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Advanced Project Schedule Risk Analysis Presented by David T. Hulett, Ph.D. Hulett & Associates, LLC Project Management Consultants Los Angeles, CA USA (310) © 2002 Hulett & Associates, LLC.
© 2002 Hulett & Associates, LLC 2 AgendaAgenda Introduction Activity distributions and data entry Risk along a schedule path Risk of parallel paths -- the Merge Bias Effect of limited resources Effect of constraints
© 2002 Hulett & Associates, LLC 3 Agenda (continued) Sensitivity Analysis Risk Critical Path Risk in statused schedules Probabilistic branching Conditional branching Correlation
© 2002 Hulett & Associates, LLC 4 Pitfalls in Relying on CPM CPM network scheduling is deterministic Single-point activity durations OK only if everything goes according to plan CPM durations are really probabilistic assessments There are no facts about the future
© 2002 Hulett & Associates, LLC 5 Objectives of a Schedule Risk Analysis Improve the accuracy of the schedule dates Validate the CPM or contract dates Establish a schedule contingency Identify the risk-driving events Communicate about and understand the project Continuously monitor changing schedule risk
© 2002 Hulett & Associates, LLC 6 Three Basic Components of Schedule Risk Analysis Risk of the activity duration DesignUnit 1 30d
© 2002 Hulett & Associates, LLC 7 Three Basic Components (continued) Risk of duration along a Path Start Design Unit 1Build Unit 1 Finish
© 2002 Hulett & Associates, LLC 8 Three Basic Components (continued) Risk at a point where parallel paths merge Start Build Unit 1 Build Unit 2 Design Unit 1 Design Unit 2 Finish
© 2002 Hulett & Associates, LLC 9 Risk of an Individual Activity Simple activity duration estimates are risky Activity duration risk is similar to cost element risk DesignUnit 1 30d
© 2002 Hulett & Associates, LLC 10 4 Common Probability Distributions UniformTriangular
© 2002 Hulett & Associates, LLC 11 4 Common Probability Distributions (continued) NormalBETA
© 2002 Hulett & Associates, LLC 12 Data Collection Assemble subject matter experts including people on the project Ask them to review the highest-risk items – Pareto analysis – top 30% + of the elements contains most of the risk Experts review elements – What areas are risky? What causes the risk? – What are the optimistic (low), most likely and pessimistic (high) durations for those elements? – Baseline schedule may not be the most likely duration
© 2002 Hulett & Associates, LLC 13 Data Collection (continued) Judgmental estimates. Do not have historical data Motivational biases – Want to make the project look good – project manager – Do not want to be seen as unable to do the job Cognitive biases – Anchoring and Adjusting – underestimate risk – Availability – focus on what is dramatic or current – Representative – what does the information represent – Unthinkable consequences
© 2002 Hulett & Associates, LLC 14 Data Collection (continued) Conduct the Risk Interview with facilitator Challenge the teams ranges Identify the places where failure might occur – tests fail – Likelihood of failure – Time to diagnose, plan and execute response, retest Document the issues and findings
© 2002 Hulett & Associates, LLC 15 Data Entry & Data Editing Data can be entered by task Data can be entered as common % ranges Entering or editing in Excel and copying over is easy Select activities manually or by a code in some field, to indicate similarities among activities – E.g. all test activities get –25% and +100% – E.g. all fabrication activities get –30% and +40% – This is called risk banding
© 2002 Hulett & Associates, LLC 16 Risk Along a Contiguous Schedule Path Path risk is the combination of the risks of its activities This is also like cost risk, adding risks of individual cost elements to get the risk of the total Start Design Unit Build Unit Finish Test Unit
© 2002 Hulett & Associates, LLC 17 Really Simple Schedule This schedule finishes on September 3 – 7-day weeks, like a model changeover, refinery turnaround If we can get into trouble with this simple schedule, we can get into trouble with real project schedules
© 2002 Hulett & Associates, LLC 18 Add Duration Risk to the Schedule using Triangular Distributions We are using Risk+ from C/S Solutions. Other packages from Palisade and Monte Carlo from Primavera. PERTMASTER Professional and Open Plan Professional have simulation capabilities built-in.
