Journal of the Operational Research Society, vol. 50 (2)

LOGICAL SOFT SYSTEMS MODELLING FOR INFORMATION SOURCE ANALYSIS - THE CASE OF HONGKONG TELECOM

Frank H. Gregory, City University of Hong Kong

Lau Siu Pong, Hongkong Telecom

 

Abstract

The paper describes the use of logico-linguistic modelling, a logically enhanced version of Soft System Methodology, to identify the information needed to support decisions made in a marketing department of a Hong Kong telecommunications company. This case indicates that logical complexity need not be a barrier to stakeholder comprehension. However, cross-cultural difficulties were encountered when using the basic SSM method.

Key Words: Information Requirements Analysis, Soft Systems Methodology, Modal Logic, Logico-linguistic Models, Organisational culture.

CONTENTS

INTRODUCTION

BACKGROUND

THE PROJECT

THE CULTURAL CONTEXT

EVALUATION

CONCLUSIONS

APPENDIX 1: LOGICAL CONNECTIVES USED IN LOGICO-LINGUISTIC MODELING

APPENDIX 2: TRUTH

APPENDIX 3: LOGICAL POWER

REFERENCES

 

INTRODUCTION

The paper aims to make a contribution in three areas. Firstly, it seeks to show that the use of a logically enhanced version of the Soft Systems Methodology (SSM) conceptual model building technique can be viable in practice. Secondly, it demonstrates that logical modelling can be usefully employed at the front end (problem structuring) of information system development and need not be confined to back end (programming) support. Thirdly, it illustrates problems encountered using an SSM approach in an environment where the corporate culture is "fast paced" and the ethnic culture is Chinese.

The study not only employed a new extension of SSM but did so in a cultural, linguistic and economic environment radically different from previously documented SSM cases. The research was exploratory action research, which, it is hoped, will lead to improvements in methodology; the findings are not intended as a demonstration of an optimal solution to a specific problem.

 

Logico-linguistic Models

It has been argued that the conceptual models of human activity systems used in SSM are logically inadequate for some of the purposes, notably information system design, for which they are used. In a series of theoretical papers1,2,3 it has been argued that this shortcoming could be rectified by producing logically enhanced versions of the SSM models. The paper describes the use of these "logico-linguistic" models for the identification of information requirements to support planning in a marketing department of Hongkong Telecom. The project demonstrates that the models are not, as has been suggested, too complex to be used in client led modelling. In this area the study showed that stakeholder comprehension need not be a barrier to practical implementation.

 

Information Source Analysis

The information systems literature, with its emphasis on repetitive data processing, pays scant attention to the information needed to support irregular planning procedures. In this context the tools employed by traditional information system design methodologies, such as data flow diagrams, are of little use. Of much greater relevance in the context are the broad based models (SSM conceptual models, Cognitive Mapping, Strategic Choice, meta-game and hyper-game models) developed in Soft Operational Research.

The previous exposition of logico-linguistic modeling1 emphasised the connection with programming in logic; the present paper describes the use of these models to determine the sources of information needed to support planning activities. Here there is no direct connection to programming, and the aim was an improvement of the "information system" in the wider sense of the phrase. The term "Information Source Analysis" is used to describe the process in order to distinguish it from Wilson's4 Soft Systems "Information Requirements Analysis (IRA)" and from the narrowly defined "User Requirements Analysis" found in software engineering. Both of these are founded on an input-process-output model (such as a data flow diagram or process model) while Information Source Analysis is founded on a cause and effect model. In this area the study indicates that logico-linguistic modelling can be a valuable ‘aid to thinking’ at the front end of an information system design project.

 

Cultural Factors

Although, due to staff movements, the study had little impact on the host company, the methodological findings, taken with the results of similar studies, were significant. In the area of SSM, it suggests that model development by means of an iterative stakeholder ‘debate’ is not culturally feasible in a Chinese environment. In the area of client led analysis and design, it indicates that the normal duration of such projects may be inappropriate for organisations in a highly dynamic economy.

 

Contents

The paper divides into four main sections. As the findings of the study are mainly methodological, the first section (Background) gives an account of SSM in the context of information systems design. The authors’ objectives are to capitalise on the strengths of SSM and to identify, and develop remedies for, its weaknesses. Given this, an extensive discussion of what the authors’ consider to be strengths and weaknesses is necessary.

The second section (The Project) is mainly concerned with a chronological account of the model building process and how the recommendations for change were arrived at.

The third section (The Cultural Context) contains reflections on the project. It gives an explanation of the particular events in terms of the wider environment.

The methodological nature of the findings means that the evaluation of results is a complex issue. The fourth section (Evaluation) separates out a number of different issues in order to determine which aspects of the project were successful and which were not.

 

BACKGROUND

The authors’ believe that there are deep seated problems with the generally accepted methods of information system design and that current issues in the relevant literature do little to resolve these fundamental problems. Therefore, it is necessary to look back at the historical roots of the problem. It is against this background that the real significance of Wilson’s pioneering work in the use of SSM for information system design can be appreciated. While Wilson’s method solves two of the problems connected with the traditional methods, two fundamental problems remain.

Following Wilson there has been considerable work on connecting SSM to information system design (Avison & Wood-Harper5, Lewis6, Savage & Mingers7, Merali8, Miles9, Jayaratana10). However, although the methods advocated by some of these authors may be improvements, they do not resolve the fundamental problems overlooked in Wilson’s method. Wilson, therefore, remains the benchmark.

