DYNAMIC MODELLING TO ASSESS THE BUSINESS VALUE OF ELECTRONIC COMMERCE George M. Giaglis, Ray J. Paul Department of Information Systems and Computing Brunel University, UK {George.Giaglis, Ray.Paul}@brunel.ac.uk
Georgios I. Doukidis Department of Informatics Athens University of Economics and Business, Greece
[email protected]
ABSTRACT Prior to adopting Electronic Commerce (E-Comm), organisations need to assess its real business value and compare it to the costs of the associated investments. The intangible nature of most E-Comm benefits may render the development of a business case very difficult in practice. In this paper, we present a case study of E-Comm investment evaluation. Computer-based models of the business processes to be affected by E-Comm were developed and dynamically simulated to assist in gaining insight on the real benefits and dangers associated with the planned business change. Drawing on the results of the case study, we discuss the potential of Dynamic Process Modelling to support assessment of E-Comm business value.
1. INTRODUCTION Business-to-Business Electronic Commerce (E-Comm) applications have become an increasingly common vehicle for facilitating communication and information exchange between firms. However, despite the great publicity, even hyperbole, surrounding E-Comm, existing practical applications have not always been able to deliver in practice the business benefits they promise in theory. This has resulted in lower adoption rates than initially expected. Historically, the growth of E-Comm has been more an evolution rather than the much-anticipated revolution. One of the main reasons that may explain the reluctance of organisations to adopt E-Comm on a great scale may be the significant amount of organisational change required. Indeed, E-Comm applications have been described as bearing a close resemblance to Business Process Re-engineering (BPR) efforts. Kalakota and Whinston (1996) point out that “the broad goals of reengineering and
electronic commerce are remarkably similar: reduced costs, lower product cycle times, faster customer response, and improved service quality”. Such a radical change will necessarily pose a fundamental question to managers and decision-makers: can the benefits achieved by employing EComm outweigh the costs needed for setting up and maintaining the necessary infrastructure and applications? E-Comm applications may account for significant expenditure, especially for small and medium firms: hardware, software, telecommunications, training, and business re-organisation, to name a few. Although these costs are relatively easy to estimate as long as a specific business scenario has been envisaged, intangible benefits assessment is usually problematic, albeit very significant (Brown 1994). The primary thesis of this paper is that the main benefits an organisation can gain from E-Comm are inherently qualitative and cannot be easily assessed a priori and be expressed in monetary terms. There exists a need for developing mechanisms that will help organisations realise the real business value of EComm applications and overcome this problem of measurement. This paper reports on a real-life case study where discrete-event simulation models of business processes were developed to assist two companies to identify the problems faced in their co-operation, formulate appropriate solutions based on E-Comm applications, and realise the expected impacts of these solutions on key business performance indicators. The next section will introduce the problem of evaluating E-Comm investments and explain why Business Process Simulation (BPS) constitutes an effective mechanism that can overcome many evaluation problems. The subsequent sections will report on a practical application of the theoretical ideas in a real-life inter-organisational setting. The approach followed will be outlined, the modelling considerations will be discussed, and results from simulation runs will be presented. Finally, lessons learned from the case study will be discussed, and the suitability of BPM and BPS to support E-Comm investment evaluation will be assessed.
2. E-COMM INVESTMENT EVALUATION The process of detecting, measuring, and comparing the costs and benefits associated with the introduction of information systems (like E-Comm applications) is generally known as information systems investment evaluation. The problem of pre-implementation (ex ante) evaluation of Information Systems (IS) is one of the oldest problems in Information Technology and still continues to puzzle researchers and practitioners alike (Farbey et al 1993). E-Comm applications are merely instances of specific classes of IS, namely Inter-Organisational Information Systems (IOS). As such, E-Comm investments are equally as difficult to evaluate as any other type of IS. In order to evaluate an E-Comm investment, the costs and benefits associated with it should be measured and compared. Costs are relatively easier to measure, at least the direct ones, usually during the feasibility study and the development of specific project proposals. However, in comparative terms, it is significantly more difficult to obtain hard evidence of the expected benefits.
