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	<title>Monte Carlo Simulation &#8211; GleeYM</title>
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		<title>Is it important to focus on Access Road Construction for mega Complex remote project? 4 Figures Depict a Complete Story!</title>
		<link>https://www.gleeym.com/2021/02/16/accessroad/</link>
					<comments>https://www.gleeym.com/2021/02/16/accessroad/#respond</comments>
		
		<dc:creator><![CDATA[mindmap]]></dc:creator>
		<pubDate>Tue, 16 Feb 2021 18:56:01 +0000</pubDate>
				<category><![CDATA[Cost Risk Analysis]]></category>
		<category><![CDATA[Decision Making]]></category>
		<category><![CDATA[Monte Carlo Simulation]]></category>
		<category><![CDATA[PMO]]></category>
		<category><![CDATA[Project]]></category>
		<category><![CDATA[Quantitative]]></category>
		<category><![CDATA[Risk]]></category>
		<category><![CDATA[Schedule Risk Analysis]]></category>
		<category><![CDATA[Software]]></category>
		<category><![CDATA[Access road construction]]></category>
		<category><![CDATA[Construction project]]></category>
		<category><![CDATA[Cost overrun]]></category>
		<category><![CDATA[Distribution Graph]]></category>
		<category><![CDATA[Energy]]></category>
		<category><![CDATA[Flash flood]]></category>
		<category><![CDATA[Integrated risk analysis]]></category>
		<category><![CDATA[Mega complex project]]></category>
		<category><![CDATA[Mining]]></category>
		<category><![CDATA[Oil & Gas]]></category>
		<category><![CDATA[Risk drivers]]></category>
		<category><![CDATA[Risks]]></category>
		<category><![CDATA[Schedule delay]]></category>
		<category><![CDATA[Sensitivity Analysis]]></category>
		<category><![CDATA[Uncertainty]]></category>
		<category><![CDATA[Weather]]></category>
		<category><![CDATA[What if analysis]]></category>
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					<description><![CDATA[Real Estate Development Project &#8211; Better way to Envisage Your Project&#8217;s Future. How? 4 Graphs are Enough to Illustrate! Keywords Access road construction, Mega complex project, Construction project, Schedule delay, Cost overrun, Sensitivity analysis, Uncertainty, Risks, Weather, Flash flood, Energy, Oil &#38; Gas, Mining, Monte Carlo simulation, What if analysis, Distribution graph, Cost risk analysis, [&#8230;]]]></description>
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					<h1 class="elementor-heading-title elementor-size-default">Real Estate Development Project - Better way to Envisage Your Project's Future. How? 4 Graphs are Enough to Illustrate!</h1>				</div>
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					<h2 class="elementor-heading-title elementor-size-default">Keywords</h2>				</div>
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									<p style="text-align: justify;">Access road construction, Mega complex project, Construction project, Schedule delay, Cost overrun, Sensitivity analysis, Uncertainty, Risks, Weather, Flash flood, Energy, Oil &amp; Gas, Mining, Monte Carlo simulation, What if analysis, Distribution graph, Cost risk analysis, Risk drivers, Schedule risk analysis, Integrated risk analysis</p>								</div>
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					<h2 class="elementor-heading-title elementor-size-default">Summary</h2>				</div>
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									<p style="text-align: justify;">Energy and mining projects are complex and mostly being executed in remote areas. Site accessibility, weather, uneven terrain, and mobility are the factors that make it more difficult to execute remote area projects. After asset acquisition and getting all necessary permits, the construction of an access road to actual site area is a topmost priority.</p><p style="text-align: justify;">Flash flood is unpredictable and can be showstopper in hilly terrain. Analyzing the impact of flash flood, using Monte Carlo simulation, helps to examine the various scenarios and plan mitigation actions to minimize the risk.</p>								</div>
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					<h2 class="elementor-heading-title elementor-size-default">Case Study</h2>				</div>
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									<p style="text-align: justify;">The construction of access roads is an extremely important that needs to be done at the right time. Any delay in construction can delay the site access and mobilization of team and equipment for field development, and It also needs to be done with the best equipment and materials available, keeping in mind the specific needs of the client.</p><p style="text-align: justify;">Flash Floods are unpredictable. Mostly, water follows its path, but it changes its direction depending upon the water quantity and pressure, etc.</p>								</div>
