Self-organization in social systems
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[edit] Introduction
Our group’s interest for the one-week intensive complex systems course is in self-organization of social systems. We know many self-organization definitions exist across various disciplines from earlier in this course, Ilya Prigogine, Wikipedia, etc. Our focus, however, is on 5 case studies illustrating what we view as self-organizing social systems
[edit] Definition of Self-Organizion and Main Concepts
Our working definition:
Self-organization is a process where order emerges without external control based on local interactions of constituent components.
Other definitions:
A self-organizing system not only regulates or adapts its behavior, it creates and evolves its own structure. Structure means the components of a system are arranged in a particular order requiring both connections, that integrate the parts to the whole, and separations that differentiate subsystems to avoid interference.
The ability of systems to construct or change its own behavior or internal organization.
Self-organization represents the spontaneous emergence of order in natural and physical systems (Kauffman 1993)
[edit] Case Studies
[edit] US Department of Defense Community of Interest Data Strategy
Across the Department of Defense (DoD), broad leadership goals are transforming the way information is managed to accelerate decision-making, improve joint warfighting, and create intelligence advantages.
The DoD Net-Centric Data Strategy (NCDS) document outlines the vision for managing data in a net-centric environment. Net-centricity compels a shift to a "many-to-many" exchange of data, enabling many users and applications to leverage the same data-extending beyond the previous focus on standardized, predefined, point-to-point interfaces. Hence, the net-centric data objectives are to ensure that all data are visible, available, and usable-when needed and where needed-to accelerate decision cycles.
As a key enabler to achieving the data goals outlined in the DoD NCDS, an inclusive term of “Communities of Interests (COIs)” was defined as “a collaborative group of users who must exchange information in pursuit of their shared goals, interests, missions, or business processes, and who therefore must have shared vocabulary for the information they exchange”.
A COI Roadmap document is an evolving document and is intended to be used as a general guidance to assist COIs in understanding their key attributes, roles and responsibilities. Also, it defines the cross and hierarchical functional relationships amongst the new organizational constructs. These relationships are critical to the successful implementation of COIs. The document articulates the business rules associated with the processes for the selection, development and implementation of COIs. Specifically, the document identifies processes for the establishment of COIs through the posting of the products to the registries and catalogs. Furthermore, the Army is in the process of evaluating tools and services that can be utilized enterprise wide to support the COIs in their mission to share and exchange information in a Net-Centric environment. This document lays out the relationship to portfolio management as it relates to COIs.
The COI roadmap document is a component of the overall Army Net-Centric Data Strategy (ANCDS) roadmap document, which is currently in Draft. The ANCDS roadmap will address, in further detail, the required data assets for information sharing and exchange in a Net Centric environment. It will also depict the relationships of the data assets to the DoD data goals, and the dependencies amongst the data assets.
Observations
The U.S Department of Defense has identified the inherent complexity in the data exchange between military systems. It realizes the issue cannot be solved with the development of a centralized, managed data model, so the DoD is taking a decentralized approach to data management. It is providing an underlying structure (build on rules of COI formation) and allowing the COI's to self-organize to handle the problem. The realization of whether this strategy will result in a global solution to the problem is still under investigation.
References:
DoD Net-Centric Data Strategy, 9 May 2003
Army Community of Interest Roadmap , Nov 2005
[edit] Eco-Industrial Parks
Industrial ecology advocates a system level approach to reducing the adverse impact of industry on the environment. “The exchange of wastes, by-products, and energy among closely situated firms is one of the distinctive features of the applications of industrial ecological principles” (Ehrenfeld and Gertler, 1997). Such a collection of firms is referred to as an eco-industrial park (EIP) or an industrial ecosystem, and the interactions of these firms is referred to as industrial symbiosis (Chertow, 2000). The industrial district of Kalundborg, Denmark is such a system, and in fact has served as the prototype of successful EIP’s. One of the distinctive features of Kalundborg is that it did not arise through any master plan or government edict but rather it evolved over a 25-year period through a series of independent business deals negotiated by the various pairs of firms that now form the ‘ecosystem’. Each link in the network was added because the parties believed that it would be to their economic benefit to do so, rather than in pursuit of any system level goal such as reduced adverse environmental impact. Nor has Kalundborg been a static structure. Rather it has proven to be quite capable to adapt to changes required by economic change and technological innovation (Ehrenfeld and Chertow, ???). Government influence is not, however, totally absent. It has existed through its requirements that industry in general meet certain environmental standards. Thus it constitutes part of the environment in which Kalundborg evolved.
