Adding risk events to the project schedule
‘Risk events’ are events that may, or may not, occur and that have an impact on the project schedule. Risk events are often described as threats if they have increase the risk of failing to meet targets, and opportunities if they reduce that risk.
Tamara provides a rich environment for describing risks (both threats and opportunities). The type of risk event that can be included in Tamara broadly fall into five categories:

A risk event resulting in one or more delays to a specific task (for example, material delivery is delayed, equipment must be repaired, or waiting for contractor to arrive)

Multiple but identical risk events independently producing the same potential delays to specific tasks (usually a risk that may apply to a set of identical tasks within a project, for example improper connection of the generator on a wind turbine, where there are many wind turbines being constructed in the project)

Risk events producing a change in productivity (which may affect many tasks. For example, having to switch to a less competent contractor could reduce productivity levels in several parts of a project)

Risk of extra work – sometimes called probabilistic branching (for example, rework of a design, reapplying for a permit)

Disruption risk events (risks that will cause a temporary halt to the whole project or some part of it. It causes the same delay to all applicable tasks that are active at the moment the risk event strikes. For example, an earthquake, fire, H&S inspection, or chemical spill that leads to the temporary shutdown of the whole or part of a construction site). Select one of the links to learn how each of these types of risk can be added to your schedule in Tamara.
Modeling a risk event resulting in one or more delays to a specific task
Risk events attached to specific tasks are entered, removed and edited in the Taskspecific Risk window, which is accessed by clicking the TaskSpecific Risk button in the Project Overview tab:
This opens the following interface:
The table has the following fields:

ID – an identification number provided automatically by Tamara. ID numbers apply to individual projects. If a risk is deleted, its ID number is not reused to avoid confusion with older models

Risk description – a brief description to help identify the risk

Expected frequency – either the probability (between 0 and 1) that the event will occur, if the risk could only occur once, or the expected frequency (greater than 0) if it could occur several times within the project

Independent – check this box if the risk can occur in multiple places within the project schedule, but each occurrence is independent of any others – see explanation here

Single Event – check this box if the risk can only occur once

Delay duration – this is the number of working days of delay that will be experienced in the execution of this task if the risk event occurs. Tamara will automatically include the additional costs associated with any resources dedicated to the task:

Delay (min) – the minimum number of days that will be added to the task

Delay (most likely) – the most likely number of days that will be added to the task

Delay (high P90) – a high estimate of the possible number of days that will be added to the task. There is only a 10% chance that the delay would be longer (i.e. a 90% chance it will be less) should the risk occur


Additional cost amounts – this is any extra cost that would be incurred if the risk event occurs, excluding the increased use of resources allocated to the task which are already accounted for. It is assumed that these extra costs are unrelated to the length of the delay (i.e. independent):

Cost (min) – the minimum additional cost if the risk occurs

Cost (most likely) – the most likely additional cost if the risk occurs

Cost (high P90) – a high estimate of the possible additional cost if the risk occurs. There is only a 10% chance that the cost would be greater (i.e. a 90% chance it will be less) if the risk occurs


