Pertmaster Training Deck

7/21/2019 Pertmaster Training Deck

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Schedule Risk Analytics with PertMaster

Improving Schedule Quality &

Validating Capability to Execute


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Course Outline

An introduction to schedule riskanalysis theory

CPM vs$ Schedule %is 'nalysis

(etter estimates )or completiondates

E))ect o) se*ed distributions

+he parallel paths e))ect +ypes o) schedule

Schedule Review

Schedule Chec %eport

Pre,'nalysis Checs

Identi)ying Pro-ect .rivers

Risk Identification

Estimate /ncertainty

%is Events0 %is %egister

Develop Preliminary Risk Model Estimate /ncertainty0

Importing )rom Primavera &MS Pro-ect

+as .etails

Quic %is

+emplated Quic %is Correlation

%is Events

+as Existence

Probabilistic (ranching

%is %egister


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Course Outline

Preliminary Analysis & Review %is 'nalysis 1ptions

(uilding an Impacted %is Plan

.istribution 2raph

+ornado 2raph

(oomars

.istribution 'naly3er

inal Model & Report

Mitigation Planning

Mitigation Plan 'nalysis

P,Schedules /pdating Primavera


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Pro!ect Risk "ypes

#stimate $ncertainty Model

%is .istributions e$g$ 4pt estimates

Monte Carlo simulation

%eduction o) ris exposure Contingency

%is responses =e$g$ mitigation>

Risk #vents Model

%is register?log

PI Matrices

Estimate /ncertainty @ %is Events A +otal %is Exposure


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$ncertainty vs% Risk #vents

Duration aria'ility Risk #ventRisk #ventMinimum MaximumMost iely Maximum


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Schedule Risk Analysis "heory

'n Introduction


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Overview of traditional CPM

Predicts single completion date and cost

/ses single values )or activity durations and costs

.oes not tae uncertainty into account

8"d

,,?,,?,,


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CPM with schedule risk analysis

Quanti)ies probability o) completing pro-ect on time and budget

/ses 4 point estimates )or durations and costs =minB most lielyB max>

+aes uncertainty into account

8"d

,,?,,?,,

7d 8"d 86d


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(etter estimates for completion dates

Single,Path Schedule

CPM schedule )inishes on .ecember 8"B relies on combinations o)durations that eual #" days

ielihood o) the 8"th .ecemberD


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#)ercise* ind out chance of meetin+ ,-th Decem'er

1pen TrainingDesignBuild_1Path.plan)rom the Samples )older

Risk | Run Risk Analysis

Save plan i) reuested

eep de)ault analysis options and clicAnalyze

Identi)y chance o) completing on time



#)ercise* ind out chance of meetin+ ,-th Decem'er



.hy is there only a ,/0 chance1

.istributions are se*ed F most liely is nearer to minimum than maximum

+here is a greater chance an activity *ill tae more time rather than lesstime to complete$



#ffect of skewed distri'utions

Ghat *ould be the chance o) completing the pro-ect on time i) eachdistribution *as symmetricalD

2-0

+here)ore0 Gith skeweddistributions the chance o) hitting a schedule enddate *ill be less than 2-0



#ffect of parallel paths

+his pro-ect also completes on .ecember 8"

Is it more or less risy than single pathD

ielihood o) .ecember 8"th )inishD



#)ercise* Parallel paths

1pen TrainingDesignBuild.plan)rom the Samples)older


Save plan i) reuested

eep de)ault analysis options and clicAnalyze

Identi)y chance o) completing on time

Schedule *ith parallel paths more or less risyHD



More risky3



Com'ined effect of skew and parallel paths

Skewed Distri'utions

4Parallel Paths

5"ypically less than 6-0

chance of hittin+ completiondate



8"d

7Most likely8 schedule

' ;most liely< schedule has deterministic activity durations eual to themost liely durations

+he chance o) completing the pro-ect on time *ill be dependent on durationuncertainty and parallel paths

+he date it gives is not the most liely

7d 8"d 86d



Deterministic duration always most likely1

Schedules o)ten contain activities *here the duration estimates are not themost liely$

