Managing projects front-end: incorporating a strategic early
view to project management with simulation
Karlos A. Artto *,...
Simulation modeling is introduced as a tool that
enables continuous management of the functionality of
the project product...
investment life cycle from the customer's point of view.
At the tactical and operative levels, the perspective is
limited ...
project. Economic calculations re¯ecting the ®nal
customer's Ð or investor's Ð life cycle costs with the
project product a...
Further, the cases provide more detailed understanding
of features and practical application of the discrete-
event simula...
6.2. Case example 2: de®nition of a materials handling
system
Case 2 includes a study of a new facility investment
project...
supplier and the recommendation based on the simula-
tions. In addition to the direct bene®ts, the representatives
indicat...
conducted for decisions concerning the implementation
of the logistical management scheme.
The simulation model was constr...
capacity increase in a paper mill. Later, in the manu-
facturing phase of the system, simulation was conducted
to evaluate...
World Congress on Project Management, vol. 2. Slovenia: Interna-
tional Project Management Association, IPMA, 1998. p. 506...
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Managing projects front end

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  1. 1. Managing projects front-end: incorporating a strategic early view to project management with simulation Karlos A. Artto *, Juha-Matti Lehtonen, Juha Saranen Department of Industrial Management, Helsinki University of Technology (HUT), P.O. Box 9500, FIN-02015 HUT, Helsinki, Finland Received 17 June 1999; received in revised form 1 November 1999; accepted 10 December 1999 Abstract The article introduces a project management approach, which focuses on adopting a strategic view in the project implementation process. Such strategic view means that a consideration on the purpose of the project as a whole must be maintained in the course of project implementation. This includes adopting and maintaining the focus on the functionality and operability features of the project product. The functionality simulation approach itself is well known, e.g. in system engineering design. This article puts discrete event simulation in place in the project implementation process by suggesting that it can help to introduce new insights to conventional project scope management practices. Four simulation cases are presented to illustrate empirically how the manage- ment focus is casted in a strategic way to the functionality and operability of the project product. The cases provide understanding of the use of such simulation approach in the course of the project implementation process. The suggested simulation of the func- tionality of the project product introduces a directing view to project scope management, and this way it provides directions for operative tools that are designed for putting the component parts of the project together. # 2001 Elsevier Science Ltd and IPMA. All rights reserved. Keywords: Project scope management; Simulation modelling; Life cycle management 1. Introduction This article suggests an approach that enables main- taining a strategic view on the ®nal project product during the project implementation. This approach sup- plements traditional static approaches by using simula- tion modelling for managing the functionality of the project scope. Project management literature argues that the task of project scope management is to manage the functionality of the project product Ð among some other tasks. However, the content of project scope management is ambiguous as it is often intermixed with management of the scope of work. Not only is clarity needed in project scope management, but also a focus should be brought to speci®c activities dedicated to managing the functionality of the project product already in the project implementation. The traditional investment calculations re¯ect the economic bene®ts. Disadvantages with traditional investment calculations include that they are static, and they are based on simplifying assumptions. The assumptions might not re¯ect the underlying production process in an appropriate manner. Another all too common outdated practice is the traditional design approach of constructing subsystem capacities to match conservative assumptions or worst-case scenarios. This tends to lead to substantial overcapacity Ð especially when the worst-cases are added several times on each other. The article suggests discrete event simulation as a project management tool. Such simulation approach is well-known in the system engineering design area. However, the literature does not recognize the linking of the simulation as a continuous management concern to the whole time span of project implementation. The life cycle costing applications, if used during the project process, would provide somewhat analogous but a static approach. Life cycle costing, however, focuses more on calculating the economic result of di€erent solutions than analysing the functionality of the solution. 0263-7863/01/$20.00 # 2001 Elsevier Science Ltd and IPMA. All rights reserved. PII: S0263-7863(99)00082-4 International Journal of Project Management 19 (2001) 255±264 www.elsevier.com/locate/ijproman * Corresponding author. Tel.: +358-9-451-4751; fax: +358-9-451- 3665. E-mail addresses: karlos.artto@hut.® (K.A. Artto), juha-matti. lehtonen@hut.® (J.-M. Lehtonen), juha.saranen@hut.® (J. Saranen).
