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RIMPL’s new consultant: David Ekhtiari


David Ekhtiari

David has been working with us since December, doing some project planning consulting, learning about our methodology and software and , most importantly, writing training material for newer RIMPL applications to make it easier for those coming after him to learn. David’s title is Project Controls and Risk Management Consultant. He is a skilled Primavera P6 user who has trained others in its use. David came to us already able to use Primavera Risk Analysis, our preferred simulation tool.


We asked David to tell us something about himself, to which he responded as follows:


“Growing up in Tehran, I was well-known for my natural curiosity and interest in all things technical, and one day dreamed of becoming a passenger aircraft pilot. Fast forward to 2002, and I graduated as a mechanical engineer / designer of HVAC systems. However, through friends working in the field, I soon became acquainted with and keenly interested in Project Controls.


Initially I taught myself through texts on project planning & controls, project scope management and Primavera planning software. It wasn’t long before I started seeking formal courses in Primavera P6. This led to my first planning role, in which, in 2008, I was engaged as a planning engineer for construction of a cement factory in Hamah, Syria.


Between 2010 and 2013, I worked intermittently for a subsidiary of the Research Institute of Petroleum Industry (RIPI) called RCTEC, which specialised in industrial plants and EPC projects. Again I worked as a planning engineer, mainly on structural/mechanical/piping type projects. During this period, I also made a couple of visits to Australia, where I provided Primavera P6 tutoring, before coming to RIMPL at the end of 2013.


With hobbies including skiing, driving, cycling, reading and surfing the internet, I am also keenly interested in improving my knowledge of project management & risk through following discussions on professional groups on LinkedIn and technical forums.”


RIMPL’s new WA Representative: Peter Hudson


Peter Hudson

Peter is a chemical engineer with extensive experience in strategic project development, execution and management. He has been responsible for the successful delivery of a range of EPC and EPCM projects and engineering services activities covering the oil & gas, petrochemical, mining and mineral processing industries and port and pipeline infrastructure.


Peter has several times been the client representative for work done by RIMPL’s Risk Management Team.


We are delighted and privileged to have Peter providing crucial assistance to RIMPL in developing client opportunities in WA and elsewhere!


Peter can be reached through his email: peter(at)anothen.com.au

or via his mobile: 0417 931 792


We are planning to be in WA more in 2014, starting with attending a Floating LNG Workshop in Perth 18-21 May sponsored by the Society of Petroleum Engineers, then meeting with potential clients over the rest of the week.


The next step: Integration of Project Cost & Schedule Risk Analyses


Among quantitative risk analysts, there is a trend to integrate Cost and Schedule Risk Analyses (Integrated Risk Analysis, or IRA for short). But what is IRA, and what are the pros and cons compared with the traditional approach of separate cost and schedule risk analyses? This article seeks to answer these questions.


RIMPL is passionate about the advantages of IRA over separate or serial Schedule Risk Analysis (SRA) and Cost Risk Analysis (CRA) and has developed its methodology and software to make IRA practical and reliable and a measurably superior method of forecasting project time and cost outcomes.


We can summarise the comparison of IRA with Serial SRA & CRA as follows:


Integrated Cost & Schedule Risk Analysis (IRA)Schedule Risk Analysis (SRA) to Cost Risk Analysis (CRA)
More rigorous if done correctlyLess rigorous
Harder to do correctlyEasier to perform
Can provide key driver information, unifying schedule and cost drivers in one ranking as influences on project cost Cannot reveal cost consequences of schedule delays – schedule drivers are separate from cost drivers

The following detailed discussion compares the two approaches and explains the above summary.


Traditional Approaches to Combining Cost and Schedule Risk Analyses


Separate Roots: Cost Risk Analysis (CRA) versus Schedule Risk Analysis (SRA)


Estimators and cost controllers have traditionally come from the ranks of quantity surveyors and cost engineers, while project planners and schedulers have tended to emerge from the ranks of design and construction engineers. The first group is concerned with counting and quantities while the second group is more concerned with how things are put together.


This has carried through to the application of Monte Carlo simulation: cost risk analysis tends to be performed by practitioners with estimating or cost control backgrounds, using spreadsheet based tools like @Risk and Crystal Ball. They may be used to compiling Trend Registers in which all uncertain items with cost impact are listed, including those driven by schedule. In the latter category, cost controllers assume some time rate of cost expenditure to forecast cost ranges in the Trend Register.