GhyD

Estimator *as too optimistic Estimator *as too pessimistic

Estimator *anted to add their o*n contingency

+he original estimate *as inaccurate

1thersD



Schedule types

Schedules can be categori3ed as the )ollo*ing0

8$ +he %ealists schedule =;most liely

!$ +he 'ggressive schedule =optimists>

4$ +he Cautious schedule =pessimists>

5$ +he Scale to it schedule =politicsJ>

etKs loo at !B 4 and 5 in more detailH



.hat type is your schedule1

.o you no* *hether the durations in your schedules are cautiousBaggressive or the most lielyD

1btaining three point estimates and running a schedule ris analysis *illhelp identi)y the type o) schedule you are *oring *ith$



6% A++ressive schedule

'ctivities have durations that are less than their most liely durations

+he ris analysis *ill tell us about the chance =i) anyJ> o) hitting the aggressiveschedule date

'ny advantages or disadvantages to *oring to an aggressive scheduleD

9d

7d 8"d 86d



9% Cautious schedule

Perhaps the *orst type o) schedule 'ctivities *ith durations that are greater than their most liely =i$e$ the durations

include contingency>

Ge *ould expect some activities to tae longer than planned and others shorterthan planned$ L1GEVE% *e do not no* *hich activities *ill do *hat$

7d 8"d 86d

8!d



7d 8"d 86d

8!d

Parkinson:s ;aw

Gor expands to )ill the time available )or its completion



.hy run a =uantitative analysis1

+o help create more realistic schedules

+o improve a*areness o) pro-ect ris and uncertainty

+o identi)y schedule assumptions

Communication0 .evelop a better understanding o) the schedule amongstthe pro-ect team



PertMaster Risk Methodolo+y

Schedule %evie* (est Practices Chec

Pre,'nalysis Chec

%is Identi)ication



.evelop Preliminary %is Model Enter Estimate /ncertainty

Map %iss to 'ctivities

Preliminary 'nalysis & %evie*

'naly3e 4pt Estimates

'naly3e %is Events

inal Model & %eport

%is Event plan

%esponse planning

RiskMana+ement

Process

(ased on*PM(1 Chapter 88




Schedule %evie* (est Practices Chec

Pre,'nalysis Chec

%is Identi)ication







'naly3e %is Events

inal Model & %eport

%is Event plan

%esponse planning

(ased on* PM(1 Chapter 88


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Schedule Review

Validating the uality o) the schedule


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Schedule Review

Schedule Check Reprt Checs )or Scheduling (est Practices

ot all categories need to be ;"



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Summary* Duration @uick Risk

Can be applied to 'llB Selected or iltered tass

/se to create minimumB most liely and maximum estimates based on apercentage o) the remaining duration

2ives a )eel )or uncertainty in the schedule


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Run an Analysis


Set Iterations

Set report to be displayed

Clic the &ptinsbutton )or additional options %is .ata

'nalysis

Garnings

ClicAnalyze


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Distri'ution raph

.uring the analysisB the durationB start date and )inish date o) each tas andthe duration and )inish date o) the entire pro-ect is recorded )or eachiteration$

(y de)aultB the Distri)utin *raph displays a distribution o) the )inish date)or the schedule ris analysis$

/se the tas list in the le)t,hand pane to vie* the distribution )or anindividual tasB summaryB or milestone

+o open the Distri)utin *raph0

Risk | Distri)utin *raph +oolbar (utton


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Distri'ution raph

Sho*s the result o) the ris analysis

Pro-ect+ree Statistics

+abs )or .istribution +ypes

Controls


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Distri'ution raph

Pro-ect +ree =le)t> Can navigate to the desired activity Can expand and contract the tree Can )ilter the displayed activities

Listogram =center> +abs )or .istribution types Lighlighters =can be customi3ed>

Statistics =right> Summary o) results

Controls


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Distri'ution raph

!7?eb?"7 "9?Mar?"7 89?Mar?"7

Distri'ution Bstart of interval

"

!""