  2. 2. Simulation modeling is introduced as a tool that enables continuous management of the functionality of the project product already during the project imple- mentation. The objective of this article is to put discrete- event simulation in place to the project management framework with management emphasis on project scope. The research methodology is based on empirical cases that illustrate how simulation was applied. The cases provide understanding of the project phases, where the simulation was used. The case examples are derived from production facility contexts. 2. Prioritising project objectives: managing the ultimate project result The traditional project management approach of straightforward managing of project objectives of time, cost, and scope, is criticised by Anttila et al. [1]. Anttila et al. argue that only the ®nal end result matters. Based on the reasoning above, time, cost, and resources are only constrained project objectives that are to ful®l the boundary conditions of time and cost and using the right amounts and quality of di€erent resources. How- ever, the current project management methodologies focus on management of these constrained objectives in the implementation process rather than management of something that would occur with the use of the project product in the future at the time after project completion. Turner [2] considers historical and other background factors that might serve as reasons to the `outdated' phenomenon why project managers may have especially heavy focus on managing time. Similarly, Morris [3] criticises that the traditional project management con- cept dedicated to delivering on time, in budget, and to speci®cation, is outdated since it does not suciently focus on optimising the potential commercial bene®ts of project delivery. De®ning and managing the ®nal project product that alone is of worth in the actual operations phase, is supported by the recent studies of Jaafari [4] and Jordanger [5]. Both authors criticise managing the project by traditional objectives of time, cost, and scope. As we are interested in management of the `project product' (or actually its functionality), it is useful to recognise that the closest project management sub-area to our de®nition, i.e. `project scope management', as de®ned in project management literature in general, does not focus only on management processes asso- ciated with the features of the project product. Concepts of `scope of the project product', and `scope of work' become intermixed. For example, current project man- agement standards PMBOK [6] and ISO 10006 [7] de®ne the two fundamental concepts of project scope management and Work Breakdown Structure (WBS) in the following manner: ``Project scope management is a subset of project management that includes the pro- cesses required to ensure that the project includes all the work required, and only the work required, to complete the project successfully''; ``Work Breakdown Structure (WBS) is a deliverable-oriented grouping of project elements that organises and de®nes the total scope of the project''. The conclusion is that management of the result-oriented project product and the resource-oriented project work facets become intermixed in the well known and accepted de®nitions introduced above. However, the management of solely the project product with its functionality should not be dismissed out of hand, neither conceptually nor in empirical applica- tions. Thus, this article adopts a `project product's functionality' oriented context of the current project scope management sub-area. Accordingly, the scope is de®ned here as: The scope is the sum of products and services produced in the project. The term `project pro- duct' is used as a synonym to scope. Scope contributes to the purpose or bene®t associated with the project. It includes aspects of (1) quality of the project product, and (2) performance, functionality and technical prop- erties of the project product. The implications of the scope de®nition above are that project scope management should focus on ful- ®lling individual needs of the customer of the project. The related tools include prototyping the functionality of say an IT system, or simulation of the functionality of the project product. 3. Phases in the project implementation life cycle A typical construction project life cycle including phases of feasibility, planning and design, execution, and turnover and start-up is introduced in PMBOK [6] with reference to Morris [8]. According to Artto et al. [9], the investment project phases are preparation, execution and operation, whereas the phases associated with the project company deliverable are sales and marketing, execution and after-sales services. A sample generic project life cycle of a production facility con- struction project is illustrated in Fig. 1. However, such life cycle focuses on project implementation only; it is important to understand that the technical and opera- tional functionality of the ®nal deliverable taken over by the customer at the end of the project matters as the most important parameter that contributes to the bene®ts obtained from the investment. Fig. 1 illustrates also di€erent management levels depicted in the ®gure as pipelines or tubes. The levels are de®ned as operative, tactical, and strategic. Turner [2], and Turner and Payne [10] use the terms operative, strategic, and integrative levels in project management application in a somewhat di€erent context. The strategic view allows a perspective on the whole sphere of the 256 K.A. Artto et al. / International Journal of Project Management 19 (2001) 255±264
