4
Combining Problem Structuring Methods with Simulation: The Philosophical and Practical Challenges

Kathy Kotiadis and John Mingers

Kent Business School University of Kent, Canterbury UK

4.1 Introduction

Combinations of problem structuring methods (PSMs) such as soft systems methodology (SSM) with simulation methods such as discrete-event simulation (DES) and system dynamics (SD) report benefits. These benefits include: the PSM enabling the participation of staff in the modelling process (Lehaney and Paul, 1996), enabling a better understanding of the situation of interest (Paucar-Caceres and Rodriguez-Ulloa, 2007; Kotiadis, 2007) and enabling the situation to be expressed and structured (Paucar-Caceres and Rodriguez-Ulloa, 2007; Kotiadis, 2007). A 10-year review (1998–2008) of mixing operational research (OR) methods in practice (Howick and Ackermann, 2011) only found around 15 papers to involve a simulation method (DES and/or SD). From this we can extrapolate that, although hundreds of simulation papers have been published in that time period, only a handful of these involve a multimethodology. In addition, the review (Howick and Ackermann, 2011) also revealed that most of these simulation combinations involved a PSM.

In this chapter we reflect on the barriers to such combinations, which can be seen at various levels such as the philosophical level – paradigm incommensurability – and the cognitive level – type of personality and cognitive difficulty of switching paradigm. We explore the literature and argue that the philosophical problems are not insurmountable. In addition we examine the practical aspect to such ‘multiparadigm multimethodology’ combinations. More specifically we explore the potential benefits and the possible barriers through a case study where SSM was combined with DES modelling within a healthcare context – community-based intermediate care. Reflecting on the practical application at the philosophical level reveals a multiparadigm multimethodology, with an interplay strategy for mixing the soft and hard paradigms. Although many of our reflections focus on DES, some are also applicable to SD.

PSMs are introduced next. Following that, the chapter focuses on the theoretical and practical concerns when combining OR methodologies from different paradigms. These concerns apply to combinations of simulation with PSMs. The next section reviews some relevant empirical examples of such work. Then our case study is described, and in the final section we reflect on its relevance to the concerns described earlier.

4.2 What are Problem Structuring Methods?

PSMs have evolved within OR over the last 30 years in order to better deal with messy, wicked and complex problems that are not amenable to the traditional, largely quantitative, OR techniques. The term ‘PSM’ was popularised by Rosenhead (1989) in his book Rational Analysis for a Problematic World as an alternative to the terms ‘soft OR’ or ‘soft systems’ which were felt to have unfortunate connotations.

PSMs are defined by a range of characteristics that are in contrast to those of traditional ‘hard’ techniques (Mingers and Rosenhead, 2004). Very briefly these are as follows:

  • They deal with unstructured problems characterised by multiple actors, multiple perspectives, conflicts of interest, major uncertainties and significant unquantifiable factors.
  • They must enable the modelling of alternative perspectives.
  • They, and their associated models, must be accessible to the actors involved to facilitate their genuine participation.
  • They must be flexible and iterative.
  • They must allow local rather than global improvements.

The most well-known PSMs (Rosenhead and Mingers, 2001) include soft systems methodology (SSM), strategic options development and analysis (SODA – now developed as ‘Journeymaking’), strategic choice analysis (SCA) and drama theory. Others that could be included are system dynamics, viable systems model (VSM), interactive planning and critical systems heuristics.

While the development and use of PSMs in themselves have been extremely successful (Mingers, 2000b), it has been argued by many people (Jackson, 1999; Midgley, 1997b; Mingers, 2000b; White and Taket, 1997) that significant benefits can accrue by combining different methodologies together – what has been termed ‘multimethodology’. This can consist of simply combining several PSMs together, which is relatively unproblematic, or it can involve combining PSMs with more traditional, hard techniques. Empirical evidence shows that this has occurred less often (Munro and Mingers, 2002; Howick and Ackermann, 2011) for reasons to be discussed below, but considerable benefits could be gained by encouraging such combinations.

4.3 Multiparadigm Multimethodology in Management Science

Several other authors have proposed the idea of combining together methodologies or parts of them using different terms: ‘coherent pluralism’ (Jackson, 1999), ‘creative design of methods’ (Midgley, 1997a), ‘pragmatic pluralism’ (White and Taket, 1997) and ‘complementarity’ (Pidd, 2004b). All of these accept the general arguments for the combination of different methods from different paradigms and most have gone to great lengths to explain or suggest how to achieve a combination at the methodology level, though they differ in the underlying rationale and the particular approach taken. Their views fall into two camps: those that believe that genuine multiparadigm multimethodology is possible, that is that methodologies, and parts of methodologies, from different paradigms, can be combined together coherently; and those who believe that methodologies can only be combined together having respect for their underpinning paradigms. Mingers and Brocklesby (1997) make four general arguments for multiparadigm multimethodology. First, that the world is complex and multidimensional and using different paradigms enables one to focus attention on different aspects of the situation. Second, a problem goes through different phases and more than one methodology might be required to tackle all phases. Third, multiparadigm multimethodology is common practice even if there are limited reports in the literature. Finally, triangulation of the situation using different methodologies can generate new insights while enhancing confidence in the results through a reciprocal validation (Mingers, 2002).

This leads us to explore the problems associated with the feasibility of multiparadigm multimethodology work, particularly at the philosophical level, which generally has not received as much attention even though it was discussed by Mingers and Brocklesby in 1997. They reported different levels of problems: (a) philosophical (particularly the issue of paradigm incommensurability); (b) cultural (the extent to which organisational and academic cultures militated against multiparadigm work); (c) cognitive (the difficulties that the individual experiences when moving from one paradigm to another); and (d) practical (takes more time, may be a lack of experience of several methods, innate conservatism – especially of funding bodies and journals, pressure to do something not ‘risky’ by organisation/client) (Mingers, 2001). Each of these will be explored briefly in the following subsections.