© 2002 Hulett & Associates, LLC 19 What is a Simulation? How do you find total project results? – Cannot add distributions – Must combine distributions Combining distributions using simulation – Almost all possible combinations of durations – Perform the project many times
© 2002 Hulett & Associates, LLC 20 Combine Distributions by Simulation Monte Carlo simulation – Very General – 50-year old method Computer performs project many times – Exercise is a simulation – Each calculation is an iteration Brute force solution – All combinations of possible costs or durations
© 2002 Hulett & Associates, LLC 21 Number of Iterations How many iterations should we do? – Accuracy demanded – 2,500 is sufficient – Final reports, ==> 10,000 iterations Latin Hypercube – Stratified sampling for more accuracy
© 2002 Hulett & Associates, LLC 22 Common Sense Results can be Wrong! Well, if we just use the right most likely durations in our schedules we will get the most likely completion date. Right? Wrong! Wrong!
© 2002 Hulett & Associates, LLC 23 Monte Carlo Simulation Results for Really Simple Schedule CPM date is not even the most likely – Thats about 9/10 CPM date 9/3 is <15% Likely to be met 80% Target is 9/21
© 2002 Hulett & Associates, LLC 24 Risk at Merge Points: The Merge Bias Many parallel paths merge in a real schedule Finish driven by the latest converging path Merge Bias has been understood for 40 years Build Unit 1 Build Unit 2 Design Unit 1 Design Unit 2 Finish Start
© 2002 Hulett & Associates, LLC 25 Much Schedule Overrun Risk Occurs at Merge Points Complex schedules have activities in parallel Merge points are important events – Completion of the project – Major design review – Beginning integration and test Delay on any path may potentially delay the project This extra risk is called the Merge Bias
© 2002 Hulett & Associates, LLC 26 Example of Merge Bias Example of the Merge Bias – Make three project paths that are exactly the same – Same durations – Same risks – Start on the same day CPM says this project, too, finishes on June 17 Is this reasonable? Is this project just as risky as the one-path project? More risky? Somehow less risky?
© 2002 Hulett & Associates, LLC 27 This Schedule has Three Equal Parallel Paths Two paths are collapsed Each path has exactly the same structure
© 2002 Hulett & Associates, LLC 28 Evidence of the Merge Bias Three Path Schedule One Path Schedule
© 2002 Hulett & Associates, LLC 29 Evidence of Merge Bias (continued) Three Path ScheduleOne Path Schedule
© 2002 Hulett & Associates, LLC 30 Whats Happening Here? Likelihood of Two Events at Once Success is only in the green area Other scenarios represent failure
© 2002 Hulett & Associates, LLC 31 Resource Problems With real projects resources may be scarce Unless resources are added, some activities must be delayed or stretched out Critical Path Method (CPM) scheduling allows resource leveling and delays the project Each iteration is a CPM solution Each iteration must be resource-leveled Each iteration is a CPM solution Each iteration must be resource-leveled
© 2002 Hulett & Associates, LLC 32 What Happens if Resources are Limited? Limited Test Equipment means delaying Units 2 & 3 Resource leveling delays completion from 9/3 to 10/23
© 2002 Hulett & Associates, LLC 33 Leveling Resources and Schedule Risk Resource Leveled Simulation Simulation Not Resource Leveled
© 2002 Hulett & Associates, LLC 34 Imposing Constraint Dates on the Project Finish Date Constraints are placed on the important delivery dates This can help CPM scheduling – Negative float develop feasible schedules Constraints are also used to make the project show success Constraints left in the schedule frustrate risk analysis of the very items you care about
© 2002 Hulett & Associates, LLC 35 Imposing Constraint Dates on the Project Finish Date (continued) We leave the Must Finish On 9/3/02 constraint on the finish milestone
© 2002 Hulett & Associates, LLC 36 Effect of a Not Later Than Or Must Finish On Constraint on the Simulation Project gives you a message about the constraint This tells you that you have a constraint that is binding You can complete if you manually click the message If you turn off messages you will never know whether you have constraints that bind Do Not Turn Off the Scheduling Messages
