The aim of this article is to present a proposal of interconnection between models and probabilistic simulations of project as possible ways to determine EAC (Final cost) through Earned Value Analysis. The article proves that the use of the 3 main models of projection (constant index, CPI and SCI) as the basis of a triangular probabilistic distribution that, through Monte Carlo simulation will permit associate and determine the probability according to the accomplishment of budgets and costs of the project.
Earned Value Management involves more that just cost and schedule. Six Business Systems, including EVM, are the basis of credible program performance management.
Here's a suggestion of how to "connect the dots."
The document provides information about cost management processes according to PMBOK 5. It includes definitions and explanations of processes for planning cost management, estimating costs, determining budgets, and controlling costs. Key aspects covered are cost estimation techniques, calculating estimates at completion, variance analysis using earned value management, and establishing cost baselines and performance measurement.
Topic: Project Management, Referece: PMBOK 5, PMI.
Degree: MBA, Syllabus: Alliance University. Date : Jan 2015.
Please note: This was prepared as a teaching aid. Not for commercial purposes. Sharing to spread the knowledge of Project Management. Note : Copyright belongs to respective owners. List of top references used to prepare these slides given.
If you have any questions, comments, improvement suggestions, Email to: niranjanakoodavalli@gmail.com
This document discusses project cost management principles and processes. It explains that IT projects often experience cost overruns and provides examples. The key processes for managing costs are estimating costs, determining budgets, and controlling costs. Estimating involves developing cost approximations, while determining budgets allocates the estimate to work items to establish a baseline. Controlling costs involves monitoring performance against the baseline and approving changes. Earned value management is presented as a technique to integrate scope, time and cost data to track project performance.
Study of Probability Distributions of Cpi and Spi in Earned Value Analysistheijes
Earned Value analysis (EVA) is the most efficient tool used for transitional review of project execution .It is helpful to project managers and management team to value the progress of project work throughout the project life cycle. The Earned Schedule (ES) is used to approximate the time or duration of project/ s for appropriate evaluation of project execution. ES also help to forecast the time required to complete the project. When combined with schedule analysis, ES can enhance the project. EVA provides the controlling tool for better decision making in project management. The paper discuss about the probability distribution of Cost performance Index (CPI) and Schedule performance Index (SPI). Best fitted distribution will help for forecasting project duration effectively. This helps the Project Manager to prevent the over budgeted cost in future. So an attempt is made to find the alternative distribution of CPI and SPI for better decision making. If the project schedule performance shows poor results then manager need to take the corrective action with the help of this tool. Weibull, Gamma and Exponentiated Exponential Distribution functions are used to study the effect of SPI on CPI. For making better decision in project scheduling, Project managers can review the parameters using EVM tool. The tool is useful in all types of civil engineering and software engineering projects.
Economics of project evaluation cpm module2ahsanrabbani
Introduction: The competencies required for developing business cases comprise a range of skills, including those for:
• facilitation and negotiation
• demand management
• risk management
• value management
• economic, social, environmental and budget analyses, and
• strategic planning.
This document discusses risks that can lead to software project delays or failures. It identifies several categories of risk, including risks due to product size, business impact, customers, process maturity, technology, staff size and experience. It also discusses approaches for identifying, assessing, prioritizing and mitigating risks, including building a risk table to estimate probability and impact of each risk. Project managers are advised to take a proactive approach to risk management to avoid reactive crisis management when risks occur.
This document provides an overview of earned value analysis for project management. It defines key earned value terms and discusses how earned value can be used to enhance project performance by providing early awareness of potential issues. The document outlines an agenda for an earned value analysis training, including introducing earned value concepts and metrics, comparing forecasting methods, defining terminology, and providing a calculation example. It emphasizes that successful earned value implementation requires establishing a work breakdown structure, cost and schedule baselines, and processes for tracking progress and costs.
Earned Value Management involves more that just cost and schedule. Six Business Systems, including EVM, are the basis of credible program performance management.
Here's a suggestion of how to "connect the dots."
The document provides information about cost management processes according to PMBOK 5. It includes definitions and explanations of processes for planning cost management, estimating costs, determining budgets, and controlling costs. Key aspects covered are cost estimation techniques, calculating estimates at completion, variance analysis using earned value management, and establishing cost baselines and performance measurement.
Topic: Project Management, Referece: PMBOK 5, PMI.
Degree: MBA, Syllabus: Alliance University. Date : Jan 2015.
