Simulation
Based Training (SBT) – the
Next
Generation of Project Management Training
By Prof. Avraham SHTUB
Faculty of Industrial
Engineering and Management
Technion - Israel
Institute of Technology
Haifa 32000, ISRAEL
Abstract
Teaching
project management is not an easy task. Part of the difficulty is the
one-of-a-kind nature of projects. Being one-of-a-kind and focusing on a unique
product, service or result means that in teaching project management we must
consider a very wide array of possible situations (scenarios) with which the
project manager and his team should learn to cope.
Traditional
project management teaching is based mostly on textbooks, articles and case
studies. Textbooks present a body of knowledge in the project management area
including best practices that proved to work well for a variety of projects.
Many textbooks integrate some case studies with which the reader has an
opportunity to implement the material learned. These case studies are valuable
and widely used but they suffer from an inherent shortcoming — they are static
in nature. Simulation Based Training (SBT) offers a solution to this problem.
This
paper discusses the use of SBT for training and educating in project
management, and presents a specific example of SBT platform.
Introduction
Traditional
teaching and training of project management is based on lectures, reading
materials and case studies. The advantage of case studies is that they can
represent a real project and provide the lessons learned from it. A case study
presents a snapshot of a situation at a specific time point. It is hard to
understand the dynamic nature of projects by analyzing static case studies.
Dealing with the dynamics of projects is most important throughout the project
life cycle. During the planning, monitoring and control stages of the project,
managers must take into account the fact that changes are an inherent part of
project management due to uncertainty. Change management as part of the
monitoring and control processes is vital to the success of modern projects.
Uncertainty
is typical to most projects. This uncertainty leads to project risks (and
opportunities) and to the need for proper risk management. Most textbooks on
project management deal with risk management in the planning phase focusing on
how to identify and how to mitigate risks. Some books go a step further and
discuss the issue of residual risks and ways to buffer against such risks. The
art and science of risk monitoring and control is very difficult to teach and
even more difficult to practice using only books, articles and static case
studies.
Simulated Based Training (SBT)
presents a unique approach to the teaching and training of project management. In
the following sections the need for SBT in the project management training
arena is discussed. Next the
use of simulation in training is discussed and finally a specific tool for SBT
in project management is presented.
The
Need
The
need for experienced, well-trained project managers is growing fast. The number of new PMI (Project Management
Institute) members and the number of new PMPs (Project Management
Professionals) is an indication that project management is a fast-growing
discipline. Another indication is the
growing number of undergraduate and graduate programs mainly in Engineering,
Business and Management of Technology that offer project management courses or
even a degree in Project management. The
traditional approach for training new project managers is to teach the
appropriate body of knowledge and to train the new project managers on the
job. The number of books on project
management is growing very fast. Since
classroom education may not be enough in this area, the PMP accreditation
requires the accumulation of enough on-the-job experience (e.g. working hours)
in project management in addition to passing an exam based on the best
practices listed in the Project Management Body of Knowledge. On-the-job training is expensive and time
consuming.
Most
expensive is the cost of errors made by the trainees. In some fields sophisticated simulators
replace on-the-job training or reduce it to a minimum while ensuring that the
quality of training is the highest possible.
This is common, for example, in training pilots who spend many hours on
advanced simulators to save the high cost of actual flights. The cost of on-the-job training in this case
should also include the cost of risks associated with mistakes frequently made
by inexperienced pilots. In a similar way, training project managers on the job
is expensive due to the high cost of mistakes made by inexperienced project
managers.
Modern
project management systems combine models (in a model base) and data (in a
database). These systems are based on an enterprise-wide approach that supports
comprehensive management of projects in a stochastic dynamic environment across
the enterprise. Extensive use of the Web enables group decision-making and
collaboration. In order to utilize these capabilities managers have to
understand the models and best practices discussed in the Body of Knowledge, to
learn how to implement the methodologies and to gain some hands-on experience
in doing it as individuals and as team members.
This
fast development of new methodologies, tools, techniques and software packages
for project management was not accompanied by a similar progress in developing
teaching and training tools. Traditional teaching based on textbooks, articles
and case studies is still the backbone of most training programs in the area of
project management.
