We are now in starting point of EPC execution phase where the contract of EPC work will be delivered. One of the critical month in the execution phase is when the resource loaded & cost incurred so “expensive”.
DEVELOPMENT OF FEASIBLE ALTERNATIVES
To identify the month when the resource and cost are mostly loaded, we need a method to demarcate when the “expensive” month will occurred.
Figure 1. Pareto’s Law Distribution Figure
DEVELOPMENT OF OUTCOMES FOR EACH ALTERNATIVE
Referring to Pareto’s Law that 80% cost will be incurred by 20% of activities. This law implies that even we have to control all the activities but our major attention should be to expensive month that produce cost 80% of total project cost.
Figure 2. Cost Distribution Over Time During Project Life cycle.
SELECTION OF CRITERIA
To identify expensive month that produce total cost ± 80% of total project cost we need to Sort out the month from the most expensive.
Figure 3. Identified most Expensive Month Using Pareto’s Law (80% cost incurred).
Figure 4. Cost Breakdown Structure and Cost Distribution Model
ANALYSIS FOR THE ALTERNATIVES
Based on above cost sorted in figure 34, we can identify that the most critical and expensive month is in October 2014 (US$ 33,107,402). The most critical range of time are from Mid of 2014 to Mid of 2015 where majority activities would be Procurement, and Fabrication and Construction and the end of the project for “Hook Up and Commissioning”.
SELECTION ON THE PREFERRED ALTERNATIVES
Using the Pareto’s Law on Resource Load or cost forecast give us a picture of “by when we need money Mostly” and by when we need resource loaded mostly. This Pareto’s Law is helpful to manage the project cash flow.
PERFORMANCE MONITORING AND POST EVALUATION RESULT
Pareto’s Law is applicable for cash flow management and cost phasing. The existing cost distribution is based on current situation. On the real project, it’s imperative to re-forecast the cost and the distribution over project life cycle time.
Memory Jogger 2nd Edition (2010).Tools for Continious Improvement and Effective Planning. GOAL/QPC
Alfred Ultsch (2002).Proof of Pareto’s 80/20 Law and Precise Limits for ABC-Analysis.Retrived on November 9, 2013 from http://www.informatik.unimarburg.de/~databionics/papers/ultsch02proof.pdf
Better Explained. Understanding the Pareto Principle (The 80/20 Rule).retived on November 9, 2013 from http://betterexplained.com/articles/understanding-the-pareto-principle-the-8020-rule/