  3. 3. investment life cycle from the customer's point of view. At the tactical and operative levels, the perspective is limited only to the project implementation. It is important to adopt a strategic view to the project product in the implementation phase. This requires that the operation of the project product with its function- ality and operability features are considered. Simulation modelling enables such considerations. The strategic view adopted by simulation during the implementation is shown in Fig. 2. The ®gure emphasises the importance of focusing on the functionality and operability of the project product in project implementation: whereas the duration of the implementation might be, say few months or even years, the operations phase might be ten, twenty, or even thirty years or so. Applying life cycle costing can be considered as one important means of adopting a strategic level view on the project. Investment product life cycle aspect from the ®nal customer's perspective is suggested by Artto [11] with an implication that product or project supplier should adopt the ®nal customer's perspective and model life cycle costs that the ®nal customer incurs for the Fig. 1. A sample generic life cycle for project implementation. Fig. 2. Strategic view in project scope management adopted by simulating the functionality of the project product. K.A. Artto et al. / International Journal of Project Management 19 (2001) 255±264 257
  4. 4. project. Economic calculations re¯ecting the ®nal customer's Ð or investor's Ð life cycle costs with the project product are of importance. Although project cost management is generally concerned only with the cost of the resources needed to complete the activity, it should also consider the e€ect of decisions during the project on the cost of using the project product. For example, reducing e€orts in design phase may reduce the cost of the project at the expense of an increase in the customer's operations. Aspects of investment life cycle analysis and life cycle costing is discussed in Grice [12], Smith [13], Steens [14], Summers et al. [15], van Baaren and Smit [16]. Implications to the investor's project product life cycle aspect could also be derived from the extensive discussion of the importance of cus- tomer orientation and customer satisfaction in project management literature. For a discussion of the project end-product related and other customer satisfaction related research, the interested reader is advised to con- sult e.g. Laufer [17], Pinto and Slevin [18], and Pinto et al. [19]. 4. Discrete-event simulation as a tool for project scope management Computer simulation is not a new method. Simula- tion is widely applied, e.g. in system engineering design. In project management, simulation can be used either in simulating the project product or the implementation, e.g. with aspects of time, cost, or other parameters. In addition some simulation applications in the project management ®eld relate to project management training and education (see e.g. Cano et al. [20], Tsuchiya [21], Lustig [22]). The change that enables its extensive usage comes both from increased computing capacity that has enabled visualisation as well as simulation software packages that signi®cantly lower the cost of applying simulation. Naylor et al. [23] who de®ne simulation as ``a numerical technique for conducting experiments on a digital com- puter, which involves certain types of mathematical and logical models that describe the behaviour of a system over extended periods of real time''. The discussion in this article is further restricted to discrete-event simulation. In discrete simulation the state variables change instan- taneously at separate points in time [24], in contrast to both continuous-time models used in process modeling and static Monte-Carlo simulations applied to project risk calculations [25]. According to Bowersox [26], the main advantage of discrete event simulation is that it incorporates the impact of time into performance eva- luation. There are plenty of reports concerning applications of discrete-event simulation in project management. Luk [27] explains how the Hong Kong Airport transfer system was simulated in connection to the new airport project to evaluate system features before ®nal design and con- struction. The functionality and operability of the system was evaluated under conditions corresponding to operation scale up to 10 years ahead. The model was also used for internal training and as a public relations tool. Farhadi [28] reports using simulation in designing an automated material handling system. The model was build to detect possible bottlenecks in the proposed system and to ®nd changes to meet the design speci®ca- tions. Marmon [29] reports how simulation was used to study a new production facility. With the simulation model their new process could be justi®ed and ®ne- tuned. The aim for the future is to use the model in estimating the e€ects of changes in the product mix on the systems behaviour. Kauhaniemi [30] reports that simulation was used in a new factory project of a semi- conductor-based acceleration sensor manufacturer. The simulation model was applied throughout the project. The two main application areas were allowing employee participation in the project through a 3D-model and using the model as a test environment for machinery under di€erent scenarios. During the last decade dis- crete event simulation has gained a signi®cant role in engineering design. IIE Solutions (former Industrial Engineering) has published simulation software buyer's guides and special issues on discrete event simulation on regular basis since 1989. What is lacking, however, are concepts and research on how discrete event simulation should be applied in the project management frame- work for project de®nition, management of the project product, and management of the investment life cycle with methodologies that allow dynamic considerations of the operability of the project product in its operation environment. 