Theory of Constraints Handbook - James Cox Iii [445]
These latter features of the soft approaches are reflected by multiple “+” signs emphasizing the level of their contribution to the personal and social domains of problem context, across the whole spectrum of phases of problem intervention in the M-B classificatory framework. By contrast, hard approaches tend to be situated to provide analysis and assessment within the material world. Furthermore, the notion that soft approaches meet a need to facilitate learning about a problem aligns with Checkland and Scholes’ view that soft systems approaches can or should also be conceptualized as “learning systems” (1990, A8).
TABLE 23-4 Mapping of SSM and CM
For instance, and for Table 23-4, we note that within the action and implementation phase that both SSM and CM are designed to seek out and seek accommodation of disparate views/or consensus, and to seek enlightenment and empowerment for problem constituents as well as the problem owner and analysts. In stark contrast to hard OR/MS methods, we further note that the primary purpose of such soft methods is to understand better, not necessarily to identify best alternatives.
CM, similarly to SSM, seeks to effect a representation of how individuals view a problem, what it means to them, and how they make sense of it. The axiology or purpose of CM is to surface and understand these beliefs in order to generate consensus about possible strategic action. In contrast, we reaffirm that hard OR/MS relates mostly to the material world and focuses on analysis and assessment, leading to action in that domain. However, both hard and soft methods and methodologies may also be described as systems approaches. The nature of systems approaches and methodologies will be explored further in the next section.
Systems Approaches
Systems approaches to problem-solving typically conceptualize “problems” as existing within a notional whole or synthetic system, where a system can be defined as any grouping of people, events, activities, things, or ideas, connected by some common reason or purpose (Senge, 1990). As such, many systems can be best described as notional. In general, we can describe systems as being natural, for example, ecological systems; as being designed, for example, a car or an organization; or as being a human activity system, for example, a sports team or an ad hoc work group. Systems thinking attempts to reflect and illustrate the importance of holism, of boundaries, of feedback, of reciprocal relationships, and the notion that, say, activities or events, while perhaps separated by distance and time, cannot be understood in isolation, but instead need to be understood in terms of the patterns of relationships that create them and the patterns of behaviors that emerge from those relationships.
Systems thinking entails, above all, a sensibility about matters systemic (Espejo, 2006); that is, consideration of the big picture, the need to think holistically, to consider the whole as a network of relationships of interconnected parts or subsystems, and the need to understand feedback. Systems thinking, according to Senge (1990), involves learning to recognize structures that occur repeatedly—a notion that accords with TOC practice.
We often seek to understand a problem or problem situation by