© 2002 Hulett & Associates, LLC 37 Effect of a Must Finish On Constraint If the results are captured at the milestone, the results are very uninteresting and uninformative
© 2002 Hulett & Associates, LLC 38 Effect of Must Finish On Constraint Cannot go Earlier since the Milestone does not Move If the results are gathered at the summary task, the results show only the threat side of the distribution
© 2002 Hulett & Associates, LLC 39 Must Finish ON will have Different Results if you use Summary Bar or Milestone Even if finish milestone might not be later, Test Unit can be, in Project. Were using the Project summary bar for our results Whats happening here? MS Project allows the predecessor activities extend PAST the FIXED milestone
© 2002 Hulett & Associates, LLC 40 Effect of Finish Not Later Than Constraint Collecting data at the Summary Bar – Correct because MS Project allows activities to exceed the date Collecting data at the Finish Milestone – Incorrect because Constraint holds
© 2002 Hulett & Associates, LLC 41 What are the Highest Risk Activities? We do not know in advance which path will delay the project Monte Carlo simulation tells us which is most likely – Activities on critical path in most iterations Path delaying the project may not be the critical path identified by CPM This is Schedule Critical not Technically Critical – Combination of risk and low float (slack)
© 2002 Hulett & Associates, LLC 42 What are the Highest-Risk Activities? Critical Unit 2 is Identified for Risk Mitigation Units 1 & 3 are Shorter and Not Risk Mitigated
© 2002 Hulett & Associates, LLC 43 What are the Highest-Risk Activities? (continued) Unit 2 is Closely Managed but Units 1 & 3 still Have Risk
© 2002 Hulett & Associates, LLC 44 Use Sensitivity Analysis First Opportunities only in the CPM critical path for Unit 2 Even if Units 1 & 3 are shorter, Unit 2 keeps schedule from shortening
© 2002 Hulett & Associates, LLC 45 Risk Criticality of Activities Risk Criticality is the likelihood that an activity will be on the path that delays the project – Activity may not be technically risky – Activity may not be risky, but path is Percentage of iterations on the critical path
© 2002 Hulett & Associates, LLC 46 Risk Critical GANTT Chart The Critical Path has been managed and is only 18% likely to delay the project. Now turn attention to Units 1 & 3
© 2002 Hulett & Associates, LLC 47 Handling Statused Activities Risk range on remaining duration – Actuals are not risky Hence the Min Rdur, ML Rdur, Max Rdur What happens when an activity has actual progress? – Design Unit has 70% complete, 9 days to go – On track to finish on 9/3
© 2002 Hulett & Associates, LLC 48 Adjusting the Durations for 15 days of Actual Progress With only 9 days to go on Design, risk ranges adjusted to remaining duration. YES! Leave original risk ranges even though Design has progress? NO!
© 2002 Hulett & Associates, LLC 49 Handling Statused Activities (continued) If you do not change the risk ranges, expected completion is 10/5
© 2002 Hulett & Associates, LLC 50 Handling Statused Activities (continued) After changing the risk ranges to reflect progress, expected completion is 9/12
© 2002 Hulett & Associates, LLC 51 Probabilistic Branching Many projects have points where there is a possibility of failure, a discontinuous event Have to model the likelihood of the failure and its consequence for the schedule Called Probabilistic Branching Probabilistic branching is an advanced feature found in PERTMASTER and Monte Carlo
© 2002 Hulett & Associates, LLC 52 Model the Probabilistic Branch Typically we do not include failure in schedule – Add FIXIT and Retest – Preserve the 9/3 finish date (with 0 duration) Enter ranges for the new activities
© 2002 Hulett & Associates, LLC 53 Logic of Probabilistic Branch Succeed 70% Branch Fail 30% Branch New Activities
© 2002 Hulett & Associates, LLC 54 Branching in the Risk Entry Table
© 2002 Hulett & Associates, LLC 55 Typical Bi-Modal Result Distribution Success Failure