4.3.1 Paradigm Incommensurability

The notion that paradigms are incommensurable is said to have originated at the beginning of the last century (Schultz and Hatch, 1996) but the debate is more extensive in organisational theory compared with management science. At the centre of the debate, the seminal book by Burrell and Morgan (1979) (Sociological Paradigms and Organisational Analysis) challenged the dominant functionalist (positivist) orthodoxy by putting forward four paradigms which were claimed to be incommensurable, that is mutually exclusive, unable to be combined or linked because their underlying assumptions are thought to be incompatible. However, Willmott (1993) argues that ‘Paradigms (Burrell and Morgan's book) assumes, and strongly endorses, a restriction of analysis within the confines of four, mutually exclusive “ways of seeing”’ (Willmott, 1993, p. 682) and objects to the polarisation of either a subjective or objective approach to social science. He also makes the point that a close reading of the thesis by Kuhn (1970) reveals that Burrell and Morgan's conceptualisation of paradigms is constrictive and ignores Kuhn's account of scientific activity as

a process of movement in which ‘new’ paradigms emerge, phoenix-fashion, from the ashes of those they replace. It is important to recognise that Kuhn (1970) stresses the substantial continuity and overlap between the paradigms in the mediation of ‘normal’ and ‘revolutionary’ moment of scientific practice.

(Willmott, 1993, p. 686)

In the remaining part of this section we will be concerned particularly with the way in which others view the approach for combining the hard and soft paradigms in interventions. The views that will be presented will not include those that generally accept multiparadigm multimethodology but are not particularly interested or engaged in the debate about how it is done at the paradigm level.

Pidd (2004b), who also believes Kuhn to have suggested that paradigms are incommensurable, acknowledges that this notion is a contributing factor to the difficulty of combining methodologies. More importantly, he uses the point made by Ormerod (1997) about people managing to work successfully in both soft and hard approaches to propose that either Kuhn was wrong or soft and hard OR do not belong to different paradigms. In his book he portrays the relationship between soft and hard OR/MS as shown in Figure 4.1.

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Figure 4.1 The soft and hard paradigm. From Pidd (2004a) and Brown, Cooper and Pidd (2005).

Describing from left to right: (a) represents incommensurability; (b) describes hard and soft feeding on each other ‘in an eclectic and pragmatic way’ (Pidd, 2004a, p. 19) in (c) the soft methods are seen to contain the hard methods, which means that ‘understanding of meanings gained in soft OR/MS enables a sensible attempt at hard OR/MS’ (p. 19); and (d) illustrates soft and hard OR being intertwined and is similar to the view of Checkland and Scholes (1999) presented in Soft Systems Methodology in Action (p. 282). The latter illustration (d) in Figure 4.1 specifically applies to a case study involving data mining and SSM in the public sector (Brown, Cooper and Pidd, 2005) and visually seems closer to illustrating multiparadigm multimethodology than the other representations.

Similarly Schultz and Hatch (1996) distinguish three metatheoretical positions for doing multiparadigm research: (a) paradigm incommensurability; (b) paradigm integration; and (c) paradigm crossing. We will now focus on (b) and (c). Paradigm integration, according to Schultz and Hatch, enables the synthesis of ‘a variety of contributions, thus ignoring the differences between competing approaches and their paradigmatic assumptions’ (Schultz and Hatch, 1996, p. 532). They criticise this position on two accounts. First, in a few cases it ‘represents simple resistance to multiparadigm thinking’ (p. 533), for example to abandon all but one paradigm as suggested by Pfeffer (1993). Second, in many cases it ‘provides an overall framework that mixes and combines terms and implications of arguments grounded in different paradigmatic assumptions without considering the relationship between the assumptions themselves’ (Schultz and Hatch, 1996, p. 533). We will focus on paradigm crossing as it provides a theoretical basis and explanation of multiparadigm work in practice.

Paradigm crossing is about how multiple paradigms are dealt with by an individual researcher without ignoring them, as the integrationist position, or refusing to confront them, as the incommensurability position. Schultz and Hatch (1996) focus on strategies for paradigm crossing and they add a new one to the existing ones in the literature. The existing strategies are the sequential, the parallel, the bridging, and interplay (Schultz and Hatch's strategy). In the sequential strategy the relationship between paradigms is linear and movement from one paradigm to another is unidirectional. In the parallel strategy different paradigms are all applied on an equal basis instead of sequentially. The sequential and parallel strategies leave the boundaries of each paradigm deployed intact but in the bridging strategy the boundaries are more permeable. In fact, Gioia and Pitre (1990), who first articulated the bridging strategy, argued that paradigm boundaries are ill defined and blurred, and that it is ‘difficult, if not impossible, to establish exactly where one paradigm leaves off and another begins’ (p. 592). Therefore the boundaries are better conceived as transition zones.

The interplay strategy ‘refers to the simultaneous recognition of both contrasts and connections between paradigms rather than differences’ (Schultz and Hatch, 1996, p. 534). Researchers using this strategy will transpose the findings from one paradigm in such a way that they inform the research conducted in a different paradigm. Therefore the researcher can move back and forth between paradigms allowing cross-fertilisation between the paradigms while maintaining diversity. The main difference of the interplay with the other strategies is ‘in the nature of the relationship it constructs between the researcher and the multiple paradigms it specifies’ (Schultz and Hatch, 1996, p. 535). It is this approach that is closest to that advocated by Mingers (1997b) and appears to fit the last illustration of Pidd (2004a) (Figure 4.1) which is essentially a representation of a paradigm strategy.

Tashakkori and Teddlie (1998) also explore the paradigm strategies for combining qualitative and quantitative methodologies and categorise the sequential and parallel under mixed method studies, but they do not refer to the bridging or interplay strategies although they acknowledge a mixed model studies category that could incorporate them.