5. The role of discrete event simulation in relation to project objectives and project management Table 1 shows proactive future-looking generic tools that allow appropriate front-end management of respective objectives. The `scope' is understood widely enough as the core objective comprising the project product with its functionality and performance char- acteristics. The tools for project product functionality management are discrete-event simulation, and project product prototyping. Also life cycle costing is often used to support decisions concerning scope and functionality. 6. Case examples Four empirical cases are introduced in order to put discrete-event simulation into place in project scope management throughout the project implementation. 258 K.A. Artto et al. / International Journal of Project Management 19 (2001) 255±264
  5. 5. Further, the cases provide more detailed understanding of features and practical application of the discrete- event simulation approach. The authors participated in conducting the simulations in all cases. 6.1. Case example 1: chocolate paste department Case 1 describes a feasibility-phase investment plan- ning situation occurred in a chocolate paste department of a confectionery manufacturer. The chocolate paste is consumed either by the confectionery manufacturer on its six production lines or sold to outside customers. In connection to renewal investments and anticipated increase in demand simulation was applied in the cho- colate paste department to: . analyse how much more capacity is required to meet a future demand forecast of 20% consump- tion increase. . assess the production increase achievable with a proposed new piping arrangement that would con- nect all except two processors to all chocolate tanks. Chocolate paste is produced in three processing stages that are mixing the ingredients, rolling and a processing stage. The pastes are then stored each in their own, dedicated tanks or containers either for further con- sumption in the manufacturing lines or direct paste deliveries to outside customers. The chocolate paste department model is shown in Fig. 3. The consumption data was based on a seasonal peak month of previous year. Because there were no data on actual tank levels, an additional variable describing the tank initial conditions was included. The variables whose e€ect were evaluated were . consumption (present situation versus 20% increase) . piping (present situation versus investment in piping) . tank initial conditions before the test period (tanks half full versus tanks full) A full experimental design was performed with the three variables at two levels each. The performance of the paste department was measured primarily by deliv- ery shortages and secondarily, to indicate potential for such shortages, by capacity utilisation of roller and processors. Table 2 shows the summary results of experiments. The ®rst row (average) shows overall average results. As an average the processors in the chocolate paste department is not fully used and the roller is more uti- lised than the processors. The rows below the average show the results when a€ected by each variable. The simulation showed that the increased chocolate paste consumption can be met with the present capacity. The system output was generally restricted by con- sumption, not production capacity. If the consumption were further increased, the ®rst capacity bottleneck would not be the processors but the roller. The piping investment did not increase production with the paste mix used. The explanation is that the roller is the bot- tleneck and the piping only increases the time that the lots must wait to get roller. For the company this showed that their bottleneck is the roller and not the processors as they thought. It also showed that the projected consumption increase can be met without capacity increase, saving some 500,000 ECU roller investment. Table 1 Front-end management tools Project objective Decision making subject Tools for project implementation Tools for project product functionality Time Activities and resources Schedule forecasting, PERT and CPM, Monte Carlo simulations Cost Work, activities and resources Cost estimates, Monte Carlo simulations Sensitivity analyses Scope De®nition of the project product, and features of the deliverable Engineering design databases, component databases, con®guration management, change management, product breakdown structure Discrete-event simulation of functionality of the project product, prototyping functionality, life cycle costing Fig. 3. Chocolate paste department model. K.A. Artto et al. / International Journal of Project Management 19 (2001) 255±264 259