 

Problems with Traditional Methods

The well established methods of information system design, such as Structured Methods, Information Engineering and SSADM (Structured Systems Analysis and Design Method), enjoyed considerable success in the 1970s. However, these methods suffer from a number of limitations that have become more apparent in the 1980s and 90s.

Firstly, feasibility analysis is narrowly focused. Traditional methods, generally, proceed from the point where a decision to build a computerised information system has been made. They do not adequately address the issue of whether an information system, or what type of information system, will be a practical solution to the organisation’s problems.

Secondly, they are limited to the computerisation of transactions (simple bureaucratic procedures such as order processing, payroll and stock control). Although simple management information can be obtained as a by-product, they cannot be used to produce sophisticated decision support systems or systems with an artificial intelligence capability.

Thirdly, traditional methods work by modelling existing documents and manual procedures. They give no guidance about how to proceed in a green field situation.

Fourthly, they assume that the users know, and can precisely specify, what information they require.

 

Wilson’s Method

Checkland’s Soft Systems Methodology (SSM) employs three modelling devices i.e. rich pictures, root definitions, and conceptual models of human activity systems. The root definitions and conceptual models are built by stakeholders themselves in an iterative debate organised by a facilitator. The strengths of this method lie, firstly, in its flexibility, the fact that it can address any problem situation, and, secondly, in the fact that the solution belongs to the people in the organisation and is not imposed by an outside analyst.

SSM can be seen as a problem structuring method and as such an SSM project has no fixed outcome. The end result might be that the problem simply disappears or that the unstructured problem turns into a structured problem that is tractable to other methods. In Checkland’s11 practical work the results have tended to be fairly general - a change of thinking in the organisation that might be manifest in the establishment of new organisational objectives, new strategy or a decision to restructure along general lines.

If the type of solution has already been determined then there is no need to use SSM. However, this does not prevent SSM from being used to produce detailed results. In 1984, Wilson published an account of two downstream developments of Checkland’s SSM. "Organisational Mapping" showed how a conceptual model of a desirable human activity system could be expanded and compared with a similar model taken from an organisational chart to produce detailed plans for restructuring. "Information Requirements Analysis (IRA)" showed how the SSM conceptual models could be developed into a detailed information system design. IRA calls for the addition of two modelling devices: "Information Categories" which show the required information inputs and outputs from the activities identified in an expanded conceptual model; and the "Maltese Cross" a matrix which shows the inputs and outputs from the information categories and shows where new information processing procedures are required. A completed Maltese Cross is sufficient for the detailed design of a transaction processing system.

 

The Significance of Wilson’s Work

Wilson’s method has the capacity to solve two of the four problems encountered with established methods. Firstly, as the SSM conceptual models are not intended to represent the existing system there is no problem with green field situations. The final conceptual models (those that remain at the end of the debate) are models of a desirable, not an actual, state of affairs. SSM treats every situation as a green field. Wilson’s method has, therefore, great advantages over established methods if an information system is required for a new enterprise.

Secondly, SSM can be used to determine whether a computerised information system is a suitable solution to an organisational problem. SSM aims to build systems which are, to use Checkland’s term, culturally feasible and systemically desirable. As a type of systems analysis (in the broad sense of the term) it is capable of identifying the areas where information needs to be improved and the general type of information system required i.e. management support, transaction processing or data storage.

Wilson offers a unified method which can assess the feasibility of building an information system, identify the type of system required and then, if a transaction processing system is required, proceed to detailed design.

 

Feasibility analysis

Sometimes information systems problems are clear cut and the solution obvious. In these cases a thorough feasibility analysis may be unnecessary. However, information systems problems are often unstructured problems. The members of an organisation may be aware that their existing system is slow and inaccurate. But it is not always, or even usually, sensible simply to determine why a system is slow and inaccurate. The problem might lie in the source of data, the existing data processing procedures, in data storage, or in data retrieval or in a mismatch between the information system and the activities it is intended to support.

Thorough systems analysis is required to find out where the problem lies and to determine if a computerised system can provide a solution. Unfortunately this is not always done. A typical scenario is that when an organisation experiences information systems problems, outside consultants are called in to offer a bid to provide a new system. These consultants usually offer a standard solution in terms of, say, new payroll, order processing and stock control systems. It is only after a contract has been signed that the consultants begin detailed systems analysis. Such systems analysis is severely limited: firstly, it is limited in scope because it is only concerned with the area relevant to the pre-determined solution; secondly, it will be limited to a certain narrow type of analysis depending on the pre-determined platform (e.g. data flow diagrams will probably be used if the consultants are building a third generation processing system, entity-relationship modelling if they are building a fourth generation data-based system). This limited systems analysis is not likely to solve an information system problem that is caused by the source of the data or by a mismatch between the system and the activities it is intended to support.

Wilson’s method has not become very popular and this might be explained by the fact that it is generally perceived as just another way of building a transaction processing system. It should, in fact, be regarded as a method of systems analysis in which a transaction processing system is just one of many possible outcomes.

 

Logico-linguistic Modelling

Gregory’s logico-linguistic method1,2,3 was developed to solve the problems encountered with the established information system design methods by building on the strengths of SSM. While Wilson’s method solved two of these problems, two remained. Wilson’s method is restricted to the design of transaction processing systems and provides no facility for building other types of information system such as decision support systems or knowledge based systems. His method also assumes that the people in the organisation know what information is needed to support their activities. This shortcoming is particularly striking because his method always calls for new activities to be included in the model.