This debate about strategies is an attempt to understand and communicate the multimethodology work undertaken that could be classified as multiparadigm. This debate is in its infancy and it is interesting to see the authors that are currently engaged attempting to communicate with the audience not only by words, but also with pictures, as if words cannot go deep enough under the surface into the subconscious where most of the work arguably took place. A picture is worth a thousand words and perhaps in such situations a more useful communication tool.

4.3.2 Cultural Difficulties

Peoples' assumptions about the world and how to deal with its problems are to some extent a cultural issue that has resulted through socialisation and education. In management science there are communities, particularly educational ones, that are perceived as more hard OR focused or to have a more balanced number of hard and soft OR specialists than others. However, the latter are thought to be fewer, particularly as many working in the field of management science emerge from a variety of positivist disciplines, for example mathematics, computer science, engineering, and so on. Undoubtedly this must affect both the type of research or projects undertaken in these departments as well as the student's experience and attitude to problem solving immediately after university. It is logical to assume that this culture also feeds into industry. PSMs are probably not even considered by the majority of management scientists in the first instance when reviewing a problematic situation and many will simply turn to the old familiar approaches. In the event that PSMs are considered for use either alone or with a traditional hard OR method, there is probably a degree of fear about being competent in their use.

On the other hand, Pidd (2004a) makes some interesting points on the clients' view about someone being able to shift from hard to soft work. The first one is that the client might be unwilling to believe that someone might be competent enough to carry out both technical work and high-quality soft work. He points out that ‘competence in using soft approaches cannot be picked up by reading a chapter in a book important though that is. As Eden and Ackermann point out, there must be skills to be practised and practicalities that must be attended to’ (Pidd, 2004a, p. 205). If clients do feel this way it is understandable because many MS/OR degree programmes weigh in favour of quantitative approaches and their questioning the analyst's competence is not unreasonable as it would be very difficult to prove success in problem structuring skills. We cannot resist reminding the reader of the famous anecdote of Checkland (1999a) that if someone told him that they had used his methodology (SSM) and it worked he would have to reply:

How do you know that better results might not have been obtained by an ad hoc approach? If the assertion is: The methodology does not work, the author may reply, ungraciously but with logic, How do you know the poor results were not due to simply your incompetence in using the methodology?

(p. A12)

4.3.3 Cognitive Difficulties

This category of problems will be divided into difficulties in shifting paradigms and the personality of the management scientist.

4.3.3.1 Difficulties in Shifting Paradigms

Ormerod (1997) believes that mixing methods is possible and that switching between paradigms was not an issue for him, and that the limitations lie in the competence of the consultant and the participants rather than the methods themselves. However, Brocklesby (1995) acknowledges that shifts in paradigms can be a ‘painful experience for the individual concerned’ (p. 1290) but that it is possible for a person to become multimethodology literate given sufficient determination. In a later work he says that ‘the process of transforming an agent who works within a single paradigm into someone who is multimethodology literate is perhaps unlikely, although by no means impossible’ (Brocklesby, 1997, p. 212). However, for this to happen a number of obstacles must be overcome.

First, the agent must become paradigm conscious. Second, the agent must believe that the new paradigm offers something worth having and fits with the agent's personality and beliefs. Third, effective performance in a paradigm necessitates learning its propositional and common-sense knowledge. Brocklesby uses the work by Varela, Thompson and Rosch (1991) that identifies two types of knowledge: propositional and common-sense, needed for someone to act effectively in a ‘new paradigm’. He explains that in soft OR (otherwise known as problem structuring methods) the propositional knowledge needed to create rich pictures and produce root definitions can be acquired from textbooks, but in order to be effective in soft OR one must work directly with people, and respond to developing situations, which cannot be captured in a propositional format. However, to become proficient in a new paradigm the newcomer has to acquire relevant propositional knowledge, but this is only the first step and that ‘really’ knowing the paradigm and acting effectively in it means active bodily involvement, experience and practice. He also says that acting effectively within a new paradigm requires both learning and unlearning.

In addition, Pidd (2004a), similarly to Brocklesby (1995), also believes that it is harder than some people think to move from ‘one intellectual universe to another’ (p. 205) and suggests that perhaps the answer is to have different people carry out the hard elements of the work and others to undertake the soft (PSM) parts. Although he does also point out that the two must respect one another's insights, this could be construed as an indirect warning that these two groups will find it difficult to collaborate.

4.3.3.2 Personality

The empirical evidence cited earlier shows that the combination of a hard and soft methodology is less common than that of two hard or two soft methodologies. This finding may be an indication that operational researchers find it difficult to work across two paradigms and there is evidence that this may be related to particular personality types (Mingers and Brocklesby, 1997). The first personality described is the ‘analytical scientist’ personality type who prefers quantitative, aggregate data and shows distaste for qualitative data because he or she values precision, accuracy and reliability. The second personality is described as the ‘particular humanist’ and prefers to conduct research via personal involvement with other people, and prefers qualitative data. Furthermore, he or she is consultative and zealously promotes consensus and acceptance. While it is likely that most management scientists overlap these categories, there will be some that will fit into one category more than the other:

for such people it may be surmised that they will experience some difficulties in moving from one paradigm to another, and/or experience a certain internal tension or discomfort if they are compelled to work in a paradigm that calls for actions and behaviours that do not ‘fit’ their cognitive processing preferences.

(Mingers and Brocklesby, 1997, p. 499)

An example of these difficulties is mentioned by Doyle (1990) who found that users experienced considerable difficulty when trying to cope with both SSM and Jackson's system development (JSD).

Consideration of the importance of the personal characteristics of the practitioner in both choosing and using multiple methods and, in particular, of how difficult it is for individuals to work across paradigms combining technical, quantitative analysis with soft facilitation skills, will be further explored in the case study discussion.