Brown (1994) distinguishes between hard and soft benefits of IS. Hard benefits are a direct result of the introduction of the information system and are easily measured (for example, the reduction in data-entry staff made possible by the introduction of an electronic ordering system). The problem of measurement is mainly related to the remaining three categories of so-called “soft” IS benefits: intangible, indirect and strategic (see Figure 1).
Attributable to the IS
Weakly Indirect
Strategic
Hard
Intangible
Strongly Non-Quantifiable
Quantifiable Measurable
Figure 1. Different types of IS benefits Intangible benefits can be attributed to particular applications but they cannot be easily expressed in quantitative terms. Benefits of this type arise, for example, with the introduction of an EDI system to allow a company’s customers to place their orders electronically. A second-order effect of such a system might be locking-in customers by making it more difficult to them to switch to another non-EDI capable supplier. This is a clear business benefit, but how can the company predict the real effect of the EDI system on customer loyalty and its bottom line implications on revenue generation? Indirect benefits are potentially easy to measure but cannot be wholly attributable to the proposed investment and can only be realised as a result of further investments, enabled by the new system. For example, the implementation of the EDI system mentioned above would provide the infrastructure on which further E-Comm applications can be subsequently built at reduced costs. Although this is a potential benefit made possible by the initial EDI system, it cannot be realised unless further applications are also successfully introduced. Finally, strategic benefits refer to positive impacts that are realised in the long run and usually come as a result of the synergistic interaction among a number of contributing factors. They are the outcome of, for example, a new business strategy or a better market positioning of the organisation, which can only be partially attributed to a given E-Comm application. Such benefits are notoriously difficult to quantify in advance due to their very nature and to the risk associated with their realisation. In order to evaluate their Information Technology investments, most companies use simple accounting techniques, notably cost-benefit analysis
(CBA) or Return on Investment (ROI) (Ballantine et al 1994, Willcocks and Lester 1991). However, when trying to apply any of these financial techniques for assessing a particular E-Comm investment, one of the main problems will be the difficulty of identifying and measuring the intangible, indirect, and strategic benefits expected by the system. One way to overcome this problem of measurement is to employ some quantitative technique that will allow for studying the business processes affected by an E-Comm investment. Thus, we can obtain some tangible, quantifiable results on the expected impact of EComm applications on business performance. These results can then feed an established IS evaluation method such as CBA or ROI. The underlying notion behind this argument is simple. E-Comm investments do not usually constitute an end in themselves, but are generally part of a wider business reorganisation in which E-Comm plays a specific role (significant or otherwise). In such cases, it is important that the investment in the wider business change is evaluated and not the IT investment alone (Farbey et al 1993). In other words, it makes sense to concentrate our efforts on the wider business processes that surround the E-Comm investment and study the impact of E-Comm using the business process as the fundamental unit of analysis.
