Organized Complexity in Business

From being treated marginally in the mainstream theories, concepts and models of management and organization theory complexity now is acknowledged as a core characteristic of business, not to be simplified but to be understood and exploited. This introduction explains that and why in the present economy various types of complexity are deliberately used by CEOs to grow their business profitable, as digital technology both creates complexity and offers opportunities to exploit complexity. Complexity-based tools are applied in addition to the traditional reductionist concepts and methods. The acknowledgment of the roles of complexity does not necessarily obsolete conventional concepts in management but lays bare their boundaries of applicability. This book provides therefore both an introduction on administrative tools to deal with complexity and a meta-view on conventional management methods, not to replace these blindly but to make clear their boundaries and where these still can be useful. Successful CEOs have always intuited these boundaries, but now a language develops that this intuition can be turned into education, research, rationality, and communication. The objective of this book is to provide insights into how to deal with the various types and levels of complexity, not in a apodictic of narrative way, but in a cognitive-analytical way, turning intuitions into effective administrative instruments.

A first step in understanding complexity is to acknowledge that different types and levels of complexity exist, each of which is to be dealt with in a specific way. The main categories of complexity are objective complexity and subjective complexity. In objective complexity, the non-linear, non-Newtonian causal density of social and economic reality is accepted, whereas conventional management and organization concepts assume dominantly linear causality. Subjective complexity results from observing and trying to deal with non-linear complex systems through the lens of concepts and models based on linear causality. This is so at the individual level, but it also results in institutional-induced complexity. Much experienced, subjective complexity results from a too-narrow and too-shallow cognitive base. One of the steps in order to be in control in a dynamic complex environment is to broaden and to deepen the individual and collective cognitive bases. Post-modern complexity helps us to connect the obsolete dualism of the management and organization concepts dating from the modern era to those of the contemporary era in which diversity is key. Complexity not only is a real phenomenon, it is also a stance to understand and reevaluate familiar concepts and models by making assumptions visible, that their codification is outside the field of business administration, making visible the limitations of the normative paradigms of neo-classical economic theory, and help to understand the provenance of concepts to avoid the emptiness of sign-type communication.

The principle of Ockham’s Razor underlying scientific explanation and thus conventional MBA concepts is no longer tenable in business. But the human need for simplicity cannot and should not be denied. In dealing with complexity a constant awareness is needed, at the individual level, group level and institutional level, for a constant and strong need for simplicity. As different types of complexity exist, so can different types of simplicity be discerned. The most responsible type of simplicity is that which is achieved through an intellectual effort of understanding the new complexity of a situation, acknowledging that the new complexity cannot be understood through conventional theories. A more short-cut but unreliable simplicity is achieved through the myopia of learning. The simplicity of the era of modernism was achieved through institutional reductionism, especially denying or suppressing the marginal in society. The post-modern movement has broken this up, but also for other reasons the effectiveness of institutions is reduced. In that context, the simplicity of MBA methods was achieved through reductionism, of which the limits no longer can be denied. A specific type of simplicity in business is the phenomenon of dominant logic. For reasons of focus a dominant logic is needed, but relying too heavily on a successfully dominant logic, especially in a changing complex organization will derail the organization. This demonstrates a more general principle that simplicity is not absolute, but is bound to time and situation, simplicity always is needed and always is to be distrusted.

In the multiplicity of definitions of complexity, this chapter elaborates on different types of complexity. The system definition of complexity focuses on how complex systems work, whereas the cybernetic definition of complexity explains how in complex systems goals are achieved, including survival in changing circumstances. Various types of non-linear causalities are introduced. The latter provides a link with concepts used in management and organization, especially the issue of in-control. Because control is programmed at multiple levels in society and organization, the concept of culture is opened up beyond its usual simulacra. Beniger’s four levels of control are related to complexity via the complexity of feedback. This chapter introduces concepts like dynamic objectivity, Kolmogorov complexity, detail complexity, subjective complexity, epistemic complexity, and generative complexity. This unearths some limitations to Ashby’s Law of requisite Variety. In addition to different definitions of complexity, this chapter presents a taxonomy of different types of complexity. Each of these types of complexity requires a different handling in order to cope with it, varying from mathematical modeling, to operational procedures, to reduction of complexity through growth of knowledge. Especially the difference between organized complexity, as to be used in business, and disorganized complexity is explained. This chapter lays a basis for dealing effectively with the various types of complexity. The idea of ICAS is consistent with the concept of the organic organization dating back to the sixties of the twentieth century. Now a better understanding, evaluation of that concepts is possible, as well as a better instrumentation. With that, the distinction between disorganized complexity and organized complexity is introduced. The growing complexity in the economy implies a shift from traditional, physical asset-based administrative instruments to information-based administrative instruments. With that, it becomes clear what Drucker’s concept of information-based organization is in administrative terms.

