EDI IMPLEMENTATION: A BROADER PERSPECTIVE1 Caroline Chan School of Business and Electronic Commerce Monash University, Churchill, Victoria 3842, Australia Phone: (61-3) 9902 6159, Fax: (61-3) 9902 6524 Email:
[email protected] Paula M. C. Swatman Director of Interactive Information Institute RMIT University, Melbourne, Victoria 3001, Australia Phone: (61-3) 9660 5272, Fax: (61-3) 9660 2387 Email:
[email protected] ABSTRACT EDI has become a popular area for academic research since the late 1980’s. Yet most of the studies which have been undertaken have tended to focus either on the strategic planning and requirements elicitation for EDI, which take place before the system is implemented, or have been concerned with issues such as the integration of EDI into internal applications. In this paper we look at the implementation of EDI in a broader way, considering the implementation process in terms of both a ‘change process’ as well as technological diffusion and taking into account the factors influencing that process. We suggest that a model based on this view will describe the implementation process in the real world and allow the creation of a more comprehensive picture of the events which take place during the implementation process.
1. INTRODUCTION Electronic Commerce (EC) has changed the way organisations perform their activities and Electronic Data Interchange (EDI), which is a part of EC, is crucial to companies in a number of industry sectors (including automotive, retail, apparel and transport). Since it was first implemented in the late 1960’s, EDI has formed the backbone of many industries’ supply chain management strategy and has been acknowledged as contributing benefits such as reduced order lead-time, improved level of service to customers, reduced labour costs, fewer errors in ordering, and even more efficient business processes. Despite these benefits, firms still have problems in implementing EDI successfully. Kwon and Zmud (1987) stated that a better understanding of the Information Systems (IS) implementation process and the factors contributing to this process would enable organisations to develop a more effective implementation strategy. This view supports the earlier argument by Ginzberg (1979), who suggested that the better the handling of the implementation process, the greater the chances of successful implementation. There are at least three reasons why a model of the EDI implementation process should be built: 1. Prior studies in this field were more concerned with implications of adoption of the technology (see, for example Iacovou, Benbasat and Dexter 1995, Howells and Wood 1995). These studies which unquestionably enrich our understanding of the factors influencing EDI adoption, do not provide much detail concerning the subsequent stages of the EDI implementation process itself. Our understanding of the whole process of the implementation is still very limited. 2. The need to understand the implementation process is fundamental to the strategic planning of EDI. Although some researchers (ie. Galliers, Swatman and Swatman 1995) suggest employing strategic information system planning for effective EDI implementation, the discrepancy between ‘the plan’ and ‘the fact’ may decrease the usefulness of such planning, because lack of understanding may prevent the plan 1
This paper was published in the proceedings of "Bled'98" -- 11th International Conference on Electronic Commerce, Bled, Slovenia, June 8-10, 90-108.
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from being implemented in practice. A model based on ‘the fact’ will increase awareness of users when implementing the system. 3. Information systems implementation (including EDI) occurs within a complex, changing environment involving many factors that create ambiguity, so that cause and effect relationships can be difficult to discern (see, Corbitt and Brown-Parker 1996, Goodman and Griffith 1991). A process model will provide a better understanding of the implementation which, in turn, will result in more effective handling of the activities or tasks to be performed. This paper will explore critical factors influencing the EDI implementation process based on empirical studies, explaining the process of EDI implementation, and finally suggesting the development of a model of the EDI implementation process which has a broader perspective and takes into account different views of the process.