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					<h2 class="elementor-heading-title elementor-size-default">Project Schedule</h2>				</div>
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									<p style="text-align: justify;">Level I project schedule is shown in fig. 1:</p>								</div>
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										<img fetchpriority="high" decoding="async" width="800" height="146" src="https://www.gleeym.com/wp-content/uploads/2021/02/Access-Road-Schedule-1024x187.png" class="attachment-large size-large wp-image-2672" alt="Level I Schedule developed by Gleeym for schedule and cost risk analysis" srcset="https://www.gleeym.com/wp-content/uploads/2021/02/Access-Road-Schedule-1024x187.png 1024w, https://www.gleeym.com/wp-content/uploads/2021/02/Access-Road-Schedule-300x55.png 300w, https://www.gleeym.com/wp-content/uploads/2021/02/Access-Road-Schedule-768x141.png 768w, https://www.gleeym.com/wp-content/uploads/2021/02/Access-Road-Schedule-1536x281.png 1536w, https://www.gleeym.com/wp-content/uploads/2021/02/Access-Road-Schedule-600x110.png 600w, https://www.gleeym.com/wp-content/uploads/2021/02/Access-Road-Schedule.png 1574w" sizes="(max-width: 800px) 100vw, 800px" />											<figcaption class="widget-image-caption wp-caption-text">Fig. 1- Level 1 Schedule</figcaption>
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					<h2 class="elementor-heading-title elementor-size-default">Uncertainty and Risk</h2>				</div>
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									<p>There can be a long list of  risks but considered only three (3) top risks.</p><ol><li>Flash Flood – Recurring flash flood from May to Sep to hamper Access Road Construction and Plant site.</li><li>Delay in delivery of Bulk Material to site</li><li>Unavailability of Skilled Labor</li></ol><p>Risks were mapped to the activities along with the uncertainties.</p>								</div>
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					<h2 class="elementor-heading-title elementor-size-default">Monte Carlo Simulation</h2>				</div>
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									<p style="text-align: justify;">After schedule check, mapping uncertainties and risks to schedule activities ran the Monte Carlo Simulation. The “Distribution Graph” is showing the results for a schedule in fig. 2:</p>								</div>
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										<img decoding="async" width="800" height="438" src="https://www.gleeym.com/wp-content/uploads/2021/02/Access-Road-S-curve-1024x560.png" class="attachment-large size-large wp-image-2693" alt="Access Road S curve performed by GleeYM" srcset="https://www.gleeym.com/wp-content/uploads/2021/02/Access-Road-S-curve-1024x560.png 1024w, https://www.gleeym.com/wp-content/uploads/2021/02/Access-Road-S-curve-300x164.png 300w, https://www.gleeym.com/wp-content/uploads/2021/02/Access-Road-S-curve-768x420.png 768w, https://www.gleeym.com/wp-content/uploads/2021/02/Access-Road-S-curve-600x328.png 600w, https://www.gleeym.com/wp-content/uploads/2021/02/Access-Road-S-curve.png 1098w" sizes="(max-width: 800px) 100vw, 800px" />											<figcaption class="widget-image-caption wp-caption-text">Fig. 2 - Distribution Graph (S Curve) for a Schedule</figcaption>
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									<p style="text-align: justify;">With uncertainties and risks, the chances of meeting target date are almost 0%. The distribution graph shows that there will be a 50% (mean) chance that the project will be completed on 22-10-2021 i.e., 57 days.</p>								</div>
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									<p style="text-align: justify;">What about the time-phased cost? The “Distribution Graph” is showing the results for a cost in fig. 3:</p>								</div>
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										<img decoding="async" width="800" height="517" src="https://www.gleeym.com/wp-content/uploads/2021/02/Cost-1024x662.png" class="attachment-large size-large wp-image-2709" alt="Time phase distribution graph for cost by Gleeym" srcset="https://www.gleeym.com/wp-content/uploads/2021/02/Cost-1024x662.png 1024w, https://www.gleeym.com/wp-content/uploads/2021/02/Cost-300x194.png 300w, https://www.gleeym.com/wp-content/uploads/2021/02/Cost-768x496.png 768w, https://www.gleeym.com/wp-content/uploads/2021/02/Cost-600x388.png 600w, https://www.gleeym.com/wp-content/uploads/2021/02/Cost.png 1032w" sizes="(max-width: 800px) 100vw, 800px" />											<figcaption class="widget-image-caption wp-caption-text">Fig.3 - Distribution Graph (S Curve) for a Cost</figcaption>
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									<p style="text-align: justify;">With uncertainties and risks, the chances of meeting target estimated costs are almost 3%. The distribution graph shows that there will be 50% (mean) chance that extra cost will be $ 1,445,705. Furthermore, there will be an 80% chance that total project cost will be around $11.72 M.</p>								</div>
