Theory of Constraints Handbook - James Cox Iii [444]
The development of such soft approaches to address the design limitations of hard OR/MS approaches and methods paralleled the angst of early OR/MS pioneers such as Churchman (1967) and Ackoff (1977; 1979) about the sterility and inappropriateness of overly mathematical approaches for tackling complex social and business problems. Friend and Jessop (1969) developed SCA in the 1960s, as did Mason and Mitroff (1981) with SAST. Checkland and Scholes’ (1990) major developments of SSM took place in the 1970s, as did major developments of Soft Game Theory by Howard (1971) and Bennett (1977), and Robustness Analysis by Rosenhead et al. (1972); CM was developed by Eden et al. (1983) in the 1980s; and the major drive to explore hard and soft methods in multi-methodology began to flourish in the early 1990s. However, the work of Munro and Mingers (2002) some 10 years later showed that up to that point, almost all claimed examples of multi-method intervention comprised either all hard or all soft methods, not both in combination.
Such soft approaches may provide the opportunity, in Ackoff’s terms (1978), to dissolve the problem altogether, to resolve the problem satisfactorily, rather than just optimize or solve a technical problem that is an incomplete or inappropriate representation of the wider, relevant system domain.
Despite the growing evidence that soft OR is able to reach problems that traditional or hard OR cannot handle, such as organizational and individual behaviors and inconsistencies, soft OR is still not well accepted universally. While it is appreciated in the UK and elsewhere, it receives scant coverage in the United States. The hostile reception from journals like Operations Research and Management Science, which refuse to accept any papers that are “not based on rigorous mathematical models” (Simchi-Levi, 2009, 21), is the topic of current debate (Mingers, 2009a; 2009b).
Much of the soft OR story applies equally well to TOC. Indeed, most users of TOC TP would acknowledge their real benefit is in probing the very notion of what the problem is, why it exists, and what might be the outcomes if it did not exist, before diving into mathematical detail. However, there is also skepticism in traditional circles about whether TOC is a bona fide methodology, worthy of publication (Ronen, 2005).
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Given the similarity in standing and appreciation offered to nontraditional approaches, one might argue that the time is right for TOC academics and practitioners to unite with academics from across a number of related disciplines, including soft OR, to persuade more editors that applications and theoretical developments that do not necessitate a mathematical approach are nevertheless worthy of publication and dissemination. In terms of rigor, TOC does have one clear advantage—the CLR governing the use of the TP provide strict logic protocols that lend rigor to the endeavors of TOC analysts.
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Soft OR Methods—Theoretical Underpinnings
In this section, we draw together and reinterpret the prior discussion of soft OR methods in the context of the M-B framework, described earlier. We note, in particular, that soft approaches have been designed and developed to assist with all phases of problem intervention—appreciation, analysis, assessment, action—but especially as they relate to matters in the social and personal domains of the M-B classificatory system.
Table 23-4 provides examples illustrating how two soft OR methods, namely SSM and CM (Cognitive Mapping), map to the M-B framework. The “+” symbols indicate the relative extent to which each tool is purposively designed to attend to each phase of problem intervention in each of the problem dimensions. We note, for example, that SSM and CM have not been expressly designed to contribute to the analysis and understanding of underlying causal relationships in the material world—although their use may well contribute to doing so.
As may be inferred from commentary on the characteristics of hard OR/MS approaches,