5""

:""

7""

8"""

Dits

"N !"?eb?"7

6N !7?eb?"7

8"N !9?eb?"7

86N "4?Mar?"7

!"N "5?Mar?"7

!6N "6?Mar?"7

4"N "6?Mar?"7

46N ":?Mar?"7

5"N ":?Mar?"7

56N "#?Mar?"7

6"N "#?Mar?"7

66N 8"?Mar?"7

:"N 8"?Mar?"7

:6N 88?Mar?"7

#"N 88?Mar?"7

#6N 8!?Mar?"7

7"N 84?Mar?"7

76N 85?Mar?"7

9"N 85?Mar?"7

96N 87?Mar?"7

8""N !:?Mar?"7

Cumulativere=u

ency

>ew Store

#ntire Plan * inish Date

CumulativeProbability

.istribution %ange


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ormattin+ the isto+ram

%rmat | *raph+ ormatting labelsB colorsB vie* o) the histogram

%rmat | ,ighlighters+

Create highlighters

%rmat | -ayut+

Select *hat sections are displayed in the histogram vie*

%rmat | Statistics *rid+

Select the )ont and )ont si3e


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ormattin+ i+hli+hters

%rmat | ,ighlighters+ 1pens the Lighlighters dialog

AddF creates an additional highlighter

DeleteF completely removes the highlighter

Oou can toggle the highlighter in the ,ighlighterspane located directlybeneath the graph

+ypes o) Lighlighters Arr(s=point to a single value> Shade )et(een $alues =pic t*o values to shade bet*een>


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ormattin+ i+hli+hters E Arrows

+o create a ne*Arr(0 ClicAdd

SelectArr()or Type

Select alue 1 =.eterministicB +arget or Percentile>

I) Percentile enter the percentile to be highlighted

Choose the line colorB line thicness and description


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ormattin+ i+hli+hters E Shadin+

+o create a ne* Shade )et(een $alues highlighter ClicAdd

Select Shade )et(een $alues)or Type

Select alue 1=.eterministicB +arget or Percentile>

I) PercentileB enter the percentile to be highlighted

Select alue /=.eterministicB +arget or Percentile>

I) percentileB enter the percentile to be highlighted

Choose the line colorB line thicness and description


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Identifyin+ & alidatin+ Pro!ect Drivers

+ornado 2raphs


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Identifyin+ Pro!ect Drivers

/se the Trnad *raphto identi)y & validate pro-ect drivers

Duratin Sensiti$ity& Criticality "nde#are most o)ten used

Risk | Trnad *raph


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Identify i+h Risk Activities

+he critical path is use)ulH .etermines the earliest the pro-ect can )inish

.elay on the critical path delays the pro-ect

+he path that most deserves ris management

Criticality "nde#H .uring the ris analysisB the number o) times an activity *as critical is

recorded

+he percentage o) iterations a given activity landed on the critical path ACriticality "nde#


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Criticality Inde)

Criticality identi)ies activities that are liely to be on the critical path giventhe uncertainty in the schedule$

+here)oreB reduce durations and?or uncertainty on activities *ith a highcriticality index to improve the chance o) completing the pro-ect on time$

8""N criticality0 I) tas is delayedB pro-ect is delayed$

ocus on the tass *ith high criticality index )irst$


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#)ercise* Criticality Inde) B, of ,

1pen TrainingDesignBuild_criticality.plan

/nit ! is on the +raditional Critical Path should *e concentrate on /nit !D

/nit 8 no longer critical buthas more uncertainty

=company has not made this unit type be)ore>

/nit ! given less uncertainty=company has made similar units be)ore>


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Criticality Inde) Shows $nit , more riskyF


CPM sho*s *e should )ocus on /nit !D

%is 'nalysis sho*s *e should )ocus on /nit 8

+raditional CPM can ;Mas< %issJ


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Duration Sensitivity

Ghat maes an activity have a high duration sensitivityD 1n the critical path

ong duration

%elatively large uncertainty on duration

Sensitivity identi)ies activities that delay the pro-ect )inish$ /se it to identi)ythe tass that are in)luencing the pro-ect )inish due to their range o)uncertainty$

I) the activities identi)ied in the Duratin Sensiti$ity tornado do not maesense =ey activities missingB minor activities sho*ing as drivers>B revie* thepro-ect schedule F many times poor logic is a )actor

I) the activities appear correctB but out o) orderB a detailed analysis *illtypically yield better results


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"ornado raph

Trnad *raph is used to display and ran sensitivityB criticality andcruciality values$

+abs )or +ornado 2raphs


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"ornado raph

Trnad *raph =le)t> Sho*s the activities raned by sensitivity

Select *hich activities to vie* using thecontrols

.ouble,clic the bar to be taen to the activityin the 2antt Chart

Tls | Bkmark isi)le TasksF adds aboomar to the activity )or later re)erence

Statistics =right>

.isplays 'nalysis .etails

.isplay Settings


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"ornado raph E Duration Sensitivity for a Gey Activity

