Top positive review
4.0 out of 5 starsThoughtful, Innovative & Yet Somewhat Lacking in Conclusiveness
Reviewed in the United States on March 12, 2015
Basically, the soft systems methodology (SSM) can in effect facilitate the incremental re-engineering of human activity systems without an explicit reverse engineering phase. Such systems are called soft because they present persistently ill-formed problem situations, largely due to their inherent complexity and contingent behavior. These attributes are typically characterized by the lack of consistently repeatable behaviors/outcomes. In particular, they exhibit nondeterminism (due to variabilities of various human agents and their institutions) as well as nonstationarity (per sporadic changes in their makeups and circumstances). Such dynamism of agendas and situations, moreover, serves to vastly complicate the static complexity of human organizations and society. In consequence, their inherent intractability results in the futility of positivist schemes for analyzing or improving them. Accordingly, the SSM or similar approaches are vital in effectively exploring such systems, as well as in incrementally improving them.
Checkland and his associates originally attempted to apply typical systems engineering methods in dealing with human activity systems, but soon recognized their unsuitability for dealing with the ill-formed problem situations as endemic to human activities. Similarly, they found general systems theory had nothing of value to offer. They then gravitated to the inquiry system concept espoused by Singer/Churchman as a means of systematically investigating and improving human activities, which the SSM characterizes in its Real World Domain. Complementary systems thinking is performed in a corresponding SSM Systems Thinking Domain. These two SSM partitions together constitute the inquiry system, which can be traversed iteratively to serve as a learning system regarding a target human activity system. The SSM focuses and prompts the learning process, which enables incremental improvements in the targeted system. Conceptually, the SSM is composed of the following seven elements:
1. Perceiving - the Problem Situation
2. Formulating - the Focal Issues Perspective
3. Composing - the Root Definition (of the selected system aspects)
4. Predicating - the Conceptual Models
5. Comparing - Conceptual Models with the Focal Issues Perspective
6. Deciding - Desirable/Feasible Changes
7. Activating - Changes to Problem Situation.
Elements 3 and 4 reside in the Systems Thinking Domain, and are referred to as Mode 2 or interpretive steps of the SSM. The other elements occur in the Real World Domain, and they are termed Mode 1 or intervention steps. The iterative looping through all seven steps realizes a Singerian inquiry system, which is intended to yield an increasingly accurate characterization of the human activity system’s problem situation. A defined template for the root definition in Element 3 serves as the basis for the conceptual models. They are composed in Element 4 of (nebulous) ideal types of generic elements, as tailored for human activity systems in general. Next, the SSM process tends to ameliorate selected undesirable aspects of the problem situation. Here, judgments regarding the comparative discrepancies between actual and ideal system attributes rely on the use of an adaptation of Vickers’ appreciative system in Element 5, as do decisions regarding remedial options in Element 6. Promising system changes are then introduced in Element 7.
In the book’s systems thinking portion (approximately the first 40 per cent), I found the content to be a quite interesting and palatable background survey. However, there seems to be no incisive definition of systems thinking, one that is precise, coherent, and declarative. Various examples and fragmentary rationale do not suffice, especially in view of its broad range of interpretations and applications appearing in the literature at large. Consequently, my impression of systems thinking is that of a catch-all collection of disparate notions and techniques compiled via breadthwise importation of assets of plausible or speculative worth. Systems thinking thus seems to be a sketchy high-level concept whose inherent vagueness and ambiguity can sometimes be exploited opportunistically. In particular, a systems practitioner can morph it into whatever configuration that incident circumstances may suggest. Alas, I remain quite unclear as to what in essence constitutes systems thinking per se; other authors, moreover, reinforce my perplexity.
In the systems practice portion of the book, my view of SSM is largely favorable. For example, SSM could support the conjoined exploration of related problem and solution spaces. In general, moreover, I believe that the SSM architecture has considerable promise for such use in engineered physical systems, especially software-based ones. (In my experience, such systems invariably manifest some aspects of soft systems.) An SSM-type approach might for example be valuable when investigating upgrades to an existing engineered system that is poorly structured or documented. Alternatively, the SSM inquiry capability might be used when an existing system is possibly going to be used for different functions, or in different environments. Of course, it would seem that the SSM’s utility for soft systems is beyond dispute, with only a few reservations. Although they would all seem tractable to resolution, my main concerns are:
1. the modest scale/depth and large number of problem situations addressed, given the limited time and staffing applied, can hardly suffice to demonstrate ample conclusiveness
2. no treatment of certain major concerns for ill-structured human activity systems is presented: nondeterminism, nonstationarity, indefinite boundaries, change side effects, for example
3. the utilization of Vickers’ appreciative system concept seems glib and oblique
4. by definition holons are elements in a particular form of level structure called a holarchy; an activity level, however, is erroneously conflated with activity flow in SSM.
In his thirty-year retrospective, Checkland makes two comments that I found disconcerting. First, he says that the above seven-step SSM process has been simplified to four steps. The seven-step version is already sketchy enough, and it seems that SSM is now devolving to the status of lore. Then, he notes that the handmade diagrams, as contrasted with ones that might be constructed and supported with a drawing tool, are preferable in conveying the provisional stage of their formulation. For many reasons, these handmade drawings would definitely be an impediment to the practical full-scale use of SSM, for clients and systems practitioners alike.
Aside from my reservations about the lack of closure of systems thinking coverage in this book, I consider the SSM concept to be quite intriguing and promising overall. Disconcertingly though, there appear to be surprisingly few follow-up publications in recent years that extend of further elaborate SSM. This might in part be attributable to the (apparent) lack of an integrated SSM environment. In any case, SSM would seem to merit further implementation development, especially in that at present it appears to essentially be just an architecture of a methodology, albeit one usable for manual application. Despite the definite appeal of the SSM concept, however, my appreciative system scores the book at only Four Stars.
