**1. Problem Definition**

Downstream Oil&Gas Business Unit in a company plan to make a new Gas Station. The Project Management Division asked to make a cost estimation for the Project.

Previously, PM division has developed some Gas Station and found that there were some change order occure during contract which led to cost overrun. Therefore, it is necessary to prepare cost contingency for the Project to anticipate the additional cost.

**2. Development of Feasible Alternative**

There are 4 methods to estimate cost (also time) contingency, i.e. [1]:

- Expert Judgment
- Predetermined Guidelines
- Simulation Analysis
- Range Estimation
- Expected Value

- Parametric Modeling

For this case, Author uses Simulation Analysis with Range Estimation method.

Range estimating is a risk analysis technology that combines Monte Carlo sampling, a focus on the few critical items, and heuristics (rules of thumb) to rank critical risks and opportunities. This approach is used to establish the range of the total project estimate and to define how contingency should be allocated among the critical items. [2]

**3. Development of the Outcomes for Alternative**

The following steps will be used to determine cost contingency using range estimating [3]:

- Determines of ranges for each cost items.
- Determines the probability that each item can be completed within the estimate.
- Running Monte Carlo simulation for the cost range.
- Determines of critical items based on result of Monte Carlo simulation.
- Determine of contingency with reference to critical items only.

Following are base estimates for each cost items:

Based on analysis on previous project, Estimators has developed following table of Range of each cost item. A good estimate should have equal probability of overrun and underrun (i.e., a 50% probability). This is a risk neutral approach, the assumption being that some projects will overrun while others will underrun and, in the long run, they will balance out. [4]

But, since Estimators has risk-aversed attitude, P80 will be used. It means that probability of 80% that the Project will not overrun.

After determining range and desired probability of cost items, further step is to conduct Monte Carlo simulation with 1.000 iterations. The results as follows:

**4. Selection of the Acceptable Criteria**

To find out what cost items categorized as critical items, Author use Bottom Line Critical Variances table as follows:

**5. Analysis and Comparison of the Alternatives**

By using above criteria (for Classes 3, 4, 5), critical items result as follows:

**6. Selection of the Preferred Alternative**

The last step is to determine the cost contingency, as shown in the following table:

The key to performing a project risk analysis using range estimating is to properly identify those items that can have a critical effect on the project outcome and in applying ranges to those items and only to those items [6].

Hence, the total cost contingency will be used for this project is $ 40.690 (only for critical items).

**7. Performance**** Monitoring and the Post Evaluation of Result.**

It is necessary to conduct strict cost control during implementation of the Project to prevent the cost overrun exceed the cost contingency.

**References:**

- AACE International. (2008). Recommended Practice No. 40R-08,
*Contingency Estimating – General Principles*, page 3 – 4, AACE International. Morgantown, WV. - AACE International. (2008). Recommended Practice No. 41R-08,
*Risk Analysis and Contingency Determination Using Range Estimating*, page 1, AACE International. Morgantown, WV. - Wain, Yosep Asro. (2014). Contingency Estimation in Storage Tank Project. Retrieved from: https://kristalaace2014.wordpress.com/2014/07/07/w20_yaw_contingency-estimation-in-storage-tank-project/
- Ibid 2
- Ibid 2
- Ibid 2
- Sadat S.D. (2013).
*W3_SSD_Contingency Cost Determination in Transformer Installation Project*. Retrieved from http://simatupangaace2014.wordpress.com/2013/09/21/w3_ssd_-contingency-cost-determination-in-transformer-installation-project/

Nice Pak Rico!!! VERY interesting case study!!!

Couple of follow on questions…..

1) Did you run a statistical process control check to make sure that there were no OUTLIERS in your data? Surprising how just a few outliers can skew the results.

2) What you MIGHT want to experiment with is instead of using the MEAN, try using the MODE or the MEDIAN values? See if that makes your calculations better or worse. Your objective is to get the variance as low as possible.

3) For the 4 high risk items (Yes under critical) what happens if you increased the contingency from P80 to P90?

Again you’ve picked a really interesting case study and you probably can get another blog out of it if you are willing to experiment with different distributions and modifying the P levels in line with the risk of each WBS item….

BR,

Dr. PDG, Guangzhou, China

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