Please note: This was prepared as a teaching aid. Not for commercial purposes. Sharing to spread the knowledge of Project Management. Note : Copyright belongs to respective owners. List of top references used to prepare these slides given.
If you have any questions, comments, improvement suggestions, Email to: niranjanakoodavalli@gmail.com
This document discusses project cost management principles and processes. It explains that IT projects often experience cost overruns and provides examples. The key processes for managing costs are estimating costs, determining budgets, and controlling costs. Estimating involves developing cost approximations, while determining budgets allocates the estimate to work items to establish a baseline. Controlling costs involves monitoring performance against the baseline and approving changes. Earned value management is presented as a technique to integrate scope, time and cost data to track project performance.
Study of Probability Distributions of Cpi and Spi in Earned Value Analysistheijes
Earned Value analysis (EVA) is the most efficient tool used for transitional review of project execution .It is helpful to project managers and management team to value the progress of project work throughout the project life cycle. The Earned Schedule (ES) is used to approximate the time or duration of project/ s for appropriate evaluation of project execution. ES also help to forecast the time required to complete the project. When combined with schedule analysis, ES can enhance the project. EVA provides the controlling tool for better decision making in project management. The paper discuss about the probability distribution of Cost performance Index (CPI) and Schedule performance Index (SPI). Best fitted distribution will help for forecasting project duration effectively. This helps the Project Manager to prevent the over budgeted cost in future. So an attempt is made to find the alternative distribution of CPI and SPI for better decision making. If the project schedule performance shows poor results then manager need to take the corrective action with the help of this tool. Weibull, Gamma and Exponentiated Exponential Distribution functions are used to study the effect of SPI on CPI. For making better decision in project scheduling, Project managers can review the parameters using EVM tool. The tool is useful in all types of civil engineering and software engineering projects.
Economics of project evaluation cpm module2ahsanrabbani
Introduction: The competencies required for developing business cases comprise a range of skills, including those for:
• facilitation and negotiation
• demand management
• risk management
• value management
• economic, social, environmental and budget analyses, and
• strategic planning.
This document discusses risks that can lead to software project delays or failures. It identifies several categories of risk, including risks due to product size, business impact, customers, process maturity, technology, staff size and experience. It also discusses approaches for identifying, assessing, prioritizing and mitigating risks, including building a risk table to estimate probability and impact of each risk. Project managers are advised to take a proactive approach to risk management to avoid reactive crisis management when risks occur.
This document provides an overview of earned value analysis for project management. It defines key earned value terms and discusses how earned value can be used to enhance project performance by providing early awareness of potential issues. The document outlines an agenda for an earned value analysis training, including introducing earned value concepts and metrics, comparing forecasting methods, defining terminology, and providing a calculation example. It emphasizes that successful earned value implementation requires establishing a work breakdown structure, cost and schedule baselines, and processes for tracking progress and costs.
project control using earned value analysis - Part 01 waleed hamdy
Project control using earned value analysis - Part 01
Mission of the projects control division
Why the earned value management?
Establishment of the Performance Measurement Baseline
EVM Analysis & Forecasting
This document discusses best practices for construction cost estimating and project management. It emphasizes the importance of collaboration among all stakeholders in developing detailed, line-item cost estimates. It also outlines various types of cost estimates, cost categories, and techniques for ongoing cost control such as earned value management. Key principles include transparency, independent cost research, and updating estimates over time based on changes to requirements or conditions.
Earned Value Management (EVM) is a technique
that forecasts the project giving an early warning of cost &
schedule. It not onely measures the project performance but also
measure the progress of the schedule. It is an effective tool to
measure cost, schedule & performance of the project. The EVA is
useful in various fields such as IT, Industries and Construction
companies etc.
The value of Earned Value Analysis (EVA) is dependent on
two key areas i.e. Precise Cost information and pragmatic
progress of project. If these two key areas are efficient then
benefit of the project will definitely get valued. This paper
summarizes the evolution, basic terminologies of Earned value
Analysis and effective use of it in the construction industries by
MS Project. There are many ways to implement EVA in the
construction project. MS Project is a tool to determine the EV
and its parameters in an efficient way with accuracy and within
time constraints.
