Modularity, networks and growth of complexity

Herbert Simon and Albert Ando (Simon and Ando 1961) have developed the concept of near decomposability, which is based on the idea that systems of interactions can be separated into groups (modules) according to the strength of interactions. If there are groups of elements among which interactions are much stronger than among other elements, while they show less strong interactions with other groups of interactions, it is assumed that these intergroup interactions can be neglected.

The obvious danger in this assumption is that interactions between groups are neglectable, which may be correct in the short run or under normal conditions but may also be wrong under longer terms and more unusual conditions, which leads under positive feedback to the crossing of thresholds and phase transitions and then may be observed as increased stress, risk and ‘catastrophes’.

While the system can be applied to the analysis of systems it may, under conditions, also be turned around to the explanation of emergence and system change.

Simon-Ando decomposability implies that microstates may be aggregated into (different) macro-states that describe aggregate system behaviour respectively macro-state variables. This is relevant for the analysis of different views, explanations and approaches to the analysis of an issue such as it occurs in science in general and in social sciences in particular.

Decomposability, i.e. separable modularity of a system correlates with flexibility, adaptability and ease of change of a system such as an organization. Thus, decomposability, innovation and the inverse of risk correlate. Decomposability is related inversely with risk as non-decomposable systems are characterized by systemic interlinkages that are more difficult to account for and manage. Near decomposability (Simon ) involves the assumption that interlinkages among a systems (possibly developing) modules can be neglected for analytical and extrapolation purposes. If non-decomposable systems are taken to be decomposable or decomposed according to non-fitting schemes, risk increases relative to a better match between partial model and its extrapolation. It is a viable assumption that interpretation schemes associated with non-fitting problem decompositions based on erroneous models are at the root of individual organizations threatening business failure as well as the economic crisis currently affecting the world economy.

Is complexity measurement of organizations posible and feasible?

Organizations can be seen as hierarchical systems with business line / unit and departmental ‘modules’ that allow execution of specific functions through specific capabilities concentrated in particular areas. This confers economies through separation of work but also leads to interpretation and filtering problems in non-standard or changing situations - interpretative blindness and inertia are fostered in organizations. Therefore, organizations need to be heterarchical. Particularly in conditions of increased complexity and speed of change we face today. 

Heterarchical structures allow faster and broader interpretation of information, but also demand higher interpretative capabilities by management. Given traditional and often still normal ‘linearly’ organized procedures and structures, these interpretative capabilities determine to a large extent the success of an organization – as Edith Penrose already highlighted.

On the other hand, functional and departmental decomposability, i.e. separable modularity of an organization correlates with flexibility, adaptability and ease of change of an organization.

Does measurement of decomposability (e.g. based on Simon’s near decomposability) allow for a measurement and thus management of organizational complexity? What do you think?

A discussion I have started in the Quantitave Complexity Management Group on Linkedin:

Research Interests: Schumpeter and Strategy

Presently, a rapid pace of technolgical, business and social changes begs the question in how far "creative destruction" by entrepreneurs favors the emeregnce of new companies versus established old and often large scale organizations.
The reason to connect strategy and Schumpeter is that industry development seems to involve a shift from entrepreneurial small companies to large scale bureaucratic ones, that produce innovations in a mechanized, routinized fashion. This shift in technological characteristics and organization size requires a switch between different tools and methods of strategy formulation, planning and implementation if companies go through the transition. Companies that are in different phases on this path or are faced with these different environments need different market entry (or defense) and innovation strategies. Companies that operate under different conditions need different tools and approaches that reflect their needs, obviously.

Entrepreneurs need different strategies than established companies. Likewise they have different sets of resources and capabilities. However both may posses what the other needs such that they could learn from one another.

Schumpeter has described the entrepreneurial type of company in his "Theory of Economic Development", while he the second one is depicted in "Capistalism, Socialism and Democracy". The later description is influenced by observations on industry concentration in the US running up to and large scale research projects during WWII.

In the 1980s, Foster and Kaplan's book on the Attacker's Advantage put small innovative companies back onto the screen, management literature-wise and academically, after increasing limits to growth had been experienced by established large companies in the 1960s and 1970s.

Nowadays, the creative and innovative virtues of young companies are widely acknowledged. There are calls for organizational giants to learn to dance (like these small companies). Successful change and rejuvenation programs such as GE's six sigma initiative have been implemented. However, the question is whether the emergence and importance of small companies, high speeds of technological change and associated fluid organizational forms are there to stay at relatively elevated levels - which also involve cost in terms of social strain and coordination cost. Alternatively, one can ask whether there will be a (relative) shift back to more routinized, bureaucratic, large-scale organization regimes, when todays start-ups grow into large organizations. These then explore the incremental possibilities of radical breakthrough innovations that have been discovered and developed until a certain point in time (which we might already have passed unwittingly). This issue is about the relative importance of radical and incremental, small and large scale organizations and fluid or stable patterns of development, not complete either-or scenarios.

These questions have important practical implications in terms of managing organizations and technologies and for strategy formulation and implementation.

Research Interests: Strategic Change

How to change social systems? Use business organizations as research object.

Relation to strategy formulation implementation and update - Strategy as learning process.

The organizatinal perspective on change of social systems supplies a useful and simple area to study the micro-level of chnage in social systems. Analysis on this levels requires input from perspectives such as individual and social psychology, human behavior such as anthropology, humanethology and as linking field of evolutionary psychology.