3. BUSINESS PROCESS SIMULATION (BPS) Discrete-event Business Process Simulation (BPS) offers a theoretically attractive mechanism for modelling and studying complex phenomena in quantitative terms. Simulation of business processes constitutes one of the most widely used applications of operational research (Law and Kelton 1991) as it allows for understanding the essence of business systems, identifying opportunities for change, and evaluating the impact of proposed changes on key performance indicators. Perhaps more importantly, it allows decision-makers to experiment with alternative business configurations without the need for disrupting the actual system operations. Simulation models have been used in various practical business modelling applications (for example, Nissen 1994, Lee and Elcan 1996, and Hunt et al 1997). On the subject of E-Comm and multi-organisational modelling, Yarden (1997) discusses a simple simulation meta-model structure for modelling Electronic Commerce payment transactions over the Internet. Along the same lines, simulation models have been used (Mylonopoulos et al 1995a, 1995b, Giaglis 1996) to assess the expected benefits of inter-organisational changes made possible by the use of Information Technology at an industry-wide scale. Ninios et al (1995) report on a similar setting and present the development of an object oriented modelling environment to facilitate the use of industry simulation models. The above examples show that Business Process Simulation has already been identified as a suitable tool for business modelling and has been successfully employed in individual applications. Taking the idea of BPS a step further, we propose the design of business simulation models that will incorporate the effects of IT applications (such as E-Comm) in models and will
allow for experimentation and analysis of alternative investments. Simulation offers a number of distinct advantages for that purpose: a) Business process simulation does not only depict the immediate environment of the information system, but also addresses the wider business processes that the system affects. Therefore, BPS models can be used to assess the additional expenditure incurred by processes that remain outside the scope of the information system. According to Farbey et al (1993), such non-automated processes, however trivial, may account for a large percentage of the total process costs. b) Simulation models can facilitate comparisons between heterogeneous investments since they can be used for studying the organisational impact of a wide variety of diverse business decisions (both IT and non-IT related). c) Simulation models can provide the benchmarks of what can be achieved from a particular investment. These benchmarks can be subsequently used to provide a measure of the success of the actual implementation. d) Once in use, simulation models support a culture of measurement within the organisation that allows for continuous evaluation of opportunities to support process improvement (MacArthur et al 1994). In the following sections we will present a real-life case study that was employed in order to test the hypothesis that BPS can effectively support the evaluation of IT investments, with emphasis on E-Comm applications.
4. THE CASE STUDY The study refers to a business change effort jointly undertaken by two collaborating organisations in Greece: a major pharmaceuticals company (that will henceforth be referred to as ‘ABC S.A.’) and one of the regional distributors of its products (a small company that we will call ‘XYZ Ltd.’). The project aimed at assessing the potential of redesigning the trading communications scheme between the two companies and evaluating the possibility of introducing E-Comm applications for supporting the redesigned processes.
4.1. The Companies ABC S.A. is the Greek subsidiary of a well-known multinational family of companies. ABC was founded in 1974 with an initial aim to market the parent company’s products in Greece. Today the company employs more than 300 people in three sites. The headquarters are in Athens, while the plant and the warehouse are located a few miles north of the city, in Mandra. Furthermore, the company operates a smaller office in Thessaloniki (the second largest city in Greece). This office is responsible for managing ABC sales for Northern Greece. The case study presented herein was carried out within the Medical Division of ABC. This division trades hospital consumables (for example, surgical dressings, disposable surgical packs and gowns) and medical devices (for
example, blood glucose monitoring systems). Its customers include hospitals, health care organisations, networks of physicians, and the government. ABC (Medical Division) employs a network of collaborating distributors across Greece to deliver its products to customers. One of these distributors is XYZ Ltd. XYZ is a small company (employing at the time of the case study nine people, of which five are the company’s drivers) and is based in Thessaloniki. XYZ has signed, since 1993, an agreement to act as ABC’s exclusive distributor of Medical Division products for the whole of Northern Greece.
4.2. Scope and Objectives of the Study Due to the special nature of the health care business and the subsequent urgency of most customer demands, XYZ has to operate within strict deadlines regarding deliveries. Indeed, each order has to be fulfilled with 24 hours if the products are to be delivered within Thessaloniki or within 48 hours for the rest of Northern Greece. However, since the beginning of the collaboration between the two companies in 1993, it has been noted by management that the aforementioned targets are virtually never met in practice. Preliminary discussions between ABC and XYZ representatives did not result in any definite proposals for solutions. However, the two companies agreed that the problems seemed to be arising from inefficiencies in the ordering process as well as due to the inability of XYZ to maintain an optimal level of product inventory to support order fulfilment. The extant communication and information exchange scheme between the two companies was deemed to be cumbersome and inflexible. Since these inefficiencies represented a major source of customer dissatisfaction it was decided that a more in-depth study of the problem should be sought and the possibility of introducing electronic communications along the value chain should be examined. In this context, the study presented here was conducted. The objectives of the study were: (a) To examine in detail the existing processes of customer order fulfilment, invoicing, and warehouse management, where co-operation between ABC and XYZ is taking place; (b) To propose alternative processes by which the existing problems could be alleviated; and (c) To evaluate the potential of introducing appropriate E-Comm applications to facilitate the communication between the two companies.