This document provides an overview of earned value management (EVM) concepts in 5 easy pieces:
1. Define planned value using a credible schedule
2. Measure physical percent complete for work periods
3. Calculate earned value as planned value multiplied by percent complete
4. Use earned value variables to calculate performance indices
5. Take corrective actions based on performance index analyses
Production Planning and control: Forecasting techniques – causal and time series models, moving average,
exponential smoothing, trend and seasonality; aggregate production planning; master production scheduling; materials
requirement planning (MRP) and MRP‐II; routing, scheduling and priority dispatching, concept of JIT manufacturing
System.
Project Management: Project network analysis, CPM, PERT and Project crashing.
This document provides an introduction to project management techniques PERT and CPM. It defines key concepts like activities, events, nodes, dummy activities and paths in a network diagram. It explains the stages of project management including planning, appraisal, implementation and review/control. The document outlines the steps to determine critical path in CPM and describes crashing a project to reduce duration. It compares PERT and CPM, noting PERT uses 3 time estimates and is probabilistic while CPM uses one estimate and focuses on tradeoffs between time and cost.
Introduction
CPM/PERT or Network Analysis as the technique is sometimes called, developed along two parallel streams, one industrial and the other military.
CPM (Critical Path Method) was the discovery of M.R.Walker of E.I.Du Pont de Nemours & Co. and J.E.Kelly of Remington Rand, circa 1957. The computation was designed for the UNIVAC-I computer. The first test was made in 1958, when CPM was applied to the construction of a new chemical plant. In March 1959, the method was applied to maintenance shut-down at the Du Pont works in Louisville, Kentucky. Unproductive time was reduced from 125 to 93 hours.
PERT (Project Evaluation and Review Technique) was devised in 1958 for the POLARIS missile program by the Program Evaluation Branch of the Special Projects office of the U.S.Navy, helped by the Lockheed Missile Systems division and the Consultant firm of Booz-Allen & Hamilton. The calculations were so arranged so that they could be carried out on the IBM Naval Ordinance Research Computer (NORC) at Dahlgren, Virginia.
There are four duration types in Primavera P6 that control how duration, resource units, and resource units/time are synchronized for activities:
1) Fixed Units/Time: Units/time remains fixed while duration or units may change
2) Fixed Duration and Units/Time: Duration and units/time remain fixed while units may change
3) Fixed Units: Units remain fixed while duration or units/time may change
4) Fixed Duration and Units: Duration and units remain fixed while units/time may change
The duration type balances the equation of Duration x Units/Time = Units and determines which variable(s) change when another is modified. The appropriate duration type depends on whether the project priorities are
The document outlines procedures for creating, maintaining, and distributing integrated project schedules for engineering, procurement, shipping, and construction activities. It assigns responsibilities to various roles including the Director, Manager of Planning and Controls, Manager of FEMC, Construction Coordinator, Manager of Engineering, Project Engineer, Scheduler, and Assistant Manager of Materials. Key responsibilities include developing master and sub-schedules, ensuring accuracy and logic, monitoring deviations, and providing schedule and performance updates.
Project monitoring and control involves collecting data on project performance and using it to control the project and ensure it stays on track. Key aspects of monitoring include what to monitor (inputs, outputs, time, costs, quality), when to monitor (regularly and at milestones), and how (meetings, reports, Earned Value Analysis). Earned Value Analysis compares the budgeted cost of work performed, actual cost of work performed, and budgeted cost of work scheduled to calculate cost and schedule variances, helping project managers identify issues. Other techniques for monitoring and control include critical ratios and re-planning as needed to correct deviations from the project plan.
A gentle introduction to earned value management systems (neutral)Glen Alleman
Earned value management systems (EVMS) provide a framework for project managers to track schedule and budget performance. Key elements of EVMS include defining the scope of work, establishing a time-phased budget baseline, and periodically calculating metrics like cost and schedule variance to forecast project outcomes. While full ANSI/EIA-748 compliance requires addressing 32 criteria, a simpler approach focuses on 10 criteria like identifying tasks, establishing budgets and schedules, and recording costs to generate regular performance metrics. EVMS gives project managers visibility into whether work is on track and whether budgets need adjustment.
Educaterer India is an unique combination of passion driven into a hobby which makes an awesome profession. We carve the lives of enthusiastic candidates to a perfect professional who can impress upon the mindsets of the industry, while following the established traditions, can dare to set new standards to follow. We don't want you to be the part of the crowd, rather we like to make you the reason of the crowd.
