Overcoming Limitations of PERT-Based Scheduling
Using a Monte Carlo Simulation
Michael Thornton, Faculty Mentor: Dr. Borinara Park, Department of Technology, Illinois State University
• Having realistic estimates of activity and total project duration is critical in
both project and organizational planning.
• Uncertainty exists in all projects, efforts need to be made to account for this
uncertainty
• Both PERT and Monte Carlo Simulation attempt to analyze and account for
this uncertainty by recognizing the variability in activity and project
duration variability.
PERT (Program Evaluation & Review Technique)
PERT uses a given range of
duration values to
calculate a single
“expected duration” for
each activity
Utilize sources of project environment uncertainty,
characteristic of given industry sectors, in order to
illustrate:
1. The limited ability of PERT to account for major
sources of schedule risk in estimating project
duration.
2. The range of schedule risks Monte Carlo Simulationbased scheduling technique is capable of accounting
for in estimating project duration.
Utilizing various aspects of project schedules in a Pharmaceutical Product Research &
Development Project:
• PERT method was used to estimate the project duration and probability to complete the
project within one standard deviation above the estimated duration
• Monte Carlo Simulation-based scheduling was used to build various models to potentially
account for industry specific risk in project duration
• Compare and contrast PERT calculated and Monte Carlo simulated outcomes for individual
sources of schedule uncertainty.
1) In a project environment characterized by highly probable risk events
requiring significant project re-work, PERT is not capable of providing
realistic project duration estimates due to an inability to account for
probability and potential impact posed by occurrence/s of project risk
events.
2) In a project environment characterized by consistently high probability of
risk event occurrence, the [Monte Carlo Simulation-based scheduling
technique’s] ability to correlate activity duration with probability of risk
event occurrence add limited value to project duration estimation (due to
the consistently high probability of risk event occurrence).
These expected durations are used to create the project schedule and identify
a single critical path
3) In a project environment characterized by projects composed of activities
with highly variable durations and duration variability, the Monte Carlo
Simulation-based scheduling technique is capable of utilizing
representative stochastic values and probability distribution shapes to
identify project duration inputs with the capability to significantly impact
total project duration.
Expected durations for “critical activities” are added together to provide an
“Expected Project Duration.”
4) In a project environment characterized by the existence of any given
number of “near-critical path activities,” the Monte Carlo Simulationbased scheduling technique is capable of reducing project duration
uncertainty through the identification of tasks with relatively high critical
index values.
Variance in “critical activity” is calculated and used to provide the total
duration variance and project duration standard deviation
Monte Carlo Simulation
5) In a project environment characterized by a single/dominant critical path,
the capability to calculate critical indexes of non-critical activities [using
Monte Carlo Simulation-based scheduling techniques] does not seem to
add significant value in the estimation of total project duration.
Monte Carlo simulation uses a given range of duration values and probability
distribution shape to describe the range of possible durations of an activity
Monte Carlo Simulation based scheduling technique runs a simulation with a
given number of iterations, during which each activity durations falls
randomly within the assigned distribution of possible durations for that
activity
The total project duration is measured and recorded for each iteration and
plots each value for total project duration recorded on a frequency
distribution chart when completed
The Program Evaluation and Review Technique (PERT) has been developed to
evaluate the uncertainty or risks in projects whose activities’ duration cannot
be determined for certain. PERT has been criticized for its several limitations
(such as suitability of a beta distribution for activity durations and its focus on
a single critical activity path).
Due to the severe limitations associated with PERT-based scheduling
practices, project schedulers should begin to utilize Monte Carlo simulationbased scheduling method to better understand the variability in project
duration. This shift will require current scheduling professionals to recognize
the limitations of PERT and how Monte Carlo simulation can be used to
overcome these deficiencies. Transitioning from the commonly utilized PERTbased scheduling method to Monte Carlo-based scheduling method can be
made easier with the development of specific standard practices for
professionals using Monte Carlo simulations.
The audience will understand how Monte Carlo simulation-based scheduling
methods can be applied to reduce uncertainties in the variability of project
duration. The set of standard practices will help professional schedulers
transition from PERT to Monte Carlo simulation-based scheduling.
With the information provided by the Monte Carlo simulation, additional
tools can be used in order to further analyze the results of the simulation.
What differentiates PERT and Monte Carlo simulation
based scheduling?
• PERT is only capable of accounting for duration uncertainty using a
weighted average technique
• Monte Carlo simulation has capability of accounting for a large variety of
uncertainty facing project duration using sophisticated modeling
techniques
Michael Thornton
Email: mpthorn@ilstu.edu
Web Address: http://www.linkedin.com/in/mthornton1