Duratin Sensiti$ity identi)ies *hich activities are liely to delay the pro-ect

Lo*everHGe may be interested in the activities that are liely to delay an intermediatetas or milestone

Ghich activities in a schedule can in)luence the completion o) a intermediatetas or milestoneD


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"ornado raph E Sensitivity Settin+s

Choose Sensitivity Measurement Persons Product Moment

SpearmanKs %an Correlation

Measure Sensitivity o)0

Entire Plan Summary

'ctivity

Gith0

'll +ass Child +ass 1nly

ogical Predecessors 1nly


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"ornado raph E ormattin+

%rmat | Chart+ +as iltering options =same as in controls belo*>

(ar )ormatting and coloring

%rmat | Statistics %nt+

Select the )ont and )ont si3e

%rmat | -ayut+

Select *hat sections are displayed in the tornado vie*


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(ookmarks

(oomaring the tass in the +ornado allo*s the activities to be re)erenceduicly bac in the 2antt chart

(oomars can be addedB deletedB and )iltered

(oomars can also be used to navigatethrough the 2antt Chart


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Summary* Results

Distri)utin *raph .isplays the distribution results o) the ris analysis

Can vie* the distribution o) the entire pro-ectB summaryB or activity

Trnad *raph

.isplays and rans sensitivityB criticality and cruciality values


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Summary* Schedule Review

(e)ore running an analysisB use the Schedule Check Reprtto chec )orscheduling best practices

/se Duratin !uick Riskto populate the minimumB most lielyB andmaximum values in order to run a uic analysis

Sanity chec the results o) the Duratin !uick Risk analysis in theTrnad *raph

%evie* the Duratin Sensiti$ityand Criticality "nde# graphs to identi)yand veri)y the pro-ect drivers

I) the uic analysis results mae senseB then continue *ith a more detailedanalysisB i) notB revie* and revise the schedule


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Schedule %evie*

(est Practices Chec

Pre,'nalysis Chec

%is Identi)ication







'naly3e %is Events

inal Model & %eport %is Event plan

%esponse planning



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Risk Identification


;%isy< areas o) the pro-ect

ocus 'reas0

Critical path

ear Critical Path

Ligh %is 'ctivities

Is the uncertainty based on PhaseD 'reaD Sub,areaD ContractorD

%is Events

/se the Pro-ect %is %egister

'dd additional riss & opportunities as necessary


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Schedule %evie*

(est Practices Chec

Pre,'nalysis Chec

%is Identi)ication







'naly3e %is Events

inal Model & %eport %is Event plan

%esponse planning



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Develop Preliminary Risk Model

.eveloping the model taes all o) the inputs collected in %is Identi)icationand applies them in the best possible *ay


Import )rom Primavera or Microso)t Pro-ect

+as .etails

.uration Quic %is

+emplated Quic %is

Correlation

%is Events

+as Existence

Probabilistic (ranching

%is %egister


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Importin+ from Primavera

2etting the schedule data into PertMaster )rom P:?P6


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Importin+ from Primavera

%ile | Prima$era

Pro-ect in P6?: database Can open multiple pro-ects and entire EPS nodes Can )eed bac analysis results

Pro-ect in P6?: E% )ile Can export )rom P6 to an E% )ile Can not )eed bac analysis results


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Importin+ from Primavera P2H E Setup

I) it is the )irst time connecting to P6?: )rom PertMasterB run the Cnnectin0izard)irst

%ile | Prima$era | Cnnectin 0izard


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Importin+ from Primavera P2H E Setup

+o import data )rom P6?: or to store analysis results in P6?:B ser De2ined%ieldsneed to be created in P6?:

In P6?: F 3nterprise | ser De2ined %ields+

Create the ser De2ined %ields needed


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Importin+ from Primavera E Mappin+s

Import mappings

Choose *here uncertainty is stored in Primavera

Choose ho* to import resources ? costs

Garnings

ins to other pro-ects Planning units


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Importin+ from Primavera E Mappin+s