Include – check this box if the risk should be included in the schedule risk analysis. This is useful if one wants to simulate different scenarios in which some risks are included or exclude, or if the risk is provisional (i.e. we aren’t sure if there is a real issue yet)
Risks can also be imported from Pelican.
Simple example
Open the example model called Build a house that comes with Tamara. The base schedule looks as follows:
Two risks are to be added to this schedule:
Risk A: The selected builder rejects the initial offer, requiring a renegotiation of the contract. A 10% chance of this occurring, producing (min, most likely, max) = (5,10,20) days delay
Risk B: There are repeated mistakes made by the builder. On average, 3 mistakes are expected, and each one will independently result in (1,5,30) days delay.
These risks are added to the risk register, accessed by selecting the Risk Register icon from Tamara’s Task Overview menu:
Risk A, builder rejects offer, is a single event (i.e. it will only occur once, if at all). The 10% probability is entered in the Expected frequency field, and the minimum, most likely and maximum delays of (5,10,20) entered in their respective fields. The risk is live (i.e. still exists) so the Include? box is checked.
Risk B, mistakes by builder, is not a single event (i.e. several events can occur). The average number of expected events (3) is entered in the Expected Frequency field, and the minimum, most likely and maximum delays of (1,5,30) for a single mistake are entered in their respective fields. The risk is live (i.e. still exists) so the Include? box is checked.
These risks are now connected to the schedule by selecting them in the Risk Register column of the Main View window:
Looking at the simulation results, we see the duration of Select builder, which was originally 10 days but now has Risk A applied to it, has the following distribution:
There is a 90% chance it is still 10 days (Risk A doesn’t occur), but a 10% chance it lies somewhere between 15 and 28 days (equating to a delay of between 5 and 20 days).
The duration of Build house, which was originally 250 days but now has Risk B applied to it, has the following distribution:
It was estimated that the builder would make 3 mistakes on average, each producing a delay of (1,5,30) days. Internally, the actual number of mistakes was simulated by Tamara using a Poisson(3) distribution:
The Poisson distribution shows that there is about a 5% chance that no mistakes will be made, which is why the results show about a 5% chance of the task taking the original 250 days. Internally, Tamara used the following distribution to model the delay from a single mistake:
The mean of this distribution is 9.2 days, so on average (statistically) we would expect to have 3 * 9.2 = 27.6 days of delay, taking the total duration to 277.6 days, which you can see is about the center of gravity of the simulation results histogram.
Modeling multiple but identical risk events independently producing the same potential delays to specific tasks
Many projects involve repeating the same set of tasks multiple times. For example, the set of tasks could be:

To build an overpass bridge (there may be several such bridges for a motorway or railway line construction project);

To erect a wind turbine (there may be many wind turbines built for a wind farm construction project);

To inspect pylons of a certain type (there will be many pylons to inspect for a complete transmission line refit project); or

To install a prebuilt bathroom (there may be two or more bathrooms for each floor of an office tower block construction project)
It is often the case that there are risks associated with such sets of tasks that similarly are repeatable. For example, each time a wind turbine is installed there might be a risk of the generator being faulty, or a crane failing, or connectors being fitted incorrectly, or bearings being misaligned. If one was building a farm of many turbines, such a risk event could happen to each turbine, or some, or none.
Tamara allows you to enter such a risk event a single time, rather than create a separate identical risk event for each place in the project it could occur. This reduces the work required to set up a schedule risk model and makes it very easy to adjust the probability or impact sizes since they are located in one single place.
In order to use this feature, one enters the risk event into the TaskSpecific Risk table, and additionally checking the Independent box.
Risks can also be imported from Pelican.
Example
You can follow this example by loading the file ‘Three Towers’ from the examples folder. In the following project, three electric cable towers (pylons) are to be built and connected together:
For each task, the same specialist team is used so, for example, land excavation on Tower 2 starts after the excavation on Tower 1 finishes, etc.
This project represents a set of tasks repeated for each tower and therefore the construction of each tower shares duplicates of the same potential risks as the others.
We will add a risk that, when stability for a tower is tested, it fails with 60% probability and would then produce a delay of (40,45,55) days:
Now we link the risk to each Test stability task:
This means that there are three independent chances for this risk to occur, each with 60% probability. There is therefore only 40% * 40% * 40% = 6.4% chance that the risk does not occur at all. Without the risks included, the project duration was 53 days. The simulation result shows this not has only a 6.4% chance of occurring as expected:
You can also see three slightly overlapping distributions, representing whether the risk event occurs 1, 2, or 3 times.
Modeling the risk of a change in productivity
In the Productivity Risk Factor dialog, one can enter a risk event that affects productivity. For example:
You plan to use a particular experienced subcontractor for completing some tasks in the project. However, it is estimated that there is a 30% probability that this subcontractor is unavailable, in which case you will have to revert to a second subcontractor who will take between 10% and 50% longer to complete the tasks, most likely 20%.
The risk is entered as follows:
You can add this productivity risk factor to a Work Type Category. Then, for each task to which that Work Type Category has been assigned, Tamara will simulate the risk event so that it occurs 30% of generated scenarios, and when it does occur adds between 10% and 50%, most likely 20% to the estimated duration of the tasks.
Modelling the risk of additional work
Tamara also includes the capability of adding new tasks to a schedule as a result of a risk event occurring, a technique often called probabilistic branching. This is illustrated with an example model called ‘Three towers with extra work’ that comes with Tamara.
In this example, there is a 20% probability that it will be necessary to obtain a permit from the local authority before beginning construction, which would take between 20 and 40, most likely 25 days.
We must first include the possible extra task(s) in the base schedule model, including all the antecedents and precedent logical links. It is best practice to set the duration to zero. For example, in MS Project, Task 2 Obtain permit has been added to the schedule:
MS Project interprets this as a milestone by default because of the zero duration, so we must . Note that Task 4 (Tower 1 Excavate land) has Obtain permit as its predecessor, so if Tamara changes the duration of Task 2 it will affect the rest of the schedule. After importing this model to Tamara, you need to define an Unplanned Work event by clicking the Unplanned Work button in the Task Overview tab:
This opens the following window, where you click Add, enter a description and a probability of occurrence, and then Save:
You can add more, and delete, unplanned work risk events by clicking the appropriate buttons. The table has the following fields:

ID – an identification number provided automatically by Tamara. If a risk existence is deleted, its ID number is not reused

Risk description – a brief description to help identify the risk

Probability – the probability (between 0 and 1) that the risk event will occur

Include? – check this box if the risk event should be included in the schedule risk analysis. This is useful if one wants to simulate different scenarios in which some risks are included or exclude, or if the risk is provisional (i.e. we aren’t sure if there is a real issue yet)
Then we connect the Unplanned Work event to the schedule, by selecting the event from those listed in the Unplanned Work field for the Obtain permit task:
Finally, we need to specify what the duration will be when this event occurs, by selecting the corresponding cell in the Work Amount Uncertainty column, choose Custom, and enter the duration the task will take in days (a percentage variation from Base will not work since this is zero). Negative values are not allowed since they would break the logic of the base schedule:
During a simulation, Tamara will randomly generate scenarios in which the unplanned work event occurs (with the probability defined) or does not occur. In a random sample where the unplanned work event occurs, all tasks connected to that particular unplanned work event will be simulated to occur together. In a random sample where the unplanned work event does not occur, the schedule dependency logic is maintained but the connected tasks are given a duration of zero. You can attach multiple unplanned work events to a single task, in which case the task will take a nonzero value if at least one of the risk existence events is simulated to occur.
In the worked example, the distribution of the duration for the Obtain permit task looks as follows:
There is an 80% probability it is zero (i.e. the risk event did not occur), and the remaining 20% is spread between 20 and 40 days. This results in a project completion date as follows:
The example model ‘Commercial Construction’ illustrates another application of the risk existence method.
Modeling disruption risk events
Disruption risk events temporarily stop all activity across the whole project, or across a section of the project. Disruption risks are connected to moments in time, not to individual tasks. In other words, whether these disruption risk events occur or not does not depend on which tasks are currently active in the project. Examples are:

Partial site shutdown due to earthquake, strike, or security breach;

Entire project postponement due to legal dispute or funding issue;

All contractor work halted due to discovery of illegal workers; or

Construction work halted pending H&S investigation of an accident
Tamara allows you to incorporate the occurrence of such risks using the Disruption table, which has the following fields:

ID – an identification number provided automatically by Tamara. ID numbers apply to individual projects. If a risk is deleted, its ID number is not reused to avoid confusion with older models

Risk description – a brief description to help identify the risk

Frequency –either the expected frequency of the number of risk events that may occur during the defined period if the risk event is repeatable (Single Event parameter is not ticked). For example, a strike or an earthquake may occur more than once, but a building collapse cannot; or the probability of an unrepeatable risk event occurring (Single Event parameter is ticked), e.g. a building collapse.

