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
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
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
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 dierent solutions
than analysing the functionality of the solution.
0263-7863/01/$20.00 # 2001 Elsevier Science Ltd and IPMA. All rights reserved.
International Journal of Project Management 19 (2001) 255±264
* Corresponding author. Tel.: +358-9-451-4751; fax: +358-9-451-
E-mail addresses: karlos.artto@hut.® (K.A. Artto), juha-matti.
lehtonen@hut.® (J.-M. Lehtonen), juha.saranen@hut.® (J. Saranen).
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
The traditional project management approach of
straightforward managing of project objectives of time,
cost, and scope, is criticised by Anttila et al. . 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 dierent 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  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 
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 suciently
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 
and Jordanger . Both authors criticise managing the
project by traditional objectives of time, cost, and
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  and ISO 10006 
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 
with reference to Morris . According to Artto et al.
, 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 dierent management levels
depicted in the ®gure as pipelines or tubes. The levels
are de®ned as operative, tactical, and strategic. Turner
, and Turner and Payne  use the terms operative,
strategic, and integrative levels in project management
application in a somewhat dierent 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
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
 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
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 eect of decisions during the
project on the cost of using the project product. For
example, reducing eorts 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
, Smith , Steens , Summers et al. , van
Baaren and Smit . 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 , Pinto and Slevin , and Pinto et
4. Discrete-event simulation as a tool for project scope
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. , Tsuchiya ,
Lustig ). 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
Naylor et al.  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 , in contrast to
both continuous-time models used in process modeling
and static Monte-Carlo simulations applied to project
risk calculations . According to Bowersox , the
main advantage of discrete event simulation is that it
incorporates the impact of time into performance eva-
There are plenty of reports concerning applications of
discrete-event simulation in project management. Luk
 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  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  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 eects of changes in the product mix on
the systems behaviour. Kauhaniemi  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 dierent 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
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
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-
. 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 eect 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
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 aected 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
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
Scope De®nition of the project product,
and features of the deliverable
Engineering design databases, component
databases, con®guration management,
change management, product breakdown
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
6.2. Case example 2: de®nition of a materials handling
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 dierent 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. Dierent
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 eect 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 dierence. The results of the
simulation, presented in Table 3, show that the materials
handling con®guration of the model is sucient 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
dierence between the scope initially suggested by the
Overall averages and factor eects on performance measures
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.
Average utilisation of the lifts in worst case simulation
Loading logic I Loading logic II Dierence
Layout 1 79.2 70.9 8.3
Layout 2 68.6 60.5 8.1
Dierence 10.6 10.4
260 K.A. Artto et al. / International Journal of Project Management 19 (2001) 255±264
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
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 eects were evaluated. The variables were:
. production capacity (present versus the increased
. paper machine production cycle length (present
. number of dierent 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
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
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 oered would be included.
6.4. Case example 4: logistics performance analysis of a
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.
The change in performance of dierent variables compared to the
sheet-to-order base case (n.s. = not signi®cant at p = 0.05 level)
From 5 to 3
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
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-
The product has a modular design. It will be assem-
bled to order from module buers. 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
The scenarios were constructed to present the fore-
casted demand of the next three years. This time span
was considered sucient 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 aected. 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 oerings 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.
Module inventory trade-o results
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
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-
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-
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.
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
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  i.e. the inherent business sense
aspect associated with the project is emphasised with
sucient 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.
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Case results summary
Case Application area Phase Case objective Project scope management bene®ts
1 Manufacturing facility
Feasibility Analysing impact of future
demand on investment scope
Avoiding investment in unnecessary
2 Manufacturing facility
Choosing layout and material
handling system solution
Smaller investment with increased
3 New logistics con®guration Feasibility,
Testing solutions for faster
Better logistics con®guration and
operating capital requirement
4 Logistics system concept
Manufacturing Ensuring achievement of
Reliable system de®nition and
operating capital requirement
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