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										<img loading="lazy" decoding="async" width="800" height="413" src="https://www.gleeym.com/wp-content/uploads/2021/02/PCF-1024x529.png" class="attachment-large size-large wp-image-2720" alt="Probability Cash Flow performed by Gleeym" srcset="https://www.gleeym.com/wp-content/uploads/2021/02/PCF-1024x529.png 1024w, https://www.gleeym.com/wp-content/uploads/2021/02/PCF-300x155.png 300w, https://www.gleeym.com/wp-content/uploads/2021/02/PCF-768x397.png 768w, https://www.gleeym.com/wp-content/uploads/2021/02/PCF-600x310.png 600w, https://www.gleeym.com/wp-content/uploads/2021/02/PCF.png 1276w" sizes="(max-width: 800px) 100vw, 800px" />											<figcaption class="widget-image-caption wp-caption-text">Fig. 4 - Probabilistic Cash Flow (PCF)</figcaption>
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									<p style="text-align: justify;">What if to visualize the impact of Flash flood to schedule only? The “Distribution Graph” is showing the impact of Flash flood to a schedule in fig. 5.</p>								</div>
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										<img loading="lazy" decoding="async" width="800" height="466" src="https://www.gleeym.com/wp-content/uploads/2021/02/Flash-Flood-1024x597.png" class="attachment-large size-large wp-image-2733" alt="Analyzing impact of single risk to a schedule. What if analysis" srcset="https://www.gleeym.com/wp-content/uploads/2021/02/Flash-Flood-1024x597.png 1024w, https://www.gleeym.com/wp-content/uploads/2021/02/Flash-Flood-300x175.png 300w, https://www.gleeym.com/wp-content/uploads/2021/02/Flash-Flood-768x448.png 768w, https://www.gleeym.com/wp-content/uploads/2021/02/Flash-Flood-600x350.png 600w, https://www.gleeym.com/wp-content/uploads/2021/02/Flash-Flood.png 1096w" sizes="(max-width: 800px) 100vw, 800px" />											<figcaption class="widget-image-caption wp-caption-text">Fig. 5 - What if Analysis with Flash Flood Risk Only</figcaption>
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									<p style="text-align: justify;">With only Flash flood risk, the chances of meeting target date are almost 0%. The distribution graph shows that there will be 50% (mean) chance that schedule overrun will be 29 days. Furthermore, there will be an 80% chance that project completion date will be 29-10-2021 i.e., 34 days.</p>								</div>
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									<p style="text-align: justify;">&nbsp;While access roads can be constructed by any means necessary, it is much more cost-effective to use specialized contractors trained in their construction. Each contractor has specific standards that must be met before they begin any work.</p>								</div>
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									<p style="text-align: justify;">Access roads are crucial for any oil and gas project, not just for safety but also to allow construction equipment to enter the site, move materials, and complete the project. </p><p style="text-align: justify;">This is a story of a project that will be started out with a big dream and ended with great success. Nothing is easy; everything is challenging, but the results will be rewarding.</p>								</div>
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									<h3>Question: What if to build a bridge to over come the impact of a Flash Flood?</h3><h3> </h3><h3>Answer: I will discuss it in the next article.</h3><h3> </h3>								</div>
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		<title>Capital Project Petrochemical Process Plant, IRR, and NPV Analysis &#8211; Webinar</title>
		<link>https://www.gleeym.com/2020/08/25/capitalproject/</link>
					<comments>https://www.gleeym.com/2020/08/25/capitalproject/#respond</comments>
		
		<dc:creator><![CDATA[mindmap]]></dc:creator>
		<pubDate>Tue, 25 Aug 2020 22:10:20 +0000</pubDate>
				<category><![CDATA[Change Management]]></category>
		<category><![CDATA[Cost Risk Analysis]]></category>
		<category><![CDATA[Decision Making]]></category>
		<category><![CDATA[Monte Carlo Simulation]]></category>
		<category><![CDATA[PMO]]></category>
		<category><![CDATA[Project]]></category>
		<category><![CDATA[Project Control]]></category>
		<category><![CDATA[Risk]]></category>
		<category><![CDATA[Schedule Risk Analysis]]></category>
		<category><![CDATA[Oil&Gas]]></category>
		<category><![CDATA[Risk Register]]></category>
		<guid isPermaLink="false">https://www.gleeym.com/?p=1607</guid>