These shortcomings can also be found in other methods linking SSM with information system design. The methods advocated by Avison & Wood-Harper, Lewis and Savage & Mingers all call for using SSM as a front end to traditional methods for designing transaction processing systems with implementation in a third or fourth generation language. Therefore, they cannot meet the challenge of artificial intelligence and systems for high level decision support. Only the logico-linguistic method, with its fifth generation solution, has the logical power to do this.

The initial impetus to the development of logico-linguistic modelling was a concern with the theoretical problem of how an information system can have a connection to the real world. This is a problem in both SSM and established methods because none of them base their information system design on a model of the real world. Wilson’s designs are based on a notional conceptual model and structured methods, for example, is based on models of the movement of documents. Even when the information output from the system does correspond to the real world there is the further problem that the real world changes. Neither Wilson’s nor the established methods specify any mechanism, either in the software or in the management of system, whereby changes in the real world which affect the truth value of the system’s output can be recognised. Systems maintenance relies on user requests, but this assumes, and the assumption is unwarranted, that the users will always know when the system’s output is false.

The solution to this theoretical problem also goes a long way to solving the other two, more generally recognised, problems. The solution calls for the addition of an empirical component and a falsification mechanism. If the stakeholders do not know what information is needed to support activities, this fact will become evident when they try to build the empirical component. The empirical component will also indicate the direction for research that will identify the required information. This combined with a falsification mechanism enables the models to be used for the construction of knowledge based systems with learning capability, thereby increasing the number of possible solutions that can follow from SSM analysis.

Although logico-linguistic modelling was developed to solve problems in the transition from SSM to information system design, there are good indications from student projects, where it has be used to address a wide variety of problem situations, that it can be useful as a general method of system analysis.

The essential arguments behind logico-linguistic modelling are analytic and follow, a priori, from general epistemological premises. As such they are not open to refutation by experience and, in fact, these arguments have never been challenged. However, Gregory also claimed that his theoretical findings indicate a practical method of information system design. This contention is empirical and has been challenged. Klein has suggested that logico-linguistic models are too complex to be used for stakeholder driven modelling. This has occasioned a dialogue between Klein and Gregory12,13,14. The main finding from the Hongkong Telecom study is that it clearly demonstrates that the logico-linguistic method can be used in stakeholder driven modelling.

 

THE PROJECT

The project was an action research project which in many aspects conformed to the standard SSM modus operandi. Lau, a member of the planning staff, and second author of this paper, acted as analyst/facilitator. He constructed the preliminary models. In iterative consultation with other people in the planning team Lau developed the models into their final form. However, logico-linguistic models differ from standard SSM models, which are purely notional, in that they contain empirical elements as well as purely notional ones. The latter stages of the model building required real world research into what actually causes a plan to be successful.

The final model of the information source requirements was compared with the sources of information that were actually available to the planning department. Information that was currently unavailable or inadequately provided was thereby identified and recommendations for improvement followed.

 

The Problem Situation

Lau, a market analyst with Hongkong Telecom, was undertaking a part-time Masters degree in information systems at the City University of Hong Kong. He was interested in developing an Executive Information System (EIS) to support the activities for the Business Market Business Unit which is charged with planning the marketing of new business products.

Hongkong Telecom had previously enjoyed a franchise for the provision of all telephone services in Hong Kong. In July 1995, that privileged position ceased and for the first time the company was faced with competition. It was, however, a successful and well managed company and economic pundits did not expect that competition would do it any serious harm. Nevertheless, the market for communication technology and services is extremely fast moving in Hong Kong, and good planning for new products was vital for the company's future success.

It was not anticipated that the project would immediately result in a fully computerised EIS. Rather it was intended to undertake analysis to determine if an EIS would be suitable and if so to broadly determine its configuration. It this context SSM and logico-linguistic modelling were appropriate tools. Gregory took the role of supervisor for the project.

 

The Model Building Process

Stages 1 to 3

The project proceeded in a manner very close to the conventional seven-stage model of SSM11 although there was no attempt to rigidly adhere to the seven-stage model.

Stage 1 is entry into the situation that is considered problematical. This did not need to be undertaken in this project because the analyst was already part of the problem situation.

Stage 2 is the expression of the problem situation. This was fairly perfunctory. It comprised discussions between Lau acting as analyst and Gregory. In these discussions gave a fairly clear picture of the project. Because of this, and the fact that Lau was part of the problem situation, the drawing of rich pictures, that sometimes takes place in Stage 2, was felt to be unnecessary.

With an analyst/facilitator from outside the organisation Stages 1 & 2 are crucial and time consuming in terms of both man-hours and elapsed time. The interviews, discussions and presentation in these stages consume the time of the analyst and, probably more importantly, take up the time of members of the client organisation. Having an insider as analyst/facilitator saves this expense. The downside to this arrangement is that an insider fails to bring the fresh perspective on the problem that might be expected from an outside analyst. In the present project this was compensated by the fact that Gregory constantly challenged the analyst's assumptions and criticised his evaluation of the problem.

Stage 3 is the formulation of the root definition of relevant systems of purposeful activity. Stage 4 is the building of Conceptual Models of the systems named in the root definitions. These stages proceeded as they normally do in an SSM project. The situation was slightly unusual in that the analyst was himself one of "Actors" defined in the CATWOE analysis. The analyst produced a number of root definitions and conceptual models. These were discussed with Gregory, colleagues and managers. The root definition and conceptual model shown in Figure 1 were the ones selected as most appropriate. The conceptual model was then decomposed and each of the activities taken to a higher resolution level. This expansion of the model followed traditional SSM modelling techniques


 

See Figure 1 below

 

From this point the project began to diverge from the normal SSM path as the analyst began to use the addition arrows and logical constants to develop the logico-linguistic model. The logico-linguistic model developed gradually through iterations and discussion between Gregory, Lau, Lau's colleagues and managers. The final model is given in Figures 2a and 2b. There are a number of steps in the development of an SSM conceptual model into a logico-linguistic model. These must now be explained.