Growth of complexity and economic growth, especially the growth of productivity, is inseparable and interconnected. Not only is specialization a form of complexity, especially the information space of our society and thus of our economy, is becoming more complex. Workers (labor relations) and consumers become more complex as do some products and services. So are markets and industries. Traditional managerial responses to complexity, especially increased bureaucracy, fall short to deal with the new complexity, as do romantic concepts of complexity. The concept of intelligent complex adaptive system (Bennett & Bennett) is introduced in this chapter. Its original descriptive presentation is commented and is linked to a number of concrete administrative instruments, to overcome the intuitive nature of its original description. Traditionally the problem of complexity, as induced by limitations in education and communication, was curbed by a number of institutions, including typical trade and business institutions. The successful management books of the twentieth century used to be not only based on economic thinking, but especially in making people to act, based on the art of making things seem true, not on understanding new complexities. This worked well in the era of institutional simplification. The friction between the economic need for a higher complexity and the suppressing of complexity by institutions, as laws, regulations, conventions, and conventional business concepts, was answered by the liberalization of markets and a reduced role of the state. The knowledge base, individual, collectively and especially institutional, does not keep up with the increase of complexity, resulting in a number of disasters, failures and immoral behavior. In society, this was responded to with risk management and re-regulation. The perception of a risk society nestled itself in society. But as concepts and tools of risk management often are based on concepts dating back to the modern era, their underlying assumptions don’t fit the present time, and risk management paradoxically has become a source of risk itself in a complex society. This chapter presents a conceptual model for economic complexity, demonstrating that re-regulation is no answer to complexity, neither are the popular narratives in management books, nor the flight into culture to “explain” everything, because what is needed is a new administrative technicality.

Complexity cannot be dealt with without a proper organization of information. Information reduces entropy while maintaining the state of complexity. This organization of information requires a good understanding of what information is, respectively, a theory of information. The mathematical definition of information, based on Shannon’s mathematical theory of communication is too simple to deal with the various types of complexity. This chapter presents a more differentiated model of information elaborating on the concept of control as defined in cybernetics. Various types of information are introduced like discursive information, goal-information, axiological information, material information, eidetic information, allelopathic information, effect information, pragmatic information, and reproductive information. With that, a model of types of information is presented which undergirds the concept of the information-based organization. This model is also a meta-model through which well-known but somewhat intuitive management concepts now can be logically interlinked, replacing the Weberian bureaucratic hierarchy with a hierarchy of types of information, with goal information at the top and reproductive information at the bottom. This also lays the foundations for a model of governance and administrative information space beyond conventional management information. Also, the relation between data and information becomes clear in operational, programmable ways, as relevant for AI and machine learning. This differentiated model of governance and administrative information explains why in the contemporary economy the organization of information precedes the structure, in the Weberian sense, of an organization design.

The conventional tactics to solve complex decisions by reductionism falls short to deal with the new complexities. Successful CEOs use abstract thinking and reconceptualizing to make effective decisions in new complex situations. The conventional paradigmatic model of decision-making applies to well-structured problems, which are to be found in operations, but not at the level of strategy and governance. A decision-problem that can be solved through a calculation or algorithm, as pretended in AI, is not a decision-problem, but a calculation. More data in itself does not solve complex decisions nor does it result in better decisions, except within the limitations of a well-structured problem, what are rare. A decision-problem is a state-of-mind acknowledging that existing routines, practices, heuristics, and concepts are incapable to provide the insight needed for new situations and reconceptualization is needed. What is needed is integrative complexity to open up the limitations of cognitive complexity (Sect. 6.​3.​3) This chapter presents a taxonomy of complex decision-problems, like professional induced complex decision-problems, reflexivity complex decisions, decision-rights complexity, epistemological complex decisions, discovery/justification complex decisions, and how to handle these for different executive tasks, based on the extended international doctrine for administration.

