Poor Man s Approach to Monte Carlo

Similar documents
Project Risk Management

Project Management Professional (PMP) Exam Prep Course 06 - Project Time Management

SCHEDULE CREATION AND ANALYSIS. 1 Powered by POeT Solvers Limited

WHY ARE PROJECTS ALWAYS LATE?

Risk Video #1. Video 1 Recap

Project Management. Managing Risk. Clifford F. Gray Eric W. Larson Third Edition. Chapter 7

Project Theft Management,

PROJECT MANAGEMENT: PERT AMAT 167

PROJECT COST MANAGEMENT

Making sense of Schedule Risk Analysis

Project Management Techniques (PMT)

Performance risk evaluation of long term infrastructure projects (PPP-BOT projects) using probabilistic methods

CHAPTER 5 STOCHASTIC SCHEDULING

Chapter-8 Risk Management

Program Evaluation and Review Technique (PERT) in Construction Risk Analysis Mei Liu

ADVANCED QUANTITATIVE SCHEDULE RISK ANALYSIS

After complete studying this chapter, You should be able to

Haeryip Sihombing 1. Risk. Risk Management

UNIT-II Project Organization and Scheduling Project Element

Project Management. Chapter 2. Copyright 2013 Pearson Education, Inc. publishing as Prentice Hall

Pension Drawdown Monte Carlo Simulation. for. Example Client. Created by Mark Barden Vision West and Wales

Fundamentals of Project Risk Management

Project Management. Session 5 Budgets and Estimation Andre Samuel

Unit 9: Risk Management (PMBOK Guide, Chapter 11)

Cost Risk Assessment Building Success and Avoiding Surprises Ken L. Smith, PE, CVS

RISK ANALYSIS GUIDE FOR PRIVATE INITIATIVE PROJECTS

For the PMP Exam using PMBOK Guide 5 th Edition. PMI, PMP, PMBOK Guide are registered trade marks of Project Management Institute, Inc.

Every project is risky, meaning there is a chance things won t turn out exactly as planned.

Project Planning. Identifying the Work to Be Done. Gantt Chart. A Gantt Chart. Given: Activity Sequencing Network Diagrams

International Project Management. prof.dr MILOŠ D. MILOVANČEVIĆ

A METHOD FOR STOCHASTIC ESTIMATION OF COST AND COMPLETION TIME OF A MINING PROJECT

COST MANAGEMENT IN CONSTRUCTION PROJECTS WITH THE APPROACH OF COST-TIME BALANCING

Schedule Risk Analysis Simplified 1

Project planning and creating a WBS

How to Satisfy GAO Schedule Best Practices

Uncertainty in Economic Analysis

Project Management Certificate Program

Analytical Finance 1 Seminar Monte-Carlo application for Value-at-Risk on a portfolio of Options, Futures and Equities

Use of the Risk Driver Method in Monte Carlo Simulation of a Project Schedule

Full Monte. Looking at your project through rose-colored glasses? Let s get real.

Kevin Woodrich, FSA, FCA, EA, MAAA Cheiron R. Evan Inglis, FSA, CFA Nuveen NCPERS 2018 Annual Conference & Exhibition May New York, NY

PROJECT MANAGEMENT COURSE 5: PROJECT TIME MANAGEMENT. G.N. Sandhy Widyasthana

GPE engineering project management. Project Management in an Engineering Context

Optimal Search for Parameters in Monte Carlo Simulation for Derivative Pricing

Integrating Contract Risk with Schedule and Cost Estimates

Managing Project Risk DHY

To acquaint yourself with the practical applications of simulation methods.

Cost Risk Assessments Planning for Project or Program Uncertainty with Confidence Brian Bombardier, PE

An Automated Framework for the Integration between EVM and Risk Management

Research on the Impact of Project Network Topology on Project Control

A Comparative Assessment of the PERT vs Monte Carlo simulation for. Schedule Risk Assessment

Planning, Scheduling and Tracking Of Ongoing Bridge Construction Project Using Primavera Software and EVM Technique

Monte Carlo Introduction

Integrated Cost Schedule Risk Analysis Using the Risk Driver Approach

SAMPLE. DETERMINING ACTIVITY DURATIONS TCM Framework: 7.2 Schedule Planning and Development. AACE International Recommended Practice No.

for Major Infrastructure Projects

CHAPTER 9: PROJECT MANAGEMENT

COPYRIGHTED MATERIAL. Index

Risk vs. Uncertainty: What s the difference?