The success of Kalundborg led to the effort to create similar EIP’s in a number of locations, many with limited or little success. As a result “In the field work on eco-industrial parks at present there is a tug between two basic polarities: engineered systems or self-organizing systems” (Cote and Cohen-Rosenthal, 1998). In particular, observers of Kalundborg, the ‘poster-child’ for the self-organizing approach, have noted that critical to its development was the trust and cooperation that arose and that has been instrumental to its success (Gibbs, 200?, Jacobsen and Anderberg, 2001). This trust and cooperation cannot be expected to arise naturally just because some central planning effort has identified a number of firms with the potential to achieve the exchange of wastes, by-products, and energy that define an EIP.
This debate between engineered versus self-organizing systems with the goal of reducing adverse environmental impact has recently moved to a larger scale under the guise of Earth Systems Engineering. Its advocates see the coming need to intervene in nature and engineer fundamental natural systems (Allenby, 1999). Its opponents say that the lessons of nature, whose utilization is a core concept of industrial ecology, “are more likely to lead away from tightly managed, centralized approaches, and favor approaches with as little intervention as feasible” (Friedman, 2000).
References:
Allenby, B. 1999. Earth systems engineering: the role of industrial ecology in an engineered world. Journal of Industrial Ecology 2(3), 73-93.
Chertow, M. R. 2000. Industrial symbiosis: literature and taxonomy. Annual Review of Energy and the Environment 25, 313-337.
Cote, R. P. and Cohen-Rosenthal, E. 1998. Designing eco-industrial parks: a synthesis of some experiences. Journal of Cleaner Production 6, 181-188.
Ehrenfeld, J. R. and Chertow, M. R. ????. Industrial symbiosis: the legacy of Klundborg, in ???????, 334-348.
Ehrenfeld, J. and Gertler, N. 1997. Industrial ecology n practice. Journal of Industrial Ecology 1(1), 67-79.
Friedman, R. M. 2000. When you find yourself in a hole, stop digging. Journal of Industrial Ecology 3(4), 1519.
Gibbs, D. 200?. Trust and networking in inter-firm relations: the case of eco-industrial development. Local Economy, pp-pp.
Jacobsen, N. B. and Anderberg, S. 2001. Understanding the evolution of industrial symbiotic networks – the case of Klundborg. ISIE Conference, Leiden, The Netherlands.
[edit] SEMCO Approach
Prior to the 1980s, Semler and Company organized itself via the classical hierarchy with all final decisions made by the autocratic head of the company. This head was Antonio Semler, the founder of the company. By the early 1980s, Antonio’s son Ricardo returned from his MBA program at Harvard Business School with new ideas and philosophies that pitted the father against the son. Ultimately, Antonio gave the reins to Ricardo and let him develop his new structure for the company. Among other things, one new part of the company structure was the lattice organization, which created small self-managed groups that were completely accountable and responsible for all aspects of producing a set of products. In addition, SEMCO initiated a democratic process for all enterprise strategy decisions, which illustrated Ricardo’s trust of his employees to guide the company through their input in decisions. The adoption of the democratic process coupled with the success of the autonomous production teams led SEMCO to apply the autonomous team concept in all parts of the company. Each team had the freedom to create whatever structure worked best for their task. Universally, each team had full accountability and responsibility instead of a manager of the team. Teams discovered that the manager’s role was still important, however now as a facilitator to the team by delivering information and tools for making informed team decisions. Lastly, the continuous evolution of the self-organization style led the company to divide into "manufacturing units" of 150 people. These communities were responsible for all parts of a production line, including marketing, sales, HR and financial management, to name a few.
These new structures supported a strong growth in the product diversity of the company, as well as profitability. In 1980, 90% of the company profits came from shipbuilding supplies. By the mid 1990s, SEMCO manufactured over two thousand different products in many different markets, from electronics to marine pumps to filters. In addition, banking services and environmental consulting became new parts of the company, with 10-15% of profits coming from the environmental consulting area. The new focus on environmental consulting, and diversification in general, illustrates the high level of complexity SEMCO now manages as a networked, self-organizing structure instead of the previous hierarchical control structure.