Select the pro-ect=s> to import =P6?:>

Import mappings

Set your planning units

Choose ho* to importresources?costs

Choose *hich 'ctivity Codes?/ser.e)ined )ields to import

Garnings

ins to other pro-ects

Planning units


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Chec all dates0

Clic on the "mprt Checksheet

oo at the grey bars F these are the dates in Primavera

Start Checkand %inish Checkuser de)ined )ields

Importin+ from Primavera E erifyin+ the Import


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Summary* Importin+ from Primavera

PertMaster imports a copyo) the schedule

'ctivity codes and Custm Data "tems are included in the import

.e)ine Custm Data "tems in Primaverapriorto importing into PertMaster

/se Custm Data "tems to store uncertainty estimates and analysis results

Map the Custm Data "tems to the )ields in PertMaster

Veri)y the import on the "mprt Checksheet in PertMaster

+IP0 I) you having issues *ith the P4 )ileB use the P4 Pro-ect ile %ecoveryProgram =PG$exe>B located in the P4P%12S directoryB to rebuild the )ile


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Importin+ from Microsoft Pro!ect

Pro-ect in server database MSP Server Can )eed bac analysis results

Pro-ect in local database )ile =MP.> MSP !""# ? !""4 ? !""" ? H

Can )eed bac analysis results Ghen ased 'ppend or 1ver*riteB choose 1ver*rite

Pro-ect in )ile =MPP> MSP !""# ? !""4 ? !""" ? H Can not )eed bac analysis results

Pro-ect in MP )ile MSP !""" ? H Many other tools Can not )eed bac analysis results


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Settin+ up Microsoft Pro!ect

PertMaster can add a custom toolbar to Microso)t Pro-ect

%ile | 4icrs2t Pr5ect | Add Tl)ars and ie(s t 4S Pr5ect


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Importin+ into PertMaster

iles can be imported into PertMaster t*o *ays0

Start the import in Microso)t Pro-ect using the &pen "n Pert4asterbutton on the PertMaster toolbar

Start the import in PertMaster using %ile | 4icrs2t Pr5ect | &penPr5ect


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Import Mappin+s E "asks

+he Import Mapping dialogprovides a *ay to map )ields )romMicroso)t Pro-ect to )ields inPertMaster

+here are three tabsB TasksBProbabilisticB Resources and Cost


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Importin+ from Microsoft Pro!ect E Completin+ the Import

+he pro-ect is then opened in PertMaster

Save the )ile

%evie* any import *arnings


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Chec all dates0

Clic on the "mprt Checksheet

oo at the grey bars F these are the dates in Microso)t Pro-ect

Start Checkand %inish Checkuser de)ined )ields

Importin+ from Microsoft Pro!ect E erifyin+ the Import


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Applyin+ #stimates in PertMaster

/sing +emplated Quic %is


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"ask Details

Estimate uncertainty can be entered )or individual tass

Task Details | Risk And ncertainty | Duratin ncertainty

Estimates can also be entered directly into

the Minimum .urationB Most iely .uration

and Maximum .uration columns


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Duration @uick Risk

/sed to assign estimates toactivities uicly

Creates minimumB most liely andmaximum estimates based on apercentage o) the remaining

duration o) each activity

Can be applied to 'llB Selected oriltered tass

Lo*everB Duratin !uick Riskcan be too generic


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"emplated @uick Risk

Templated !uick Risk allo*s duration distributions to be assigned to tassbased on a template

Creates estimates based on percentages

+he template is stored in the plan )or re)erence to can be re,applied

+emplates can also be saved and re,used on di))erent plans$


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"emplated @uick Risk

Can apply di))erent shapes to di))erent groups o) tass

or Example0 Categories tass by ;.uration uncertainty

or exampleB longer design means shorter manu)actureD


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Define Correlation

1ther *ays to de)ine correlation

Correlate groups o) variables together

Sho* correlations in a column

In the %is %egisterB *hen a ris impacts many tass


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Correlation E Central ;imit "heorem

Ghat is the Central imit +heoremD

' mathematical theorem that states *hen large numbers o) randomsamples are combined they converge to*ards a ;central limitB the less variance , unless you havecorrelation


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#)ample* Correlation and level of detail

Create the plan belo*0

're the t*o versions o) this pro-ect the sameD


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%un the analysisB and compare P8 and P! durations *ith the Distri)utin

Analyzer


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+hey are not the sameB because ata di))erent level o) detail