4.3.4 Practical Problems

Finally, there are practical difficulties that constrain multimethod work (Mingers, 2001). It takes time to undertake such work, which means that many, particularly academics, might choose the clean-cut single method work, which is easier to explain and sell to clients, funding bodies and journals. Furthermore, multimethod work requires the knowledge and experience of several methods, which can be a problem, especially if there is one analyst.

In this section we have discussed some of the problems involved in multiparadigm work. One of the main arguments against it – paradigm incommensurability – has been shown to be flawed as Kuhn's work was misinterpreted and therefore the issue is still open for discussion. The issue of cultural feasibility draws attention to obstacles that are socially constructed. We have also covered problems of personality type in working within different paradigms and the difficulties of switching from one paradigm to another. The main purpose of the case study is to enable us to contribute our experience on these points. In the next section we will describe some practical applications relevant to our case study.

4.4 Relevant Projects and Case Studies

There are examples of PSMs and hard OR used together (Mingers, 2000b), with the most popular PSM being SSM (Bennett and Kerr, 1996; Coyle and Alexander, 1997; Pauley and Ormerod, 1998). A more recent survey (Howick and Ackermann, 2011) also found that SSM was in recent years the most popular method in multimethodologies (12 out of 30 papers reviewed from 1997 to 2008). The review reports only four instances of SSM involving simulation (two SD and two DES), which is an underestimate of the actual number as only papers in four general OR journals were used. However, we will now review a relevant subset of the papers describing a multimethodology involving a PSM and simulation. Of course, in light of the case study to follow we are particularly interested in those using SSM and applied to healthcare and those that express views about their paradigm strategy.

The starting point in the simulation methodology is about understanding the problem, which could also be described as the problem structuring phase. For this stage there are no guidelines or a structured technique to help the analyst in this task. It is surprising therefore that it is not common practice for problem structuring methodologies and techniques to be used in simulation methodology. However, Lehaney and Hlupic (1995) review the use of DES for resource planning in the health sector and suggest the use of SSM as an approach for improving the process and project or research outcomes. Lehaney and Paul (1996) examine the use of SSM in the development of a simulation of outpatient services at Watford General Hospital. The paper is concerned with the hypothesis that simulation can be developed through the use of SSM and that the acceptability of the final model may be increased through the participate nature of SSM. In this case the aim was to see if SSM could be used in the model building process even though simulation had been selected as the tool of analysis. The authors argue that this multimethodology allows the modelling of the actual patient experience and the participation of staff in the modelling process. In addition, the participation paved the way for acceptance of the conceptual model and gave rise to the final simulation being credible.

Lehaney, Clarke and Paul (1999) report on an intervention that utilised simulation within a soft systems framework and they call it soft-simulation. The project was for an outpatient dermatology clinic and the SSM approach was to use primary task root definitions. The paper includes a lengthy discussion on critiques, challenges and responses to issues about SSM or DES or their combination. The only challenge relating to their paradigm approach relates to the issue of paradigm incommensurability. They explain that SSM and simulation modelling are not completely different approaches as ‘they are both useful in facilitating debate and decisions, and are therefore both useful in similar areas, with each strengthening the other’ (p. 889) and, in their case, the notion of different paradigms is inappropriate. Because of this last statement one might think that their paradigm position is that of paradigm integration.

Lane and Oliva (1998) have explored the methodological synthesis of SSM and SD. They identify with the position of paradigm integration. They assert that SD does not belong to one paradigm and can therefore be recrafted and applied to others. Mingers takes a similar view (Mingers, 2000a; Mingers and White, 2010), arguing that SD exemplifies critical realism. Critical realism is a new paradigm, which aims to go beyond the current paradigms while recognising both their strengths and weaknesses (Archer et al., 1998; Bhaskar, 1978; Fleetwood and Ackroyd, 2004; Mingers, 2004). Methodologically, critical realism encourages a plurality of research methods and is therefore entirely compatible with multimethodology.

A study by Paucar-Caceres and Rodriguez-Ulloa (2007) put forward a framework for combining SSM with SD which they call soft systems dynamics methodology. Unlike Lane and Oliva (1998), they explain that their approach is multiparadigm multimethodology and test the framework on a small enterprise involved in commercialising steel products. Although they describe paradigm crossing, the specific strategy adopted is difficult to pinpoint with any certainty. In our opinion both the interplay and bridging strategy are likely candidates. This study proposes that a key benefit of using SSM is that it enables the problem situation to be expressed and structured.

On the other hand simulation is also commonly used to develop our understanding of a problem, which is a function often attributed to PSMs. Robinson (2001) describes using simulation modelling in a soft intervention to aid the improvement of a user support helpline service at Warwick Business School. He describes his approach as qualitative simulation and a multimethodology because the first part of his study follows the hard OR methodology, though he departs at the validation stage from the hard methodology due to the lack of accurate data making it impossible to validate the simulation model. The intervention from then onwards focuses on a facilitated discussion centred on the model. The most striking difference to most traditional DES users is that the model was used as a focus for debate, a means for learning about the problem situation and for reaching an agreement to act. Robinson argues that the power of the simulation methodology and the DES technique means that lack of accurate data does not need to be a hindrance to DES. Although he does not use a specific PSM, Robinson compares his steps and outcomes with SD and SSM. The purpose of his paper as he describes it is to demonstrate that DES can be used to support soft OR interventions. He places his approach closest to pragmatic pluralism because the mixing of paradigms was not intended. It could be described as an example of paradigm crossing but it is more difficult to identify the precise strategy, although the author describes features from both the sequential strategy and the interplay. In terms of matching his approach to one of the diagrams featured in Figure 4.1, one only needs to look at the title of his paper ‘Soft with a hard centre’.