4.3. The Business Processes The overall process to be considered in this case study is the Order Fulfilment Process (OFP). This can be thought of as the collection of activities that occur from the time a customer places an order until the time this order is fulfilled (i.e. the customer has received the products and the corresponding invoice). Further to ordering and invoicing, the OFP encapsulates the warehouse management operations that may affect the order lead-time.
Figure 2 shows the parties involved in the OFP as well as the existing communication between the participants (both physical and informational exchanges). The OFP consists of three inter-related, but more or less independent of each other, sub-processes: (a) The Order Taking Process (OTP). This process is triggered every time a customer places an order and ends when the order has been authorised and is ready for further processing by XYZ. (b) The Invoicing Process (IP). This process is triggered for every customer order and ends when the customer receives an invoice corresponding to that order. The main requirement here is that ABC management want to reduce as much as possible the time it takes to invoice customers, as delays may have significant effects on ABC’s cash flow availability. (c) The Warehouse Management Process (WMP). This process refers to XYZ's task to maintain an appropriate level of inventory in its warehouse to be able to efficiently fulfil customer orders.
Orders Invoices
Customers THESSALONIKI & NORTHERN GREECE
Orders
Deliveries Orders
Stock Replenishment
ABC Warehouse and Plant ATHENS Documents, Information
Orders
Order Confirmation
XYZ Office and Warehouse THESSALONIKI
Backorders
ABC Salesmen
ABC Sales and Marketing THESSALONIKI
Invoices
Copies of Despatch Notes
Out of Scope
Out of Scope
ABC HQ ATHENS Products
Out of Scope
Figure 2. Information and material exchanged in the OFP
4.4. Problems of the existing situation The major problems identified by both ABC and XYZ management during preliminary discussions on the performance of the aforementioned business processes can be summarised as follows: a) Excessive Order Lead Times. Customer orders are usually fulfilled much slower than the stated targets (24 to 48 hours). This holds especially true for backorders. b) Poor internal and external customer service. Long lead-times result in customer dissatisfaction that is expressed through a growing number of complaints about delivery delays.
c)
Excessive Invoice Lead Times. The time it takes for the invoice to reach a customer is unnecessarily long, resulting in poor cash-to-cash cycle for ABC. d) Out of balance inventory and excessive stock levels. In order to ensure that orders could be fulfilled without any need for backordering, ABC warehouse managers have followed a policy of over-stocking XYZ warehouse. However, this has caused considerable costs to XYZ due to the need to maintain large inventories. Furthermore, it is questionable whether this policy has managed to achieve much more than camouflaging the internal process inefficiencies. e) Duplication of work. XYZ use a warehouse management software package to monitor their stock. ABC warehouse managers also need to know the level of XYZ inventory in order to be able to schedule inventory shipments. ABC uses a different warehouse management software package. Apart from duplicating work (double key-in of Despatch Notes in the two systems), the stocks reported by the two systems do not always match due to data entry errors that cannot be traced. f) Information Sharing. Because of incompatibilities between ABC and XYZ information infrastructure, the companies have been relying in paper forms for exchange of information. Apart from duplication of effort and slow processing times, this has resulted in building a culture of limited information sharing between the two partners. Poor, incompatible, sometimes non-existent IT infrastructure has been identified as one major contributor to the problems faced by ABC and XYZ. It was therefore decided to examine the potential of adopting electronic messaging applications to facilitate the exchange of information between the two companies. The companies’ management wanted to introduce EDI to support exchange of data between the firms. It was also believed that such a system could be the starting point for building a wider Inter-Organisational Information System (IOS) that will strengthen the links between the companies and effectively make them work as a single virtual enterprise. ABC also wanted to use this project as a pilot for introducing similar systems to foster closer relationships with their other distributors across Greece. However, such a change would necessarily involve significant expenditure on behalf of both firms. The main problem facing the management was to evaluate the magnitude of benefits that could be achieved by the proposed change in order to assess whether it would surpass the associated investment costs. It was decided to pursue a more in-depth study of the processes and to employ Business Process Modelling and Simulation.