  6. 6. 6.2. Case example 2: de®nition of a materials handling system Case 2 includes a study of a new facility investment project of a major Nordic beverage manufacturer. Dur- ing the period 1992±1998 the manufacturer reduced the number of its production facilities from seven to three. The beverage manufacturer is seeking ways to develop its operations continuously. The simulation model pre- sented here was built in 1998 to study one subsystem of a new intended facility, the materials handling system. During the investment project several other simulation studies, that addressed di€erent functions in the facility, were carried out. The simulation was applied to assist in early engineering phase of a project with 12 month's implementation. The length of the life cycle of the planned materials handling system was estimated as 10 years. The objectives of the study described here were to de®ne the transfer capacity needed and to develop control logic for the materials handling equipment. Di€erent block layout and lift loading logic alternatives were evaluated. Prior to simulation the system had been analysed with the help of a static CAD-based model. The tentative analysis indicated that the scope suggested by the supplier for the materials handling system might include unnecessary extra capacity. The aim of the investment was to construct a multi-¯oor facility where all material is moved on pallets controlled and run by ®xed automated equipment. According to the plans there is a monorail system on each ¯oor. The monorails are connected to lifts by conveyors. The lift area of the model is shown in Fig. 4. The simulation model was built on block layout CAD-pictures. The system supplier provided the cycle times as well as the preliminary structure of the monorail-system, conveyors and lifts for the simulation modelling. The weekly pro- duction schedule was developed by the manufacturer. The use of simulation allows explicit and modular de®nition of rules for lift and monorail vehicle control logic. Rules are applied when pallets are fed to the system. Signi®cant part of the control logic consists of rules for job assignment and prioritisation of jobs. As a tentative analysis showed that the lifts formed a possible bottle- neck in the system, the utilisation of the lifts was chosen as the measure of performance. The simulation run was constructed to present a worst case where: . the absence of process co-ordination leads to unnecessary movement of pallets, i.e. all pallets coming from bottle sorting are fed to storage instead of some being used directly in production . the production peak and the peak in incoming empty re®ll-bottle ¯ow occur at the same time. Two layout alternatives and lift loading logics were developed. In Layout 1 the bottle sorting process was located on the lower production ¯oor on the same side of the monorail systems as the lifts. In Layout 2 bottle sorting was located on the same ¯oor with production. The two layout alternatives were constructed to estimate the e€ect of the location of the bottle sorting process on lift utilisation. In lift loading logic I each pallet was loaded separately whereas in lift loading logic II two pallets were loaded in the lift at the same time. The superiority of the less time-consuming loading logic II was apparent without analysis, but the scenarios were constructed to estimate the di€erence. The results of the simulation, presented in Table 3, show that the materials handling con®guration of the model is sucient to ful®l the transfer needs of the facility independent of the choice of loading logic and layout. Layout 2 was chosen due to the lower utilisation of the lifts. The company estimated that due to the increased accuracy provided by the simulation model, an unne- cessary investment in the materials handling capacity by the worth of 300 000 ECUs was avoided. This was the di€erence between the scope initially suggested by the Table 2 Overall averages and factor e€ects on performance measures Shortages (%) Roller utilisation (%) Processors utilisation (%) Average 1.0 76.6 62.7 If 20 increase in consumption 2.0 82.3 67.1 If investment in piping 1.1 76.5 62.7 If tank initially full 0.8 70.3 58.4 Fig. 4. The lift area of the model. Table 3 Average utilisation of the lifts in worst case simulation Loading logic I Loading logic II Di€erence Layout 1 79.2 70.9 8.3 Layout 2 68.6 60.5 8.1 Di€erence 10.6 10.4 260 K.A. Artto et al. / International Journal of Project Management 19 (2001) 255±264
  7. 7. supplier and the recommendation based on the simula- tions. In addition to the direct bene®ts, the representatives indicated that the 3D-model showing material move- ment increased the understanding of proposed system in the commissioning phase. The manufacturer was also planning to utilize the model as a training tool for the employees with the purpose of giving a systems view of the functioning of the facility in the operations phase. 6.3. Case example 3: paper mill capacity increase The third example is a feasibility study of a new logistics con®guration conducted in mid-90s for a Nor- dic paper mill. The mill produces paper that is sold to customers in sheets. The aim was to analyse the feasi- bility of changing the present make-to-order deliveries to sheeting-to-order from a reel inventory with the bene®t of considerably faster order delivery. Later, in the man- ufacturing phase of the system, simulation was con- ducted to evaluate the applicability of the solution. At the same time the mill was building additional produc- tion capacity, and it was considered that the simulation would provide requirements for the logistics system con®guration. The main objectives were to ®nd out whether the target delivery times could be achieved and what would the required reel inventory then be. The mill layout for reel inventory and its capacity were initially ®xed. The simulation model demand data was based on a one quarter long sample of orders and deliveries. Model features were based on personnel