 

    

  

  See Figures 2a & 2b below

 

The logico-linguistic model

SSM models are expressed in the language of commands. The words in the bubbles in SSM models are imperatives, they instruct the reader to do something viz. "obtain this", "develop that", "study this". Commands do not have truth values (they are neither true nor false). However, tacit truth bearing statements do underlie the models. Take bubbles 1 and 2 and the arrow between them shown in Figure 1. This is underpinned by a truth bearing statement of the form "In order to obtain the existing profile of target customers, target customers must be identified". If bubbles 1 and 2 were not underpinned by such a truth bearing statement there would be no need to perform the activity specified in bubble 1.

The first step towards a logico-linguistic model is to convert the commands into truth bearing propositions. This is easily accomplished. For example "Identify target customers" in Figure 1 becomes "Customer/market need is identified" in Figure 2a. It needs to be pointed out that few of the bubbles from the original model (Figure 1) survived intact to the final model (Figures 2a and 2b). During debate and more detailed analysis most of the original elements were refined and revised. The second step is to introduce the additional connectives. These are: broken arrow, double headed arrow, AND box, OR box, ANDOR box. The solid single headed arrow remains the same (see Appendix 1).

The object of these steps is to increase the logical power of the models. This can be useful for a number of reasons. If, like Wilson, we are going to use the models as a foundation for the design of an information system intended to be informative about real world events, then the models will need to have the power to represent causal sequences. Models containing these additional connectives can, traditional SSM models cannot3. In the present project traditional SSM models were enough to build a consensus about the main business and goals of the unit. It was when the analysis proceeded to consider how the desired physical events could be brought into effect that the logico-linguistic models started to be useful.

The bubble diagram format of the model is the easiest to comprehend but there are direct equivalents in predicate logic, PROLOG or simple English1. For example, the broken arrow going into element 4 represents a sufficient condition and the box containing elements 41, 42, 43, represents conjunction. In ordinary English this could be expressed as "IF the characteristics of target customers is studied AND the cost of sales estimated and compared among different channels AND agreement is reached between a competent sales manager and marketing manager THEN an effective sales channel will be selected". The solid arrow leading out of element 9 represents a necessary condition. It states that it is not possible for all of the elements 2, 3, 4, 5, 6, 8 to be true unless accurate profitability analysis is carried out.

 

Introducing the modal operators

Logico-linguistic modelling calls for the introduction of two modal operators. "M" indicates facts about the real world and all such facts may be subject to change. "L" indicates definitional rules which are used to identify and classify real world objects and events. In the Hongkong Telecom case the introduction of the modal operators did not proceed in the manner suggested in the theoretical exposition of logico-linguistic modelling. This called for the construction of the definitional model and then the addition of factual rules. However, it was clear that the conceptual model that Lau had produced was a model of how to develop a marketing plan rather than a definition of a marketing plan. In a conventional SSM project this would have been a serious error but, as logico-linguistic models can clearly distinguish between definitions and factual rules, it was possible to formulate the definitions at a later stage.

To make this perfectly clear, traditional SSM calls for consideration of "what" is to be achieved and then consideration of "how" to achieve it. In the terminology of logico-linguistic modelling the call is for a definition of a desirable state of affairs and then a model of events that will cause that state of affairs to come into existence. In this case Lau's model was initially of "how" a marketing plan is developed(Figure 1). Later on consideration was given to "what" defines a marketing plan.

At this point it was realised that producing marketing plans was not very interesting and that the desirable state of affairs was actually "a successful marketing plan". A successful marketing plan could be defined in terms of one or more of the achievement of the stimulation target (subscription, usage or revenue), meeting the market share, achieving the customer satisfaction index target. With this definition in place, the factual elements in the model were revised in the subsequent iterations. Other definitions were then added to the model. The solid arrow between element 4.1 and element 4 represents a logically true necessary condition. In simple English it says "by definition, the sales channel cannot be effective if the sales target is not achieved".

 

Stage 5

Stage 5 consists of a comparison between models and the real world. In the Hongkong Telecom case this was achieved by producing a table (part of this is given in Table 1). The table listed the elements from the logico-linguistic model, the information required to make the element true (bring it into effect), the information currently available, the distribution channel and the inadequacy or improvement needed.

 

 

See Table 1 below

 

This stage was rather similar to the information category stage in Wilson's method. With Wilson, activities from a conceptual model are listed and the information inputs to the activities and the information outputs from the activities are identified. There was, however, a very important difference. In Wilson's method the information categories are constructed below the line between the real world and system thinking4, this indicates that they are constructed a priori. In the present case the information requirements were obtained empirically by research in the real world. Lau produced the table by looking at the records of past planning projects and questioning the people that had been involved in them. The relationship between the entries is a matter of factual truth rather than logical truth.

Elements that had an "L" connection to element 7 were not included in the table as they played no role in the causal account of how the desirable state of affairs can be achieved. Only the elements at the periphery of Figure 1, those with no arrows going into them, needed to be included because the internal elements, those with arrows going in, would, by implication, be true if the external elements were true.