Project Management Chapter 13

KERN COMMUNITY COLLEGE DISTRICT BAKERSFIELD COLLEGE INDA B132 COURSE OUTLINE OF RECORD

6/7/2018. Overview PERT / CPM PERT/CPM. Project Scheduling PERT/CPM PERT/CPM

PMP Exam Preparation Workshop Chapter 7 Project Cost Management

A UNIT BASED CRASHING PERT NETWORK FOR OPTIMIZATION OF SOFTWARE PROJECT COST PRITI SINGH, FLORENTIN SMARANDACHE, DIPTI CHAUHAN, AMIT BHAGHEL

RISK MANAGEMENT LECTURE 5. Ahmed Elyamany

Iowa Public Employees Retirement System Economic Assumptions Review

1 of 14 4/27/2009 7:45 AM

Real Options and Risk Analysis in Capital Budgeting

Economic Scenario Generator and Investment Strategy in a Low Interest Rate World

PERMUTATION AND COMBINATIONS APPROACH TO PROGRAM EVALUATION AND REVIEW TECHNIQUE

ROM SIMULATION Exact Moment Simulation using Random Orthogonal Matrices

Monitoring Accrual and Events in a Time-to-Event Endpoint Trial. BASS November 2, 2015 Jeff Palmer

Simulation. Decision Models

Probabilistic Completion Time in Project Scheduling Min Khee Chin 1, Sie Long Kek 2, Sy Yi Sim 3, Ta Wee Seow 4

Understanding the Principles of Investment Planning Stochastic Modelling/Tactical & Strategic Asset Allocation

Introduction to Monte Carlo

u w 1.5 < 0 These two results imply that the utility function is concave.

Achieve PMP Exam Success Five-Day Course Syllabus

CONTINGENCY. Filed: EB Exhibit D2 Tab 2 Schedule 7 Page 1 of 10

Project Cost Risk Analysis: The Risk Driver Approach Prioritizing Project Risks and Evaluating Risk Responses

Retirement Plan. John and Mary Sample

SENSITIVITY AND RISK ANALYSIS OF THE ECONOMIC EVALUATION OF INVESTMENT PROJECTS CASE STUDY: DEVELOPMENT PLAN IN SUFIAN CEMENT PLANT

Appendix A Decision Support Analysis

CISC 322 Software Architecture

STOCHASTIC COST ESTIMATION AND RISK ANALYSIS IN MANAGING SOFTWARE PROJECTS

Quantitative Risk Analysis with Microsoft Project

CHAPTER 6 CRASHING STOCHASTIC PERT NETWORKS WITH RESOURCE CONSTRAINED PROJECT SCHEDULING PROBLEM

Chapter 2 Uncertainty Analysis and Sampling Techniques

Roll No. :... Invigilator s Signature :.. CS/B.TECH(IT)/SEM-5/M(CS)-511/ OPERATIONS RESEARCH AND OPTIMIZATION TECHNIQUES

Indirect cost associated with project increases linearly with project duration. A typical line for indirect cost is shown in figure above.

Mohammed Rafiuddin CEO and General Manager, BIOSI Biohazards Solutions Innovators

SAMPLE. CPM SCHEDULE RISK MODELING AND ANALYSIS: SPECIAL CONSIDERATIONS TCM Framework: 7.6 Risk Management

Learning Objectives. Manage Your Project Risks Like a Pro! 10/16/2015

Risk analysis in adopting FES-exoskeleton system in rehabilitation programs

An Investigative Study of Risk Management Practices of Major U.S. Contractors

Information Technology Project Management, Sixth Edition

LIFECYCLE INVESTING : DOES IT MAKE SENSE

PROJECT SCENARIOS, BUDGETING & CONTINGENCY PLANNING

Measurement of contingent liabilities

Carlo Simulations. Brian Freeman, PE, PMP, QEP 1 Dec Copyright 2011 IES. 6 th Kuwait ASSE Conference

Transcription:

Poor Man s Approach to Monte Carlo Based on the PMI PMBOK Guide Fourth Edition 20 IPDI has been reviewed and approved as a provider of project management training by the Project Management Institute (PMI). 1 Version 4.1 Monte Carlo Answers the Question: What is the probability of this project being successful? Monte Carlo: Uses project models and simulations that translates the uncertainties specified at a detailed level into their potential impact on objectives that are expressed at the level of the total project Or, put another way: How likely are you to stay out of trouble on your project? 2 Version 4.1 Integrated Process Developers, Inc. Page: 1 For permissions and other rights

Monte Carlo Monte Carlo uses probability distributions based on historical information to predict the probability of potential outcomes The basic steps of the Monte Carlo technique 1. Determine the probability distribution for the variables being considered (duration and work/) 2. For each variable within its specific range, select a value randomly within the probability distribution. 3. Run a deterministic analysis using the combination of values selected for each one of the variables 4. Repeat steps 2 and 3 a statistically significant number of times to obtain the probability distribution of the result 3 Version 4.1 Monte Carlo A Example Based on a Project of 60 days Analysis Indicates 1 Standard Deviation = 10 days Probability of Occurrence 98% 84% 50% 16% 2.27% Project Duration 40 days -2σ 50 days 60 days 70 days 80 days -1σ u +1σ +2σ Adapted from PMBOK Guide Fourth Edition, pg. 300, Fig 11-16 4 Version 4.1 Integrated Process Developers, Inc. Page: 2 For permissions and other rights

Monte Carlo A Example Based on a Project Estimate of $600,000 Analysis Indicates 1 Standard Deviation = $25,000 Probability of Occurrence 98% 84% 50% 16% 2% Project (,000) $550-2σ $575 $600 $625 $650-1σ u +1σ +2σ Adapted from PMBOK Guide Fourth Edition, pg. 300, Fig 11-16 5 Version 4.1 vs. Duration Monte Carlo Analysis Pessimistic (98%) Most Likely (50%) Optimistic (2%) 6 Version 4.1 Integrated Process Developers, Inc. Page: 3 For permissions and other rights

vs. Duration Monte Carlo Analysis -2σ -1σ u +1σ +2σ $650 $625 $600 $575 $550 Project (,000) uncertainty Baseline without Risk Responses (Plan meets Scope Statement & Requirements +2σ Scope Reqmt. Project Plan with Risk Responses ( Contingencies and Buffers Scope Reqmt. +2σ uncertainty Project Duration (days) 40-2σ 50 60 70 80-1σ u +1σ +2σ 7 Version 4.1 vs. Duration Monte Carlo Analysis $650 $625 $600 $575 $550 Scope Reqmt. Project (,000) Scope Reqmt. Project Duration (days) 40 50 60 70 80 8 Version 4.1 Integrated Process Developers, Inc. Page: 4 For permissions and other rights

vs. Duration Monte Carlo Analysis $650 $625 $600 $575 $550 Project (,000) uncertainty Baseline without Risk Responses (Plan meets Scope Statement & Requirements Scope Reqmt. Project Plan with Risk Responses ( Contingencies and Buffers Scope Reqmt. uncertainty Project Duration (days) 40 50 60 70 80 9 Version 4.1 Poor Man s Monte Carlo Analysis B O = 6 M.L. = 10 P = 17 C O = 12 M.L. = 15 P = 20 A O = 3 M.L. = 5 P = 10 E O = 12 M.L. = 15 P = 20 D F G O = 4 M.L. = 10 P = 12 H O = 3 M.L. = 5 P = 9 O = 4 M.L. = 5 P = 8 O = 3 M.L. = 5 P = 12 A - Analytical Design B - Develop Design C - Build Parts D - Assemble Prototypes E - Determine Test Requirements F - Calibrate Test Equipment G - Perform & Analyze Tests H - Update Design 10 Version 4.1 Integrated Process Developers, Inc. Page: 5 For permissions and other rights

