems. Berlin: Springer
  5. Gleick, J. (1987): Chaos: Making a New Science. New York:Penguin.
  6. Graicunas, V.A. (1937): Relationships in Organization. In: Gulick, Urwick, L.F. (Eds.): Papers on the Science of Administration, New York:IPA
  7. Luhmann, N. (1984): Soziale Systeme. Frankfurt am Main: Suhrkamp Verlag
  8. Kiel, L.D. (1992): The NonlinearParadigm: Advancing Paradigmatic Progress in the Policy Science. System Research, 9 (2), pp.27-42
  9. Kiel, L.D. (1993): Nonlinear Dynamical Analysis: Assessing Systems Concepts in a Government Agency. Public Administration review. March/April, 53, pp.143-153
  10. Kiel, L.D. (1994): Managing Chaos and Complexity in Government. A New Paradigm for Managing Change, Innovation and Organizational Renewal. Jossey_Bass: San Francisco
  11. Merry, U. (1995): Coping with Uncertainty. Westport, CT: Praeger
  12. Stacey, R.D. (1991). The Chaos Frontier. Oxford: Butterworth-Heinemann
  13. Stacey, R.D. (1995): The Science of Complexity: An Alternative Perspective for Strategic Change Processes. Strategic Management Journal, 16, pp.477-495
  14. Stacey, R.D. (1996): Complexity and Cretivity in Organizations. San Francisco: Berrett-Koehler Pub
  15. Waldrop, M.M. (1992): Complexity. The Emerging Science at the Edge of Order and Chaos. New York:Simon and Schuster
  16. Weick, K.E. (1995): Sensemaking in Organizations. Beverly Hills, Ca: Sage