The final study we review does not involve simulation but expresses views that are important to our study because of the paradigm strategy discussion. The study combined SSM with data mining and was applied to the public sector (Brown, Cooper and Pidd, 2005; Pidd, 2004a) with an the aim to modernise the UK's personal tax system. Data mining was used to obtain representative models of the UK taxpayer groups and their interaction with the current taxpayer system, and SSM was used to extract models including the features that are considered desirable and necessary in the future tax system. The methods were not deployed sequentially but in parallel; they declare their strategy as two interwoven lines which represent hard and soft methods (see Figure 4.1). Brown, Cooper and Pidd (2005) explain that ‘though both the hard and the soft OR made valuable contributions to the study it was significantly enhanced by their combination’ (p. 4) and those findings from each approach fed into the other.

The studies that link hard and soft approaches report clear benefits in dealing with complex situations. However, we argue that not all previous authors have adequately declared or tackled their paradigm position and it is therefore not always clear if they are describing multiparadigm multimethodology – critical pluralism (Mingers, 1997a; Mingers, 1997b; Mingers, 1999; Mingers and Brocklesby, 1996) or pragmatic pluralism (White and Taket, 1997) – (crossing or integration) or coherent pluralism (Jackson, 1999) (incommensurability). This is understandable as their work was groundbreaking and there were other, more practical and theoretical issues to tackle which have paved the way for philosophical ones. We will describe a case study that uses DES and SSM to evaluate a healthcare system for older people called Intermediate Care. We will then argue that it is a multiparadigm multimethodology and the position adopted is that of paradigm crossing with an interplay strategy.

4.5 The Case Study: Evaluating Intermediate Care

The case study that follows describes the use of SSM and DES modelling to evaluate the operational function of an intermediate care (IC) system, which is a health and social care system for older people in the UK. In the description of the following case the first author will describe her own feelings and experiences as this is clearly seen as important in applying a multimethodology.

4.5.1 The Problem Situation

The Department of Health (DH) had allocated a significant amount of money and resources to this area. Specifically, it pledged to invest £900 million a year by 2003–2004 in IC services (Department of Health, 2001a). The creation of IC services for older people was in order to relieve the over-utilised acute hospitals and long-term institutional care settings from those who do not benefit from these services. These would include: ‘Hospital day units and community based services aimed at maintaining people in their home communities in good health, preventing avoidable admissions, facilitating early discharge and active rehabilitation post-discharge and supporting a return to normal community-based living wherever possible’ (Department of Health, 2000, p. 4). The DH published guidance on service models for intermediate care (Department of Health, 2001a), which included services with specific goals of preventing hospital admissions, enabling earlier discharge from hospital by providing rehabilitation closer to home and preventing admission to long-term care.

An Elderly Strategic Planning Group and its Joint Planning Board commissioned the University of Kent in 2000 to evaluate one of their IC systems. The project team based at the Centre for Health Service Studies had four main team members including the first author who was the only person with OR/MS knowledge. The others were a health service researcher and two geriatricians. Each of the members of the team had a different role/task and the first author's task was to evaluate the operational function of the IC system, which is broadly described in this case study.

At the start of the project, the first author had recently graduated with a management science degree with little soft OR content; her practical experience in OR was a final-year project applying DES modelling in a traditional ‘hard’ way in a manufacturing environment, but she was eager to apply simulation modelling again in research to obtain a PhD. In fact, she joined the team because the project leader, a geriatrician, thought that simulation modelling could be useful in healthcare – especially as exploring resource requirements, a typical use of simulation modelling, is also important to health and social care managers.

Initially, there was a considerable amount of vagueness about what the operational function was and what they (stakeholders) wanted to evaluate. This vagueness is not unusual in a complex societal problem, particularly if it is a large and important real-life problem. DeTombe (2001) argues that

complex societal problems are often ill defined or multi-defined, hard to analyse and to handle. Knowledge and data are missing or contradictory, the causes of the problem vague and it is often not clear in which direction the problem is going. Many phenomena, many parties, private and governmental are involved. The problem often has or will have a large impact on (parts of) society.

(p. 231)

This description fits this problem accurately and can perfectly describe the starting point to this research. DeTombe mentions that these complex societal problems involve interdisciplinary study and that the methodology for handling complex societal problems is multidisciplinary. This lack of understanding and vagueness could have described IC in 2000, at the start of the project, as there was hardly any IC literature available and many of the health and social care employees did not even recognise the term ‘intermediate care’.

The main problem with structuring the problem was that both the project team and the stakeholders did not understand the DH's conceptual vision of an IC system and its functions. The IC stakeholders had translated the DH's vision into practice by simply setting up the individual services but had not been able to examine the system as a whole, which is why the DH had commissioned the project. In fact one might say that they had set up services but not a system to ‘hold’ them together.

Part of the evaluation could be achieved through the simulation methodology but the vagueness encountered prevented an understanding of what needed modelling in that system. It was then realised that SSM did not provide any tools for extremely confusing and complex situations such as the one encountered. After some consideration of the methodologies and techniques taught (e.g. SSM, SODA/cognitive mapping and robustness analysis) the first author felt that SSM was more appropriate as it provided a much more structured approach to understanding than the other PSMs. Deciding to use SSM was not a comfortable decision as she was not experienced in applying it and, furthermore, she would have little supervisory support in using it due to the lack of expertise at that time in the academic department. It was clear, though, that a useful simulation model could not be built unless the system and its operations were understood. However, it was almost immediately evident that engaging in SSM meant that her attitude changed and the line of questioning moved from ‘how does this work?’ to ‘how could this work?’, not just because of the SSM requirements, but also in terms of the simulation modelling. In simulation modelling this line of questioning is usually left to the end of the model development phase. This new line of questioning benefited employees that previously were not able to explain the situation, as it was confusing even to them, but they nevertheless had ideas and an understanding of what could work and was desirable. The next subsection will examine the SSM approach in this investigation.