Aside from the success of the company, SEMCO illustrates that the right environment for change will allow for the successful transition from hierarchy to self-managed network control. In this case, Ricardo Semler created the right environment for this transformation, which illustrates that leadership can play a major role in this process.
Observations
- SEMCO dealt with a high level of complexity from its product diversity by evolving from hierarchical control to self-organizing production teams to a perpetually self-organizing network
- A supportive environment fueled the transition to a self-organizing structure
Reference:
Killian, Kelly and Francisco Perez. Ricardo Semler and Semco S.A. Thunderbird: The Garvin School of International Management http://www.thunderbird.edu/pdf/about_us/case_series/a15980024.pdf
[edit] Ambiguous Shared Space
In the city of Drachten in the Netherlands, the "Laweiplein" is a major intersection which carries almost 20,000 cars per day – or an average of ca. 20 cars / minute in daytime (7:00 and 23:00). In 2003, a street designer called Hans Monderman designed an unusual intervention to make this busy, congested and accident-prone intersection safer.
The traditional intervention in a system like this would have been adding rules (more rules, more traffic lights, stricter speed limits, more road markings…) and enforcing them more strictly (radar, etc.). The traditional intervention would have tried to further reduce ambiguity and separate the movement space of cars, bycicles and pedestrians.
However, Hans Monderman took a very different approach – he decided to increase ambiguity and integrate the movement space of the traffic participants.
In 2003, Laweiplein was changed from a signal-controlled intersection to a “shared-space” intersection. After the intervention, the intersection is virtually naked: no traffic lights, no signs, no road markings, no division between road and sidewalk. The Laweiplein is now a textured intersection where the sidewalk merges with the roadway, with fountains at the intersection entrances.
"But in spite of the apparently anarchical layout, the traffic, a steady stream of trucks, cars, buses, motorcycles, bicycles and pedestrians, moved along fluidly and easily, as if directed by an invisible conductor." (Lyall, 2005)
According to city engineer Koop Kerkstra, accident rates have fallen about 20 Percent since the conversion, and travel time for crossing the city has improved dramatically. (Garrick, 2005)
"Who has the right of way?”, asks Hans Monderman. "I don't care. People here have to find their own way, negotiate for themselves, use their own brains." (Mondermann, H. as quoted in Lyall, 2005).
References:
Garrick, N. W. (2005) Care to share? Roads & Bridges
Lyall, S. (2005) New York Times, January 23, 2005)
[edit] Olympic AT&T Pavilion
Six months before the 1996 Olympic games in Atlanta 1996, AT&T was invited to move its pavilion from the edge of the Olympic village to the center. That was the good news. The bad news was that the AT&T design team had just completed 10 months of hard work on the first version, and now there was a need to redesign it at a new place to serve 75,000 customers a day instead of 5,000, and to finish the design in half the time.
It was clearly understood that there was no way to do it by the linear process it done before. The 23 members of the design team were a dispirited group when they assembled to meet the challenge. One of the group member's commented: " we are about to turn a disaster into a catastrophe." Two days later, the atmosphere was rather different. A totally new design had been created; everybody agreed that it was much better than the first design. As they planned, they ordered materials for delivery. Perhaps most important, everybody was still talking to each other, and some of them even described it as a 'fun' undertaking.
Using Open Space Technology made all the difference.
Open Space Technology, invented by Hrisson Owen, enables groups of any size to organize themselves to deal with complex, important issues and accomplish something meaningful by inviting people to take responsibility for what they have passion to do. In Open Space meetings and events, participants create and manage their own agenda in parallel working sessions around a central theme of common challenges.
Hrisson Owen on OS: One thing I can tell you for sure – Don’t try to explain Open Space! But DO talk about conditions, results and experience:
Conditions: Real serious business issue. Lots of complexity. Lots of diverse views. Plenty of conflict. And a decision time of yesterday.
Results: Every issue on the table. All discussed. Written reports. Priorities and action plans.