In most cases the information requirements could be matched with some sort of information provision. But in many cases this provision was inadequate. Five areas of inadequacy were identified. Three of these were concerned with the internal organisation of the company but two were of a general nature and can be described here.

One was newspaper clippings which were cited as the source of information needed to support market trend identification, the study of competing products/services and competitor’s offers. The clippings were circulated on a daily basis, they were not catalogued and filed for future reference. The existing situation might help to keep staff up to date but they could not be called upon as an integral part of the planning procedure.

The other inadequacy concerned changes in the market situation e.g. demographics, economics, consumer behaviour, and was identified as information required for market trend identification. The cited source was the Hong Kong Monthly Digest of Statistics. While this provides a wealth of information it had not been determined which figures were relevant to the market for the company's products.

 

Stages 6 & 7

Stage 6 is the identification of changes that are systematically desirable and cultural feasible. In the present case this consisted of a set of recommendations. None of the recommendations involved any cultural or political feasibility problems. The only problems that would be involved in the implementation of the recommendations would be the normal ones of time and money. There were four recommendations for action:

a) The setting up of a storage cataloguing and retrieval system for newsclippings.

b) Asking the company's forecasting department to build a model of how general economic data such as employment, GDP, import & exports etc., might affect the market for the company's products.

c)Designing a standard form and establishing feedback channels from sales staff.

d)Setting up a centralised marketing database which would pool the resources of several departments.

 

Model maintenance

The distinctive feature of models that differentiate between logical and factual universals is that they facilitate testing and amendment. They not only include hypotheses about the real world but also provide criteria by which the hypotheses can be substantiated or falsified. The main hypothesis in the case model was that given a quality product with a competitive price and effective sales channel and market communication plan and back-end support and good planning management then the marketing plan would be successful. The criterion for success is that the product marketed reaches stimulation or market share or customer satisfaction targets.

If in the next planning exercise, the conditions in the hypothesis and the criterion for success are met then the model will be substantiated and greater confidence can be placed in it. If, on the other hand, the conditions of the hypothesis are met but the criterion for success is not met, then the hypothesis will have been falsified. In this eventuality the model would be in need of revision. Such revisions would consist of additions to the model - conditions that were not thought of when the model was first produced. There is no reason why the model could not be maintained indefinitely and survive through radical changes in the organisation and its environment.

This process conforms to common sense ideas. We formulate rules to explain events in the world, we find exceptions to the rules and then formulate new rules to accommodate the exceptions. While this framework is common in the physical sciences it is comparatively rare in many areas of management science. In information system design methodologies, for example, the notion of falsification simply does not exist. In the computerised information systems built by these methodologies the implicit factual rules cannot be shown to be false by particular facts, if the system goes wrong there is no mechanism to detect the defective rule. Error detection mechanisms are concerned only with logical consistency not with consistency with real world facts.

 

THE CULTURAL CONTEXT

Hong Kong and Cantonese

As a venue for a case study, Hong Kong has a significance far beyond its size. Hong Kong has one of the world most successful economies and one of the world’s highest standards of living. It is generally described as a "fast pace" society in which change is continuous and very little remains static for very long. Hong Kong has, traditionally, been described as a bridge between China and the West. The vast majority of the Hong Kong’s population are ethnic Chinese who’s native language is the Cantonese dialect. However, English is (for the moment) the official language. Almost all executives and professionals and most clerical workers are reasonably proficient in English. They are also very familiar with (and may in some cases embrace) Western ideas, values and modes of behaviour.

This synthesis of influences is most striking in the linguistic behaviour of University educated Hong Kong people. They will normally talk to each other in Cantonese but write down what they say in English. There are difficulties in writing down Hong Kong Cantonese because it has absorbed a lot from English and this cannot be easily represented using Chinese ideograms.

In the Hongkong Telecom case, Lau produced models in English but discussed these with his colleagues in Cantonese. Reports of these conversations were written directly in English. Hong Kong people are so proficient in these linguistic acrobatics that there is no reason to believe that the meaning of the models were in any way compromised. The models can be taken as fully representative of what was thought. The significance of Cantonese as the medium of discussion lies in the cultural and behavioural ramifications.

The behaviour of educated Hong Kong people tends to change depending on whether the social context is Western or Chinese. This often leads Western people to the mistaken belief that the values and normal modes of behaviour of most Hong Kong people are always exactly the same as their own. A good indication of which tendency is in operation is the language that is being used. If they are talking in Cantonese the behavioural context will tend to be Chinese, if they are talking in English the behavioural context will tend be Western.

 

Chinese Values

Westerners find some Chinese values, such as respect for teachers, easy to recognise because it is not that long ago that similar values existed in Western society. Other values are difficult to recognise because they do not conform to, and in many cases are antithetical to, what has existed in the history of Western culture.

Some values are so ingrained that they are hardly ever questioned. For example in the West, "telling the truth" goes back to the Ten Commandments and the Greek ideal. In Chinese, and many other Eastern societies, "avoiding confrontation" is a similarly ingrained value. The problem here is that, in the Chinese system of values, avoiding confrontation is often considered more important than telling the truth (that is, the truth as it is understood in the West, see Appendix 2).

In a context that involves Western and Chinese elements "a debate" can involve a head on clash of values. For a Westerners a debate tends to be considered constructive and beneficial. When people have adversarial positions a debate will help the truth to emerge to the benefit of all parties. For Chinese the display of adversarial positions is inherently bad and they will tend to subvert the truth in order to avoid such displays.

