The document discusses schedule risk analysis for an industrial waste water treatment plant project in Saudi Arabia. It describes: 1) Conducting a cost risk analysis that examined the impact of variable cost and sales revenue variations on profits and identified the likelihood of these variations. 2) Performing a schedule risk analysis by estimating the impact of project delays, using Monte Carlo simulation to determine the probability of completing the project on time or with delays, and identifying causes and mitigation plans for delays. 3) Outlining the key steps of the schedule risk analysis including developing a baseline schedule, defining uncertainty in activity times, running Monte Carlo simulations, and interpreting sensitivity results.

1. Schedule Risk Analysis
Asaman Patnaik
Project schedules are plans for future activities based on estimates of time and cost. There is
always a factor of uncertainty in predicting these estimates. Estimates about activity time and
cost are predictions for the future and depend on human beings who often tend to be overly
optimistic (most of the projects worldwide experience time overrun of more than 50%) or, on the
contrary, may add some reserve safety to protect themselves against unexpected events.
Thus, knowledge about the potential impact of these estimation errors on the project objective is
a key add-on to the construction of a project’s baseline schedule. Schedule Risk Analysis is a
simple but effective technique that connects the time and cost risk uncertainty of individual
activities to the base line schedule by replacing the deterministic duration for each task by a
distribution representing the range of likely durations.
Steps for Schedule Risk Analysis:
1. Baseline schedule: Construct an activity timetable
2. Define uncertainty: Define activity time and cost probability distributions
3. Run Monte-Carlo simulations: Run multiple project progress simulations
4. Interpret the simulation results: Interpret the sensitivity measures
1. Baseline schedule
The construction of a project baseline schedule involves the definition of start and finish times
for each project activity, using earliest and latest start calculations.
The project baseline schedule serves as a point of reference. In case everything goes according
to plan, then the project can be completed as per this base line schedule which is very unlikely.
2. Define risk/uncertainty
Time and cost estimates are often subject to a margin for error. It is more accurate to estimate a
range of duration and cost estimates for project activities.
3. Monte-Carlo simulations
Monte-Carlo simulation is a simple technique to quickly generate multiple runs simulating real
project progress. Each simulation run generates duration for each project activity.
4. Sensitivity results

2. The output of a schedule risk analysis is a set of measures that define the degree of activity
criticality and sensitivity. Each measure gives the project manager an indication of how sensitive
the activity is towards the final project duration or total cost
A case study of cost and schedule risk analysis carried out for an Industrial Waste Water
Treatment Plant Project at Saudi Arabia is outlined in the subsequent paragraphs.
ABOUT THE PROJECT
Make up water for the client’s existing plant at Saudi Arabia is met by purchasing from a utility
company. The effluent generated in the plant is also sent for treatment at a common effluent
plant for which the client pays the treatment cost.
The client proposes to set up an Industrial Waste Water Treatment Plant to treat about 6000
cum/ day of waste water, to generate around 3600 cum/day of treated water that can replace
part of makeup water being used in the plant. The IWWTP shall generate about 2200 cum/day
of reject that still needs to be sent to CETP.
Thus, by setting up the project, client will reduce the cost towards purchase of makeup water of
3600 cum/day and also reduce the cost of treatment of effluent from 6000 cum/day to 2200
cum/day.
TCE was asked by the client to carry out the cost risk analysis and schedule risk analysis for the
project.
A. Cost Risk Analysis
Cost Risk Analysis carried out consisted of the following:
A1 Impact: Impact of variation in cost and sales revenue on the financial indices such as
Profit before Tax (PBT) and Contribution was calculated. This was estimated by carrying out the
financial evaluation of the project, followed by a sensitivity analysis for variation of 5 to 20% in
(a) variable costs (b) sales revenue and combination of both (a) and (b).
For each of three scenarios the variation of PBT for base case, 5%, 10%, 15% and 20% were
plotted.
Further, considering stable operation in 3rd
year, the trend of PBT and contribution was analyzed
for the above 5 cases to indentify the sensitivity.
For decrease in sales revenue, two options were analyzed. (1) Decrease in makeup water price
(2) Decrease in productivity.
A2 Likelihood: The likelihood of variation in cost, sales volume was identified.

3. Key items of variable cost are treatment cost (45%), chemicals (22%) and electricity (13%). The
price trends for these were analyzed, and also the future trend as per Dow’s Chemical Index
was analyzed, to predict likelihood of increase in variable cost.
The trends of makeup water cost over the last 10 years were analyzed, to predict the likelihood
of decrease in sales price.
A3 Conclusion
Based on the above, the risk on financial parameters of the project was analyzed and mitigation
plan suggested.
B. Schedule Risk Analysis
The schedule risk analysis was carried out to find the impact and likelihood of project
delay.
B1 Impact
The impact on project cost, revenue and profit for 10 years period were estimated for base case
(on schedule), delay of 3 month, 6 months, 9 months and one year.
B2 Likelihood
The likelihood of project delay was estimated using Monte Carlo Simulation as follows:
1. The probabilistic duration of each activity the project was analyzed and mutually agreed
with client on three scenarios:
(a) Likely (Probable)
(b) Best Case (Minimum)
(c) Worst Case (Maximum)
2. The overall project duration was found out for the above three scenarios.
3. Based on the minimum and maximum duration, a Monte Carlo Simulation was carried
out by generating 1000 random numbers. The simulation was done 500 times. Based on
the same, the probability of project completion with 80% and 90% confidence level were
found out.

4. B3 Causes of Project Delay and Mitigation Plan
The probable causes of project delay and mitigation plan were identified and tabulated.
0.00%
2.00%
4.00%
6.00%
8.00%
10.00%
12.00%
14.00%
16.00%
353637383940414243444546474849
Likelihood%
Project Completion in Months
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
100.00%
35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
Likelihood%
Project Completion on or before, months