Correlation maes them the same


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Correlation and level of detail

'dd correlation to re)lect reality as best as possible *ithin reason

Easiest to use Templated !uick RiskB *hen categori3ing by G(S


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Resources and Cost $ncertainty

Modeling cost,loaded resources


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Cost $ncertainty

Costs can be assigned to individual activities and G(S items in a pro-ect

' cost assignment can be time,dependent =e$g$ labor> or time,independent=e$g$ materials>


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"ime independent costs

Scenario0 ocate premises involves hiring an agency *hich is a )ixed )ee o)

R6B"""$

Insert the Cst 7Remaining8column$

Plan | Resurces0 'dd a resource *ith a spread loading$

'ssign 6""" units to the tas ;ocate premises< Step through ris analysis and cost does not change


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"ime dependent costs

Scenario0 %e)urbish premises *ill need 4 decoratorsB at R!"" per day each$

Plan | Resurces0 'dd a resource *ith a >ormalloading and cost K6--$

'ssign 4 decorators to the tas ;%e)urbish premises

Select to Vie* S,Curves or Listograms Select *hich data to vie* in report

Select *hich line items to vie* in report

.istribution %eport =right>

.ata +able =bottom>

Sho*s the data used )or the S,curves

Lighlight percentile =lo*er right corner>

Gith ! data sets selected *ill highlight and report variance bet*eenthe t*o

Gith 4 or more data sets selected *ill highlight values =*ill notcalculate variance>

Distri'ution AnalyJer E ormattin+


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Distri)utin Analyzer

'llo*s multiple distributions to be compared F entire plansB activities Can compare )inish dateB start dateB durationsB costB etc$



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Schedule %evie*

(est Practices Chec Pre,'nalysis Chec

%is Identi)ication



.evelop Preliminary %is Model

Enter Estimate /ncertainty Map %iss to 'ctivities



'naly3e %is Events

inal Model & %eport

%is Event plan

%esponse planning



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Response Plannin+

.eveloping and modeling ris mitigation plans

Risk Re+ister E Miti+ation overview


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Ghere *eare no*

Ghere *ecould be

Lo* *e could get there

Risk Re+ister E Addin+ miti+ation


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'dd t*o mitigation actions )or the response to the ris

2ive them Start and inish dates 2ive them an estimated cost

or the other rissB mae post,mitigation assessments the same as )or pre,mitigation

Risk Re+ister E Runnin+ the analysis


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Tls | Build "mpacted Risk Plan

(uild a pre,mitigation plan only

%un the ris analysis

Compare )inish date distribution *ith the plan be)ore you added your riss

Risk Re+ister E Risk si+nificance


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Sho* a duration sensitivity tornado

In the Display mdesectionB choose Risks ote the signi)icance on pro-ect duration o) your ris

"ornado raph E Risk Mode


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Ghen the analysis includes riss )rom the Risk RegisterB use Risk 4de to

revie* the sensitivity analysis o) the impact o) the riss

Risk Re+ister E Miti+ation 'enefit


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Sho* the e))ect o) mitigation on pro-ect duration and pro-ect cost

(uild both Pre, and Post,mitigation plans

Reprts | Distri)utin Analyzer

I) it already has distributionsB %ile | Clear Reprtand then%ile "mprt Data=see next slide )or example comparison>

1ptional0 Sho* the e))ect o) the speci)ic mitigation o) your ris

Risk Re+ister E Compare S?curves


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Risk Re+ister E Sanctionin+ miti+ation


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Choose an action to approve and sanction

%ile | Return t plan 'dd the action as a tas to the pro-ectB *ith durationB cost and lins



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Risk | Register

Mar the action as Sanctined



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Speci)y the corresponding tas in the pro-ect that *ill complete the action

+he action changes status to Plannedand taes the tasKs dates and costs


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Creatin+ & Displayin+ P?Schedules

/sing probabilistic schedule data

to trac and manage uncertainty

P?Schedules


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PertMaster calculates the percentile date =e$g$ P6"B P7"B P9"> )or each

activity in the schedule

Selected percentile dates can be assigned to each activity and thendisplayed on the 2antt chart