The use of simulation in the learning
process
Confucius
said: "I hear and I forget. I see and I remember. I do and I
understand."
This
is the essence of Simulation Based Training. We must do things ourselves in
order to really understand them. In his article, James I. Grieshop [Grieshop
1987] stated that: "Games and simulations (ranging from role playing to
case studies, from guided fantasy to problem solving) have become widely
recognized methods for instruction and learning. Since the early work in the United States in
the late 1950s and in Europe in the late 1960s, gaming/simulation has become
increasingly important to training and decision-making processes in academic
settings as well as in business, the military, and the social sciences."
More
than twenty years later it seems that the same trend persists and games and
simulations are recognized as important facilitators of the learning and
training processes in many fields.
Grieshop
(1987) listed some of the benefits of games and simulations:
1. Emphasize questioning over answering on the part of
players.
2. Provide opportunities to examine critically the
assumptions and implications that underlie various decisions.
3. Expose the nature of problems and possible solution
paths.
4. Create an environment for learning that generates
discovery learning.
5. Promote skills in communicating, role-taking, problem
solving, leading, and decision-making.
6. Increase the motivation and interest in a subject matter.
Grieshop
(1987) states that evidence is offered for:
1. increased retention,
2. energizing the learning process,
3. facilitation of understanding the relationships between
areas within a subject matter.
Since
the publication of Grieshop's work in 1987, simulation has been used for
training in a wide range of fields: In Engineering [IJEE Special Issue on
Simulators for Engineering Education and for Professional Development 2009], in
management of quality [Wang 2004], in supply chain management [Knoppen and
Sáenz 2007], and in process re-engineering [Smeds and Riis 1998, Thoben et al.
2007]. Empirical research [Millians 1999, Ruben 1999, Randel et al. 1992, Wolfe
and J.B. Keys 1997, Meijer et al. 2006, 569–583] has expanded our knowledge of
this training approach by presenting new ways of understanding and implementing
simulation for training.
Today
it is widely accepted that learning through simulation is based on three
pillars: [Keys 1976, Kolb 1984, Kirby 1992]:
1. learning from content — the dissemination of new ideas,
principles, or concepts.
2. learning from experience — an opportunity to apply
content.
3. learning from feedback — the results of actions taken and
the relationship between the actions and performance.
A
well designed simulator supports a process of action-based learning. Instead of
talking about different ways of doing things, simulators offer an opportunity
to try different ways of doing things without risking the consequences of doing
so in the real world.
Simulators
create an environment that requires the participant to be involved in a meaningful
task. The source of learning is what the
participants do rather than what they are told by the trainer.
Thompson,
Purdy & Fandt (1997) list the advantages of using simulations as a learning
tool:
1.
Simulators are characterized as tools enabling the
acquisition of practical experience and acceptance of an immediate response of
the learned system to the user’s decisions and actions.
2.
Simulators offer a realistic model of the interdependence
of decisions that the trainee makes.
3.
Simulation-based training reduces the gaps between the
learning environment and the "real" environment.
4.
Simulators facilitate training in situations that are
difficult to obtain in the "real world".
5.
Simulations promote active learning, especially at the
stage of debates that arise because of the complexity, interconnectedness, and
novelty of decision-making.
Wolfe
(1993) notes that simulations develop critical and strategic thinking skills.
He claims that the skills of strategic planning and thinking are not easy to
develop and that the advantage of simulators is that they provide a strong tool
for dealing with this problem.
An
important development in the design of training simulators is to provide the
learners with automatic or semi-automatic feedback on their progress. A learning history mechanism was used in
several simulation-based teaching tools.
The user of these systems obtains access to past states and decisions
and to the consequences of these decisions.
Learning histories encourage the users to monitor their behavior and
reflect on their progress [Beyerlein et al. 1996, Guzdial et al. 1996].
Learning histories enables analysis of the decision-making process as opposed
to analysis of results only and therefore it is very effective because the
direct influence on the user’s actions can be seen. For example, learning
history is used as a quality improvement tool for programmers [Prechelt 2001].