Contrary to what is assumed in the romantic concept of complexity, complexity does not substitute for coordination. This chapter describes the different coordination mechanisms appropriate for the different levels of complexity. To achieve this first it is explained what coordination actually is and is to achieve. Despite being a core function of the firm, even explaining its existence vis-à-vis the market, no elaborated theory of coordination exists. A definition of coordination based on economic organization theory is presented in this chapter. The multiplicity of coordination mechanisms is arranged on two axes: imposed coordination versus self- (or horizontal) coordination, and implicit versus explicit coordination. The structure school of coordination used to be dominant in business administration but due to the declining costs of information the process school now is dominant. More in general, the decline of costs of information and the higher need for horizontal coordination implies a shift from the logic of structure to the logic of flow. As a consequence, in the manufacturing of complex products like airplanes the Bill of Material is the coordination mechanisms, creating a virtual organization over the conventional structure of suppliers and assembler. Second is introduced a taxonomy of levels of complexity. The highest level of complexity often is seen as the level of stigmergic coordination, as e.g. in the domain of social production. Stigmergic coordination is seen by many the form of self-coordination teams in business. However, the assumed free interaction between individuals as mode of coordination and innovation requires specific rules, a well-defined context, tolerance for narrative practices, as set out in the Interactive Theory.

Explicit empirical research on how businesses deal with complexity is still thin. But using the lens of complexity a number of observations can be made. This chapter presents three such cases. IBM masters the complexity of its business (and with that the dynamics of its industry) by organizing all its information in one database, disembedded from the structure of its organization, in which all its external and internal transactions are recorded with multiple attributes creating a multidimensional organization. Ashby’s Law of Requisite Variety cannot be achieved in organizations through Weberian structure, only through information. Procter & Gamble in 2000 responded to pressure by the capital market to centralize its organization and to reduce its product range, instead by designing and implementing an information system, maintaining the required decentralization while solving the problems of decentralization and maintaining the variety in its in products while solving the problems of a large variety in products as induced by conventional organization methods. The Academic Medical Center (hospital) solved the complexity of gastrointestinal oncology patients, not by restructuring its organization, but by adding a fast track across the medical departments involved, thus creating more complex expertise around the patient, improving its diagnostics and treatment, while maintaining the required specialized medical departments; simple for the patient but more complex for the executive board and its staff departments. The question is not how to get rid of complexity, but what is the most efficient place for complexity in the organization.

Abstract thinking is core in and the first instrument for dealing with complexity. What matters is what type of abstract thinking is applied. Authentic abstract thinking is about the willingness to see and acknowledge new possibilities, to see new connections, and to question assumptions. Authenticity here is used in the existentialist way, which is about the willingness, the courage to see new opportunities and to make choices. This authentic abstract thinking is opposed to the abstract thinking used in artificial intelligence and machine learning. Mathematical abstract thinking, especially in economics and business, is reductionism, identifying a dominant causal relation, identifying how act to be successful. Authentic abstract thinking if different from out-of-the box thinking, it is an intellectual activity, although with CEOs it often has more the nature of slow intuition as explicit analytics. Because authentic abstract thinking is about questioning assumptions held by others and thus questioning the status quo, the tendency to do so also depends on the personality of the CEO and his social context. The art of abstract thinking is to move an organization from its conceptual past into its conceptual future (§ 11.4). Related to personality is that those CEO dealing successfully with complexity have developed themselves a high load of cognitive complexity on which is based a high capability of integrative thinking. They master multiple, often conflicting concepts and models and are able to switch perspectives and viewpoints. Authors like O’Toole and Martin deserve more appreciation when they explain that successful CEOs “look for simplicity beyond complexity” and “wade into complexity.” Martin’s description of CEOs dealing successfully with complexity as mastering the art (but it is as related to personality) of integrative thinking is consistent with research dating back to the sixties on characteristics in thinking of political leaders. This denies the main stream popular management books that emphasize simplicity. They need to do so in an institutional environment that is hostile to questioning the waning assumptions underlying those institutions, but seeing the new opportunities created by the declining costs of information.

Complexity leadership as coined by Uhl-Bien & Marion takes issue with the conventional concepts of leadership, especially the popular transactional leadership. Building on the concept of complexity of Herbert Simon, dating back to the sixties, complexity leadership is about creating conditions in the organization in order that members of the organization themselves can observe unexpected and deep changes in the environment and initiate a response to it to maintain the accomplishment of the mission of the organization, while maintaining its integrity.