Single Event – ticking this box means that the risk can occur only once

Overlap – ticking this box means that if the risk event is repeatable, a second event can occur while one is still suffering from the delay caused by the first event

Delay (min) – the minimum number of days that the project or subproject will be suspended

Delay (most likely) – the most likely number of days that the project or subproject will be suspended

Delay (high P90) – a high estimate of the possible number of days that the project or subproject will be suspended. There is only a 10% chance that the delay would be longer (i.e. a 90% chance it will be less) should the risk occur

Start – the starting date of the defined period

Finish – the finish date of the defined period

Calendar – the calendar against which the delays will be added. Any tasks that share this calendar and are active at the moment a suspension risk event occurs will be delayed by the same amount of time

Include? – check this box if the suspension risk should be included in the schedule risk analysis. This is useful if one wants to simulate different scenarios in which some risks are included or exclude, or if the risk is provisional (i.e. one isn’t sure if this is a real issue yet)
Risks can also be imported from Pelican.
The example model Construction project example includes some disruption risks:
The first three suspension risks are storms that could occur between May and July each year of the project. They don’t overlap as one storm must finish before another starts, and there are expected to be on average 4 storms within the May to July window each year.
The Earthquake suspension risk is expected to occur twice over nearly 2.5 years, with delays of 010 days. The delays can overlap – meaning that whilst one is recovering from the effects of a first earthquake, a second could occur.
Finally, the contractor quitting suspension risk has a 5% chance of occurring, can only happen once (single event) – which also means that whether the overlap parameter is checked or not is irrelevant – and will cause a delay to the whole project of 3080 days if it occurs.
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 VoseNBootSeries
 VosejkProduct
 VoseRuinSeverity
 VoseRuin
 VosejkSum
 VoseTimeDividendsA
 VoseRuinNPV
 VoseTruncData
 VoseSample
 VoseIdentity
 VoseCopulaSimulate
 VoseSortA
 VoseFrequencyCumulA
 VoseAggregateDeduct
 VoseMeanExcessP
 VoseProb10
 VoseSpearmanU
 VoseSortD
 VoseFrequencyCumulD
 VoseRuinMaxSeverity
 VoseMeanExcessX
 VoseRawMoment3
 VosejSum
 VoseRawMoment4
 VoseNBootMoments
 VoseVariance
 VoseTimeShortTermInterestRateA
 VoseTimeLongTermInterestRateA
 VoseProb
 VoseDescription
 VoseCofV
 VoseAggregateProduct
 VoseEigenVectors
 VoseTimeWageInflationA
 VoseRawMoment1
 VosejSumInf
 VoseRawMoment2
 VoseShuffle
 VoseRollingStats
 VoseSplice
 VoseTSEmpiricalFit
 VoseTimeShareYieldsA
 VoseParameters
 VoseAggregateTranche
 VoseCovToCorr
 VoseCorrToCov
 VoseLLH
 VoseTimeSMEThreePoint
 VoseDataObject
 VoseCopulaDataSeries
 VoseDataRow
 VoseDataMin
 VoseDataMax
 VoseTimeSME2Perc
 VoseTimeSMEUniform
 VoseTimeSMESaturation
 VoseOutput
 VoseInput
 VoseTimeSMEPoisson
 VoseTimeBMAObject
 VoseBMAObject
 VoseBMAProb10
 VoseBMAProb
 VoseCopulaBMA
 VoseCopulaBMAObject
 VoseTimeEmpiricalFit
 VoseTimeBMA
 VoseBMA
 VoseSimKurtosis
 VoseOptConstraintMin
 VoseSimProbability
 VoseCurrentSample
 VoseCurrentSim
