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Brief methodology for undertaking QSRA/QCRA

Lets first understand what is QRA and Monte Carlo?


Quantitative Risk Analysis (QRA) is a forecasting technique used to predict project cost and/or schedule outcomes, and to estimate an appropriate level of contingency. The QRA seeks to develop realistic project schedules and estimates for a genuine prediction on how the project may result. In the past, project contingency has often been set by means of an uplift (E.g. 10% on cost/time). This approach is rudimentary, often provides no justification on why a certain uplift is applied, and may result in an entirely inadequate risk contingency.

There is generally a finite number of occasions on which a project can baseline schedules/budgets; we can maximise our chances of success by utilising Monte Carlo Analysis (MC).

Monte Carlo is a mathematical technique utilising random sampling, within specified distributions to calculate the probability of explicit outcomes. The underlying principal of the method is rooted in the law of averages, and the law of large numbers; creating a mathematical prediction of how the process may eventuate.

MC uses input duration ranges, as opposed to single point estimates for activity durations, to offset the inherent uncertainty in estimating. For a holistic coverage of possible cost/schedule outcomes, Risk Events (with a defined probability of occurrence, as well as an impact duration range) can be assigned to activities within the programme and contribute to the analysis (effectively extending the linked activity by the nominated impact duration value, on any iteration in which it appears). The Risk Analysis model is simulated hundreds, or thousands of times, and on each iteration a value is randomly selected from within the defined duration range for each activity. The most widely used, and easily understandable, range distribution is a triangular distribution (often referred to as a 3-point estimate and provided as a minimum, most likely, and maximum). The MC simulation is entirely random, plotting the outputs of each iteration as it works to create several useful insights. MC analysis undertaken on a project schedule takes cognisance of logic uncertainty and calendars, creating forward and backward pass calculations for each relationship in the plan, ultimately providing confidence intervals based on the range of start/finish dates for each milestone/activity.

Cumulative distribution graphs (S-curves) can be created to inform probability distributions (from which we can extrapolate confidence percentiles e.g. P50/P90.) For example, a P50 project completion date of 1st December 2018 occurs within the 50th percentile of the output dates; this means that in 50% of all iterations the project finish date is on, or before, 1st December 2018.

A relatively risk adverse organisation may prefer QRA models to provide a P90 confidence of meeting the schedule/cost target, where the results of the analysis show that in only 10% of iterations this value is exceeded. Conversely, a more risk tolerant organisation may be willing to accept a confidence percentile south of P50.

A QRA can help to provide a realistic forecast, and illustrate the key driving factors within a plan, in addition to quantifying the schedule benefits of timely interventions. This information is conducive to effective, risk-based decision making.

QSRA

The purpose of a Quantitative Schedule Risk Analysis (QSRA) is to provide assurance that key milestones/objectives within a project schedule will be met.


A QSRA can help to provide a realistic forecast, and illustrate the key driving factors within a plan, in addition to quantifying the schedule benefits of timely interventions. This information is conducive to effective, risk-based decision making.


The following inputs are necessary prior to analysis:


· Reviewed and agreed deterministic plan, considered suitable for analysis. If the existing project plan file is not suitable, a plan of

· Duration ranges for each line in the plan – minimum (optimistic), most likely (deterministic) and maximum (pessimistic). Depending on the Distribution type selected, a 2-point range (Min to Max) may be sufficient.

· Project Risk Register. (Note – there may be a requirement to hold a separate risk review prior to the QSRA process to ensure sufficiently mature Quantitative risk information is held)

Workshop – A workshop may be held with project stakeholders to review the analysis inputs. Several component parts of the analysis can be established at the workshop, such as risk impact mapping and duration uncertainty.

Programme – The programme must be representative of the programme of works, and must follow planning guidelines (attached). The programme should be reviewed in the workshop, to the following end:

- A review of activity durations to assign Duration Uncertainty values to the deterministic programme durations. The project team must ensure that the Duration Uncertainty estimates do not account for the impact of Risk and should account for only the inherent uncertainty in estimating the activity duration. The project team must challenge uncertainties and risks to ensure that optimism bias has been accounted for, and that all values provided are met with sufficient challenge.