At least 19 administrative instruments or tools used by executives can be identified, some existing for quite some time, some more recent, that are used by executives in different combinations and weights to master complexity and the accompanying uncertainty. Except for multidimensional information and the platform concept to support workers, none of these is really new, but well proven. In the conventional trade books these tools often are presented separately, as success factors in themselves, from the perspective of organized complexity these 16 tools constitute a coherent body of administrative and organization tools for the contemporary economy. Now these tools, which often were promoted separately in focused trade books, can be understood and applied in their interrelatedness, offering a more effective administration of organizations. These 19 tools also offer a proven toolbox to deal with uncertainties and risks in business, these are offensive tools as opposed to the defensive tools of risk management. One of the tools, fast feedback information, today emphasized by cheap sensors, and fast and cheap communications, and especially because of its use in AI and machine learning, turns out to be of limited value to deal with complexity, if not creating risks. Different types of feedback loops are identified, performance feedback, extrinsic feedback, autonomous feedback (from, e.g., social media), cognitive feedback, intellectual feedback, emotional feedback. Especially the types of social feedback loops very much complicate the free interaction between workers, to an extent that the social dominates the material hampering innovation. Through the social domain with its autonomous feedback, feedback also turns into a resource for the firm.

Complexity is not a design parameter in organization design nor is it an administrative instrument in itself. In situations with new complexities, in which the causal patterns are unknown and are difficult to know by induction, the design thinking as defined by Dorst applies. The unknown is addressed through open abduction design thinking in which it is acknowledged that neither the what nor the how is known to achieve value for the user. In line with the authentic abstract thinking and reconceptualization to master complexity, in this abductive thinking reframing, seeing options detached from experience, conventions, and other routines is the way to go forward. In practical terms organization design to achieve a defined customer value proposition now follows the rule “process follows proposition” which replaces the old Chandlerian rule “structure follows strategy,” consistent with the shift from logic of structure to logic of flow. The design of such a complex process may be bottom-up, following the Logik der Sache. But especially in complex products the complexity in design is to be mastered through architecture and modularity. The conventional organization structures often remain in place, but by function change into an infrastructure (platform) supporting the processes. The resulting matrix-type organization is not a problem as its working is ensured by a redesign of the resource allocation process following Herbert Simon’s theorem of simplicity: “in the simplicity of process we maintain the complexity of state.” This solves the limitations of the Bowerian bottom-up resource allocation process and explains the new concepts of management control. In addition of the upward causality defined by the Logik der Sache, in organization design the downward causality of corporate governance needs to be addressed as well, including the regulatory/institutional requirements imposed on a business. These conflicting logics are to be solved by a proper definition and organization of information. Along these lines the concept of the information-based organization, in which the salient role of intangible assets is acknowledged.

At first sight the increasing complexity of organizations suggest that management of change will be correspondingly more complex. Seen through the conventional lenses of management of change the modern organizations being more complex are more complicated to change in perception. The butterfly effect in chaos theory suggests that small interventions may result in large changes in the system. This effect does not satisfy the idea of planned change and complex organization is still about achieving set objectives. The increasing dynamic complexity of the economy implies that the episodic management of change, in which an adaption is followed by a period of equilibrium, now is obsolete. The increasing complexity with its higher causal density in organization implies two transformations of the conventional management of change. The first is that not only the capability for continuous adaptation, following the cybernetic concept of control, is integrated in the design of the organization, but that continuous (proactive) adaptation is one of its processes. The second transformation is that the conventional management of change is being replaced by systemic change. In systemic change the executives identify the few (new) critical system parameters of the organization, to be changed in order to facilitate the members of the organization to work in new ways. No large-scale intervention is needed. This follows the old Interactive Perspective Model from organizational behavior, that the context is more influential in defining behavior as are personal attributes. But now the context is more complex as in the past.

Complexity is not simple, but to live the life we want, we cannot without some degree of complexity. The most elegant way to deal with complexity, to reduce its complicatedness without forfeiting the benefits of complexity, is to have a proper education, knowledge, a fitting style of thinking, which is a sufficient complex cognitive structure. This can be accomplished at an individual level, but is more difficult in a social setting with vested interests, sound bite type media, and pressure for immediate results, in which one needs some benign aggression to create time for thinking and in which communicating new insights is hampered by a sign type use of language. Understandably the narcissistic persons will be the best to deal with the increasing complexity. They do so by having a vision to change the world and to create meaning. Productive narcissists are independent thinkers, are willing to take risks, in a way simplify their world by not listening to other people, although they can be oversensitive to criticism. Narcissistic leaders only can be successful as far their ideas fit in the Zeitgeist, like Bill Gates and Steve Jobs. But the world has more types of personality who also are entitled to some ontological security in life through understanding instead of a continuous struggle of reflexes. We therefore need to educate each other, in the workplace and in institutions of educations. A challenge will be to produce management books that do not have the reductionist simplification and neither the escapism of romantic complexity.