2. EDI IMPLEMENTATION Electronic Data Interchange (EDI) is the exchange of documents between organisations in standardised electronic form from one computer application to another computer application (Clarke 1992), EDI can also be defined as computer-to-computer exchange of business information between organisations or various units within organisations (Arunachalam 1995). In the early days of EDI research, most of the research in this field focused on the benefits of EDI (see, for example, Meier 1992) and the ways in which EDI implementation would deliver many benefits from cost reduction to providing better customer service (Emmelheinz 1992). These studies then expanded to include the integration of EDI (Swatman 1993, Cox and Ghoneim 1996), often involving detailed analysis of a case study and the extent of EDI usage in organisations (Massetti and Zmud 1996). A parallel theme in EDI implementation research concerned the factors contributing to success and failure of the implementation (see, for example, Roberts 1995). Studies investigating the factors influencing the adoption and implementation of EDI include the relationship between the influencing factors and the level of success of the implementation (see, for example, Benbasat, Bergeron and Dexter 1993; Doukidis and Fragopoulou 1994; Premkumar, Ramamurthy and Nilakanta 1994; Williams 1994; Iacovou, Benbasat and Dexter 1995; Mackay 1995; and Drury and Farhoomand 1996). These authors have identified several factors which affect the adoption and implementation of the technology which we now discuss in some detail. Implementation is a comparatively recent topic for researchers interested in the overall EDI phenomenon. At least until very recently, the majority of authors investigating this aspect of EDI have tended to focus upon influences and implications of EDI implementation. Only a very few studies have taken into account the various stages of the implementation process for example the work of Doukidis and Fragopoulou 1994, which was carried out in Greece. These authors investigated the introduction of EDI when it was forced upon a smaller company by an influential trading partner. The study examines the relationships between four groups of factors which generally influence the adoption and implementation of EDI: • technology related factors • infrastructure related factors • organisation related factors; and • organisational environment related factors toward the stages in the implementation process: • adoption • implementation; and • evolution. The results of this study make it quite clear that ‘the rule’ (the factors generally influencing adoption) does not apply to these ‘forced’ companies, in which the implementation is initiated by the other party. The case study suggests that EDI implementation is, thus, not a straight-forward process but rather one in which the various stages and processes can be influenced and affected by factors such as level of proactivity/reactivity.
3. FACTORS INFLUENCING THE EDI IMPLEMENTATION PROCESS
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Many studies into EDI implementation have emphasised the technical characteristics of the application. These studies usually based on the theory of innovation diffusion (Rogers 1983) or information systems (IS) theory in general. By contrast, some authors (see, for example, Lucas 1986, or Emmelheinz 1992) believe that EDI implementation should be viewed in more managerial, rather than technical, terms. In this paper we suggest considering the factors influencing EDI implementation from both perspectives technical and managerial. Here, we identify three groups of factors influencing the process of EDI implementation:
3.1. Technological Factors Previous studies (Pfeiffer 1992; Premkumar, Ramamurthy and Nilakanta 1994) indicated that the characteristics of the innovation (technology) influence the implementation and adoption of EDI. In meta analysis of a general innovation study (not specifically EDI), Tornazky and Klein (1982) found that three innovation characteristics - compatibility, relative advantage and complexity - are consistently found to be related to the adoption of an innovation. In terms of EDI as an inter-organisational system, Premkumar et al (1994) argue that communicability, cost and elapsed time should be added to these original three characteristics when considering this specific technology. Premkumar et al (1994), who examine the relationship between characteristics of EDI (complexity, compatibility, relative advantage, cost, communicability and elapsed time) and the various aspects of the diffusion of EDI using a survey of 201 companies, found that three characteristics (compatibility, relative advantage and elapsed time) are major predictors for adaptation, diffusion and implementation success of EDI. We have summarised the details of their results in table 1. Table 1. A comparison of EDI characteristics and diffusion2 Innovation Characteristics
Technical Compatibility
Adaptation Internal Diffusion External Diffusion Implementation success
+
Organisationa l Compatibility
Relative Advantage
Cost
+ +
+ +
+ +
Elapsed time
+ +
+
(+) Indicates positive relationship The results of this type of study (technical characteristics) are not always consistent for example, the study by Premkumar et al (1994) found that complexity did not relate to any aspects of diffusion (including adaptation), although other authors have found complexity to be one of the factors inhibiting EDI adoption (Pfeiffer 1992; Cragg and King 1993). On the basis of earlier studies of EDI implementation, the following technology-related factors can be related to the implementation process and level of success. Compatibility Compatibility is the degree to which a technology is perceived as compatible with the existing values or needs of the organisation (Rogers 1983). In their study of innovation, Klein and Sorra (1996) found that innovationvalue fit are important factors in the effectiveness of systems implementation. Furthermore they identify three possible strategies to foster the innovation-value fit: • Persuade employees to participate in the decision to adopt the innovation • Educate employee about the need for innovation for organisational performance, and 2
Adapted from Premkumar et al (1994)
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•
Let the innovation-value fit increase over time.
