Complex systems interact with an environment where a high degree of uncertainty exists. To reduce uncertainty, enterprises (should) create intelligence. This chapter shows that intelligence has two purposes: first, to increase and to assess (thus to correct) existing knowledge, and second, to support decision making by reducing uncertainty. The chapter discusses complex adaptive systems. Enterprises are not only complex systems; they are also most of the time dynamic because they have to adapt their goals, means, and structure to survive in the fast evolving (and thus unstable) environment. Crucial for enterprises is to know the context/ecology in which they act and operate. The Cynefin framework makes the organization and/or its parts aware of the possible contexts of the organization and/or its parts: simple, complicated, complex, chaotic, or disordered. It is crucial for the success of implementing and using EA that EA is adapted to function in an environment of perpetual change. To realize this, the chapter proposes and elaborates a new concept of EA, namely Complex Adaptive Systems Thinking – Enterprise Architecture (CAST-EA).
TopIntroduction
The aim of this chapter is to introduce Complex Adaptive System (CAS) and Systems Thinking (ST) into Enterprise Architecture (EA). The combination of CAS and ST is called Complex Adaptive Systems Thinking (CAST) (Lowe & Ng, 2006).
Systems Thinking has many forms, but we are basing our concept on the ST defined by Gharajedaghi (2011). In the context of Enterprise Architecture, ST is, in essence, a holistic approach to an enterprise and its environment. Sterman (2010) defines ST as “the ability to see the world as a complex system, in which we understand that 'you can't just do one thing' and that 'everything is connected to everything else” (p. 4). In this light, we will propose a new concept of EA, which will not only incorporate the Information Technology (IT) view but also a global (holistic) view of the enterprise.
Sterman (2010) wants us to see the world as a complex system, so we will first give a brief overview of complex systems. Senge (2006) states that complex systems have to do with dynamic complexity and not detail complexity. The latter arises where there are many variables, which are difficult (almost impossible) to hold in mind simultaneously to appreciate them as a whole. The former arises where effects over time of interrelatedness are subtle and the results of actions are not obvious, or where short-term and long-term effects are significantly different, or where effects locally are different from effects on a wider scale (Flood, 1999).
Complex systems are interacting with an environment where much uncertainty exists. To reduce the uncertainty, the enterprise will create intelligence. In our discussion, however, we will show that intelligence has two purposes: to increase and to assess (thus to correct) the existing knowledge and to support decision making by reducing the uncertainty. Rabaey and Mercken (2012) are proposing the system of 'Intelligence Base' to organize the intelligence process and the exploitation of knowledge.
After the section on uncertainty and intelligence, we will discuss Complex Adaptive Systems. Enterprises are not only complex systems, but they are also most of the time CAS because they have to adapt their goals, means and structure to survive in the fast evolving (and thus unstable) environment. In this section, we will show the consequence of wanting to implement EA for a CAS.
Crucial for enterprises is to know in which context they are acting and reacting. The Cynefin framework makes the organization and/or its parts aware of the possible contexts of the organization and/or its parts: simple, complicated, complex, chaotic or disordered. Dettmer (2011) uses the Cynefin framework to determine which management methods and tools can be used in which context. Important to note is that systems can move from one context to another without the enterprise knowing about it (necessity to have an intelligence system).
As a consequence, it is crucial for the success of implementing and using EA, that EA is adapted to function in a context that may permanently change. Therefore, we are proposing a new concept of EA, namely Complex Adaptive Systems Thinking – Enterprise Architecture (CAST-EA).