©2018 Kodukula & Associates, Inc. All Rights Reserved.
How to Improve Project Schedule Success by Be8er Es:ma:on: Applica:on of Next Genera:on Risk Management Tools
Dr. Prasad S. Kodukula, PMP, [email protected]
Yun Zhang, MMF
Kodukula & Associates, Inc. Chicago, Illinois
Presented at Palisade Risk Conference
San Antonio, Texas
November 12 – 13, 2019
©2019 Kodukula & Associates, Inc. All Rights Reserved.
Dr. Prasad S. Kodukula, PMP, PgMP ! Speaker, coach, author, entrepreneur, inventor ! 30+ years of professional experience ! Spoke in 45 countries ! Coauthor or contribu:ng author of eight books ! Recognized by PMI as “Best of the Best” in project management
• 2016 PMI Eric Jene8 Project Management Excellence Award
• 2010 PMI Dis:nguished Contribu:on Award
! Founder/CEO, Kodukula & Associates, Inc. ! Cofounder/CEO, NeoChloris, Inc. ! Cofounder/CEO, 2Ci ! Lecturer, University of Chicago, Illinois Ins:tute of Technology
About Us ! Kodukula & Associates, Inc. ! Project, program, pordolio management
! Coaching, training, consul:ng ! Founded in 1995 in Chicago ! Experience with 40+ Fortune 100 companies
Relevant Books by Dr. Kodukula
Learning Objec:ves ! Develop more realis:c and accurate project schedule es:mates using next
genera:on risk management tools
! Control schedules using ra:onal risk response/management techniques
including reserves
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Presenta:on Overview ! Introduce a hypothe:cal project ! Start with determinis:c task dura:on es:mates and project schedule
! Add impact of different types of risks
! Discuss es:ma:on of reserves
! Brief model demo
! Q&A ! (Presenta:on mode & “role play” mode)
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Acme Biomedical Corp.: Project Zulu WBS
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Gather requirements
Design prototype
Get execu:ve sign-‐off
Ini:al Design Build
prototype: Trial 1
Test prototype: Trial 1
Revise/test prototype: Trial 2
Proto-‐typing
Finalize design
Get execu:ve sign-‐off
Final Design
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Prepare applica:on
Submit applica:on
Receive approval
Govt. Approval
Select suppliers
Nego:ate/ sign agreements
Procure equipment/ materials
Procure-‐ment
Get execu:ve sign-‐off
Ramp-‐up produc:on
Perform produc:on tes:ng
Launch
Launch &
Closeout Kick-‐off/plan project
Monitor/control project
Project Manage-‐ment
Project Zulu WBS con:nued
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High Level Project Schedule*
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*255 Work days (Approximately one calendar year)
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Project Schedule: Gan8 Chart
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1. Events Risk ! Caused by uncertain events with a posi:ve or nega:ve effect on project objec:ves
! Events with nega:ve impact are called threats.
• Example: Supply chain disrup:ons
! Events with posi:ve impact are called opportuni:es. • Example: Prototype successful in the first trial w/o the need for addi:onal
trials
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2. Variability Risk ! “Non-‐event” risk due to uncertainty related to es:mates causing actual
dura:ons to differ (higher or lower) from es:mated dura:ons
! Examples:
• Actual resource produc:vity happens to be lower (or higher) compared to the
es:mated produc:vity
• The actual material prices turn out to be higher (or lower) than planned
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How to Account for Variability and Events Risks in Es:ma:ng Project Dura:ons? ! Monte Carlo (MC) simula:on generates numerous possibili:es of project schedule
based on numerous possibili:es of task dura:ons
! Simula:on tool accounts for impact of risk events in accordance with individual
probabili:es of risk events.
! For example, if a risk has 60% probability of occurrence, risk impact will be included
in 600 out of the, say, 1,000 itera:ons.
! Each itera:on of the simula:on (re)calculates the project schedule using the
schedule es:ma:on model (cri:cal path method), and records the result.
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“Must-‐Know” Distribu:ons ! Normal
! Pert
! Triangular
! Binomial
! Bernoulli
! Poisson
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Variability Risk: Input Data PROJECT ZULU
Task Type of Distribu:on
Distribu:on Parameters (days)*
No. Name Minimum Most Likely Maximum 1 Start 0 2 Monitor, Control & Manage Project
3 Kickoff Project/Develop Project Plan 5 4 Gather Requirements Pert 14 15 19 5 Design Prototype Triangular 23 25 31 6 Get Execu:ve Sign-‐off 1 5 7 Build Prototype: Trial 1 Pert 23 25 31 8 Test Prototype: Trial 1 Pert 9 10 13 9 Revise/Test Prototype: Trial 2 Pert 14 15 19 10 Finalize Design Pert 9 10 13 11 Get Execu:ve Sign-‐off 2 5 12 Prepare Applica:on Pert 18 20 25 13 Submit Applica:on 5 14 Receive Approval Triangular 54 60 75 15 Select Suppliers Pert 45 50 63 16 Nego:ate/Sign Agreements Pert 27 30 38 17 Procure Equipment/Materials Triangular 36 40 50 18 Get Execu:ve Sign-‐off 3 5 19 Ramp-‐up for Produc:on Pert 45 50 63 20 Perform Produc:on Tes:ng Pert 14 15 19 21 Launch 5 22 Finish 0
*Minimum: 90% of Most Likely Maximum: 125% od Most Likely
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Events Risk (Threats): Input Data
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No. Event Proba-‐bility*
Impact
Descrip:on Distribu:on/Dura:on, days
Min Most Likely
Max
1 Applica:on rejected. 30% Task 23: Resubmit Applica4on (new task) is created.
Pert 9 10 13
2 Prototype test Trial 1 total failure
30% Task 9: Revise/Test Prototype – Trial 2 requires addi:onal :me.