The
most basic view of history recording and inquiry is the temporal sequence of
actions and events. In its simplest form,
user actions are logged and recorded, and are then accessible in various ways
for recovery and backtracking purposes [Vargo et al. 1992]. Such a mechanism is used as "undo". Several recovery mechanisms have been
developed using the simple undo/undo or undo/redo [e.g., Archer et al. 1984].
Parush
et al. [2002] described simulation-based teaching of the order fulfillment
process in a manufacturing context, using the Operations Trainer [Shtub 1999,
Shtub 2001] with a built-in learning history recording and inquiry mechanism.
The study addressed two basic questions:
1. Can
history recording and inquiry affect the learning curve during the training
phase with the simulator?
2. Can
history recording and inquiry affect the transfer of what was learnt with the simulator
onto different contexts?
The
findings showed that with the learning history recording and inquiry available
to users, better performance was obtained during the learning process itself.
In addition, the performance of learners with the history mechanism was better
transferred to a different context, compared to learners without the history
mechanism.
The
studies reviewed above demonstrated that having an opportunity to review
learning history had a positive impact on learning. However, these studies did not examine
whether the mode of history recording could have an impact on learning. History recording can be done either by
automatic mechanism or by learner control.
In automatic history recording, the training system such as the
simulator determines when to record a given state in the learning process.
These recording points are pre-determined by the simulator designer or the
instructor that prepares the training program.
In such a situation, the learner is not involved in the decision when to
keep a specific state in the learning process.
In contrast, in a learner-controlled mode, the learner determines if and
when to keep a specific state in the learning process. It was shown however that giving the learners
some control over the learning environment by letting them actively construct
the acquired knowledge produces better learning [Cuevas et al. 2004].
The
successful use of a simulator for teaching project management was reported in
several studies [Davidovitch et al. 2006, 2008, 2009]. The simulator called the Project Management
Trainer (PMT) was used in those studies as a teaching aid designed to
facilitate the learning of project management in a dynamic, stochastic
environment. The research focused on the
effect of history recording mechanism on the learning process. Two types of
history mechanisms were tested: the automatic history mechanism, in which
predefined scenario's states are always saved, and the manual history
mechanism, in which the trainee had to show an active involvement and to save selected
states manually. In [Davidovitch et al.
2006] the study focused on how project managers' decisions to record the
history affected the learning process and on the effects of history inquiry
when the ability to restart the simulation from a past state is not
enabled. In [Davidovitch et al. 2008]
the study focused on the forgetting phenomenon and on how the length of a break
period and history mode affected the learning, forgetting, and relearning (LFR)
process. Both studies revealed that
history recording improved learning; furthermore, with the manual history
mechanism learners achieved the best results.
The issue of a simulator’s functional
fidelity is also of great interest. The fidelity of a simulator is a measure of
its deviation from the real situation; it has three dimensions: perceptual,
functional and model fidelity. Perceptual fidelity refers to the level of
realism it evokes in terms of its look and feel relative to the real system.
Functional fidelity refers to the way users or trainees use and control the
simulation, its behavior and responses to user actions. Finally, model fidelity
refers to the extent to which the mathematical or logical model underlying the
simulation is close to the real processes and phenomena.
The fidelity of the simulator has been
recognized as a critical factor influencing the transfer of learning [Alessi
1988]. In order to provide a higher level of functional fidelity, the PTB
simulator includes two functionalities: the ability to control the level of
human resources and the ability to control the execution of the tasks. These
functionalities are made available to trainees as part of the scenario
development.
The ability to control the level of
human resources refers to the decision to hire or fire employees in accordance
with the changing demand for resources during the project execution; the
project manager can control the number of employees in the project in order to
match availability to needs. The ability to control the execution of the tasks
refers to the decision to split tasks during execution - a task can begin, stop
for a while and continue later.
Davidovitch et al. (2009) found that
higher fidelity improved performances in the learning phase and in the transfer
phase to a different scenario.