5. BPS MODEL DEVELOPMENT A four-phase approach was followed for modelling and analysing the processes under consideration. The approach is presented in Figure 3.
Phase 1 Data Collection
Phase2 AS-IS Modelling
Demand Patterns Activity Schedules
Phase 3 Option Development & Experimentation Feasible Options (Brainstorming)
New Business Processes Static Process Modelling (Flowcharting)
Activity Lead-Times
TO-BE Model Development
Activity Priorities Entity Life-Cycles Resource Schedules
Phase 4 Decision Making & Recommendations
IT Infrastructure
Organisational Impact (costs & benefits) Dynamic Process Modelling (Process Simulation)
Experimentation (Test against criteria)
Feasibility
Impact
Implementation Schedule
… … … …
Figure 3. The Four-Phase Modelling Approach
5.1. Data Collection Interviews with key process participants (management and employees) of both ABC and XYZ were conducted in order to capture the process essence and decompose the OFP into its component activities. The knowledge elicited by the interviews was used to define the boundaries of the process and the model(s) to be developed. A major task during this stage was to obtain relevant, quantitative process data to populate the simulation models to be developed in the next phase. Data were collected via the interviews, document and other evidence observation, as well as direct measurement in the workplace.
5.2. AS-IS Modelling An off-the-shelf packaged software solution was selected for implementing the simulation models. The main requirement of the decision-makers was that the process modelling software should be easy to use in order to allow the companies to continue using the models after the end of the project. An evaluation of different process modelling and simulation packages was carried out and Process Charter (by Scitor Corporation) was selected for modelling. An initial static process model was developed in Process Charter to depict the activities within the OFP. Figure 4 depicts this model. Next, the model was populated with quantitative data obtained during the Data Collection phase. Further data requirements emerged during the model development, and some additional data collection was deemed necessary. The resulting dynamic model was validated, mainly by obtaining the decisionmakers’consensus that the model was an adequate representation of the existing processes and the results obtained by the initial simulation runs bore a close resemblance to the actual process performance.
1 Customer
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XYZ Receive Phone Order
XYZ Receive Fax Order
ABC Receive Phone Order
ABC Receive Fax Order
Salesmen Receive Orders
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Send Orders for Authorisation
Authorise & Forward Order
Deliver Orders for Authorisation
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ORDER TAKING PROCESS (OTP)
Check & Key-in Order
WAREHOUSE MANAGEMENT PROCESS (WMP)
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Complete
Check Inventory
14 Create Backorder 20 15 Create Backorder List
Receive Products & Update Inventory
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INVOICING PROCESS (IP)
10 Issue Despatch Note (DN)
Create DN List
21 16
26 Issue Despatch Note (DN)
Send Backorder List (Post)
Send DN List (Post)
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Pick, Pack & Schedule Shipment
Process DN List (Delay)
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18 Schedule Shipment
19 Send Shipment (Delivery)
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Deliver (rest)
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Done
XYZ
11 Pick, Pack & Schedule Shipment
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Deliver (Thes)
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Issue Invoices
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30 Receive Invoices & Schedule Shipment
32
13
Done
Done
ABC Thessaloniki ABC Athens
ABC Salesmen
Customers
LEGEND:
Figure 4. The Static Process Model (Flowchart) The model was run for a (simulated) 6-month period. The results from the simulation runs are summarised in Table 1 (only the key performance indicators are included due to space constraints). It is clear that the existing processes are far from producing results within the stated management targets. Orders are fulfilled in around 60 hours (2 ½ days), while backorders need an average of nine days to reach the customers. It is worth noting that 95% of the order leadtime and 70% of the backorder lead-time are actually waiting times. In order words, orders and backorders spend more of their time waiting for something to happen rather than being processed. The same also holds true for invoices, where the lead-time is over 11 days with over the half being idle waiting time.