P/- (ar

P2- (ar

Deterministic (ar

#)ercise* Creatin+ P?Schedules


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Veri)y Task ser %ields have been

created to store P,Schedule data

Plan | Plan "n2rmatin | Task ser

%ields

I) neededB create additional )ields

#)ercise* Creatin+ P?Schedules


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Risk | Run Risk AnalysisB and choose 4re

Chec Create Task Risk Percentiles

Clic Settingsbutton0

Clic &6and thenAnalyze Close the Distri'ution raph

.ouble,clic on an activity and the P,schedule dates can be seen in theTask Detailspane0 ser %ields | Dates

#)ercise* Displayin+ P?Schedules


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"nsert | "nsert Sheet

Choose Risk &utputs.sheet

+he sheet is a di))erent vie* on the same data

It sho*s the P6" and P7" dates in columns and on the 2antt chart

+o change the )ormatting o) the P,Schedule0 %rmat | Custm Task Bars

P/- (ar

P2- (ar

Deterministic (ar

$sin+ P?Schedules as a 'aseline


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Customer expectations have been set at the 7"N date

+he P7" schedule can then be used as the ;customer baseline have started and

)inished

ote0

Continue to use deterministic schedule as your baseline =ParinsonKsla*J>

1nly use the P7" schedule to set customer expectations

Summary* P?Schedules


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Chosen percentiles can be calculated )or each activity in a schedule

+he P,Schedule dates are o)ten used as a ;rised baseline Pr5ect


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P6?: Export Mappings

Clic the &oadbutton and locatethe )ileP>e4apping?a$aAP"_:1.m2P>e =located in the %thers)older in thePertMaster installation directory>

Clic &pen

Clic pdate '(to update P4

P4 Export Mappings

Clic the &oadbutton and locatethe )ile P>4appings.m2P>=located in the %thers)older in thePertMaster installation directory>

Clic &pen

Clic pdate '(to update P4

$pdatin+ Primavera E iewin+ Results


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P6?:

ie( | -ayut | &pen Choose layout0 Risk &utput < ser Dates I) layout not in the list

Choose Import avigate to C9@Prgram %iles@Pert4aster

S2t(are@Pertmaster#@&thers

Choose layout )ile0 Risk &utput < ser Dates.pl2

P4 ie( | -ayut | &pen

Choose layout0 Risk < &utput Bars

I) layout not in the list ayouts can be trans)erred to other P4 pro-ects using the ie(L

-ayutL Trans2er


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$pdatin+ Microsoft Pro!ect

Sending data bac into MSP



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+o send the results o) the analysis bac to Microso)t Pro-ectB select the icon

on the toolbarB or %ile | 4icrs2t Pr5ect | pdate Pr5ect

$pdatin+ Microsoft Pro!ect E Mappin+s


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+he 4icrs2t Pr5ect 4appingsdialog *ill open

I) the mappings are blan0

Clic the -adbutton andlocate the )ile4SP4appings:1.m24SP=usually located in the %thers)older in the Pertmaster7xinstallation directory>

Clic &pen

$pdatin+ Microsoft Pro!ect E Mappin+s Bcont%


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+he de)ault mapping *ill no* bedisplayed in the mappings dialog

'dditional )ield mappings can beadded

Clic Sa$eto save the mapping)ile to reuse later

Chec &pen in 4SP a2ter pdate

Clic pdate '(to updateMicroso)t Pro-ect



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+he Microso)t Pro-ect )ile *ill be updated *ith the results o) the analysis

I) the option *as selectedB the )ile *ill be opening in Microso)t Pro-ect

+o vie* the resultsB select the vie* to display )rom the toolbar or menu


S h d l % i


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Schedule %evie*

(est Practices Chec Pre,'nalysis Chec

%is Identi)ication



.evelop Preliminary %is Model

Enter Estimate /ncertainty Map %iss to 'ctivities



'naly3e %is Events

inal Model & %eport

%is Event plan

%esponse planning

(ased on*PM(1 Chapter 88

Course Summary

Ri k A l i "h


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Risk Analysis "heory

.istributions se*ed to*ards minimum mean chance o) hitting )inish isless than 6"N