Specific
Example - The Project Team Builder (PTB)
The Project Team Builder (PTB) is a training aid
designed to facilitate the training of project management in a dynamic,
stochastic environment. The design of PTB is based on the research findings
described in the previous sections. Thus, for example PTB provides high
fidelity by supporting the simulation of any (real or imaginary) project. Another example is the history mechanism
built into the PTB that allows the user to go back in simulation time to review
past decisions and to restart the simulation from any past simulation time. A
student version of PTB is the basis of the book "Project Management
Simulation with PTB Project Team Builder, " Springer (2012) and
information on the full version of PTB is available at ,. http://www.sandboxmodel.com/content/ptb%E2%84%A2-training
The PTB is
based on the following principles:
·
A simulation approach — the PTB
simulates one or more projects or several work packages of the same
project. The simulation is controlled by
a simple user interface and no knowledge of simulation or simulation languages
is required.
·
A case study approach — the PTB is
based on a simulation of case studies called scenarios. Each case study is a project or a collection
of projects performed in a dynamic stochastic environment. In some scenarios the projects are performed
under schedule, budget and resource constraints. The details of these case
studies are built into the simulation while all the data required for analysis
and decision-making is easily accessed by the user interface.
·
A dynamic approach — the case studies
built into the PTB are dynamic in the sense that the situation changes over
time. A random effect is introduced to
simulate the uncertainty in the environment, and decisions made by the user
cause changes in the state of the system simulated.
·
A model-based approach — a decision
support system is built into the PTB.
This system is based on project management concepts. The model base contains well-known models for
scheduling, budgeting, resource management and monitoring and control. These
models can be consulted at any time.
·
To support decision-making further, a
database is built into the PTB. Data on
the current state of the simulated system is readily available to the users; it
is possible to use the data as input to the models in the model base to support
decision-making. Furthermore, by using special history mechanisms the user can
access data on his past decisions and their consequences.
·
User friendliness and GUI — the PTB is
designed as a teaching and training tool.
As such, its Graphic User Interface (GUI) is friendly and easy to learn. Although quite complicated scenarios can be
simulated, and the decision support tools are sophisticated, a typical user can
learn how to use the PTB within an hour.
·
An integrated approach — several
projects can be managed simultaneously on the PTB. These projects can share the
same resources and a common cash flow.
·
Integration of processes: planning
processes, executing processes and monitoring and controlling processes. All
these processes are performed simultaneously in a dynamic stochastic
environment.
·
Integration with commercial project
management tools — the PTB is integrated with Microsoft Project so that the
users can export the data to Microsoft Project in order to analyze the scenario
and to support its decisions with tools that are commercially available.
Summary
Many project managers claim that
project management is a combination of art and science. It is the art of
dealing with people in a dynamic, frequently uncertain environment and the art
of riding the learning curve in a non-repetitive environment. It is the science
of
solving hard combinatorial, stochastic problems of project planning, monitoring
and control under resource and budget constraints. SBT can support training in
both aspects of project management. By using the PTB in team settings the art
of project management can be practiced, by using SBT to plan monitor and
control projects with an increasing level of difficulty, the science of project
management is mastered.
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About the Author
Professor Avraham Shtub
Industrial
Engineering and Management
Technion - Israel Institute of Technology
http://ie.technion.ac.il/Home/Users/shtub0.html
Professor Avraham Shtub holds the Stephen and Sharon Seiden Chair in Project Management in the Department of Industrial Engineering and Management at Technion - Israel Institute of Technology in Haifa, Israel. He has a B.Sc from the Technion - Israel Institute of Technology, an MBA from Tel Aviv University and a Ph.D from the University of Washington, USA. He is the recipient of the Institute of Industrial Engineering 1995 "Book of the Year Award" for his Book "Project Management: Engineering, Technology and Implementation" (co-authored with Jonathan Bard and Shlomo Globerson), Prentice Hall, 1994. He is the recipient of the Production Operations Management Society 2000 Wick Skinner Teaching Innovation Achievements Award for his book: "Enterprise Resource Planning (ERP): The Dynamics of Operations Management" and he is the recipient of the 2008 Project Management Institute Professional Development Product of the Year Award for the training simulator "Project Team Builder – PTB". His books were published in English, Hebrew, Greek and Chinese. Prof Shtub can be contacted at