Today's Effort For A Better Tomorrow
This document provides an overview of a quantitative study examining the contribution of Earned Value Management (EVM) to project success on external projects under contract. The study tested hypotheses about the relationship between EVM principles and project success, and whether that relationship differs for fixed-price versus cost-plus contracts. Key findings included that EVM principles positively predict project success, and that fixed-price contracts may benefit more from EVM than cost-plus contracts. The study contributes to understanding how EVM can improve project planning and control for different contract types.
PLANNING AND SCHEDULING DONE BY A CIVIL ENGINEERSHafiz JUNAID
The document discusses planning and scheduling techniques used in construction projects. It describes network scheduling as a method to schedule project activities by connecting them in a logical sequence using network diagrams. The document outlines critical path method (CPM) and program evaluation and review technique (PERT) as the two main network scheduling techniques, along with Monte Carlo simulation. It provides steps to construct arrow diagrams and node diagrams for network schedules and defines key terms used in scheduling like activities, events, dummies, and logic relationships.
Earned Schedule (ES) is a method for analyzing schedule performance using Earned Value Management (EVM) data. It allows calculation of time-based performance indicators like Schedule Variance and Schedule Performance Index. The document discusses applying ES below the project level, such as to work packages and critical paths. It explains that to do so, the tasks being analyzed must be grouped and have their own performance measurement baseline created, so they can be treated as a project and have ES calculated. An example is provided analyzing the critical path tasks of a sample project. This allows schedule performance to be evaluated at different levels within a project using ES.
The document provides an overview of earned value analysis (EVA) training. It defines EVA as a project management technique for monitoring cost and schedule performance by comparing actual and budgeted resources. The training will cover what EVA is, why it is used, how EVA metrics like cost variance, schedule variance and estimate at completion are calculated, and examples of how EVA is applied. Attendees will learn how EVA can identify if a project is over budget or ahead of schedule so corrective actions can be taken.
Construction Project Schedule Template- Residential BuildingSHAZEBALIKHAN1
The excel template is a ready-to-use project schedule for a residential building construction project. The article gives the basic idea of a project schedule for residential building construction. Download the excel file through the hyperlink in the article.
The document discusses the Program Evaluation and Review Technique (PERT) which is a management tool used to define and integrate project events. PERT uses optimistic, pessimistic, and most likely time estimates to calculate the expected time for tasks. It is event-oriented and models the logical order and dependencies of activities. Variance and standard deviation are also calculated to measure uncertainty. An example project is provided showing how to determine activity times, critical paths, and the probability of meeting a deadline.
Monte carlo presentation for analysis of business growthAsif Anik
This document discusses using Monte Carlo simulation and the Brownian walk approach to forecast time series data. It describes generating random numbers as inputs to iteratively evaluate a deterministic model. This allows producing a range of probable outcomes to assist with decision making. The document outlines experiments applying this method to both raw and regression modes of forecasting productivity, installation rates, and other trends. It interprets the results as probabilities and weighted averages to understand the likelihood of different forecast scenarios. Real-life applications include asset distribution forecasting, materials forecasting, and predicting growth over time.
Fundamentals of Statistical Signal Processing - Estimation Theory (Volume I)CHIH-PEI WEN
The document discusses the history and evolution of the automobile industry over the past 100 years. It describes how cars started out as luxury items for the wealthy but became affordable for the masses with the advent of assembly line production. Today's automobile industry is a huge global business that continues advancing automotive technology while facing new challenges around urbanization and environmental sustainability.
RELABILITY OF IMPLEMENTING PRIMAVERA P6 IN FAST-TRACK PLANNING OF RESIDENTIAL...IAEME Publication
Objectives: To understanding the process of project planning in primavera p6 by using project calendar and develop the schedules. To control resources ex: - labour, non-labour, machines etc. Methodology: Site visits of ongoing projects and understanding the various tasks, plans and scheduling models, collection of project data, venture Planning and Scheduling by using Primavera P6, interpretation and tabulation of Results, conclusion. Findings: Analysis of results in primavera p6 observed that resources should be controlled are arranged to other activities of same project or another project of same enterprise. Controlled the budgeted units to control the project cost. Reliability of implementing primavera p6 it is more advantageous on ongoing parallel projects and it shows the results accurately. From the analysis observed that project time is over run due to following conventional method. Applications: This software is mainly used for getting more accurate and reliable results occurring in planning and scheduling, resource planning labour, non-labour, material etc, mainly in coding tenders, to start multiple projects at same time, requirement of cash flows, labour, non-labour, and material for every month to start the project.
project control using earned value analysis - Part 01 waleed hamdy
Project control using earned value analysis - Part 01
Mission of the projects control division
Why the earned value management?