Pert 9 10 13
3 Supply chains disrupted due to hurricane(s)
0.25* Task 17: Procure Equipment/Materials takes longer. New dura:ons are es:mated.
Pert 54 60 75
*Threat 3 follows Poisson distribu:on with a “lambda” of 0.25. Probability of no hurricanes: 77.9%, one: 19.5%, two: 2.4%, three: 0.2%
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Events Risk (Opportuni:es): Input Data
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Opportunity Proba-‐bility
Impact
No. Event Descrip:on Distribu:on/Dura:on, days
Min Most Likely
Max
1 Fast applica:on approval 20%
Task 14: Receive Approval – Task dura:on is reduced.
Pert -‐18 -‐20 -‐25
2 Prototype Trial 1 highly successful.
10%
Task 9: Revise/Test Prototype – Trial 2 is no longer required.
No Dist. -‐ 0 -‐
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Schedule Es:ma:on Model
Model O
Model for Project Schedule Es:ma:on Cri:cal Path (Microsos Project) I = Input
Task Dura:on Task Dependencies Risk events (probabili:es and impacts)
O = Output Project Schedule
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Simula:on Results/Itera:ons* for Risk Events
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Itera:on No.
Threats Opportunities
1 2 3 1 2
Applica:on is rejected. Trial 1 of prototype
tes:ng is a total failure.
Supply chain disrup:ons are caused by a hurricane(s).
Applica:on is approved quickly.
Trial 1 of prototype tes:ng is a total
success.
Task 23: Resubmit Applica4on (new task)
is created.
Task 9: Revise/Test Prototype – Trial 2
requires addi:onal :me.
Task 17: Procure Equipment/Materials
takes longer. New dura:ons are
es:mated.
Task 14: Receive Approval – Task
dura:on is reduced.
Task 9: Revise/Test Prototype – Trial 2 is no longer required.
30% 30% -‐ 20% 10%
1 0 0 67 -‐ 22 23
2 0 15 0 0 24
3 0 0 0 0 0
4 0 0 0 -‐ 21 25
5 0 0 0 0 27
6 16 17 0 0 30
7 15 0 60 0 31
8 0 0 0 0 29
9 15 0 0 0 26
10 0 16 0 0 25
*Only 10 itera:ons shown for illustra:on
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PDF with Variability and Events Risks
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Min: 234 d Mean: 272 Max: 440
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CDF with Variability and Events Risks
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Con:ngency Reserves for Project Zulu
Contingency Reserve
For PM
For Sponsor
Deterministic Estimate
255 d
17 d
10 d Determinis:c Es:mate + PM reserve (P50): 272 d
Determinis:c Es:mate + PM & sponsor reserves (P80): 282 d
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Other Risk Types 3. Ambiguity Risk: Risk related to uncertainty about future. Examples:
• Evolving requirements
• Inherent complexity in the project
4. Emergent Risk: Risk caused by events that can only be recognized aser
they have occurred; events are osen referred to as “unknown-‐unknowns”
or “black swans.” Examples: • Tsunami
• Major poli:cal upheavals
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Ambiguity Emergent
Variability Events
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Qualita:
ve
Quan:
ta:ve
Non-‐Event Event
Risk Ana
lysis App
roach
Risk Type
Next Generation Risk Analysis and Management
Manage by Using Reserves
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Current/NextGen Risk Management
No. Component Current NextGen
1 Project estimates Deterministic Probabilistic
2 Risks (threats/opportunities) Not considered Considered
3 Risk analysis Qualitative Quantitative
4 Reserves Not included Included
5 Reserve estimation Ad hoc Rational
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NextGen Project and Pordolio Management ! Two-‐day workshop
! In Chicago
! Q1 2020 (dates to be determined)
! Topics covered:
• Schedule and cost risk analysis
• Integra:on of schedule and cost risks
• Es:ma:on of reserves
• Risk mi:ga:on
• Uncertainty analysis of NPV
• Sensi:vity analysis
• Pordolio op:miza:on
• Efficient fron:er
• Decision analysis
! For more informa:on, contact: [email protected]
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APPROVED
Project Zulu Schedule ! Project team receives 272 days (P50) as the performance measurement
baseline that includes 17 days of con:ngency reserve.
! Management will keep in mind that P80 will be 282 days.
! We do not expect any ambiguity risks on the project.
! Management needs to be aware of emergent risk.
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Highlights
©2019 Kodukula & Associates, Inc. All Rights Reserved.
1. Ignoring variability and events risks is the most common reason for schedule failures.
• So… Account for them!!
2. Deterministic schedule estimates are unrealistic and overly optimistic.They lead to project failure.
• So… Stop using them!
3. Want to increase your chances of project success? Of course!
• So… START USING NEXT GEERATION RISK MANAGEMENT!!!
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Contact Informa:on ! Dr. Prasad S. Kodukula, PMP, PgMP
! LinkedIn: Kodukula
! www.kodukula.com
! www.facebook.com/KodukulaAndAssociates
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