In terms of EDI, compatibility usually refers to hardware, software, data format, or structure. Incompatibility in any of these factors could inhibit the process of implementation (Howells and Wood 1995). Premkumar et al (1994) also found that technical compatibility affects the diffusion of the technology internally and externally, as well as the success of the implementation. Complexity Complexity refers to whether the innovation or technology is difficult to understand and use, sometimes described in the innovation or systems literature as ‘ease of use’ (Borton and Brancheau 1994). In general, studies of innovation diffusion suggest that the simpler the innovation is to understand, the more quickly it is adopted (Rogers 1983). In EDI, complexity involves the understanding of the technology and system, which can be simple or complex depending on the use of the application. For example, a simple application (i.e. generating a purchase order) and relationship (one to one transaction), may be ‘relatively’ easy to understand, but when the application is fully integrated into the organisation’s business transactions and processes and involves multiple trading partners (which may have different hardware, software and standards), it will become a very complex operation and this could affect the implementation process. In fact, some studies (Pfeiffer 1992; Cragg and King 1993) found this factor among inhibiting factors for the adoption of the technology or, in other words, complexity is found to be negatively related to implementation adoption and implementation. Relative advantage Relative advantage is the degree to which an innovation is perceived as providing better benefits than other technology/innovation. These benefits may be measured in economic terms, or in terms of convenience or satisfaction. In the case of EDI, this variable is usually measured by direct benefits such as reduced transaction costs, reduced inventory levels and indirect benefits such as increased efficiency, better customer service, improved trading partner relationship, and greater market competitiveness. Some authors (Rogers 1983; Premkumar et al 1994; Borton and Brancheau 1994) have suggested that relative advantage has a positive relationship with adoption and implementation - which means the greater the benefit of the technology, the more quickly it is adopted/diffused. Based on the literature, so far only one study (Doukidis et al 1994) has found this factor not important – it is notable, therefore that this study observed the type of EDI implementation which is forced upon the organisation. Communicability Communicability of an innovation is described as the degree to which aspects of an innovation may be passed on to others (Rothman 1974). In terms of EDI, Premkumar et al. (1994) believed that information on EDI (or EDI knowledge) should be passed to various functional areas within an organisation as well as among its trading partners. Although the results of this study suggest that communicability is not related to adoption and implementation, we suggest that this factor should be considered during EDI implementation studies in addition to other factors (such as environmental factors) because training is fundamentally inter-twined with communicability. In general innovation study, this factor is assumed to be positively related to the adoption and implementation of an innovation (Tornatzky and Klein 1982). Cost Cost of technology or innovation refers to the initial cost and also to operational cost and usually is assumed to be negatively related to the adoption and implementation of the innovation. Users usually evaluate the cost against the benefits before adopting the technology. In terms of EDI, the cost will include the set up cost of hardware and software (EDI translation and communication); telecommunications/transmission costs and also training costs. The cost of an innovation, while in many cases influencing the initial adoption (see for example Saunders and Clark 1992, Premkumar et al 1994, Howells and Wood 1995, Drury and Farhoomand 1996), does not seem to affect the implementation process (Premkumar et al 1994). This is also supported the literature reviewed by Tornatzky and Klein (1984) who found that from ten studies of cost, only five (3 positively related and 2 negatively related) reported a correlation between cost and adoption-implementation. Elapsed time Elapsed time relates to the time needed to adopt and utilise the new technology. As implementation is a process
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which can extend over quite a long period of time, the consideration of elapsed time as one of the factors influencing implementation is quite reasonable. Users need to learn how to use the new technology to perform their tasks. In the case of EDI, which needs to be fully integrated to gain optimal benefits, the elapsed time may take several weeks, months or even years. Although only one study (Premkumar et al 1994) suggests considering this factor when studying the EDI implementation process, it is reasonable to include this factor among other factors influencing the implementation process, since the implementation process is related to a period of time. The survey from Premkumar et al’s study suggests that elapsed time is positively related to the implementation process, so that the longer the elapsed time, the better the diffusion of the technology.