interviews and on available technical design data. The simulation model ¯owchart is shown in Fig. 5. This ®gure also shows the variables whose e€ects were evaluated. The variables were: . production capacity (present versus the increased capacity) . paper machine production cycle length (present versus halved) . number of di€erent standard reel widths in the reel inventory (3 versus 5) Due to capacity as well as some technical limitations, a customer order has to await for a full sheeting lot size worth of orders. The average order size is around 1/4 of a sheeting lot size. Then the sheeting lot is released to sheeting, provided that there is enough reels of the right grade and width. The paper for each order is sheeted and laid onto pallets that are put into ®nished goods inventory to await shipping to the markets. The reel inventory is replenished periodically from the paper machine (PM) with the production cycle length as the replenishment period. The simulation experiment was a comparison of the sheet-to-order operating models with the present situa- tion as a base case to which each change was compared, one at a time. The base case variable values for capacity and paper machine cycle were `present' and ®ve standard widths. The comparisons were made on equal basis so that machine utilisations were set to 90% and inventory availability to 95%. Sensitivity analyses were performed for these parameters. The simulation run length was eight months and ®ve replications for each setting was performed. The results from the feasibility study for the new logistics con®guration showed (see Table 4) that the delivery time targets cannot be achieved with the current sheeting lot size, regardless of the number of standard reel widths. However, after the capacity increase target delivery time becomes almost feasible if the number of standard reel widths is also reduced. It was shown that the reel inventory maximum size will not exclude sheeting- to-order if the paper machine cycle length is reduced. The recommendation was for a more thorough analysis where also the ®xed variables of shipping time, sheeting lot size, reel inventory availability and the policies to which customers, order sizes and grades the fast delivery is o€ered would be included. 6.4. Case example 4: logistics performance analysis of a production system The fourth case is associated with a development of a logistics system concept for a global electronics manu- facturer. A logistics performance analysis was con- ducted by using simulation in 1999. The analysis was Fig. 5. Paper mill simulation model. Table 4 The change in performance of di€erent variables compared to the sheet-to-order base case (n.s. = not signi®cant at p = 0.05 level) Performance measure Paper machine cycle halving (%) From 5 to 3 standard widths (%) Capacity increase (%) Order backlog 0 n.s. À40 3 n.s. Reel inventory À24 À15 54 Average lead time À1 n.s. À26 À36 Lead time 90 fractile À11 À22 À36 K.A. Artto et al. / International Journal of Project Management 19 (2001) 255±264 261
  8. 8. conducted for decisions concerning the implementation of the logistical management scheme. The simulation model was constructed to analyse how the company logistics targets can be achieved in terms of delivery time and inventory. The objectives of the study were to determine the parameter values for inventory management and to estimate resulting inven- tories. The product has a modular design. It will be assem- bled to order from module bu€ers. Key modules are produced in-house. Some parts to be used in module production are produced in-house while other parts are bought from suppliers. Fig. 6 shows the structure of the production model. The scenarios were constructed to present the fore- casted demand of the next three years. This time span was considered sucient in respect of short lifetime of the products. The company had set targets on how much demand ¯uctuation the production system should be able to face so that their on-time delivery perfor- mance would not be a€ected. These targets were used to construct the demand model. Also alternative scenarios were constructed, in which orders exceeding a certain quantity were allowed a longer lead-time. In addition to the actual parameter values for inven- tory management, the simulations resulted in estimates of the trade-o€ between lead-time o€erings and inven- tory costs, as seen in Table 5. 7. Case results In the ®rst case simulation was applied in the very early feasibility phase of the project with intended investment in chocolate paste facility. The advantage of simulation was to assess the need for added capacity and bottlenecks in the future predicted operating envir- onment. The application of the approach with simula- tion showed that the consumption can be met with the present capacity, and the planned investment for equip- ment would not be rational as the bottleneck of the system was showed to be elsewhere. The approach showed its power due to the decision of not going for an unnecessary investment project that would not con- tribute pro®tability of the company. In the second case, savings occurred due to appro- priate functionality of a material handling system of a beverage manufacturer. The bene®ts were signi®cant; partly due to avoiding investments to unnecessary capacity, and moreover due to appropriate functionality of the system. The bene®ts in relation to the total investment costs were in the range of ca. 15±25%. Additional advantages of the simulation approach will be gained in the commissioning and operations phases where the simulation model will be applied for learning purposes of the employees responsible for operating the system. The model will be used as a continuous testing environment with savings bene®ts by reducing lift over- capacity and including training providing overview of factory wide materials ¯ows. The third case presented a feasibility study for a new logistics con®guration in connection to an ongoing Fig. 6. Structure of the production model. Table 5 Module inventory trade-o€ results Year Volume variant demand Stock reduction from policy change (%) Minor variant demand Stock reduction from policy change (%) 2000 100 17 100 88 2001 200 14 200 86 2002 270 6 250 83 262 K.A. Artto et al. / International Journal of Project Management 19 (2001) 255±264