4.5.2 Soft Systems Methodology

Initially, the IC system was explored through interviews and stakeholder group meetings and, following Checkland (1999a), CATWOE root definitions were produced, which helped construct an activity model. The aim was to find out about the stakeholder group's operational and strategic activities to manage, coordinate and improve the systems operations. Otherwise, the only link between the services would be the target population of older people. These activities could be considered as the primary tasks (Checkland, 1999b) of the IC function and if these were missing from the real system but were considered desirable and culturally feasible, then action should be taken by the system owners to put these tasks in place. Adopting a primary task approach to SSM makes the process even more focused. One might even argue that there is a hint of the hard paradigm when applying this focused SSM, and Checkland and Scholes (1999) hint at this by saying that it ‘has the advantage of providing a highly structured entry, which reassures the nervous’ (p. 66). The nervous can really be none other than those that want to abolish future uncertainty and are more comfortable with hard OR (see Table 4.1).

Table 4.1 The six key characteristics of the hard and soft paradigms (Rosenhead, 1999).

Characteristics of the hard paradigm Characteristics of the soft paradigm
Problem formulation with a single objective and optimisation. Multiple objectives, if recognised, are subject to trade-off on to a common scale
There are overwhelming data demands, with consequent problems of distortion, data availability and data credibility
Scientisation and depoliticisation; there is an assumption of consensus between stakeholders
People are treated as passive objects
There is a single decision maker with abstract objectives from which concrete actions can be deduced from implementation through a hierarchical chain of command
There is an attempt to abolish future uncertainty, pre-taking future decisions		 Non-optimising; seeks alternative solutions which are acceptable on separate dimensions, without trade-offs
Reduced data demands, achieved by greater integration of hard and soft data with social judgements
Simplicity and transparency aimed at clarifying the terms of conflict
Conceptualises people as active subjects
Facilitates planning from the bottom up
Accepts uncertainty, and aims to keep options open for later resolution

Interviews and observation revealed that one of these operational activities should be about the decision-making mechanism for patient referral to each of the services in the system as each service served different rehabilitation needs. However, it was found that there was no formal decision-making process in place to allocate patients to services. All IC employees and stakeholders were keen to change this ‘ad hoc’ referral because patients entering the ‘wrong’ service for their needs is a waste of resources and it can also put the patients' rehabilitation and even life at risk. Therefore, in addition to the tasks of determining the efficiency of the IC resources, it was decided to explore the patient referral mechanism to the IC services.

This process of understanding the IC operational function through the SSM activities model also provided the evaluation tasks for the project. Of course some activities like the evaluation of the resources were evident from the start, but others like evaluation of the decision-making mechanism for referral resulted from the SSM process. Furthermore, some of the evaluation tasks could be explored in the SSM phase. For example, the DH IC literature (Department of Health, 2002) suggested that a single standardised tool should be used for patient data collection and assessment across all services and, although desirable and culturally feasible by IC employees, this was not in place in that IC system (or any other at that time). Therefore in the SSM comparison phase the current patient assessment approach was evaluated by comparing it with a different approach that was more desirable and culturally feasible than the existing one. The outcome was to recommend the different approach, which was to adopt a comprehensive and standardised assessment instrument throughout the IC system. During the SSM comparison phase many differences were found between the real world and the systems world which in itself formed part of the evaluation.

Although SSM was only initially thought to be useful to understand the system and enable the simulation modelling, it helped structure the problem into evaluation tasks and it also enabled part of the evaluation. The SSM phase also confirmed the need to explore the efficiency of the resources and that the evaluation would require more than just a comparison. This confirmed the team's original thought that simulation modelling could be useful for this evaluation. It was decided to build a simulation model for each of the services to evaluate their resources (beds/places and staff) and a ‘whole system’ model to explore how the decision-making mechanism of patient referral affects the services. The next subsection will discuss the use of DES in the evaluation process.

4.5.3 Discrete-Event Simulation Modelling

The modeller in the initial stage of building a simulation model will dedicate a length of time to understanding the system of interest. The process of understanding the IC system during the SSM phase also doubled as the first step of building a simulation model. Therefore, the soft approach helped satisfy the needs for the hard paradigm method.

The simulation modelling phase for this case study can be divided into the phase of building the models of the IC services in order to assess their resources and the second phase of building a model of the system to examine the patient referral decision-making process. The first phase was straightforward because there were employees that had a good understanding of how each of the services worked and what the future might hold for these services that could be explored through ‘what if?’ scenarios. This meant that the simulation models of the services were built adopting the traditional hard paradigm approach.

However, the second phase had no IC employee(s) or stakeholder(s) with an in-depth understanding of the IC system, so this second phase was explored more analytically as simulation modelling was not approached in the traditional manner. As mentioned earlier, the SSM phase revealed that there was no formal decision-making mechanism in place for patients to be sent to the most appropriate service, but patients were referred in an ad hoc manner, which did not benefit the services or the patient and was not in line with DH thinking (Department of Health, 2001b). Therefore, if a model of the actual situation were built it would not actually benefit anyone, because everyone was aware of the resulting problems, particularly of inappropriate patients entering the services. The team decided to build a simulation model that did not depict the actual situation but gave the most agreeable (desirable and culturally feasible) conceptual view of the patient referral decision-making process. This would allow further exploration and evaluation of this view in a virtual environment. The remaining methodology steps after obtaining the conceptual model followed the hard paradigm. This meant that the team had moved from initially approaching simulation modelling with the hard paradigm (of the services) to applying simulation modelling under the soft and hard OR paradigms for the system model. Therefore, the simulation methodology was used with a mixture of the soft and hard paradigms.