					<description><![CDATA[Capital project for the petrochemical process plant (downstream) is slightly different from other capital projects. It requires estimating Total Installed Cost (TIC) plus Owner cost in order to find the complete project cost. Cost estimation for petrochemical process plant is comprised of equipment specification and definite plant facility information. In this case study, there are [&#8230;]]]></description>
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									<p style="font-size: 18px; line-height: 25px; margin-bottom: 25px; color: #000000; font-family: proxima-nova, 'helvetica neue', arial, sans-serif; text-align: justify;">Capital project for the petrochemical process plant (downstream) is slightly different from other capital projects. It requires estimating Total Installed Cost (TIC) plus Owner cost in order to find the complete project cost. Cost estimation for petrochemical process plant is comprised of equipment specification and definite plant facility information.</p><p style="font-size: 18px; line-height: 25px; margin-bottom: 0px; color: #000000; font-family: proxima-nova, 'helvetica neue', arial, sans-serif; text-align: justify;">In this case study, there are 2 products that will be sold in two regions. The price strategy is different so the IRR and NPV will be calculated for base case and under uncertainties and risks. Then we&#8217;ll compare the IRR and NPV under different scenarios.</p>								</div>
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					<h3 class="elementor-heading-title elementor-size-default"> Also visit following link to watch recorded webinar</h3>				</div>
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									<p><blockquote class="wp-embedded-content" data-secret="xxdiO8kGp6"><a href="https://www.gleeym.com/2020/10/20/digitalproduct/">Digital Product Development and Decision Making Under Uncertainty</a></blockquote><iframe class="wp-embedded-content" sandbox="allow-scripts" security="restricted"  title="&#8220;Digital Product Development and Decision Making Under Uncertainty&#8221; &#8212; GleeYM" src="https://www.gleeym.com/2020/10/20/digitalproduct/embed/#?secret=xxdiO8kGp6" data-secret="xxdiO8kGp6" width="600" height="338" frameborder="0" marginwidth="0" marginheight="0" scrolling="no"></iframe></p>								</div>
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		<title>SCHEDULE RISK ANALYSIS (SRA) &#8211; SCHEDULE UNCERTAINTY</title>
		<link>https://www.gleeym.com/2019/10/23/sra/</link>
					<comments>https://www.gleeym.com/2019/10/23/sra/#respond</comments>
		
		<dc:creator><![CDATA[mindmap]]></dc:creator>
		<pubDate>Wed, 23 Oct 2019 18:17:57 +0000</pubDate>
				<category><![CDATA[Project Risk]]></category>
		<category><![CDATA[Schedule Risk Analysis]]></category>
		<category><![CDATA[Correlation]]></category>
		<category><![CDATA[Monte Carlo Simulation]]></category>
		<category><![CDATA[Probabilistic Branching]]></category>
		<category><![CDATA[Risk]]></category>
		<category><![CDATA[Schedule]]></category>
		<guid isPermaLink="false">https://www.gleeym.com/?p=922</guid>

					<description><![CDATA[SCHEDULE RISK ANALYSIS (SRA) &#8211; SCHEDULE UNCERTAINTY Keywords: Schedule, Critical Path (CP), Milestone, Deterministic Value, 3-Point estimates, Monte Carlo Simulation, Correlation, Iteration, Cumulative Frequency Chart, Probabilistic Branching, Distribution, Triangular Distribution, Categories, Duration, Finish Date, Uncertainty, Skewness, Positively Skewed, Negatively Skewed. Summary: A schedule risk analysis (SRA) uses a risk-based project schedule (derived from the master [&#8230;]]]></description>
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					<h1 class="elementor-heading-title elementor-size-default">SCHEDULE RISK ANALYSIS (SRA) - SCHEDULE UNCERTAINTY</h1>				</div>
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					<h2 class="elementor-heading-title elementor-size-default">Keywords:</h2>				</div>
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		</section>
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									<p class="MsoNormal" style="text-align: justify; line-height: normal; background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-attachment: initial; background-origin: initial; background-clip: initial;"><span style="font-size: 12pt; font-family: 'Segoe UI', sans-serif;">Schedule, Critical Path (CP), Milestone, Deterministic Value, 3-Point estimates, Monte Carlo Simulation, Correlation, Iteration, Cumulative Frequency Chart, Probabilistic Branching, Distribution, Triangular Distribution, Categories, Duration, Finish Date, Uncertainty, Skewness, Positively Skewed, Negatively Skewed.</span></p>								</div>
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					<h2 class="elementor-heading-title elementor-size-default">Summary:</h2>				</div>