3.2. Organisational Factors As we mentioned before, implementation of IS (including EDI) involves more than just technological problems. In fact, empirical studies show that organisational factors influence the implementation process rather more than technological factors (see, for example Land, Le Quesne and Wijegunaratne 1992; Emmelheinz 1992). The following organisational factors should be considered when studying the implementation process. Management involvement In many empirical studies, management support and involvement are considered very significant influences in adopting and implementing EDI. Drury and Farhoomand (1996), for example, found that management attitude is the most important issue among the barriers to EDI adoption, followed by the cost of the system. A study of BHP Steel undertaken by Swatman in 1993 found that a top-down approach, where senior management took the initiative in implementing EDI, was a successful approach. Top management support for EDI implementation is also suggested by a number of other authors (see, for example, Emmelheinz 1992, Hendry 1994). A European study (Roberts 1995) also found top management support to be a critical success factor for EDI implementation. User resistance User resistance to change may result from personal insecurity or the threat of being by-passed by the implementation of technology (such as EDI or automatic trading transactions). Cragg and King 1993 identify a reluctance to use sophisticated hardware and software or applications among inhibitor factors for IS adoption. In order to deal with this problem, organisational development concepts such as overcoming user resistance using socio-technical approaches and addressing behavioural problems have been suggested to improve the likelihood of successful implementation (Desanctis and Courtney 1983). In modelling the implementation process of EDI, we suggest taking this factor into account in the conceptual model, as this is likely to affect the successful uptake of the implementation process. Human resources (expertise) A lack of expert human resources (see, for example Cragg and King 1993; Doukidis, Smithson, and Lybereas 1995) has been identified as one of the factors influencing IS implementation. Lack of the necessary expertise occurs frequently in small and medium enterprises and is a major factor in resistance to EDI implementation (Parker 1997).
3.3. Environmental/ “Climate” Factors A positive organisational climate is necessary to ensure a successful implementation (Klein and Sorra 1996). Factors such as ensuring employee skills in innovation use, providing incentives for the user and removing obstacles to innovation use are needed to improve the chances for EDI implementation success. Trading partner participation EDI is an inter-organisational information systems application and implementors depend heavily on other parties (such as trading partners, technical experts, etc.) to achieve successful implementation. Iacovou, Benbasat and Dexter (1995) for example, studied EDI in small organisations and found that partner imposition is one of the most critical adoption factors in small organisations. Training Drury and Farhoomand (1996) and Parker (1997) found that lack of training is a barrier to EDI adoption in adopting organisations. Providing employee skills in the use of the technology and providing on-going support during implementation are obvious ways of handling this problem. Training also provides communication for
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better understanding of the technology (see technological factors: communicability). Roberts (1995) also suggests training for all players in the EDI implementation, not just the operational users, to achieve a successful implementation.
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4. THE IMPLEMENTATION PROCESS AS DIFFUSION OF TECHNOLOGY AND CHANGE PROCESS. As with the implementation of other new technologies, EDI implementation can be seen either as an innovation/technological diffusion process (Goodman and Griffith 1991; Cooper and Zmud 1990; Klempa 1994; Premkumar 1994) or as an organisational change process (Ginzberg 1979 1981; Zmud and Cox 1979) Studies of technological diffusion tend to emphasise the initiation and diffusion of the technology, which occurs during the early stages of the implementation process. These studies emphasise the spreading of the ‘new’ technology to other parts of the organisation which, in the case of EDI diffusion, can be divided into internal diffusion into the organisation and external diffusion outside the organisation (Premkumar et.al. 1994). ‘New’ technology in the sense we use the term for this paper, refers to the application of technology in an organisation for the first time, regardless of whether it has been used by other organisation or not (Nord and Tucker 1987:6). Based on this notion then, IS (including EDI) implementation refers to the organisational effort to diffuse an appropriate information technology within the user community (Kwon and Zmud 1987). Although the emphases of innovation diffusion theory and change process theory differ slightly, both share a similar conception, which is the conception of change. Van de Ven, Angle and Poole (1989, p.32) point out that: “A theory of innovation is fundamentally a theory of change in a social system”. IS implementation studies based on change process theories (Zand and Sorensen 1975; Schultz and Slevin 1979; Ginzberg 1979, 1981; Zmud and Cox 1979) usually emphasise the beginning and end of the process. These authors believe that IS implementation is best described as a process of organisational change that extends over a considerable period of time. Based on this notion, implementation starts from the very beginning of the idea to implement the system and ends when a new system has been accepted and is being used as a routine. This means that in EDI implementation, the process begins when the