4.5.4 Multimethodology

The SSM and DES methodology were not applied consecutively but were both done concurrently, although some steps exceeded others. They both fed into each other at different times and each methodology enriched the findings of the other. For example, one of the SSM findings revealed that a vital operation in the system was to determine Service Entry Eligibility Criteria (Kotiadis, Carpenter and Mackenzie, 2004), which are essentially tailor-made rules for each service to ensure that only suitable older people at a physical, mental and social level are admitted. However, it was not possible to evaluate these with SSM, though they could be evaluated using the simulation models. By adding this finding to the simulation models the team were able to build models that answered questions that were more important to the stakeholders. It is undoubtedly useful to determine the utilisation of a service but even more useful to determine it while also knowing the proportion of the people admitted that are inappropriate to that service. The simulation model revealed that many of the services in that system admitted patients that did not meet all the Service Entry Eligibility Criteria, which was fed back into the SSM process in order to decide on what desirable and culturally feasible action to take. To sum up, within the simulation methodology the soft paradigm fed into the hard paradigm and vice versa. Without doubt, the project would not have been possible with just one of the two methodologies or with just one of the two paradigms.

Despite the positive impact that each methodology had on the other, the multimethodology was not without its problems. The procedure was ‘painful’ for the first author and at first the outcome of the multimethodology was largely uncertain in case the theoretical underpinnings of the simulation model in particular were flawed with this non-standard approach to the methodology. Furthermore, even if the primary task version of SSM was applied for the ‘nervous’ it was still difficult to change an attitude developed over a lifetime of positivist training in such a short period of time. Many factors enhanced the level of pain, such as providing the stakeholders with value for their money, the enormity of the impact that false results could have on this real system that provided a lifeline to many older people, and so on. This experience fits with the description by Brocklesby (1995) of paradigm shifts as a painful experience. The validation and verification of the simulation model and the acceptance of the findings by the stakeholders from both the SSM and simulation model brought some relief that at the very least the project has helped them gain a better understanding of their IC system. In fact the project achieved much more than that because it underpinned the region's IC strategy and the findings were used to introduce new services to the region. Furthermore, a one-day workshop was organised by the stakeholders to present the system simulation model and its findings not only to the participants in the study, but also to all service providers of other localities within the stakeholders' jurisdiction. It was generally thought that the new conceptual vision of how the system could work was best communicated visually and in the spirit of SSM it brought about acceptance of the region's IC strategy.

4.6 Discussion

We will now contribute our learning about combining SSM with DES with respect to the various issues that we explored earlier in the chapter. These are the paradigm position and strategy, the cognitive and cultural difficulties affecting multiparadigm work. We have not dedicated a specific section to practical difficulties as they emerge in the others that we explore.

4.6.1 The Multiparadigm Multimethodology Position and Strategy

Lehaney, Clarke and Paul (1999) explored paradigm incommensurability by discussing whether SSM and simulation as they applied them could be considered as different approaches and concluded that in their case the notion of different paradigms is inappropriate. Similarly, Lane and Oliva (1998) also expressed paradigm integration beliefs about the synthesis of SSM with SD. In our case study a multimethodology was used and both paradigms were adopted at different stages of the project. The paradigm approach to this multimethodology can be explained with the paradigm interplay strategy. The process of obtaining our conceptual model for the simulation methodology required the soft paradigm, which is an example of cross-fertilisation of the paradigms while accepting their diversity. Without doubt this is an example of the interplay strategy, although this was not something recognised at the time or even something that the researcher strived for.

Interestingly, we can deduce that the simulation method (DES or SD) combined with SSM does not necessarily lead to similar views on the paradigm positioning. Our study is more aligned to the view of Paucar-Caceres and Rodriguez-Ulloa (2007) who also put forward paradigm crossing.

In looking retrospectively on our experience and trying to make sense of it we have found it helpful to communicate our multiparadigm approach using the ‘yin yang’ symbol which represents two opposing elements of the Universe and is used to explain ‘how things work’ (Figure 4.2). In fact Zhu (2001) also uses the ‘yin yang’ metaphor to discuss information systems design at the philosophical level. The outer circle represents ‘everything’, while the black and white shapes within the circle represent the interaction of two energies, called ‘yin’ (black) and ‘yang’ (white), which cause everything to happen. They are not completely black or white, just as things in life are not completely black or white, and they cannot exist without each other. The soft and hard paradigms in OR can be considered as the two opposite philosophical principles (Table 4.1) ‘yin’ (hard) and ‘yang’ (soft), and the outer circle can be considered as the problematic situation (Figure 4.3). It should be noted that the colour of the outer circle is irrelevant and does not mean that the problematic situation is hard.

img

Figure 4.2 The yin and yang symbol.

img

Figure 4.3 The soft and hard paradigms in the intermediate care case study.

In our study there was an element of the hard paradigm (yin) when SSM was applied (primary task approach to SSM) and an element of the soft paradigm (yang) during the simulation modelling (building a simulation model of the most agreeable patient referral mechanism). Therefore, unlike Lehaney, Clarke and Paul (1999) the notion of different paradigms in this case is appropriate and furthermore the two methods in question could not be applied just with one paradigm and satisfy the objective of the study. Although both of us used SSM and DES in healthcare, there are considerable differences in our application areas and objectives that might have warranted such a different approach and opinion about our paradigm positioning. The differences in terms of the application area include the scale of our system (we modelled the interaction of several independent healthcare services versus one outpatient department) and the larger number of stakeholders and participants in our study, which also influenced our objectives. It is also possible that we might have come to the same conclusions had we tackled each other's problem. We propose that in fact the requirements of a problematic situation might dictate the paradigm strategy rather than the methodologies used, which might explain why we share more similarities with the multiparadigm approach of Brown, Cooper and Pidd (2005). However, we believe that the ‘yin yang’ symbol is a richer representation of the muliparadigm multimethodology process.

This study shows that multiparadigm multimethodology is possible and was largely motivated by the need to tackle the problematic situation. We also believe that learning about the philosophical approach is important and that the ‘journey’ (the paradigm strategy) is just as important as the ‘destination’ (the outcome). Therefore, although the approach to the project shares characteristics of the pragmatic pluralism (White and Taket, 1997) approach we are not ignoring the philosophical issue, which therefore makes it closest to critical pluralism (Mingers, 1997b).