- A review of where bespoke risks are to be mapped to the programme – This is to be an appropriate activity (or activities) the risk impact may be assigned.

Risk Register – The project risk register, with associated probability and impact values – including any planned management actions, must be addressed as it is a component part of the analysis. Existing risks should be sense checked by QSRA workshop attendees, and any links/correlation between risks should be identified before being imported into the plan. All risks should have assigned probability of occurrence values (%) as well as a Time impact ranges. The likely impact of a risk may be expressed as a 3 -point estimate (minimum, most likely, maximum) or a 2-point estimate (minimum to maximum).

QCRA

The purpose of a Quantitative Cost Risk Analysis (QCRA) is to estimate an appropriate level of cost contingency to supplement the project estimate and provide confidence that the budgetary allowance will not be surpassed.

A fully quantified risk register is essential to undertake the Cost Risk Analysis. Each applicable cost risk must have assigned probability of occurrence values (%) as well as a Cost impact ranges. The likely impact of a risk may be expressed as a 3 -point estimate (minimum, most likely, maximum) or a 2-point estimate (minimum to maximum).

The Risk Register should contain justification of the impact ranges (a qualifying statement of how costs have been built up, specific to each risk). E.g. ‘Cost impact may be X hours allowance for SME input @ £Xp/h + additional equipment costs = £Xk + Contractor prelims at £X per day ’.

The Risk Register should be cross-referenced with the Cost Model to ensure the impact of specific Risks have not been included for already in the base estimate.

QCRA should be run on Target (post-mitigated) risk assessment. This relies on the stability of the assumption, that identified mitigations are successful and the results are as expected.

A Monte Carlo Analysis can be run on the Risk Register inputs; resulting in the conception of output values specific to the project (as confidence percentiles). Specialist software (E.g @Risk, Primavera Risk Analysis etc. must be used to undertake the anlaysis).

Risks that are >70% of occurrence at Target assessment, should be transferred into the base estimate (or via contractual transfer depending on the project phase) or eliminated by terminating the linked activity/activities.

Cumulative distribution graphs (S-curves) can be created to inform probability distributions (from which we can extrapolate confidence percentiles e.g. P50/P90.)

If you like to know more about Project Risk Analysis or require any support, please contact us at info@Projcon-Advisory.com

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Project Controls Trailblazer Apprenticeship – Path forward

Project Controls Trailblazer Apprenticeship – Path forward

In this post, We are attempting to offer an overview on upcoming Project Controls Trailblazer Apprenticeship based on knowledge which comes from our engagement in the development of this standard. 

The Project Controls Technician Apprenticeship (Level 3) that is part of the Government’s Trailblazer programme that aims to establish new standards for apprenticeships and is committed to reaching three million apprenticeship starts in England by 2020. has been developed by an employer-led working group consisting of Project Control leaders from 40 organisations that deliver complex projects across engineering, energy, infrastructure, construction and manufacturing sectors. Professional bodies such as ACostE, APM, IRM and CICES have also contributed to the development together with training providers and academia

The standard and assessment plan are ready to be delivered and used and have been fully approved by the Minister of State for Skills at the Department of Education, giving the green light for the launch of the apprenticeship in Q3 2017. A funding band (core government contribution which is currently capped at £21k per apprentice has been assigned to the standard.

In beginning to promote the apprenticeship, we have found that employers have a positive approach to the Project Controls Technician apprenticeship but are not sure who to engage with to get started, how to achieve a return on investment against the new apprenticeship levy and how best to establish Project Control apprenticeships and use the flexibility in the way the programme can be configured to meet their requirements for a viable programme that at the same time satisfies the mandatory criteria required by government.

Project Controls Institute being an approved training provider (via our parent org) for this Apprenticeship has created a dedicated KB offering options to guide employers in the right direction to provide a sure start for training your Project Controls apprentices. Based on our professional knowledge, we have also devised the unique delivery approach to offer this training to our clients which can be seen on our website.