On the other hand, project planners who have transitioned into schedule risk analysis tend to use Monte Carlo simulation tools built on project planning software. When costs have been included in such modelling, it has often been through working with resource-loaded schedules. Functionality for costs has not been as well-incorporated in such SRA tools, further deterring SRA practitioners from including costs in their analyses.


Different Strokes for Different Folks


Consequently, CRAs tend to be performed by one set of practitioners using their favoured software and SRAs by another group of practitioners using different software. Even when the same analysts do both SRA and CRA, they commonly use different software due to the evolved specialisations.


Sometimes only a cost or a schedule risk analysis will be performed in response to requests from different managers with different experiences and understandings. Indeed, a CRA can be performed on a project concept before a schedule exists. This can be a useful way to make initial choices between project concepts and strategies.


But where the decision has been made to perform combined schedule and cost risk analyses, analyses will be conducted separately, often by different personnel or contractors. The assessed SRA contingency allowance is fed into the CRA as a “schedule risk allowance” using an assumed “cost burn rate” over the contingency period.


Unsafe Assumptions


The problem with this approach is that it takes no consideration of where and when schedule changes occur.


To demonstrate this point, consider the following scenario:


A schedule risk analysis reveals that an additional 30 days of contingency are required to the planned duration to be 90% confident of achieving project completion on time. It also reveals that the bulk of the duration uncertainty for the project is distributed across its construction phase. The results of the schedule risk analysis are then input to the cost risk analysis at an assumed cash burn rate of $1 million dollars a day based on the conservative assumption of peak construction manning levels.


There are three clear issues which we will identify as the ‘when’, ‘where’, and ‘why’ of the traditional approach to combining cost and schedule risk which fail to accurately characterise the true project uncertainty:


When


The first issue relating to the combining of separate cost and schedule risk analyses lies in the assumed cash burn rate per day. For the example above, because the bulk of the duration uncertainty was identified as coming from the construction phase, the assumed cash burn rate per day was calculated based on peak construction manning levels. However, this assumption is overly pessimistic, as only a proportion of the construction period will actually run at peak manning levels. What if delay occurred before all contractors had been mobilized to site? The capital cost impact of the delay would understandably be significantly reduced. Similarly, critical path delays affecting pre-execution engineering or approvals would have drastically different cost impact profiles. The calculated cost of delay is clearly dependent on when the delay occurs.


Where


The second issue relates to where in the program a delay occurs. It is likely that the schedule will consist of multiple parallel paths of tasks that ultimately converge on one completion milestone (either directly or through other connected tasks). Some of these paths will be dominant in determining the completion date of the project, occurring frequently on the critical path, whereas others will not. It is entirely possible for a chain of tasks to be significantly delayed, but never impact on the overall project critical path. However, even though they’re not impacting on the end date of the project, prolongation costs will still be incurred associated with the delays, due to longer use of hired equipment, labour, etc. Calculating the cost of a schedule allowance based on delay to project completion fails to account for these non-critical delay cost uncertainties.


What / Why / How


The final issue with the traditional approach to cost and schedule risk analysis deals with why a particular answer was given, what was driving it, and the assumptions and methodology of how it was derived. Separate cost and schedule risk analyses will almost always have different assumptions that underlie their inputs. A cost risk analysis that draws from the result of a schedule risk analysis must take account of the schedule assumptions underlying the schedule answers to accurately portray forecast cost of delay over-runs.


Further, because the schedule is analysed separately from cost, the visibility of individual schedule elements as drivers of delay cost is lost. We can indeed attribute a certain amount of cost contingency requirement to schedule, but why it is required, what drives it, and how it has been derived is very difficult to express through such a methodology.


The latest version of linked SRA & CRA


A more sophisticated serial SRA/CRA approach is described by Yuri Raydugin in his recent book “Project Risk Management”. By this method a project duration probability distribution from a SRA is transferred into a matching CRA, representing the project variable cost uncertainty. All other cost line items in the CRA represent fixed cost uncertainties and risks, and exclude variable costs. While this approach provides a variable cost probability distribution, it is still based on an assumed rate of expenditure of variable cost per unit time and divorces the schedule drivers from the cost drivers. And he advocates using a highly summarised schedule (<100 tasks), ignoring the importance of the Merge Bias Effect in producing realistic schedule forecasts.


What is Integrated Cost & Schedule Risk Analysis (IRA)?


Integrated Cost & Schedule Risk Analysis is the Monte Carlo Method simulation of a project using a schedule representation of the project overlaid by a cost estimate or control budget of the project and with treated risk events with cost and schedule impacts appropriately mapped into the cost-loaded schedule. All significant sources of time and cost uncertainty are incorporated into the model and simultaneous cost and schedule uncertainty distributions are calculated by the simulation, together with cost and schedule driver sensitivities.