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									<p style="text-align: justify;">A schedule risk analysis (SRA) uses a risk-based project schedule (derived from the master schedule) to apply statistical techniques to envisage a level of confidence in meeting a project’s completion date. This analysis focuses on uncertainty they affect the schedule overall and activities durations and completion date. SRA starts with reviewing the project schedule and performing schedule quality checks as specified by DCMA 14-points. A sequence of activities and activities relationship plays an important role to avoid “Garbage in and Garbage out”.</p>								</div>
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					<h2 class="elementor-heading-title elementor-size-default">Project Schedule Quality Check for Schedule Risk Analysis:</h2>				</div>
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									<p>There can be several other parameters that can contribute to quality SRA. Like:</p>
<ul>
<li>Contain all the activities that are necessary for the SRA.</li>
<li>Keep in mind there is a difference between “Master Schedule” and Schedule for risk analysis.</li>
<li>All activities should be linked together.</li>
<li>The sequence of activities plays an important role. Improper sequence of activities is one of the causes of conflicts in major complex projects.</li>
<li>Get the buy-in from all the key stakeholders.</li>
<li>Specify the assumptions and analyze the assumption during the simulation.</li>
<li>Specify the uncertainties for each activity i.e. min. most likely and the max. Avoid heuristics estimates. </li>
<li>Try to get rid of “Cognitive Bias”. Although it is very difficult. Support from top executives may help.</li>
<li>Depending upon the level of schedule. It takes days or weeks or even months to develop a schedule. There is no magic to perform SRA and visualize the data in seconds. Need to perform SRA several times with different scenario to compare results.</li>
<li>Overlay results to analyze and visualize the difference between various output by varying the input data.</li>
<li>Uncertainties may cover lack of knowledge activity duration estimation error, resource availability, organisational culture, internal and external factors, market conditions, political scenario, project execution methodology, resource availability, productivity, project constraints, technology constraints, Biased opinion, known – Known and even unknown – unknown (This scenario should be analyzed separately to understand the impact) etc.</li>
</ul>
<p> </p>
<p>Perform quality checks on Schedule before Monte Carlo simulation as per DCMA 14-points may be a good choice for quality checks. Few points are given below</p>
<ul>
<li>Activity logic</li>
<li><strong>Leads and Lags</strong>: Schedule must be not containing any activity with leads and lags. Decompose the activity into two activities to avoid leads and lags.</li>
<li>Check activity relationships. Avoid Hard constraints.</li>
<li>Avoid high floats in the schedule. Also, if there is any negative float then fix it up.</li>
<li>Check other DCMA’s constraints as per project nature and schedule level.</li>
</ul>								</div>
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					<h2 class="elementor-heading-title elementor-size-default">Schedule Risk Analysis (SRA):</h2>				</div>
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									<p style="text-align: justify;"><strong>Schedule risk analysis (SRA) </strong>helps to analyze the uncertainty in the project schedule using Monte Carlo Simulation. Deterministic schedule duration and finish date don’t provide enough information to answer flowing questions:</p>
<ol style="text-align: justify;">
<li>What is the probability of completing the project on the target date?</li>
<li>What if the predecessor of an activity finishes late?</li>
<li>What is the eighty (90%) chance of finishing the project?</li>
</ol>
<p style="text-align: justify;">SCR scope is:</p>
<ol>
<li style="text-align: justify;">Schedule Risk Analysis (SRA) to analyze uncertainty</li>
<li style="text-align: justify;">Correlating the activities</li>
<li style="text-align: justify;">Probabilistic Branching</li>
</ol>								</div>
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					<h2 class="elementor-heading-title elementor-size-default">List of Activities:</h2>				</div>
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									<p>List of activities are given below with duration and predecessors</p>								</div>