Finally, we will be offering further insight on this topic at Project Controls Expo in Masterclass, supported by Employer, ECITB and possibly some government representation (SFA/DoE). If you any questions in the meantime, feel free to contact us at info@ProjectControlsInstitute.com

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How does "Resource curve" work in P6?

 

How does “Resource curve” work?

 

Let say we have an activity with 100 days duration and 100 labor units. By default it use Linear spread.

It mean, when you reach 5% of duration (5th day in this example) you have 5% of total unit (5 unit in this example). And it spread evenly to that period.

So resource spreadsheet will be like this:

Now if I change to 6 %.

3

It mean, when you reach 5% of duration (5th day in this example) you have 6% of total unit (6 unit in this example). And it spread evenly to that period.

So resource spreadsheet will be like this:

Similarly, when you reach 10% of duration (10th day in this example) you have 5% more of total unit (5 unit in this example). And it spread evenly to that period.

So resource spreadsheet will be like this:

And it follow that regulation until the end of curve.

Now you understand how the resource curve work.

Hopefully it will help you to distribute resource unit as your wish:-)

 

 

 

 

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How to backup and restore Primavera P6 Oracle Express (XE) database

1
 

How to backup:

From the command prompt (go to ‘Start’ > ‘Run’ > type ‘cmd’ and click ‘OK’) using the format below

exp system/ @XE full=y file= \xedump.dmp log= \exp_xedump.log

Where:

  • is the password you used when you installed P6 Standalone or Oracle XE manually.

is the complete path to the folder where the log file and database backup dmp file are to be created (Example: file=C:\PrimaveraP6\backups\xedump.dmp log=C:\PrimaveraP6\backups\xedump.log)

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The Schedule Quality Index™

With the recent launch of the Fuse Schedule Index Calculator, we often get asked, what is the Schedule Quality Index™ and how is it calculated? 

First and foremost the Schedule Quality Index is a means of assessing how well planned a schedule.  It is a single score that is calculated from nine separate schedule check metrics.  The metrics span multiple key attributes, or building blocks of a schedule that together from the underpinnings of a structurally sound schedule. 

The Schedule Quality Index is made up of the following nine checks (metrics):

Missing Logic

In theory, all activities should have at least one predecessor and one successor associated with them. Failure to do so will impact the quality of results derived from a time analysis as well as a risk analysis. This number should not exceed more than 5%.

Logic Density™

This metric calculates the average number of logic links per activity. An average of less than two indicates that there is logic missing within the schedule. An average greater than four indicates overly complex logic, with a high likelihood of redundant links. Therefore, Logic Density™ should be between two and four.

Critical

While a highly critical schedule is not necessarily a sign of poor scheduling, it can indicate a highly risky schedule. Use this metric as a point of reference.

Hard Constraints

Hard, or two-way, constraints such as ‘Must Start On’ or ‘Must Finish On’ should be avoided. Use of such constraints can lead to inaccurate finish dates and a lack of insight into the impact of schedule changes, risk events, and earlier delays.

Negative Float

Negative float is a result of an artificially accelerated or constrained schedule, and is an indication that a schedule is not possible based on the current completion dates.

Insufficient Detail™

Activities with a high duration relative to the life of the project are an indication of poor schedule definition. Detail should be added to the schedule.

Number of Lags

A lag is a duration applied to a logic link often used to represent non-working time between activities such as concrete curing. Lags tend to hide detail within the schedule and cannot be statused like normal activities; therefore, lags should be converted to actual activities with durations.

Number of Leads

A lead, also known as a negative lag, is often used to adjust the successor start or end date relative to the logic link applied. This is a poor practice as it can result in the successor starting before the start of the predecessor.

Merge Hotspot

A merge hotspot is an indication of how complex the start of an activity is. If the number of links is greater than two, there is a high probability that the activity in question will be delayed due to the cumulative effect of all links having to complete on-time in order for the activity to start on time.

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Planning & Scheduling rules/principles

 

Planning & Scheduling rules/principles

Let us first understand the terms i.e., planning & scheduling:

Planning is control of time on a project by:

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