  9. 9. capacity increase in a paper mill. Later, in the manu- facturing phase of the system, simulation was conducted to evaluate the applicability of the solution. The capacity increase brought about by the investment project enabled reconsidering the present make-to-order logistics arrangement. Adopting the strategic view and applying simulation model as a tool in this case allowed looking up to the operations phase of the ongoing investment project already at the manufacturing phase. In addition to this, the simulation modelling was able to increase accuracy of the operating capital requirements be de®ning the reel inventory requirements and also man- ufacturing strategy by showing the delivery time per- formance. The fourth case introduced how simulation can be used in logistics system concept development. The simulation approach provided a means to de®ne the requirements for the operating capital investment. The use of simulation will ease the testing and re®nement phase of the project because the in-house production system and linkages to suppliers have already been ®ne- tuned. Table 6 shows how each case is linked in a generic project life cycle framework. All four cases present how a strategic view was adopted over the functionality of the project deliverable in its operations phase. In case 2 and case 3, simulation was applied several times during the project life cycle. The cases demonstrate how the simulation was used to manage project scope. The cases also show that simulation was used as a management tool in various phases of project implementation throughout the project life cycle. 8. Conclusions This article discussed the management of the project product side of scope management rather than the more traditional content of project scope management with a focus on how to put the component parts of the project product together. The article introduced discrete event simulation as a tool to support major decisions associated with early management of project product content that enables the desired functionality. The four case examples demon- strated that discrete event simulation can be applied throughout the project life cycle as a continuous man- agement and decision making procedure. This way a strategic view is adopted that enables considerations of the project product in its operation environment. Modelling of the technical and operational function- ality of the ®nal project deliverable in its production environment and simulating the operations phase is seen as a dynamic vehicle that supports decision making and continuous project de®nition. Modelling and simulation enable creating a dynamic test environment where the functionality and performance of the project end result or deliverable can be iteratively analysed. With such approach, the principle will be in accordance with the suggestion of Morris [3] i.e. the inherent business sense aspect associated with the project is emphasised with sucient focus on optimising the potential commercial bene®ts of project delivery. Finally, the article suggests that: 1. Management principles are applied throughout the project where the functionality of the project product handed over to the customer is actively managed as an important parameter that contributes to future pro®t accumulation in the customer's business. 2. The means to manage the functionality should incorporate experimenting with a dynamic environ- ment that supports decision making and manage- ment of future outcomes, rather than just dictating well designed activities for project implementation. References [1] Anttila V, Artto K, Walle n G. Project management by results. Project Management 1998;1:40±5. [2] Turner JR. The handbook of project-based management. UK: McGraw-Hill, 1993. [3] Morris PWG. Why project management doesn't always make business sense. Project Management 1998;1:12±16. [4] Jaafari A. Project managers of the next milennium: do they resemble project managers of today? In: Transactions of the 14th Table 6 Case results summary Case Application area Phase Case objective Project scope management bene®ts 1 Manufacturing facility design Feasibility Analysing impact of future demand on investment scope Avoiding investment in unnecessary capacity 2 Manufacturing facility design Engineering, commissioning Choosing layout and material handling system solution Smaller investment with increased functionality 3 New logistics con®guration Feasibility, manufacturing Testing solutions for faster customer service Better logistics con®guration and operating capital requirement 4 Logistics system concept development Manufacturing Ensuring achievement of logistical targets Reliable system de®nition and operating capital requirement K.A. Artto et al. / International Journal of Project Management 19 (2001) 255±264 263
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