Poor Man s Monte Carlo Analysis A O ML P 0 10 20 30 40 50 60 70 80 90 3 5 10 B 6 10 17 C 12 15 20 D 12 15 20 E 4 5 8 F 3 5 12 G 4 10 12 H 3 5 9 11 Version 4.1 Poor Man s Work/ Monte Carlo Analysis A O ML P O ML P 4 hrs 6 hrs 8 hrs $ 400 $ 600 $ 800 B 5 hrs 6 hrs 10 hrs $ 500 $ 600 $ 1,000 C 1 hrs 2 hrs 3 hrs $ 100 $ 200 $ 300 D 3 hrs 4 hrs 8 hrs $ 300 $ 400 $ 800 E 4 hrs 6 hrs 8 hrs $ 400 $ 600 $ 800 F 6 hrs 7 hrs 11 hrs $ 600 $ 700 $ 1,100 G 5 hrs 8 hrs 20 hrs $ 500 $ 800 $ 2,000 H 4 hrs 6 hrs 8 hrs $ 400 $ 600 $ 800 TOTAL: 32 hrs 45 hrs 76 hrs $ 3,200 $ 4,500 $ 7,600 12 Version 4.1 Integrated Process Developers, Inc. Page: 6 For permissions and other rights

vs. Duration Monte Carlo Analysis Project $ 8000 7000 6000 5000 4000 3000 2000 1000 0 Pessimistic Optimistic 0 10 20 30 40 50 60 70 80 88 Duration (days) 13 Version 4.1 Most Likely Poor Man s Monte Carlo Analysis Probability distributions PERT Duration & Analysis Uses a weighted average estimate to calculate duration and estimates Differs from CPM in that it uses the mean instead of the most likely duration Number of Occurrences Most Likely (Used in original CPM calculations) Shorter (50%) Optimistic (Can achieve this dur. 10% of the time) Possible Durations PERT Weighted Average = (Optimistic + 4 X Most Likely + Pessimistic) 6 Beta Distribution Pessimistic (Can achieve this dur. 90% of the time) Longer 14 Version 4.1 Integrated Process Developers, Inc. Page: 7 For permissions and other rights

Poor Man s Monte Carlo Analysis Based on the three sets of project data points All Optimistic All Most Likely All Pessimistic X days Y days Z days $ A $ B $ C Calculate the project Mean and the Standard Deviation PERT Weighted Average (50% point) = (Optimistic + 4 X Most Likely + Pessimistic) 6 PERT Standard Deviation = (Pessimistic Optimistic) 6 15 Version 4.1 Example: 16 Version 4.1 Poor Man s Monte Carlo Analysis All Optimistic All Most Likely All Pessimistic 100 days 130 days 220 days $200,000 $280,000 $440,000 PERT Weighted Average Duration = (100+4*130+220)/6 = 140 days (50% Prob.) PERT Standard Deviation = (220 100)/6 = 20 days PERT Weighted Average = (200+4*280+440)/6 = $293,000 (50% Prob.) PERT Standard Deviation = (440 200)/6 = $40,000 Integrated Process Developers, Inc. Page: 8 For permissions and other rights

Poor Man s Monte Carlo Analysis Example, cont. Wt. Average Std Dev 140 days 20 days $293,000 $40,000 Probability -2 Std Dev -1 Std Dev Wt. Average +1 Std Dev +2 Std Dev 2% 16% 50% 84% 98% 100 days 120 days 140 days 160 days 180 days $213,000 $253,000 $293,000 $333,000 $373,000 17 Version 4.1 Exercise: Risk Game! RISK GAME by Integrated Process Developers, Inc. Ver 4.1 B: E: H: K: N: $ $ $ $ $ A: C: F: I: L: O: $ $ $ $ $ $ End of Project Milestone D: G: J: M: P: $ $ $ $ $ 18 Version 4.1 Integrated Process Developers, Inc. Page: 9 For permissions and other rights

Duration Distribution Number of Rolls 30 25 20 15 10 5 0 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 68 70 72 Duration Distribution 14 12 10 8 6 4 2 0 $10,000 $10,200 $10,400 $10,600 $10,800 $11,000 $11,200 $11,400 $11,600 $11,800 $12,000 $12,200 $12,400 $12,600 $12,800 Number of Rolls $13,000 $13,200 $13,400 $13,600 $13,800 $14,000 $14,200 $14,400 $14,600 $14,800 $15,000 $15,200 $15,400 $15,600 $15,800 $16,000 $16,200 $16,400 $16,600 $16,800 $17,000 $17,200 $17,400 $17,600 $17,800 $18,000 $18,200 $18,400 $18,600 $18,800 $19,000 $19,200 Project 19 Version 4.1 Questions? 20 Version 4.1 Integrated Process Developers, Inc. Page: 10 For permissions and other rights