organisation decides to adopt the system and ends when the implementation has already been incorporated or integrated into the organisation. In many cases, the theory of change utilised by IS research is grounded in the early theories of change (Lewin 1952; Schein 1961; 1972) which state that organisational change consists of three stages: • Unfreezing; which involves activities to reduce the forces that maintain the current behaviour such as introducing/giving information that shows the benefits of the new system(s), • Moving; where the activities involved are related to developing the new behaviours, values and changes through the changing of organisational structure and business processes, • Refreezing; the step used to stabilise or “freeze” the new state or behaviour. This model of change provides a general framework for understanding the change process in the organisation and how to manage it. Applying this to EDI implementation, we find that EDI implementation process basically shares the common processes of change, except that because of EDI’s different characteristics, implementation should be viewed in a broader sense which incorporates the inter-organisational relationships involved. The first IS implementation study based on the change process was carried out by Zand and Sorensen (1975) These authors suggest that high levels of activity conducive to the three stages described above are associated with greater implementation success, while high levels of activities antithetical to the requirements of these stages are positively related to project failure. Some years later, Ginzberg (1979) focused a major study of IS implementation on the notion of organisational change theory. Using a change model that divides the implementation process into seven stages scouting, entry, diagnosis, planning, action, evaluation and termination (Kolb-Frohman 1970) he undertook a survey of the attitude of managers and management scientists in 11 organisations and 29 projects. Based on this study, Ginzberg found that success in implementation was related to the quality of handling of the implementation process. He also found that the last stage (termination) is the critical stage for the success of the implementation. This result supported the findings from Zand and Sorensen (1975), which suggest that the refreezing stage (the process stabilising the change and reinforcing new behaviour patterns), may well be the most critical stage in the process.
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Several other researchers have studied the IS implementation process, including Schutz and Slevin (1979), Kwon and Zmud (1987), Cooper and Zmud (1990), Goodman and Griffith (1991), and Klempa (1994) all of them effectively supporting the argument that a more comprehensive model of IS implementation should be built. The research results of all these authors suggest that a model of the implementation process should be built to enhance its understandability . This discussion of the theories and empirical studies into IS implementation makes it clear that no single theory (neither the theory of innovation diffusion nor that of change process in isolation) can fully capture the details and complexities of the EDI implementation process. Electronic Commerce systems (and, even more, EDI systems) are inter-organisational systems which need to be extensively diffused/integrated into the organisation’s own internal and external organisational systems to achieve optimal benefits (Swatman 1993). Table 2 shows the models employed by the various researchers who have studied IS implementation in their attempts to understand the IS implementation process. Table 2: Models of IS implementation Lewin-Schein Model (used by Zand-Sorensen) Unfreezing
Moving
Refreezing
Kolb-Frohman Model (used by Ginzberg) Scouting Entry Diagnosis Planning Action Evaluation Termination
IT Implementation Model (used by Cooper-Zmud) Initiation Adoption Adaptation Acceptance Routinisation Infusion
In the real world implementation of EDI however, the stages of the change process are not quite so clear. Organisations implementing EDI often follow a specific set of guidelines for implementation (in Australia, for example, such a set of guidelines was developed by the EDI Council of Australia (EDICA) which later became known as ECA and, most recently, as Tradegate/ECA). In guidelines of this sort, the major activities of the implementation process are suggested, such as: Developing the implementation strategy, establishing the project team, performing the audit, training the users, testing the system, and selecting trading partners. Each activity usually consists of a variety of tasks, which have to be performed by the participants to accomplish the process. The problem with such guidelines is that they do not relate to the organisation’s own, particular situation, nor can they itemise the possible problems which may arise during the implementation. For example, one major barrier for EDI implementation is trading partner-related problems such as compatibility of the system, different data formats, and lack of willingness to implement the new system. This means that organisations performing those activities/tasks may find some difficulties, constraints or even risks for which they are unprepared and to which they may not be able to find a solution. Kwon and Zmud (1987) suggested that companies endeavouring to develop better strategies needed to gain an understanding of what really happens during the implementation process. The way in which the people, the technology and the processes interact during the implementation and the factors which affect the implementation process are issues which need to be addressed before we can answer the question of how to implement EDI successfully. To answer those questions, we suggest developing a model of the process of EDI implementation based on existing theory, empirical studies and real world implementation experiences.