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										<img loading="lazy" decoding="async" width="768" height="589" src="https://www.gleeym.com/wp-content/uploads/2019/10/List-of-Activities-768x589.png" class="attachment-medium_large size-medium_large wp-image-923" alt="" srcset="https://www.gleeym.com/wp-content/uploads/2019/10/List-of-Activities-768x589.png 768w, https://www.gleeym.com/wp-content/uploads/2019/10/List-of-Activities-300x230.png 300w, https://www.gleeym.com/wp-content/uploads/2019/10/List-of-Activities-1024x785.png 1024w, https://www.gleeym.com/wp-content/uploads/2019/10/List-of-Activities-1536x1177.png 1536w, https://www.gleeym.com/wp-content/uploads/2019/10/List-of-Activities-2048x1570.png 2048w, https://www.gleeym.com/wp-content/uploads/2019/10/List-of-Activities-1320x1012.png 1320w, https://www.gleeym.com/wp-content/uploads/2019/10/List-of-Activities-600x460.png 600w" sizes="(max-width: 768px) 100vw, 768px" />											<figcaption class="widget-image-caption wp-caption-text">Picture 1 - List of Activities</figcaption>
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					<h2 class="elementor-heading-title elementor-size-default">Parameter Entry Table:</h2>				</div>
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									<p style="text-align: justify;">Parameter Entry Table is created for 3-Point estimates collected after a brainstorming session with the Subject Matter Experts (SME). Collect data is also benchmarked with archives available for similar-sized projects within the organization. <strong>Chain-of-causes</strong> is a good approach to understand the various factors contributing to uncertainty in the activity. Another development is using the Casual Loop Diagram (CLD). It helps not only to identify the key variables but to draw a relationship between cause and effect. Another methodology <strong>is Mind mapping</strong>. Mind Mapping helping to analyze the problem by lining the different variables.</p>								</div>
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										<img loading="lazy" decoding="async" width="768" height="241" src="https://www.gleeym.com/wp-content/uploads/2019/10/Parameter-Entry-Table-1-768x241.jpg" class="attachment-medium_large size-medium_large wp-image-926" alt="" srcset="https://www.gleeym.com/wp-content/uploads/2019/10/Parameter-Entry-Table-1-768x241.jpg 768w, https://www.gleeym.com/wp-content/uploads/2019/10/Parameter-Entry-Table-1-300x94.jpg 300w, https://www.gleeym.com/wp-content/uploads/2019/10/Parameter-Entry-Table-1-1024x321.jpg 1024w, https://www.gleeym.com/wp-content/uploads/2019/10/Parameter-Entry-Table-1-1320x414.jpg 1320w, https://www.gleeym.com/wp-content/uploads/2019/10/Parameter-Entry-Table-1-600x188.jpg 600w, https://www.gleeym.com/wp-content/uploads/2019/10/Parameter-Entry-Table-1.jpg 1430w" sizes="(max-width: 768px) 100vw, 768px" />											<figcaption class="widget-image-caption wp-caption-text">Picture 2 - Parameter Entry Table</figcaption>
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									<p style="text-align: justify;">Parameter Entry Table is shown above with min. most likely and max. values. Most likely is the schedule actual duration. For this article, optimistic value is adjusted to 10% of the most likely value. While Pessimistic value is 50% of the most likely value. For 3 points estimates either use PERT or Triangular distribution. The triangular distribution is the best choice to have positively skewed data with wider distribution of data.</p>								</div>
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					<h2 class="elementor-heading-title elementor-size-default">Simulation and Results:</h2>				</div>
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									<p style="text-align: justify;">Run the Monte Carlo Simulation (MCS) for SRA. There is a 90% chance that the project will finish before June 18th, 2020.  Surprisingly, there is only less than a 5% chance to complete the project on the target date.   Why there are shoulders in the output graph?  It is because the project calendar is set to five (5) working days. It is representing off days.</p>
<p style="text-align: justify;">Results are:</p>								</div>
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										<img loading="lazy" decoding="async" width="768" height="521" src="https://www.gleeym.com/wp-content/uploads/2019/10/5-days-2.png" class="attachment-medium_large size-medium_large wp-image-937" alt="" srcset="https://www.gleeym.com/wp-content/uploads/2019/10/5-days-2.png 786w, https://www.gleeym.com/wp-content/uploads/2019/10/5-days-2-300x203.png 300w" sizes="(max-width: 768px) 100vw, 768px" />											<figcaption class="widget-image-caption wp-caption-text">Picture 2 - SRA - 5 Days Calendar</figcaption>
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									<p style="text-align: justify;">What if to simulate project risk analysis for a project schedule with seven (7) days working calendars? It depends on the project nature. Usually, construction projects, commissioning and outages are following seven (7) working days calendar.</p>
<p style="text-align: justify;">In the case of seven (7) working days calendar the project target finish date is Feb 23, 2020.  results are:</p>								</div>