Establishment of the Performance Measurement Baseline
EVM Analysis & Forecasting
This document discusses best practices for construction cost estimating and project management. It emphasizes the importance of collaboration among all stakeholders in developing detailed, line-item cost estimates. It also outlines various types of cost estimates, cost categories, and techniques for ongoing cost control such as earned value management. Key principles include transparency, independent cost research, and updating estimates over time based on changes to requirements or conditions.
Earned Value Management (EVM) is a technique
that forecasts the project giving an early warning of cost &
schedule. It not onely measures the project performance but also
measure the progress of the schedule. It is an effective tool to
measure cost, schedule & performance of the project. The EVA is
useful in various fields such as IT, Industries and Construction
companies etc.
The value of Earned Value Analysis (EVA) is dependent on
two key areas i.e. Precise Cost information and pragmatic
progress of project. If these two key areas are efficient then
benefit of the project will definitely get valued. This paper
summarizes the evolution, basic terminologies of Earned value
Analysis and effective use of it in the construction industries by
MS Project. There are many ways to implement EVA in the
construction project. MS Project is a tool to determine the EV
and its parameters in an efficient way with accuracy and within
time constraints.
This document provides an overview of earned value management (EVM) concepts in 5 easy pieces:
1. Define planned value using a credible schedule
2. Measure physical percent complete for work periods
3. Calculate earned value as planned value multiplied by percent complete
4. Use earned value variables to calculate performance indices
5. Take corrective actions based on performance index analyses
Production Planning and control: Forecasting techniques – causal and time series models, moving average,
exponential smoothing, trend and seasonality; aggregate production planning; master production scheduling; materials
requirement planning (MRP) and MRP‐II; routing, scheduling and priority dispatching, concept of JIT manufacturing
System.
Project Management: Project network analysis, CPM, PERT and Project crashing.
This document provides an introduction to project management techniques PERT and CPM. It defines key concepts like activities, events, nodes, dummy activities and paths in a network diagram. It explains the stages of project management including planning, appraisal, implementation and review/control. The document outlines the steps to determine critical path in CPM and describes crashing a project to reduce duration. It compares PERT and CPM, noting PERT uses 3 time estimates and is probabilistic while CPM uses one estimate and focuses on tradeoffs between time and cost.
Introduction
CPM/PERT or Network Analysis as the technique is sometimes called, developed along two parallel streams, one industrial and the other military.
CPM (Critical Path Method) was the discovery of M.R.Walker of E.I.Du Pont de Nemours & Co. and J.E.Kelly of Remington Rand, circa 1957. The computation was designed for the UNIVAC-I computer. The first test was made in 1958, when CPM was applied to the construction of a new chemical plant. In March 1959, the method was applied to maintenance shut-down at the Du Pont works in Louisville, Kentucky. Unproductive time was reduced from 125 to 93 hours.
PERT (Project Evaluation and Review Technique) was devised in 1958 for the POLARIS missile program by the Program Evaluation Branch of the Special Projects office of the U.S.Navy, helped by the Lockheed Missile Systems division and the Consultant firm of Booz-Allen & Hamilton. The calculations were so arranged so that they could be carried out on the IBM Naval Ordinance Research Computer (NORC) at Dahlgren, Virginia.
There are four duration types in Primavera P6 that control how duration, resource units, and resource units/time are synchronized for activities:
1) Fixed Units/Time: Units/time remains fixed while duration or units may change
2) Fixed Duration and Units/Time: Duration and units/time remain fixed while units may change
3) Fixed Units: Units remain fixed while duration or units/time may change
4) Fixed Duration and Units: Duration and units remain fixed while units/time may change
The duration type balances the equation of Duration x Units/Time = Units and determines which variable(s) change when another is modified. The appropriate duration type depends on whether the project priorities are
The document outlines procedures for creating, maintaining, and distributing integrated project schedules for engineering, procurement, shipping, and construction activities. It assigns responsibilities to various roles including the Director, Manager of Planning and Controls, Manager of FEMC, Construction Coordinator, Manager of Engineering, Project Engineer, Scheduler, and Assistant Manager of Materials. Key responsibilities include developing master and sub-schedules, ensuring accuracy and logic, monitoring deviations, and providing schedule and performance updates.