At this point a word of caution is required because generalisations about cultural groups can be very misleading. It must be understood that the above remarks are intended to describe cultural tendencies rather than hard and fast rules.

 

The SSM "Debate"

In SSM the building of root definitions and conceptual models proceeds by means of an iterative debate involving the stakeholders and facilitator. It is assumed that much of this work will take place in group meetings in which the stakeholders will express their individual viewpoints. In these circumstances it can be expected that the viewpoints of two or more stakeholders will often be, prima facie, antagonistic. In these cases the facilitator is charged with producing a model which accommodates the different viewpoints.

In a Chinese context this cannot be expected to occur. In group meetings, Hong Kong people are likely to avoid expressing antagonistic viewpoints in order to avoid confrontation. If this happens then the main purpose of the debate, to bring out different viewpoints and to accommodate them, will have been defeated.

In the Hongkong Telecom case no group debate took place. Lau built the models on the basis of one on one discussions with colleagues. This was not a thought out strategy but just seemed the appropriate way to proceed. Lau is a Hong Kong Chinese and Gregory has spent more than fourteen years working in the Far East. For both authors it is has become natural to modify Western methods to fit in with Asian behavioural patterns. This modification procedure becomes so ingrained that the protagonists become unaware of it. Indeed, it was not until he discussed the case with other academics in Britain that Gregory realised that in terms of the debate the Hongkong Telecom case had deviated considerably from the normal SSM method.

 

Staff Movements

Hong Kong’s high growth and minimal unemployment rate has helped to produce an environment in which staff movements between companies is extremely rapid. Government figures indicate that the staff movements among executives and professionals are nearly 5% per year15. This has a knock on effect and rapid staff movements between departments in large organisations are also rapid.

In the Hongkong Telecom case the Head of the Business Market Business Unit was transferred a few weeks before Lau finished his report. Within three months Lau and all the other members of the unit planning team had also been transferred. The study, report and recommendations appear to have had no impact on the organisation. In these circumstances the lack of impact was almost inevitable. SSM is intended to work because the stakeholders produce and "own" the solution. If the original stakeholders have all moved on then the new staff will not own the solution and nobody can be expected to implement it.

Although there are no published figures on the duration of SSM projects, six months of elapsed time is an appropriate benchmark. SSM evolved through a learning cycle in which the Masters Degree in Systems at Lancaster University played an important role. Most of the Masters students completed an action learning project lasting approximately six months. Much of the development of SSM was based on what was learned during these projects.

Out of six SSM projects, of six months duration, recently completed at City University of Hong Kong four have been badly affected by the movement of important stakeholders. It seems that if SSM projects are to be expected to produce a "hard" change in Hong Kong organisations, the project time will need to be significantly reduced.

 

EVALUATION

In the present section the authors argue that SSM is primarily a problem structuring method rather than a problem solving method and that the criteria used to evaluate problem solving methods cannot be applied to an SSM project. The same holds good for the Hongkong Telecom project where logico-linguistic models have been used for problem structuring rather than detailed problem solving.

Evaluation of SSM projects

There are two questions that regularly occur in the context of SSM projects: one is "what difference did it make?" the other is: "could the same result have been achieved by other methods?".

In the event of an SSM project producing little physical change in an organisation, the standard line of defence is that at the end of every SSM project the stakeholders are better informed about the problem situation. Even if no physical or organisational changes have been made the people in the organisation will have had, to use Checkland’s expression, a "change of thinking" and a "learning experience", the capacity of the organisation to handle future change may have been enhanced. This can be called a "soft change", as opposed to a "hard change" which would require some change in an organisation's facilities, equipment, structure or procedures. Some academics find soft unsatisfactory and consider that a method is valid only if it brings about significant hard change in the organisation.

However, the authors consider that it is a mistake to assess a method’s validity on the basis of actual hard change. A method is valid if it provides the right answer, and the right answer for some organisational problems is not to make any hard changes. If the answer is not to make hard changes then some people might argue, post hoc, that the study has been a waste of time. The point here is that prior to the study it was not known that the best policy was not to make hard changes. Also we can argue that if the study had not been conducted then the organisation might have tried to implement non-feasible hard change with disastrous results.

The situation is analogous to a feasibility study in which the findings are negative. It can be argued of any given negative feasibility study that it has been a waste of time and money. Post hoc this argument is correct; but compared to a situation where a non-feasible project is implemented the savings brought about by a negative feasibility study can be enormous.

Criticism of SSM projects on the basis of the fact that results could have been achieved by other methods is another invalid post hoc argument. Suppose a company is having problems with profits. A SSM study might locate the problem in manufacturing and come up with recommendations for the revision of manufacturing procedure. Alternatively an SSM study might locate the problem in the company’s information system and come up with a design for a new transaction processing system. In the first case a sceptic might argue that the same results could have been achieved using a time and motion study, in the second case the sceptic would argue that the same result could have been achieved using structured methods. The point is that a time and motion study could not have identified an information systems problem and structured methods could not identify a problem with manufacturing procedures.

There is an important methodological issue here. A design method can be evaluated by its products, that is, by the success of each of its individual applications. But this is not possible with a problem structuring method. Problem structuring is a logical procedure. As such it is to be evaluated, primarily, in terms of internal consistency and completeness, and, secondarily, in terms of its range of application. A design procedure can be shown to be invalid by means of empirical evidence. This is not the case with a logical procedure.

 

Evaluation of the Hongkong Telecom case

The project did not produce any hard change in the host organisation. If it had been a commercial information systems consultancy project it would have been a failure. As an action research project it can be considered a success. A considerable amount was learned about the use of SSM in a Hong Kong organisation and about the application of logico-linguistic modelling.