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										<img loading="lazy" decoding="async" width="729" height="500" src="https://www.gleeym.com/wp-content/uploads/2019/10/SRA-7days-Cal.png" class="attachment-medium_large size-medium_large wp-image-930" alt="" srcset="https://www.gleeym.com/wp-content/uploads/2019/10/SRA-7days-Cal.png 729w, https://www.gleeym.com/wp-content/uploads/2019/10/SRA-7days-Cal-300x206.png 300w, https://www.gleeym.com/wp-content/uploads/2019/10/SRA-7days-Cal-600x412.png 600w" sizes="(max-width: 729px) 100vw, 729px" />											<figcaption class="widget-image-caption wp-caption-text">Picture 3 - SRA - 7 Days Calendar</figcaption>
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									<p style="text-align: justify;">Again, there is less than a 5% chance to meet the target date. There is a 90% chance that the target date will be close to Mar 30, 2020.</p>								</div>
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					<h2 class="elementor-heading-title elementor-size-default">Correlation:</h2>				</div>
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									<p style="text-align: justify;">Correlation is required for Schedule Risk Analysis to avoid merged biased because of parallel paths along with critical Path (CP) i.e. near Critical paths. During a simulation, these paths merged together resulting shorter project completion duration. A risk driver is an approach to deal with it. However, another approach is to correlate related activities. correlating related activities results in wider distribution. Keep in mind activities in parallel or in series also play an important role in simulation and results.</p>								</div>
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										<img loading="lazy" decoding="async" width="513" height="341" src="https://www.gleeym.com/wp-content/uploads/2019/10/Activities-Correlated.jpg" class="attachment-medium_large size-medium_large wp-image-932" alt="" srcset="https://www.gleeym.com/wp-content/uploads/2019/10/Activities-Correlated.jpg 513w, https://www.gleeym.com/wp-content/uploads/2019/10/Activities-Correlated-300x199.jpg 300w" sizes="(max-width: 513px) 100vw, 513px" />											<figcaption class="widget-image-caption wp-caption-text">Picture 4- SRA - Activities Correlated</figcaption>
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									<p style="text-align: justify;">There is a 90% chance that the target date will be Mar 30, 2020. Almost seven (7) days of difference between SRA with activities correlated and without correlation.</p>								</div>
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					<h2 class="elementor-heading-title elementor-size-default">Probabilistic Branching:</h2>				</div>
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									<p style="text-align: justify;">Probabilistic branching is useful to analyze the scenarios within schedule during Scheduling Risk Analysis (SRA). For this project, there are two branches and executed simultaneously. The interesting part is that one Probabilistic branch lies in the Critical path (CP) while other path lies in a near-critical path.</p>
<p style="text-align: justify;">Probabilistic branches are:</p>
<ol style="text-align: justify;">
<li>Activity B – Activity D – Activity E – Activity F</li>
<li>Activity C – Activity G -Activity H – Activity I</li>
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<p style="text-align: justify;">Results are:</p>								</div>
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										<img loading="lazy" decoding="async" width="510" height="347" src="https://www.gleeym.com/wp-content/uploads/2019/10/Branching-Results.jpg" class="attachment-medium_large size-medium_large wp-image-933" alt="" srcset="https://www.gleeym.com/wp-content/uploads/2019/10/Branching-Results.jpg 510w, https://www.gleeym.com/wp-content/uploads/2019/10/Branching-Results-300x204.jpg 300w" sizes="(max-width: 510px) 100vw, 510px" />											<figcaption class="widget-image-caption wp-caption-text">Picture 5- SRA - 2 Probabilistic Branching</figcaption>
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									<p style="text-align: justify;">Results are negatively skewed. It is because of various reasons and one is having two branches in a schedule. <span style="font-size: 1rem;">Further analysis can be carried out like Sensitivity Analysis and Probabilistic Gantt chart to analyze the behavior of the activities.</span></p>								</div>
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									<p style="text-align: justify;">SRA is good for analyzing the project schedule statistically. Prior quality checks help to prepare schedule for a SRA. Running MCS, again and again, helps to analyze the various scenarios and compare results.</p>								</div>
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