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Schedule Basis Memorandum - Inclusion of Statistics

posted Jul 28, 2022, 6:07 AM by jeffery jim

I am preparing a few abstracts for conventions this year. Among these papers are related to project management apart from engineering and geology. One of the key papers I am going to present would be in regards to risk distribution which was never entailed and annexed previously in preparation of Schedule Basis Memorandum (SBM) as essential submission when deriving a work program for projects by NGCs like PETRONAS. Unlike JKR PWD203 variants contract which require a conventional project contractor to submit a work program in just fourteen days, NGCs or mega projects of national interest require and allow for a longer period of time to prepare a work program. Often, the work program will be scrutinized and SBM is one of the many bases a planner or project control engineer will be based on.
2. For many years, contractor will have to prepare a work program using software like MS Project and Primavera to compute a decent work program which capitalized on Gantt Chart and PERT features which are related to Monte Carlo simulation. Here, the longest route is called critical path and this method is called Critical Path Method (CPM). This path shows the ultimate time required by the project in order to complete based on project brief, contract, cost, time and statutes.
3. Although these software and tools have been dominant in establishing basic requirement to establish a manifested contract where time is always of the essence, it lacks in robustness during the project control phase. Most of the time, the CPM established may not be the crux to delay. The inability to foresee other risks within the network and nexus of a series of works has hindered many stakeholders from tracking delays during the earlier part of project implementation stage. This is also a reason why S-curve for typical projects are always flattened at the 30% of the project duration before start to climb in linear or exponential shape toward the 90% of the total contract time.
4. In order to tackle this problem, many kind of risk analysis tools have been introduced and adopted. It can be Fishbone method, Tripod Beta method and so on; where all are then included into a risk register. The problem with risk register is a statistic subset and known as ordinal data. It is a grouping and then arithmetically summed to have a register with categorization. Less robust risk register only categorize risks as ordinal and nominal dataset. This is how data are segregated and analyzed. It is over simplified and traditional as conventional approach is much easier to understand, control and dictate but these have zero value when it comes to implementation with bigdata.
5. SBM usually incorporate these kind of oversimplified registers which often bring zero value when it comes to forecasting. These kind of registers cannot be use for further statistical analysis when associating a work program with risk assessment tools such as Primavera Risk Analysis or Safran Risk Manager. There is no way for a client to injunct a remedial or recovery plan especially when it comes to micromanagement. A specific approach is required and hence, a statistical approach for analysis is required when it comes to thorough contractual documentation and determination.
7. One of the many features in a risk management software is the allocation of risk and uncertainty distribution. This is essential where the distribution of risks are divided into many types, typically; beta pert, lognormal, triangulation and others. Unlike a typical scheduling software with uniform distribution, the inclusion of these graphs is essential when running Bayesian Belief Network and Monte Carlo simulations up to 1,000 iterations. Nevertheless, the basis to establish each task and its risk distribution should be determined based on past project bigdata. Without a prior and typical population, a posterior cannot be established nor conclusive in depicting or rendering a possibility.
8. For this reason, a call to establish specific type of distribution is indispensable and inevitable. The only variable in this kind of distribution shall be regional or internal issues when it comes to kurtosis of the graph as the eccentricity of the graph is fixed based on bigdata. Hence, this will give project control department more power to interject a possible delay before resorting to mitigation works which is too late and time consuming.
9. Another advantage of statistical and scientific approach would be great for client or top management to establish their project timeline during the initial stage of a project lifecycle as it will provide assurance that the contract brief is realistic and have at least achieved at a range between the seventy-fifth percentile to the eighty-fifth percentile which fits Pareto Rule instead of picking a number from the sky or making references from past projects with different set of risks, quantum and magnitude.

May be an image of text that says "70 60 50 Original completion date 40 risk of 30 Jaqunn 20 10 Frequency of risk encounters during project schedule Beginning contract date 2តល 30 40% 5 260% Percentage of the original project schedule Fig. 1. Distribution of risk encounters"
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