W23_SJP_Knowledge Enhancement for GPC ELPC Examinations (Part 2)

Issue Identification and Appraisal

As mentioned in the Blog 22, the final few blogs will look at areas where my knowledge is lacking and needs to be enhanced in order to increase my opportunities for be in good standing for doing the final examination.

The GPC’s self-assessment questionnaire uncovered a few deficient knowledgeable areas that need addressing. In order to better understand the subject areas development of blogs to assist learning about the areas is a way to better absorb the content. The final few blogs will all have the same problem statement, “What subject areas need knowledge advancement prior to undertaking the GPC Expert Level Project Controls examination?”

Feasible Alternatives

The deficient subject areas can be termed feasible alternatives, and these are:

  • Monte Carlo Simulation
  • Configuration Management
  • BIM Modelling
  • Project Forensics
  • Stakeholder Engagement – covered in Blog 22
  • Contract Selection
  • Management Competencies

The above list is based on the results from the GPC’s self-assessment which was performed in May’2017 and is a summary of seven areas that need enhancement in the coming weeks. Hopefully a blog can be developed for each item during the remaining weeks the course runs. For Blog 23, the subject will be “Monte Carlo simulation’, a subject the author is familiar with regarding the process and inputs required but not the setting-up and running of a full simulation for either Cost or Schedule. Initially the course provided a demo copy of “Palisade’s @Risk” software, but this has since expired, and the purchase cost of a package is very expensive, therefor this blog will use RiskAMP as the software to develop the model(s) and produce the result(s). RiakAMP can be downloaded from the internet at https://www.riskamp.com/download with a 30-day trial available in order to decide to purchase or not, with a single-user license costing around $130 for the “Personal & Learning Edition”.

Develop the Outcomes for each

Each remaining blog will develop an outcome for each ‘Feasible alternative’ (FA) subject as the subject gets reviewed, it will not identify an outcome for the other FA’s in that blog.

The use of Monte-Carlo simulation is defined in several modules within the GPCCAR, M04-4 “Assess, Categorize, Prioritize and Quantify Risks or Opportunities”, M07-10 “Conducting a Schedule Risk Analysis”, M08-7 “Validate the Time & Cost Trade-Offs” and M08-9 “Conducting A Cost Risk Analysis”. Each module provides a brief overview of what is required, but is short in assisting the Project Control Professional (PCP) in development of a model. This is probably the best approach as these types of simulations tend to be specialized and interpretation of the results need to be carefully transmitted to the project team and stakeholders.

Review of the GPC self-assessment items shows that there are four items to be addressed, see table 1 below.

Table 1 – Monte-Carlo items in GPCCAR Self-assessment

Selection Criteria

The criteria for this blog is going to use the conceptual project that was used during the development of the authors Paper 5, and blogs 18, 19 and 20.

Figure 1 – Conceptual Project Estimate & Schedule

Analysis and Comparison of the Alternatives

As mentioned above, there are four items requiring answers so they will be dealt with individually in order to satisfy what maybe be requested in the pending examinations.

Item 1 – Set-up and Run a Schedule Risk Assessment

As this is a summary schedule as opposed to a level 4 detailed schedule, results will vary, the more detailed the schedule the better results that can be obtained, however it also takes time to set-up, but for blog purposes, this level of detail is great and demonstrates the process that will be performed to get the results. One area that the author has not included here is the use of a risk register whereby specific risks are identified against specific schedule activities. In this example estimates for ‘Best’ and ‘Worst’ durations have been assumed (see below).

As already mentioned, the use of RiskAMP to assist in the Monte-Carlo analysis will be the software of choice. Setting up the sheet was not such an arduous task as expected.

Figure 2 – Schedule Inputs for Simulation

Inputs; Expected = Current Schedule Duration / Best = used a 1 to 3 month saving depending on the EPC / Worst = 3 to 6 month delay depending on the EPC. The Best & Worst cases were purely estimates for the purposes of the blog and had no scientific approach behind them.

Once the model is set-up, and the inputs are complete, all that remains is to run the simulation. In this case the option to use 2,500 iterations was chosen to provide a larger exposure to results obtained for better accuracy. Figure 3 below shows the final report provided by the software.

Figure 3 – Schedule Simulation Report

Based on the above, the simulation is telling us that there is a 42% chance of completing the project in the current schedule duration, and the 90% probability of completing the project is 86 days later. This occurs largely due to using ‘most likely’ (or average) durations as the basis of the schedule activities. This is the type of information that would be provided to the stakeholders for them to determine whether or not they acted on this or determine that more detailed analysis is required before finalizing the schedule. In certain instances, the results can be used to determine the amount of schedule reserve that should be allocated to back-end of the schedule for reporting to shareholders

Item 2 – Set-up and Run a Cost Risk Assessment

Performing a Cost Risk Assessment is a very similar process to that of the Schedule Risk Assessment, only difference that it is costs that are being evaluated, and the Best/Worst (Minimum/Maximum) are evaluations of the Cost Estimate values. Again, for the blog example it has been kept simplistic, and in real life this model would require a great deal of time in which to build an accurate model for evaluation. Building the model correctly is key to determining whether the cost (or schedule for that matter) risk assessment is going to provide valuable results. Figure 4 below provides a view of the Cost Estimate evaluation when run through Monte Carlo simulation.

Figure 4 – Cost Simulation Report

The above cost simulation shows that there is a 65% probability of overrunning the base estimate, with only a 35% chance of meeting the base estimate. The use of this information allows estimators and management to understand the risks and determine contingency levels for the final estimate package.

Selection of Preferred Alternative

There are no preferred alternatives in this case, all 4 items listed above are needed to enhance current knowledgebase ahead of the GPC ELPC Examination.

Monitoring Post Evaluation Performance

Post evaluation monitoring will be to see if what has been provided above has been fully understood and useful to assist successful passing of the examination, and then used on future projects to demonstrate the effectiveness and value of what a Project Control Practitioner provides to the project team, and decision-making process.

References

 

One Reply to “W23_SJP_Knowledge Enhancement for GPC ELPC Examinations (Part 2)”

  1. AWESOME Steve….. I am REALLY going to miss having you as a student!!! You have been so enjoyable to work with.

    When you are done, I would like to write a glowing letter of recommendation for your Linked In profile and am more than happy to serve as a reference either for your Guild application or for any job you are being interviewed for.

    BR,
    Dr. PDG, Muscat, Oman

     

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