The authors consider that the lack of impact was a result of staff movements. This indicates that anyone intended to use SSM for commercial consultancy in Hong Kong, or a similar environment, should proceed with caution. Careful estimates of project duration and staff movement rates in the client organisation are indicated. The same principle applies to organisations in other fast paced economies and to fast paced organisations worldwide.

The use of logico-linguistic models was successful in that it was shown that they can be employed to produce results that could be implemented. The stakeholders had no difficulty in understanding the models or in making suggestions for their improvement. Logico-linguistic models are more complex that other models in the field and many people have had difficulty in understanding the abstract exposition of them that has appeared in previous papers. However, when a model of a problem area is built and explained to stakeholders that are familiar with the area, they have little difficulty understanding it. Similar results have been found in teaching logico-linguistic modelling. Students have difficulty with the theory but their comprehension increases dramatically when they are tasked with building a model of a problem they are familiar with.

Whenever a new method in the field of management studies is advocated the question of whether it is capable of giving results that other methods could not regularly presents itself. In the present case it is quite possible that the same recommendations might have followed if the study had conducted using Wilson’s method. It is also possible that they would not. However, this is not the main point; the main point is that logico-linguistic modelling is more powerful (this has been demonstrated a priori in previous papers1,3)than Wilson’s method and capable of giving solutions that Wilson’s method is not capable of.

The question that needs to be resolved is "when is it more appropriate to use a less powerful method?" The use of a less powerful method will be justified in circumstances where the less powerful method is easier or quicker to use and where it is known that the less powerful method is capable of producing the optimal solution. The main purpose of this paper is to show that that logico-linguistic models can be used. It remains debatable where other methods found in information system design or in soft operational research are easier to use. It has been stated earlier13 that logico-linguistic models are close to natural ways of thinking and are not as difficult as they may at first appear to be.

Another factor is that, although the initial model is complex, as the model increases in size and detail there is no increase in diagrammatic complexity. When Wilson’s models grow they tend to become a confusing spaghetti of dozens of bubbles and arrows4 which is very difficult to read. The case is similar with other methods used for information system design, for example, Jackson's System Development16(which also fails to distinguish between necessary conditions, sufficient conditions and necessary & sufficient conditions). With this method the models begin simply but as the models increase in detail more and more notational devices need to be introduced until the models become far more complicated than a logico-linguistic model.

A second problem is the question of knowing whether a less powerful method will give the optimal solution. A less powerful method of analysis will fail to recognise the case where a more powerful solution is required. The exceptions here are cases that regularly occur and where a simple solution has been found to be optimal by testing it against more complex solutions. Operational research abounds with such cases. However, these are structured problems and as such SSM does not apply (see Appendix 3, for more details on these points).

The question has been raised as to whether the Hongkong Telecom case needed an SSM analysis. It was suggested that a marketing expert could have come up with the same recommendations. The main point here is that the problem as originally conceived was an information system problem. The original intention was to build an Executive Information System because it was thought that the problem was with information processing. It was not until the analysis was underway that it was discovered that the problem lay in the source, not the processing, of the department’s information.

While there is a plethora of mathematical and statistical tools available to provide market information, much of the information marketing managers require is unstructured. They are often willing to pay for certain types of information without being able to explain why they need it. This in turn often makes it difficult to understand exactly what they want. Indeed it was the practical problem of providing clients with the marketing information they required that originally prompted the academic research that lead to the development of logico-linguistic modelling. Problem structuring methods are just as relevant in market planning as in any other area.

 

CONCLUSIONS

Logico-Linguistic Models

One of the main outcomes of the study is its contribution to the debate between Klein and Gregory12,13,14. Klein has suggested that logico-linguistic models are too complex to be used for stakeholder driven modelling. Klein’s last words on the subject were "Both Gregory's argument and my own are theoretical ones...The practical implications of human information processing needs to be examined in the context of action research programmes..."

The project described here was a classic action research project. The findings are that the stakeholders did not have any serious problem understanding the logico-linguistic models. In spite of the fact that they had no training or previous familiarity with logic, they seem to have found them no more difficult than the traditional SSM models. This demonstrates that logico-linguistic models are not too complex to be used in stakeholder driven modelling.

Of course, it would be foolhardy to infer from this that it is generally the case that these models can be built by non-professionals. Logico-linguistic modelling is only in the early stages of practical application. Nevertheless, preliminary results are encouraging.

 

Chinese Cultural Environment

The study suggests that SSM cannot be expected to have generally application in Hong Kong, China and many other places in the Far East unless it can be applied in a non-confrontational mode. Lau’s method of one-on-one discussion seems workable. However, there could be some problems here. In some circumstances, where a lot of iteration is required, it might be a more time consuming method. Also one might speculate that the commitment to change might be far less than it would be after stakeholders had voiced agreement during a public group decision making process.

 

Staff Movements

The study indicates that speeding up the SSM process is desirable if it is to have general application in environments like Hong Kong. The area in which improvement is required is not the initial stages, e.g. entering the problem situation and building models appropriate to the problem, but the later stages of building a consensus model and making recommendations for hard change.

 

APPENDIX 1: LOGICAL CONNECTIVES USED IN LOGICO-LINGUISTIC MODELING

"AND" Box. Represents conjunction. If "AND" is true, all the elements in the box must be true.

"ANDOR" Box. Represents inclusive disjunction. If "ANDOR" is true one or more of the elements in the box must be true.