Parallel paths give rise to less chance o) completing pro-ect on time

Schedule types0 Most lielyB 'ggressiveB Cautious and Scale to it

ey is to assess ris and uncertaintyB to give realistic picture

Schedule Review

Schedule Check Reprt checs )or scheduling best practices

Pre,analysis chec =Duratin !uick Risk & Trnad *raph> to )urtherveri)y schedule

Risk Identification

%iss can be modeled through Estimate /ncertainty and %is Events

Course Summary

D l P li i M d l


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Develop Preliminary Model

%is distributions can be imported )rom Primavera & MS Pro-ect Templated !uick Risk provides a consistent method )or apply ris

assessments that can then be saved and reused

Crrelatincan be measured and de)ined

%is events can be modeled though Task 3#istenceB Pr)a)ilisticBranchingB and the Risk Register

Task 3#istence is used )or single activitiesB and Pr)a)ilisticBranching is used )or groups o) activities

+he Risk Register allo*s ualitative and uantitative assessment andanalysis

Course Summary

P li i A l i d R i


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Preliminary Analysis and Review

Risk Analysis &ptins can be set through the 4rebutton %iss )rom the Risk Register are included in the analysis by building an

impacted ris plan

Distri)utin *raph sho*s the results o) the ris analysis

Trnad *raph sho*s pro-ect drivers =sensitivity & criticality>

Distri)utin Analyzer allo*s multiple result sets to be compared

inal Model and Report

+he Risk Register can be used to model mitigation plans

P,Schedules are used to display ;rised,baselines< to a given level o)con)idence

Primavera and MS Pro-ect can be updated *ith the results o) theanalysis


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Additional Reference Material

'dvanced concepts


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Pro'a'ilistic Cash low

Modeling resource and cost pro-ections

Pro'a'ilistic cash flow

/nderstand the )ull e))ect o) ris ? uncertainty


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/nderstand the )ull e))ect o) ris ? uncertainty

on cost on schedule

on both cost and schedule together

Mae sure analysis creates data

I) option is grayed outB checsettings

#)ample* Pro'a'ilistic cash flow


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/sing %ocet sample *ith the penalty

Include the rissB pre,mitigation

%un the analysis

Create probabilistic cash )lo* graph

$ncertain spend curves ? cumulative


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$ncertain spend curves E 'y period


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$ncertain spend curves E vs% deterministic


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$ncertain spend curves E foot'all plot


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Mana+ement Costs

+here may be activities *hose duration is dependent on the duration o)


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+here may be activities *hose duration is dependent on the duration o)

other activities in the schedule0

Pro-ect management

Site supervision

Site security

Euipment hire

+hese type o) activities can be modeled using L'MM1CS

#)ercise* Mana+ement Costs B, of 6

'n agency *ill be hired to help us advertise )or intervie* and hire sta))


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'n agency *ill be hired to help us advertise )orB intervie* and hire sta))

Insert a ne* activityabove ;+rain sta)) can be modeled$

E$g$ costs associated *ith exceeding agreed contract dates in a pro-ect

#)ercise* Modelin+ Dama+es

'dd a )inish milestone activity F ;.amages start


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'dd a )inish milestone activity .amages start

'dd a hammoc activity F ;.amages< in the milestone to the hammoc =Start,to,Start>

in the ;Store ready )or opening< to the hammoc =inish,to,inish>

Constrain the milestone to 8"?Mar?"7 on Task Details | ConstraintstabBusing the Must Start 1n )ield$

#)ercise* Dama+es histo+ram

%un ris analysis and vie* the duration distribution )or the ;.amages< tas0


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y g

#)ercise* Dama+es Calendar


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.amages are going to be charged # days a *ee$ Currently the ;.amages


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p y p g

longer the last tas in the net*or

.ouble,clic on the tas ;Store ready )or openingote* In your plan this may 'e different

#)ample* Conditional 'ranchin+ macro

Chec your code is as )ollo*s0


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Close the Visual (asic editor$ +he code *ill be saved as part o) thePertMaster plan$

In PertMaster run ris analysis and step through some iterations$ Checconditional branch is operating as expected$

>ote*+he probabilistic branch can still operate *hen the conditional branchis not selected$

Macro uses

Conditional branching


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Modeling speci)ic pro-ect conditions and conseuences

Inter)acing *ith other applications

Pulling in data automatically )rom other applicationsB e$g$ Microso)tExcel

Sending data to other applicationsB e$g$ 1racle Pro-ects

Producing custom reports

'utomatically building reportsB e$g$ in Gord or Excel

Documents

Pertmaster Training Deck