 VoseLibAssumption
 VoseLibReference
 VoseSimMoments
 VoseOptConstraintMax
 VoseSimMean
 VoseOptDecisionContinuous
 VoseOptRequirementEquals
 VoseOptRequirementMax
 VoseOptRequirementMin
 VoseOptTargetMinimize
 VoseOptConstraintEquals
 VoseSimVariance
 VoseSimSkewness
 VoseSimTable
 VoseSimCofV
 VoseSimPercentile
 VoseSimStDev
 VoseOptTargetValue
 VoseOptTargetMaximize
 VoseOptDecisionDiscrete
 VoseSimMSE
 VoseMin
 VoseMin
 VoseOptDecisionList
 VoseOptDecisionBoolean
 VoseOptRequirementBetween
 VoseOptConstraintBetween
 VoseSimMax
 VoseSimSemiVariance
 VoseSimSemiStdev
 VoseSimMeanDeviation
 VoseSimMin
 VoseSimCVARp
 VoseSimCVARx
 VoseSimCorrelation
 VoseSimCorrelationMatrix
 VoseOptConstraintString
 VoseOptCVARx
 VoseOptCVARp
 VoseOptPercentile
 VoseSimValue
 VoseSimStop
 Precision Control Functions
 VoseAggregateDiscrete
 VoseTimeMultiGARCH
 VoseTimeGBMVR
 VoseTimeGBMAJ
 VoseTimeGBMAJVR
 VoseSID
 Generalized Pareto Distribution (GPD)
 Generalized Pareto Distribution (GPD) Equations
 ThreePoint Estimate Distribution
 ThreePoint Estimate Distribution Equations
 VoseCalibrate
 ModelRisk interfaces
 Integrate
 Data Viewer
 Stochastic Dominance
 Library
 Correlation Matrix
 Portfolio Optimization Model
 Common elements of ModelRisk interfaces
 Risk Event
 Extreme Values
 Select Distribution
 Combined Distribution
 Aggregate Panjer
 Interpolate
 View Function
 Find Function
 Deduct
 Ogive
 AtRISK model converter
 Aggregate Multi FFT
 Stop Sum
 Crystal Ball model converter
 Aggregate Monte Carlo
 Splicing Distributions
 Subject Matter Expert (SME) Time Series Forecasts
 Aggregate Multivariate Monte Carlo
 Ordinary Differential Equation tool
 Aggregate FFT
 More on Conversion
 Multivariate Copula
 Bivariate Copula
 Univariate Time Series
 Modeling expert opinion in ModelRisk
 Multivariate Time Series
 Sum Product
 Aggregate DePril
 Aggregate Discrete
 Expert
 ModelRisk introduction
 Building and running a simple example model
 Distributions in ModelRisk
 List of all ModelRisk functions
 Custom applications and macros
 ModelRisk functions explained
 Tamara  project risk analysis
 Introduction to Tamara project risk analysis software
 Launching Tamara
 Importing a schedule
 Assigning uncertainty to the amount of work in the project
 Assigning uncertainty to productivity levels in the project
 Adding risk events to the project schedule
 Adding cost uncertainty to the project schedule
 Saving the Tamara model
 Running a Monte Carlo simulation in Tamara
 Reviewing the simulation results in Tamara
 Using Tamara results for cost and financial risk analysis
 Creating, updating and distributing a Tamara report
 Tips for creating a schedule model suitable for Monte Carlo simulation
 Random number generator and sampling algorithms used in Tamara
 Probability distributions used in Tamara
 Correlation with project schedule risk analysis
 Pelican  enterprise risk management
 ModelRisk Cloud system
 ModelRisk Cloud introduction
 Getting your software ready
 Starting ModelRisk Cloud
 Uploading a risk analysis model
 Creating a new scenario for the risk analysis model
 Running a Monte Carlo simulation of the model
 Uploading a SID (Simulation Imported Data file)
 Building a risk analysis model that uses SIDs
 Viewing the Monte Carlo results from a simulation run
 Administrator's use of ModelRisk Cloud
 Preparing a risk analysis model for upload to ModelRisk Cloud
 ModelRisk Result Viewer