Table 1. Key Performance Indicators (AS-IS Model) Average Time Average Wait Max Time 58h 39min 55h 31min (95%) 142h 06min Order 215h 23min 150h 42min (70%) 334h 50min Backorder 269h 38min 153h 41min (57%) 602h 50min Invoice
5.3. Option Development and Experimentation The objectives of this phase were to analyse the AS-IS model, develop alternative process structures to alleviate the problems identified, and transform these structures into process models to identify the impact of each solution on key performance indicators. The model analysis brought to light a number of reasons that contribute to the inefficiencies identified. The major problems identified by AS-IS model analysis are shown in Table 2. Table 2. Major Problems of the Existing Process Problem I
II
III
Description The existing policies for forwarding backorders and Despatch Notes to ABC Athens in batch are cumbersome and inflexible. If the information systems of the two companies were able to communicate electronically there would be no obstacle to forwarding these documents as soon as they are created (possibly in the form of an EDI message), thereby avoiding two major process bottlenecks. There seems to be a bottleneck of orders in XYZ warehouse, before inventory is checked (activity #9 in Figure 4). The reason behind this may be that the existing one employee in the XYZ warehouse may be unable to cope with the existing demand. The order authorisation policy results in unnecessary delays as orders have to be exchanged between ABC and XYZ in a time consuming fashion that results in little or no added value to the process.
Based on the results of the AS-IS modelling phase, alternative process configurations were developed and discussed with ABC and XYZ management for acceptance and feasibility. Four alternative scenarios were developed and modelled with Process Charter. The scenarios were then simulated and results were compared with the AS-IS model to evaluate the impact of changes on key performance indicators. Table 3 shows the scenarios modelled and their relation to the problems of the existing processes. Table 3. TO-BE Scenarios Scenario A B C D
Description EDI is used to facilitate exchange of backorders, despatch notes, and invoices between ABC and XYZ. Same as Scenario A, plus XYZ employs two employees at the warehouse. Same as Scenario A, plus XYZ is also empowered to authorise the orders they receive. Same as Scenario A, plus XYZ employs two employees at the warehouse and is also empowered to authorise the orders they receive.
Problems Tackled I I+II I+III I+II+III
The results from the scenario runs are summarised in Figure 5. The simulations produced a number of quantitative data but, due to space constraints, only the results regarding the three main key performance indicators (average waiting times for orders, backorders, and invoices) are presented here. ORDERS Average Time 58
60
48 50
41
37 40
30
30 20 10 0 AS-IS
Sc A
Sc B
Sc C
Sc D
BACKORDERS Average Time 250
INVOICES Average Time
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68
59
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Sc A
Sc B
Sc C
Sc D
50 0
0 AS-IS
Sc A
Sc B
Sc C
Sc D
AS-IS
Figure 5. Key Performance Indicators in AS-IS and TO-BE models
5.4. Decision Making and Recommendations The purpose of this phase was to evaluate the results of the experimentation and develop a set of options that would be acceptable by the decision-makers. Simulation provided valuable insight into the ability of the proposed solutions to alleviate the problems faced by the two companies. In terms of the key performance indicators we can note the following: a) Orders: The results were somewhat surprising. Contrary to what was expected, the adoption of EDI did not result in the time savings for order fulfilment initially envisaged by ABC and XYZ. The adoption of EDI alone (scenario A) resulted in only a 17.2% reduction of average order fulfilment time. The resulted 48 hours on average needed to fulfil an order under Scenario A only marginally meet the set targets. However, simulation made it possible to realise that other (non technology-supported) changes could provide a solution to the inefficiencies of the process. Thus, the modification of the order authorisation policy and employing an extra employee at the XYZ warehouse, when combined with the EDI system