Less Tangible Results: Experience Agility, Cross-functional Relationships, Surprising Learning, Initiative, Inspiration, Energy, Momentum & Fun.
Experience: 20 years old, 60,000+ applications, 108 countries, Groups from 5-2000.
OST has four principles,
- Whoever comes --the right people
- Whatever happens --the only thing that could have
- Whenever it starts --the right time
- Whenever its over --its over
and one Law, which is actually a Traffic Law: your legs must be at the same place with your heart. Or in other words: If you are neither learning nor contributing, move on.
Basically all those conditions are intended to enable networks to self organize. More information on OST is available at www.openspaceworld.com.
OST & Complexity
For the AT&T case, there was a situation which increased the complexity at a specific time. Using OST enabled the design team to self-organize towards its new complex situation. When the OST event ended, they had a plan, the situation became more simple, and they could return to the regular procedure of the organization.
Conclusion
This case study shows us:
- There is a need to match the complexity of the internal structure of the organization to the external challenges
- Temporarily re-structuring is an affective way to match the internal & external complexity
- Networking & self organization are useful tools to complete a complex challenges
References:
Gilchrist Alison,(2000). The Well-connected Community: Networking to The Edge Chaos.
Lansing Stephen J, (2003) Complex Adaptive Systems, at Annu. Rev.Anthropol. 2003. 32:183-204/
Wellman Barry. Ed. (1999) Networks in the global village, Westview Press Colorado USA, oxford UK
Owen, harrison (1997) Open space technology, Berret-Koehler Publishers, Sun Francisco, CL, USA
[edit] Comparing Self-enforcing with Self-organization
One area of interest, coming from game theory, is a comparison between self-organization and self-enforcing concepts.
Self-enforcing is a model of a competiting relationship between every person, loosely descibing a process that maximizes your individual payoff, taking into consideration the payoff of others. One advantage is that this allows you to relatively easily evaluate the relationship quantitatively, based on simplifying assumptions that are frequently not realistic. Self-enforcing helps to understand and model of the egoistic and selfish behavior.
By contrast, self-organization is a notation that describes the collaboration process between human beings where the collective group respects individual spontaneity (an essential quality of freedom) but allows for collective unity (the opposite quality of spontaneity). Modeling self-organization helps to describe the interdependece of relations between human beings, illustrating the benefits of spontaneous collaboration that is able to achieve unity. Self-organization helps to understand the non-egoist and unselfish behavior.
[edit] Characteristics and Conditions of Self-Organizing Social Systems
We've observed some characterestics of self-organized systems that our common across some, but not necessarily all, of our case studies. With a broader set of case studies, there would likely be other common characteristics.
- Independence, freedom and spontaneity of individual people
- Passion of individuals followed by the responsibility to act on their passions
- Unity of the collective group towards a common goal while maintaining the diversity of the individuals
- Trust, coordination and cooperation amongst individuals
- Establishes an evolutionary process over time
- "The invitation comes from the top-down and the ideas/implementation comes from the bottom-up" for creating and supporting a dynamic self-organizing environment
In addition, we discussed some conditions of self-organizing systems:
- There should be a structure that aligns the individuals to a common goal
- The system must remain within constraints of the social environment
- Information should be freely (or at least easily) accessible
- Individuals should be sufficiently connected to one another
[edit] Appendix
[edit] About the authors
Shay Ben-Yosef is a Ph.D. student in sociology in Bar-Ilan University in Israel and an organizational and community consultant and facilitator.
Brian Doyle is a senior systems engineer at MITRE Corporation, a non-profit research and development center for the US government.
Stephen Levine is a faculty member in the Department of Civil and Environmental Engineering at Tufts University, teaching systems courses and doing research in the area of industrial ecology.
Daniel Livengood is a Ph.D. student in the Engineering Systems Division at the Massachusetts Institute of Technology studying the emerging complexity of product development processes, especially in the aerospace and defense industries.
Andreas Neus is a managing consultant with IBM Business Consulting Services in Germany and a researcher at the Karlsruhe Service Research Institute.
Dritan Osmani is a Ph.D. student with the Max Planck Research School in Earth System Modelling, studying modeling of international environmental agreements in the research unit Sustainability and Global Change at Hamburg University and Centre for Marine and Atmospheric Science in Hamburg, Germany.
