W15-ABM-Developing the BCWS Recovery Curve using IEAC-Part 2

  1. Problem Definition

Following my Week 14 assessment of IEAC, 4 methods were used to calculate the EAC.

After reviewing each method, IEAC 3 was determined to be the most suitable however  this still implied that the Estimated Cost at completion would be some 183% above original Budget. This is unrealistic and would appear to be an over estimate of remaining cost.

Another method is now required to determine the IEAC and this weeks blog will assess further alternatives.

2. Feasible Alternatives

Last week we considered IEAC1-4 which can be described as;

  • IEAC1 = ACWP + ((BAC – BCWP) / CPI)
  • IEAC2 = ACWP + ((BAC – BCWP) / SPI)
  • IEAC3 = ACWP + ((BAC – BCWP) / CPI * SPI)
  • IEAC4 = ACWP + ((BAC – BCWP) / ((0.2 * SPI) + (0.8 * CPI))

This week we will assess the IEAC using pproductivity  and unit cost referred to as IEAC 5.

3. Development of the Alternatives

IEAC 5 method considers the Actual productivity or unit cost of work completed to date as the basis for predicting the cost of balance works.

As noted in my week 13 blog, BCWS,BCWP and ACWP figures during Week 0 were calculated in line with the nominated split and weightages provided in notes. This has created some inconsistencies in the reporting figures where by earned values are limited by an pre determined arbitrary weighting which is misaligned with BCWS and ACWP figures – wrongly indicating that productivity is low.

As such, inclusion of week 0 figures in any productivity assessment would not provide an accurate indication of how many hours (or cost) have  been spent to date on actual tasks to establish a correct unit cost.

As such we will exclude week 0 costs and earned value and make an assessment of Productivity based on week 1 to 13 only.

Table 1 below summarises budget and estimate productivity based on the total work units required to completed the course;

CPI is based upon comparison of Budget and Actual unit cost of for works completed from weeks 1 to 13 and indicates that 3 out 5 are operating under budget.

Unit costs associated with weekly blogs and reports are however significantly over budget when considered on a unit cost basis.

Table 2 further outlines the IEAC for method 5.

4. Selection Criteria

The same selection criteria is to be applied as per week 13 blog.

  1. Realistic
  2. Reduce chance of further increases / changes

5. Comparison of the Alternatives

Table 3 outlines comparisons between all 5 methods

IEAC 5 provides the lowest IEAC ($27,717) compared to the previously preferred methods IEAC 1 & 4 ($33,233) which was also determined using CPI figures without any allowance for week 0.

6. Selection of Alternatives

IEAC 5 is considered more appropriate as a method for assessing my own IEAC. It ignores the week 0 anomalies and uses the actual unit cost of works completed so far to estimate . Unit costs do however still include learning curve inefficiencies during early phases and as such, productivity is expected to improve and assist with final cost

7. Performance Monitoring

Current Dashboard to include weekly assessment of IEAC based on unit productivity and cost – excluding week 0 figures.

References

  1. W09_SJP_Forecasts retrieved 5 November 2107 from https://js-pag-cert-2017.com/w09_sjp_forecasts
  2. Chapter  9.5 – Performance Monitoring Progress – Guild of project controls compendium and reference (CaR) | Project Controls – planning, scheduling, cost management and forensic analysis (Planning Planet).  Retrieved from http://www.planningplanet.com
  3. National Defence Industrial Association. (2014). A Guide to managing programs using predictive measures.
 

W12_TH_Contract Risk Mitigation for Tug Boat Rental

1. Problem Definition

Author has been conducting bidding for tug boat rental as part of LNG supply chain to PLN power plant on Kupang area. Duration for the contract is one year period, start from January-December 2018. This contract is very vulnerable to weather conditions because if the weather is bad then the tug boat could not be used. So that, during negotiation meeting, the prospective winner bidder proposed 2 options for its offer. First option is IDR 7,800,000,000 without condition; or second option is IDR 7,500,000,000 + IDR 22,000,000/day stand by rate if tug boat could not be used due to a bad weather.

2. Identify the Possible Alternative

Facing to this case, we have to decide which proposal option is accepted, IDR 7,800,000,000 without condition (option 1); or IDR 7,500,000,000 + IDR 22,000,000/day stand by rate (option 2).

3. Development of The Outcome for Alternative

It is clearly that if we accept first option, then contract price will be IDR 7,800,000,000.

But, for the second option, we must to ensure the stand cost that might be happened. For calculating the standby cost, we need to know the number of bad weather days during period of work. This number may be estimated by using historical weather data. The following table contains weather data for past five years from Indonesian Agency for Meteorological, Climatological and Geophysics:

Table 1. Occurrences of Bad Weather (In Days)

By using Monte Carlo simulation, it is forecasted the total bad weather days for each month in 2018, at P70 as follows:

Table 2. Occurrences of Bad Weather in 2018

Therefore, stand by cost is estimated as 20 days * IDR 22,000,000 = IDR 440,000,000,

so that the price for second option is IDR 7,500,000,000 + IDR 440,000,000 = IDR 7,940,000,000.

4. Selection Criteria

Of course, the main criterion is the lower cost. Another criteria is comes from our bidding procedure, namely the price should be lower than our owner’s estimation (OE) of IDR 8,000,000,000.

5. Analysis & Comparison of Alternative

Below table contains total cost for both options:

Table 3. Total Cost for Both Options

From the table 3, option 1 is cheaper IDR 140,000,000 than option 2

6. Selection of the Preferred Alternative

Based on comparison table above, we decided to proceed with option 1, IDR 7,800,000,000

7. Performance Monitoring and The Post Evaluation of Result

Monitoring and supervision should be conducted strictly during the execution of the work, especially in relation to the determination of whether a day is bad weather or not.

References:

  1. Sullivan, G. W. (2014). Engineering Economy 16th Chapter 12 – Probabilistic Risk Analysis, pp. 526-562. Pearson. Sixteenth Edition.
  2. Monte Carlo Simulation. Retrieved from http://www.palisade.com/risk/monte_carlo_simulation.asp
  3. Asro, Yoseph. (2014). W4_YAW_Contract Risk Mitigation|Kristal AACE 2018. Retrieved from https://kristalaace2014.wordpress.com/2014/03/17/w4_yaw_contract-risk-mitigation/
  4. Fakhri, Muhammad. (2017). W4_MFO_Contract Risk Mitigation|Emerald AACE 2018. Retrieved from http://emeraldaace2017.com/2017/08/22/w4_mfo_contract-risk-mitigation-for-topographic-survey/
  5. Weather data. Retrieved from http://dataonline.bmkg.go.id/home