(scenario D), resulted in a 48.3% saving of order fulfilment time, resulting in an acceptable average of 30 hours to fulfil an order. b) Backorders: EDI here provided an efficient mechanism for overcoming the obstacles raised by poor co-ordination and information exchange between ABC and XYZ. The adoption of EDI (scenario A) reduced the average backorder fulfilment time from 215 to 122 hours (43.3%). Although this time is not within the specified targets, it certainly provides a huge relief to ABC and XYZ management. If it further assumed that employing EDI will lead to fewer discrepancies amongst stock data held by the two companies and hence to better forecasting and replenishment strategies, it is safe to expect that actual backorder fulfilment time will be further reduced in practice because of fewer backorders actually being placed. c) Invoices: Again EDI proved, as expected, to be instrumental in substantially reducing the invoice delivery time. Scenario A resulted in a 74.7% reduction in average invoicing time (from 269 to 68 hours). Like backordering, the remaining scenarios B to D only marginally affect invoicing time, as expected. Further to simulation analysis, the four scenarios were further scrutinised in order to develop a detailed understanding of implementation challenges and transform hypotheses into detailed implementation plans. The requirements of each option regarding technology, people and skills were assessed and a formal cost-benefit analysis was conducted (on the basis of the simulation results) in order to evaluate the proposed investments. Based on the results of the analyses, detailed recommendations for change and implementation plans were proposed. However, the detailed presentation of these steps falls outside the scope of this paper.
6. DISCUSSION A real-life case study of business process modelling to evaluate an E-Comm investment was presented. The study focused on EDI evaluation but there is no reason to support that the same approach cannot be employed for other E-Comm applications as well. BPM and discrete-event simulation proved to be valuable mechanisms for realising the real business value of EDI. Both ABC and XYZ management were able to see for themselves and assess the costs and benefits associated with various proposed options. This hands-on experience helped them to overcome their doubts about adopting EDI and build their confidence in the technology, without bearing the risk and cost of developing prototype applications and disrupting the operation of their businesses. It was further appreciated how simulation proved that the adoption of EDI alone would only marginally improve the performance of the main process (order fulfilment time), contrary to what was initially expected. Management was able to identify, propose, and experiment with other options that would complement the EDI investment to achieve the desired results. If simulation had not been employed and the EDI application was adopted in the hope that order fulfilment times would be substantially decreased, it is very likely that the
management of both companies would be disappointed. Thus, they could develop a negative perception of the value of E-Comm in general and hence be unwilling to invest further in similar applications. Thus, the case study provided empirical evidence to support the argument that the application of BPM can provide an efficient mechanism for allowing organisations to assess the real business value of EDI. By assisting managers to overcome their hesitance about E-Comm and understand the benefits it can bring to their businesses, it is believed that critical user masses can be more easily built, thereby resulting in better adoption rates for E-Comm in general. The detailed simulation analysis brought to light that inefficiencies do not only occur in the interface between the two companies (as it was initially assumed), but also exist throughout the entire supply chain. In other words, it was not only the communication procedures between ABC and XYZ that were cumbersome and ineffective, but the same was true for some of the internal activities of the two companies. Taking this point further, the same may also hold true upstream in the supply chain, for example in the communication procedures between ABC and its parent company. It is imperative that changes are introduced in all stages of the value chain, both at intra- and interorganisational levels. ABC now envisages the development of further simulation applications to assess these points. This provided evidence that, once in use, simulation models can change the perception of organisations regarding modelling and can support a culture of continuous measurement and improvement of business processes, an argument in line with MacArthur et al (1994).
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