© 2002 Hulett & Associates, LLC 56 Conditional Branching Contingency Planning Problem Propulsion System Alternative A is preferred by customer – Alternative A is new and risky Alternative B is the back up, contingency plan – Acceptable, not preferred We care about the schedule, too How long do we stick with Alternative A and under what condition do we go to Alternative B? Conditional branching is an advanced feature found Monte Carlo and Risk+
© 2002 Hulett & Associates, LLC 57 Schedule with Alternatives A & B Build and Test Alt. B SNET 9/22, the day after the decision about Alt. A
© 2002 Hulett & Associates, LLC 58 Risk Information for Alternatives A and B Alternative B is Less Desirable but Less Risky Alternative A has Wider Ranges, Longer Design Time
© 2002 Hulett & Associates, LLC 59 What Happens if there is No Backup Alt. B? Zero out Build and Test Alt. B so Alt. A is the only one
© 2002 Hulett & Associates, LLC 60 If Must Go with Alt. A, (if there is No Alt. B), 80% Date is 6/10/03
© 2002 Hulett & Associates, LLC 61 If No Alternative B, Alternative A is 100% Likely
© 2002 Hulett & Associates, LLC 62 Choosing Alt. B if Alt. A Design is Later than 9/21 – 80% Date is Now 5/3/03
© 2002 Hulett & Associates, LLC 63 Switch to Alt. B if Design on Alt. A is Later than 9/21 – Which Technology is Used? Plan A is Chosen only 33% of the Time Plan B is Chosen 67% of the Time
© 2002 Hulett & Associates, LLC 64 Summary of Conditional Branch Exercise
© 2002 Hulett & Associates, LLC 65 Causes of Correlation Correlation between activity durations – When two activities durations move together – They are driven by a common risk driver State-of- the- Art Technology Software Designing Software Coding
© 2002 Hulett & Associates, LLC 66 For Ease of Data Entry, Use Quick Setup For expediency, use risk banding – Low = -25% – High = +50% – Distribution = triangular Correlation is an advanced feature found PERTMASTER and Risk+. Monte Carlo has rudimentary correlation
© 2002 Hulett & Associates, LLC 67 Simulation With No Correlation Sigma 34.1 days Range 2/8 – 8/29/03
© 2002 Hulett & Associates, LLC 68 Results of Correlated Durations Sigma 49.2 d, Larger than 34.1 d Range 2/1 – 9/28, Wider than 2/8 – 8/28
© 2002 Hulett & Associates, LLC 69 Correlation Methods Most software uses Spearman rank order correlation for Project, PERTMASTER, Excel and Crystal Ball for Excel – No known relationship to Pearson correlation Risk+ has just adopted correlation and uses Pearsons approach – This is what we think of when we specify correlation – Uses a Lurie-Goldberg iteration for non-normal distributions Monte Carlo just uses perfect positive correlation
© 2002 Hulett & Associates, LLC 70 This Correlation Matrix is Not Feasible Correlation Matrix may be infeasible Eigenvalue (determinant) test used to test feasibility DesignCodeTest Design1.0.9 Code Test
© 2002 Hulett & Associates, LLC 71 Software Performs Test Alerts the user – The matrix is inconsistent with the natural world – These coefficients could not coexist The program then offers to adjust the matrix so that it just barely passes the test – The user can see where the problems are – Risk+ allows the user to indicate the relative confidence of the coefficients, and adjusts mainly the less confident ones
© 2002 Hulett & Associates, LLC 72 Schedule Risk Analysis Summary Introduction Activity distributions and data entry Risk along a schedule path Risk of parallel paths -- the Merge Bias Effect of limited resources Effect of constraints
© 2002 Hulett & Associates, LLC 73 Schedule Risk Analysis Summary (continued) Sensitivity Analysis Risk Critical Path Risk in statused schedules Probabilistic branching Conditional branching Correlations
Advanced Project Schedule Risk Analysis Presented by David T. Hulett, Ph.D. Hulett & Associates, LLC Project Management Consultants Los Angeles, CA (310) © 2002 Hulett & Associates, LLC.
Advanced Project Schedule Risk Analysis Using Risk+ Presented by David T. Hulett, Ph.D. Hulett & Associates, LLC Project Management Consultants Los Angeles,
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