Starting with the schedule


Truly integrated cost & schedule risk analysis starts with the project schedule. For maximum realism, the schedule should represent the project strategy and how the project is to be executed. The schedule should include sufficient detail to reveal the critical and near-critical paths of the project. It should also retain the characteristic complexity of the project to ensure that the Merge Bias Effect (MBE) realistically constrains the potential for early completion. For more detail on this, please refer to our July 2013 Newsletter article “Balancing Accuracy and Credibility in Schedule Risk Analysis”.



For major and complex projects including construction, the schedule used to organise and control the overall project without becoming too detailed and unwieldy is often referred to as the Level 3 Integrated Master Control Schedule. This is usually a good basis for an IRA model.


Summarising the Estimate


The Project Estimate (Pre-Financial Investment Decision) or Control Budget (during Project Execution) is overlaid on the project schedule in a series of hammock activities (tasks that change in duration according to the durations of the tasks to which they are linked without taking part in critical path calculations). The estimate / control budget may consist of thousands of line items. The goal is to set up the cost breakdown structure so that it aligns with the schedule breakdown structure and enables costs to be summarised to differentiate between significantly different risk profiles; for example, in costing of equipment and materials packages, separating procurement and fabrication from construction.


Splitting Fixed & Variable Costs


The line item costs are a mixture of variable (time-dependent) and fixed (time-independent) costs, all of which are uncertain at the start of the project. The proportions (“splits”) of fixed and variable costs must be accurately known or estimated for each line item so that the summarised variable costs, when spread over the applicable groups of tasks in the schedule can vary realistically due to duration changes. Variable costs can vary due to task duration changes and also due to uncertainty in their rates. For example, labour and equipment hire rates may be uncertain at the start of the project.


Ranging and Reviewing the Uncertainty and Risk Inputs


Subject Matter Experts (SMEs) can provide range and rate inputs to workshops or interviews to develop consensus inputs for the IRA model schedule and cost ranges. In addition, risk events from the project risk registers with time and cost impacts incorporate the known risks that could affect the project goals. The risk events could be opportunities or threats and could affect multiple activities in the project. They may also be mapped into the cost-loaded schedule as risk factors that affect groups of activities to reflect such things as productivity, quantity uncertainty or market conditions.


Correlation: a necessary input


Correlation models are developed to ensure that groups of activities and resources that behave in related ways are represented realistically in the IRA model. This extends to risk factors that vary in related ways, such as productivity risk factors for different disciplines. Correlation inputs are essential instructions to the MCM modelling tool that correct the inherent assumption of complete independence between all inputs and enable the model to forecast realistic probabilistic spreads of schedule and cost.


Building the IRA Model


The IRA model is built from:


• the carefully reviewed and technically corrected schedule;

• overlaid by the summarised estimate;

• inputting the schedule and cost ranges;

• schedule and cost correlation models;

• mapping in the treated cost and schedule impact risk events and risk factors; and

• assigning the probabilistic weather calendars (usually derived from historical weather data) to the appropriate construction tasks.



Integrated Analysis


The analysis is usually performed at least twice and sometimes three or more times, depending on the complexity of the model and how far the client wants to go in optimising the risk profile of the IRA model and thus the project. The key point is that changes to inputs to the model depend on the wishes of the project team in reviewing the results and what the sensitivity rankings reveal about the schedule drivers and the underlying logic in particular.


What are the benefits of IRA?


IRA enables the simultaneous analysis of probabilistic schedule and cost distributions for IRA models incorporating all known and possible sources of time and cost uncertainty, such as shown in the example distributions below. It reflects the project reality that “time is money” and completely removes the fundamental problem with serial SRA & CRA: How does schedule uncertainty affect cost uncertainty?


By modelling all time and cost uncertainties together, IRA enables the analysis to calculate the cost consequences of schedule changes based on where and when they occur in each iteration and thus probabilistically from the complete simulation.


Sensivities

In addition, IRA enables the quantification and ranking of all driving sources of uncertainty in the IRA model, providing insight into the what, why, and how of assessing model behaviours and outputs. This is done by a technique we call Quantitative Exclusion Analysis (QEA), which entails the progressive removal of classes of uncertainty or individual tasks or costs or groups of tasks or costs. A full simulation without each class, group or individual contributor enables the effect of the missing element to be measured by difference at selected probability levels. This provides valuable information on the priorities to assign to optimising project schedule and/or cost risk. Examples are shown below of the results of QEA, graphically expressed:


Sensivities

More detailed analyses are possible, down to individual tasks, cost line items and risk events if needed to understand project risk better and optimise it: IRA provides the opportunity and the tools to do it.