Project monitoring and control involves collecting data on project performance and using it to control the project and ensure it stays on track. Key aspects of monitoring include what to monitor (inputs, outputs, time, costs, quality), when to monitor (regularly and at milestones), and how (meetings, reports, Earned Value Analysis). Earned Value Analysis compares the budgeted cost of work performed, actual cost of work performed, and budgeted cost of work scheduled to calculate cost and schedule variances, helping project managers identify issues. Other techniques for monitoring and control include critical ratios and re-planning as needed to correct deviations from the project plan.
A gentle introduction to earned value management systems (neutral)Glen Alleman
Earned value management systems (EVMS) provide a framework for project managers to track schedule and budget performance. Key elements of EVMS include defining the scope of work, establishing a time-phased budget baseline, and periodically calculating metrics like cost and schedule variance to forecast project outcomes. While full ANSI/EIA-748 compliance requires addressing 32 criteria, a simpler approach focuses on 10 criteria like identifying tasks, establishing budgets and schedules, and recording costs to generate regular performance metrics. EVMS gives project managers visibility into whether work is on track and whether budgets need adjustment.
Educaterer India is an unique combination of passion driven into a hobby which makes an awesome profession. We carve the lives of enthusiastic candidates to a perfect professional who can impress upon the mindsets of the industry, while following the established traditions, can dare to set new standards to follow. We don't want you to be the part of the crowd, rather we like to make you the reason of the crowd.
Today's Effort For A Better Tomorrow
This document provides an overview of a quantitative study examining the contribution of Earned Value Management (EVM) to project success on external projects under contract. The study tested hypotheses about the relationship between EVM principles and project success, and whether that relationship differs for fixed-price versus cost-plus contracts. Key findings included that EVM principles positively predict project success, and that fixed-price contracts may benefit more from EVM than cost-plus contracts. The study contributes to understanding how EVM can improve project planning and control for different contract types.
PLANNING AND SCHEDULING DONE BY A CIVIL ENGINEERSHafiz JUNAID
The document discusses planning and scheduling techniques used in construction projects. It describes network scheduling as a method to schedule project activities by connecting them in a logical sequence using network diagrams. The document outlines critical path method (CPM) and program evaluation and review technique (PERT) as the two main network scheduling techniques, along with Monte Carlo simulation. It provides steps to construct arrow diagrams and node diagrams for network schedules and defines key terms used in scheduling like activities, events, dummies, and logic relationships.
Earned Schedule (ES) is a method for analyzing schedule performance using Earned Value Management (EVM) data. It allows calculation of time-based performance indicators like Schedule Variance and Schedule Performance Index. The document discusses applying ES below the project level, such as to work packages and critical paths. It explains that to do so, the tasks being analyzed must be grouped and have their own performance measurement baseline created, so they can be treated as a project and have ES calculated. An example is provided analyzing the critical path tasks of a sample project. This allows schedule performance to be evaluated at different levels within a project using ES.
The document provides an overview of earned value analysis (EVA) training. It defines EVA as a project management technique for monitoring cost and schedule performance by comparing actual and budgeted resources. The training will cover what EVA is, why it is used, how EVA metrics like cost variance, schedule variance and estimate at completion are calculated, and examples of how EVA is applied. Attendees will learn how EVA can identify if a project is over budget or ahead of schedule so corrective actions can be taken.
Construction Project Schedule Template- Residential BuildingSHAZEBALIKHAN1
The excel template is a ready-to-use project schedule for a residential building construction project. The article gives the basic idea of a project schedule for residential building construction. Download the excel file through the hyperlink in the article.
The document discusses the Program Evaluation and Review Technique (PERT) which is a management tool used to define and integrate project events. PERT uses optimistic, pessimistic, and most likely time estimates to calculate the expected time for tasks. It is event-oriented and models the logical order and dependencies of activities. Variance and standard deviation are also calculated to measure uncertainty. An example project is provided showing how to determine activity times, critical paths, and the probability of meeting a deadline.
Monte carlo presentation for analysis of business growthAsif Anik
This document discusses using Monte Carlo simulation and the Brownian walk approach to forecast time series data. It describes generating random numbers as inputs to iteratively evaluate a deterministic model. This allows producing a range of probable outcomes to assist with decision making. The document outlines experiments applying this method to both raw and regression modes of forecasting productivity, installation rates, and other trends. It interprets the results as probabilities and weighted averages to understand the likelihood of different forecast scenarios. Real-life applications include asset distribution forecasting, materials forecasting, and predicting growth over time.