4.6.2 The Cultural Difficulties

The study was ‘advertised’ as a simulation study and not a multimethodology of SSM and DES for two main reasons. First, we knew from the start that given the questions about resource requirements simulation would be used but the need to use SSM came a few months later when the project was underway. Therefore, in the initial meetings and presentations organised, only simulation modelling was explained to the participants. The second reason, though, can be attributed to the culture in healthcare. The simulation modelling approach generated a lot of interest and was perceived by stakeholders as a new, exciting scientific approach to explore their whole system, which they knew would not be possible using the traditional community healthcare approaches, qualitative studies or randomised control trials. Explaining simulation to more than 40 healthcare professionals and stakeholders was a challenge and a priority in order to get as many ‘on board’, particularly as the data collection was a huge expense and undertaking on their part. SSM was initially considered secondary to the simulation modelling and was not explained or presented to the participants, with the exception of the key stakeholders, mainly because there was not enough time, even though over the course of the study they inadvertently provided valuable information for it. In addition, conducting studies in healthcare means that communication requires the investigator to understand a new language and attitude in healthcare systems, and the feeling is very much the same on their (healthcare stakeholders') part when explaining OR to them. The very valuable time that they offered was better spent understanding and extracting information about the system rather than explaining the merits of SSM.

4.6.3 The Cognitive Difficulties

There are a number of issues mentioned in the first section of this chapter which we will reflect on: Mingers (1997b), Brocklesby (1997) and Ormerod (2001) consider the actor's personality, feelings and competences when working across two paradigms and we will discuss whether these affected this study. We will initially consider the impact of the agent's personality. The first author, the agent for the intervention, might be considered as an ‘analytical scientist’ type if her previous hard OR experience was taken into account, but it is also possible that she is a ‘particular humanist’ type that has learnt to apply hard OR successfully but would be better at soft OR – particularly when one considers that as a female she is predisposed to communication skills (Sojka and Tansuhaj, 1997) which are essential to the SSM process. In addition, the majority of this healthcare system's employees and stakeholders are female, which might have made communication even easier than if it were a male-dominated environment. The reasons for making such a suggestion are the following two points. First, men and women are thought to communicate differently because they listen for different information; for example, a woman might concentrate more on the feelings projected during a conversation and a man more on the facts (Shakeshaft, Nowell and Perry, 1991). Second, research has shown that there might be some discomfort when communicating with a member of the opposite sex (Shakeshaft, 1987). Differences in communication between males and females such as the conversation style, the non-verbal communication, perceptions (Hartley, 1996) and the fact that women are better at one of the most important elements of communication, which is listening, because they do not interrupt as much as men (Ellis and Beattie, 1986), could have a drastic affect on such studies (Bergvall, 1999). Although the analyst's gender may have had an effect on the SSM we are not able determine objectively if the analyst is really an analytical scientist and consequently whether that affected (positively or negatively) her work across the two paradigms.

The second consideration is the agent's feelings during the intervention about working across two paradigms. Brocklesby (1997) suggests that we must question the level of discomfort that the agent felt during the paradigm shifts. The analyst in our case study felt extreme and long-lasting stress and anxiety about applying the methods in a different way to the one taught during her training and written about in books. However, the analyst had very little experience of real-life projects and of course that must have contributed to the level of discomfort, which brings us to the third issue, namely the agent's competence. As experience brings competence, Ormerod (1997) may be correct in suggesting that this is an issue when working across methods and paradigms. However, despite the analyst's feelings and lack of experience, the project was completed on time and produced results that have been used by the stakeholders in their strategy and decision making. Although we might link feelings to experience and experience to competence, competence is not just about experience and other competences should be explored.

Psychology and organisational behaviour might be useful in providing a direction for selecting the competences to explore. For example, organisational behaviourists believe that personality is a dynamic interaction of a set of traits which include gender, abilities, physique, motivation, attitudes and perception with adult experiences at work (achievements, roles, working experiences) and early development experiences (social, family, culture) (Mullins, 1993). In our intervention a personal competence and early development experience that may have positively affected the process is that the agent is bilingual and therefore accustomed to moving from one language and culture to another, which is a similar concept to moving between the hard and soft paradigm. It may be possible that such skill is transferable and that if one can master the ability to learn and unlearn new rules, just as Brocklesby (1997) suggests, one might be able to learn to move between paradigms.

4.7 Conclusions

This chapter has considered some of the barriers to multiparadigm multimethodology such as paradigm incommensurability, cognitive style and difficulties of switching paradigms. It has done this in the context of an actual application – a combination of SSM and DES within intermediate care. The main conclusions from the success of this application are: (i) That paradigm commensurability is not a barrier to such combinations. Indeed, the application was an example of a particular strategy for working across paradigms – what has been characterised as the ‘interplay’ strategy. (ii) That the notion of yin and yang is an appropriate metaphor for this approach. Overall, the multimethodology combined a hard method with a soft method but, as well as this, within the hard there was some soft and vice versa. (iii) That one's past experience and training as well as personality and perhaps gender all affect one's approach to interventions in general and multimethodology in particular. They do not, however, prevent movement towards being able to work successfully across paradigms.

A note of caution is that although some of the above conclusions have resulted from the study of a particular combination of SSM with DES, the insights on paradigm positioning may not be relevant to all simulation studies (DES and SD). Indeed we have found SD and DES combinations with a PSM, SSM in particular, that align themselves with the position of paradigm integration. More research in this area would benefit both the DES and SD communities.

Acknowledgements

Chapter text, figures and tables are reproduced by permission of Palgrave Macmillan from the article: Kotiadis, K. and Mingers, J. (2006) Combining PSMs with hard or methods: the philosophical and practical challenges. Journal of the Operational Research Society, 57(7), 856–867.

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