What are the drawbacks of IRA and how are they overcome?


The disadvantages or perhaps more correctly, the challenges of IRA are:


• The schedule and estimate must be aligned (produced on the same set of assumptions) for the combined analysis to be valid. For example if the schedule assumes a different sequence or rate of performing work from the estimate, the analysis will be wrong.

• Obtaining accurate splits between cost types - time-dependent (variable) and time-independent (fixed).

• Avoiding “double-dipping” between duration and cost ranges versus risk events or risk factors

• Spreading the costs correctly over the right groups of activities to represent the true time-variability of the costs.

• Dealing with mismatches in level of detail between the estimate and the schedule, such as where the estimate does not split out procurement costs from installation costs, preventing different risk profiles from being measured and differentiated.



Larger Projects Exacerbate the Challenges


IRA done well is a demanding environment, especially for mega projects (capex >$1bn). Large L3 Integrated Master Control Schedules and large complex estimates are to be expected.


The bigger the project the more difficult the task of developing a well-structured and responsive schedule that is technically acceptable for SRA and IRA. In addition, ensuring that the project scope is fully and properly represented is another challenge of increasing difficulty as the project grows in size.


We have already referred to the need for the complexity of the project to be adequately represented in the schedule model to ensure the MBE is appropriately represented. As the size of the IRA model increases, the effects of the Central Limit Theorem become more significant and the importance and difficulty of adequately correlating the IRA model increase.


Weather may be a major uncertainty factor for projects including construction. Being able to input the probabilistic weather calendars and model the weather realistically in all its complexity is another demanding IRA modelling element that becomes more challenging as the model size increases. But for some projects weather may be the dominant risk that must be modeled and only IRA provides the means to measure and rank the cost consequences reliably.


As the scale of the IRA model increases, the difficulty of measuring meaningful and accurate risk driver information also increases. This is because the increasingly sophisticated correlation models distort the use of correlation sensitivities as risk outputs from the analyses to rank the drivers of schedule completion and schedule cost. The correlation models behave as undeclared independent variables to bias the crucialities and cost sensitivities, making the use of QEA vital for realistic ranking of risk drivers of the IRA model. Please refer to our November 2013 Newsletter article: “Probabilistic Project Drivers”.


But as the IRA model size increases, so does the time required for producing realistic QEA results. Each element of the model to be excluded requires a full simulation of the model to provide probabilistic measurements by difference.


Overcoming the IRA Challenges requires sophisticated and powerful Tools, Skills and Experience


Unless the practitioner is experienced and understands the traps due to the above competing factors, inadequate modelling is an increasingly likely outcome as the scale of the project increases.


These large scale inputs require tools capable of evaluating and handling them quickly so that analysis may be performed in a timely way. In addition, tools to apply probabilistic weather calendars and correlation models comprehensively and quickly are also important.


RIMPL has developed software to enhance, automate and speed up the schedule and estimate range inputs, the correlation and weather inputs. In addition, RIMPL has built software to map risk events into PRA with maximum precision, to enhance analysis and automate reporting. RIMPL has also created a tool – IntegratedRiskDrivers (IRD) – to run PRA in a “batch mode” to run through a script of model elements to be excluded and their probabilistic differences in schedule and cost measured. This enables RIMPL to produce reliable QEA driver information from major project IRAs without having to use or charge for the full time of risk consultants to run PRA to produce each of the QEA outputs.


The result is to make small to large project IRA analysis practicable and realistic. This opens the door to effective risk-optimisation of complex major and mega projects, as well as for smaller projects.


IRA versus Serial SRA & CRA - Conclusions


Fully integrated cost & schedule risk analysis is recognised as the “gold standard” for modelling project time and cost risk (ibid). Yet it is still regarded by some as too hard to be practicable.


In this article we have compared Serial SRA and CRA with IRA. We have identified the fundamental flaw in separating SRA from CRA: that the project cost drivers due to schedule uncertainty and risk are not able to be identified and ranked with those due to cost uncertainty and risk. We have also shown that schedule uncertainty and risk that do not prolong the overall project but do increase internal project costs are not picked up by SRA/CRA approach.


In comparison, properly executed IRA inherently produces this missing information. IRA methodology and software produced by RIMPL handle the largest and most complex project models to provide realistic modelling and valuable opportunities to optimise project outcomes.