Fundamentals of Statistical Signal Processing - Estimation Theory (Volume I)CHIH-PEI WEN
The document discusses the history and evolution of the automobile industry over the past 100 years. It describes how cars started out as luxury items for the wealthy but became affordable for the masses with the advent of assembly line production. Today's automobile industry is a huge global business that continues advancing automotive technology while facing new challenges around urbanization and environmental sustainability.
RELABILITY OF IMPLEMENTING PRIMAVERA P6 IN FAST-TRACK PLANNING OF RESIDENTIAL...IAEME Publication
Objectives: To understanding the process of project planning in primavera p6 by using project calendar and develop the schedules. To control resources ex: - labour, non-labour, machines etc. Methodology: Site visits of ongoing projects and understanding the various tasks, plans and scheduling models, collection of project data, venture Planning and Scheduling by using Primavera P6, interpretation and tabulation of Results, conclusion. Findings: Analysis of results in primavera p6 observed that resources should be controlled are arranged to other activities of same project or another project of same enterprise. Controlled the budgeted units to control the project cost. Reliability of implementing primavera p6 it is more advantageous on ongoing parallel projects and it shows the results accurately. From the analysis observed that project time is over run due to following conventional method. Applications: This software is mainly used for getting more accurate and reliable results occurring in planning and scheduling, resource planning labour, non-labour, material etc, mainly in coding tenders, to start multiple projects at same time, requirement of cash flows, labour, non-labour, and material for every month to start the project.
Basics of probability in statistical simulation and stochastic programmingSSA KPI
AACIMP 2010 Summer School lecture by Leonidas Sakalauskas. "Applied Mathematics" stream. "Stochastic Programming and Applications" course. Part 2.
More info at http://summerschool.ssa.org.ua
The document describes a simulation project for a communication link using AM and PSK modulation. Students are asked to design and simulate a communication link using AM modulation to transmit an audio signal, investigating the effects of different message signal frequencies and modulation indices. They also simulate communication links using BPSK and QPSK modulation schemes, comparing the performance of each in terms of bandwidth efficiency and required signal power. The project uses Matlab and Simulink to generate signals, design modulators and demodulators, and simulate the overall communication links.
Planning, organizing, securing and managing resources to bring about the successful completion of specific project goals and objectives.
Contact:
Synergy school of business skills
No 25 Yellow Pages 5th Floor, Opposite Kotaka Mahindra Bank, Dr Radhakrishnan Salai, Mylapore, Chennai - 600004
Ph.No: 044-65655700 / +91 8144643424
Probability and random processes project based learning template.pdfVedant Srivastava
To understand the concept of Monte –Carlo Method and its various applications and it rely on repeated and random sampling to obtain numerical result.
Developing the computational algorithms to solve the problem related to random sampling.
Objective also contains simulation of specific problem in Matlab Software.
This document discusses probability distributions and provides an overview of the types of distributions and functions supported in the Statistics and Machine Learning Toolbox. It describes probability distributions as identifying the probability of values a random variable can take. It lists several common distributions like the binomial, normal, and lognormal distributions. It then summarizes the different types of functions available for parametric estimation, nonparametric estimation, inverse cumulative distribution functions, distribution statistics, distribution fitting, negative log-likelihood, and random number generation.
Monte Carlo simulation is well-suited for GPU acceleration due to its highly parallel nature. GPUs provide lower cost and higher performance than CPUs for Monte Carlo applications. Numerical libraries for GPUs allow developers to focus on their models rather than reimplementing basic components. NAG has developed GPU libraries including random number generators and is working with financial institutions to apply Monte Carlo simulations to problems in finance.
Monte carlo simulation for energy risk managementScott Nelson
Monte Carlo simulation is used for energy risk management in deregulated power markets. It allows modeling of uncertain risk drivers like weather, loads, and prices in a realistic way that accounts for correlations and maintains distributions. The key steps are model specification, estimation, simulation, calibration, and decision optimization. Simulation results can value portfolios, determine optimal hedging levels, assess risk, and identify profit-maximizing trades under uncertainty.