5. MODELLING THE EDI IMPLEMENTATION
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Although a number of authors have investigated the process of EDI integration ( for example, Swatman 1993; Cox and Ghoneim 1995) little work has been done on modelling the process of EDI implementation. From the discussion above, we can see that the EDI implementation process is a messy and complex problem. Two critical issues in the implementation process are: • Factors influencing the process of IS implementation; and • The broader process of IS implementation, which involve diffusion of the technology (internally and externally) as well as the change process itself. Due to the complexity of the problem, we need to find a suitable approach to modelling the process. Choosing such an approach is not easy, however, because the approach should enable the refinement of the model, by comparing what has been done (or known) with the real world situation. An example of such an approach is the Soft Systems Methodology (SSM) developed by Checkland (1981), which offers an approach that compares our thinking about the system (“system thinking”) with the real world situation. Using this approach, we expect to be able to capture a more comprehensive picture of what happens during the implementation process. In assessing the most appropriate approach, we need to think carefully about the characteristics of the study. The problem context under consideration is modelling the EDI implementation process in organisations and this involves the handling of the technology and the tasks to be performed for a successful implementation (which means the technology is fully utilised and the users are satisfied). Based on that notion, we suggest that the characteristics of the model be related to human activities in an organisation, utilise socio-technical and socio-organisational viewpoints and, most importantly, be related to a process of change and diffusion of technology (which occurs over a comparatively extended period of time). These characteristics lead us to suggest several guidelines for choosing and designing the approach to modelling the EDI implementation process: • Taking into account the different viewpoints of the actors (and the departments, areas, etc.) involved in the implementation of EDI within an organisation; • Identifying activities and tasks need to be performed during the implementation process, the constraints and risks in performing these activities; • Since the implementation process is not a discrete event or activity which can be studied at a single point in time, a longitudinal method should be used in observing the real world implementation; and • Utilising data gathering methods that allow deeper understanding of the implementation situation (ie. case studies). In summary, we suggest that the process of developing an appropriate modelling technique should use an approach such as that illustrated in Figure 1, where the literature and empirical studies are used as a basis for the model and, through case studies, the model will be refined continuously to develop a comprehensive and realistic model that represents the situation in real world EDI implementation.
Literature Review
Empirical studies
Develop Conceptual Model
Data gathering (i.e. case studies)
EDI Implementation process model
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Figure 1. Developing an EDI implementation process model
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6.
CONCLUSION
Implementation of EDI is not just a realisation of a plan it is a messy and complex process involving many factors and activities, which can not always be managed and performed in the most effective manner. Although the benefits of EDI implementation are significant to those industries where EDI is widely used, these benefits will not be gained automatically without successful implementation and to successfully implement EDI, we must first understand the process and the factors influencing that process. It is not sufficient to claim (as many consulting organisations have done) that implementing the technology successfully is all that is required. In this paper, we have suggested that the implementation process of EDI be presented in the form of a more realistic and comprehensive model that involves the factors influencing the adoption, as well as the detailed process of the implementation itself. This means that the EDI implementation should be seen as more than merely the adoption or diffusion of an innovation it must be viewed as an organisational change process takes into account the involvement of the people and the technology during the process. The influence of all relevant factors during each stage of the process should be considered in such a model, especially the factors influencing the last stage of the process (termination or refreezing). While we are not yet able to identify an appropriate modelling technique, we recommend the use of longitudinal case studies to model the process, because of the time-related issues involved in EDI implementation. One approach which might well prove appropriate is the Soft Systems Methodology (SSM), which allows for multiple viewpoints, for the inter-connectedness of technology and organisational factors and which caters for longitudinal implications. No matter which modelling technique we finally select, our approach must allow for the refinement of the model through real-world observation.
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