"OR" Box. Represents exclusive disjunction. If "OR" is true one and only one of the elements in the box must be true.

Broken Arrow. Represents implication or a sufficient condition. A broken arrow going from p to q means that if p is truethen q must be true.

Solid Arrow. Represents implication or a necessary condition, however, the direction of implication is the opposite to that of the broken arrow. A solid arrow going from p to q means that if q is true then p must be true.

Double Headed Arrow. Represents mutual implication. A double headed arrow between two elements means that if one is true then the other must be true.

"L" Modal Operator. Indicates that the relation is true as a matter of logic.

"M" Modal Operator. Indicates that the relation is true as a matter of fact.

 

APPENDIX 2: TRUTH

Theories of truth belong to the area of study known as philosophical logic or the philosophy of logic. The idea of truth implicit in this paper is that truth is a logical value ascribed to propositions or statements. This is commonly accepted among academics, as can be seen in from introductory works such as Grayling17 and Haack18. It can also implicit in the earliest textbook on logic i.e. Aristotle's Prior Analytics19. It is a concept of truth that corresponds closely to the use of the word "true" in ordinary English.

Whether there is the same concept of truth in the Chinese language would be very difficult to determine with any form of academic precision. Not only would this require a philosophical analysis of written and spoken Chinese (the two are not the same), it would also require the study of the Chinese philosophical heritage. The Chinese philosophical literature is not easily understood by modern Chinese people and it is notoriously difficult to translate into English. This sort of work is far beyond the scope of the present paper.

 

APPENDIX 3: LOGICAL POWER

What is meant by "logical power" here is simply the power of the underlying calculus. Predicate logic is more powerful than propositional logic because it has been proven that is capable of solving more problems than propositional logic. In the same way predicate modal logics are more powerful than ordinary predicate logic. In earlier papers Gregory1,3 argued that SSM conceptual models are a subset of propositional logic. In terms of information systems these might be adequate to produce transaction processing systems but not knowledge based systems.

The present paper claims that, in information system design, the use of convention SSM models could only be optimal in circumstances where it was known from the outset that a transaction processing system would be the solution to the stakeholders' problems. In the context of soft change it is doubtful that it is meaningful to call any result "optimal". For example, soft change includes an increase in the understanding of the situation on the part of the stakeholders. As every situation is connected in some way or another to every other situation (the Butterfly Effect, see Gleick20), understanding can, in theory, be increased infinitely.

The epistemological distinction between statements of definition and statements of fact is so fundamental, that the authors believe that the use of logico-linguistic models will lead to understanding of the problem situation which is better than that which can be achieved using conventional SSM models. However, quantitative evidence of this, if such is possible, could not be provided until more case studies have been conducted.

 

REFERENCES

1. F. H. Gregory (1995) Soft Systems Models for Knowledge Elicitation and Representation J.Opl Res.Soc., 46, 562 - 578.

2. F. H. Gregory (1993)SSM to Information Systems: A Wittgensteinian Approach. Journal of Information Systems 3, 149 - 168.

3. F. H. Gregory (1993) Cause, Effect, Efficiency and Soft Systems Models J.Opl Res.Soc., 44, 333 - 344.

4. B. Wilson (1990) Systems: Concepts, Methodologies and Applications. John Wiley. Chichester.

5. D. E. Avison & A. T. Wood-Harper (1990) Multiveiw: An Exploration in information Systems Development. Blackwell Scientific Publications. Oxford.

6. P. J. Lewis (1993) Culture and IS Planning Present New Challenges for Data Analysis and Modelling. Proceedings of the Conference on the Theory, Use and Integrative aspects of IS Methodologies. British Computer Society Information Systems Methodologies Specialist Group.

7. A. Savage & J. Mingers (1996) A framework for linking Soft Systems Methodology(SSM) and Jackson System Development (JSD). Journal of Information Systems, 6 (2), 109 - 130.

8. Y. Merali (1992) Analytic Data Flow Diagrams: An Alternative to Physicalism. Systemist, 14 (3), 190 - 198.

9. R. Miles (1992) Combining ‘Hard’ and ‘Soft’ Systems Practice. Systemist, 14 (2), 62 - 66.

10. N. Jayaratana (1994) Understanding and Evaluating Methodologies. McGraw-Hill. London.

11. P. B. Checkland & J. Scholes (1990) Soft Systems Methodology in Action. John Wiley. Chichester.

12. J. H. Klein (1994) Cognitive processes and operational research: a human information processing perspective J.Opl Res.Soc., 45, 855 - 866.

13. F. H. Gregory (1995) Over simplistic cognitive science J.Opl Res.Soc., 46, 274 - 275.

14. J. H. Klein (1995) Over-simplistic cognitive science: a response. J.Opl Res.Soc., 46, 275 - 276

15. Census and Statistics Department, Government of Hong Kong. Special Topic Report No.14. Jan 97.

16. M. Jackson (1983) System Development. Prentice Hall, New Jersey.

17. A. C. Grayling (1990) An Introduction to Philosophical Logic. Duckworth. London.

18. S. Haack (1991) Philosophy of Logics. Cambridge University Press. Cambridge.

19. Aristotle (1989) Prior Analytics. Translated by Robin Smith. Hackett Publishing Company. Indianapolis.

20. J. Gleick (1988) Chaos: Making a New Science, Penguin Books. Harmondsworth.

 

Figure 2a
Figure 2a
Figure 2b
Figure 2b
Table 1
Table 1

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