Practical signal processing using matlabYogesh Angal
Here are the key steps to estimate the Doppler frequency from radar returns to determine vehicle speed:
1. Demodulate the received radar signal to baseband to extract the complex envelope. This will produce a signal of the form s[n] = (A/2)exp(j2πFDnΔ + φ), where FD is the Doppler frequency related to vehicle speed.
2. Sample the complex envelope at a rate Fs higher than twice the maximum expected Doppler frequency to avoid aliasing.
3. Estimate the Doppler frequency FD from the sampled complex envelope using techniques like periodogram or autoregressive spectral estimation. The Doppler estimate allows calculating the vehicle speed as v = cFD/2F0.
4.
This document discusses using Monte Carlo simulation to price European call options. It begins by noting the uncertainty in underlying asset prices makes option pricing difficult. It then outlines the Monte Carlo simulation procedure of generating random price paths, calculating payoffs, and averaging. Key assumptions are presented for the stock price model and payoff calculation. Simulation results are shown for different numbers of simulations and compared to the Black-Scholes model, with error decreasing as the number of simulations increases.
This document provides an overview of the Candy Construction Estimating and Valuations user interface and navigation. It describes the main sections of the user interface including the title bar, application tabs, menus and toolbars. It also explains how to navigate between documents and use various keyboard shortcuts and right-click menu functions. The document concludes with information on customizing system fonts, colors, toolbars and configuring folder paths.
This document provides an overview of the topics covered in the Course 102 training materials for Primavera P6. The topics include an introduction to Primavera and P6, the project management life cycle, navigating and customizing layouts in P6, creating and managing projects, scheduling activities and resources, and reporting and controlling projects. The document outlines the objectives and content covered in each lesson.
The document provides an introduction to Primavera, a project planning and scheduling software. It defines key concepts such as activities, relationships, floats, critical paths, and resources. It also describes the basic terminology used in Primavera including activity types, calendars, constraints, cost tracking, and work breakdown structures. The document aims to familiarize users with the basic features and terminology of Primavera to help plan, schedule and monitor projects.
This document provides an introduction to Monte Carlo simulations in finance. It discusses how Monte Carlo methods can be used to value financial derivatives by simulating asset price paths over time based on stochastic processes, and taking the average of the resulting payoffs. It also describes how Monte Carlo integration can be applied to problems involving the numerical evaluation of multi-dimensional integrals. The document outlines the basic concepts and provides examples of applying Monte Carlo techniques to price European options and estimate the value of pi.
Monte Carlo simulation is a technique that uses random numbers and random variates to solve stochastic or deterministic problems that do not involve the passage of time. It is used to evaluate integrals of functions that cannot be directly integrated. The method involves defining a random variable equal to the function multiplied by the interval length and taking the sample mean of this random variable from running multiple simulations, which converges to the true expected value and integral.
This document discusses Monte Carlo simulation techniques for low power VLSI circuit design. It explains that Monte Carlo simulation involves running simulations with different input vectors multiple times to estimate power consumption statistics. It describes how the mean and variance of power consumption values are calculated from multiple samples and how the central limit theorem can be applied. It presents an equation to determine the minimum number of samples needed to estimate the mean power within a given error tolerance with a certain confidence level.
This document discusses planning and scheduling a residential construction project using Primavera software. The main goals of the project are to study the basics of Primavera, select a residential building plan, estimate quantities, schedule activities, create a work breakdown structure, budget the project, and generate reports. Primavera is a project management tool that uses critical path methodology to calculate activity durations and floats. It has Gantt chart views to display the project schedule. The document defines key terms like project, activity, resource, and time and cost parameters that can be measured using planning software. It also describes the project life cycle and monitoring process to ensure the project stays on schedule and budget.
This document provides an introduction to the graphical user interface (GUI) of Primavera P6 v8.2. It outlines the pre-requisites, including installing Primavera P6 v8.2 Client, Primavera web, Primavera Team Member, and Primavera Progress reporter. The agenda covers an overview of the P6 v8.2 client interface elements like the menu bar, tool bar, display area, top layout, and bottom layout. It also covers the main tabs in Primavera web like administer, dashboard, portfolio, project, and resources. The document concludes with allocating 10 minutes for practice with the GUI.
Earned value analysis (EVA) is a project management technique for measuring project performance and progress. It objectively compares the planned cost and schedule of a project to its actual cost and progress by integrating measurements of scope, schedule and cost. EVA allows project managers to forecast a project's final cost, completion date and variances in a timely manner to identify risks and take corrective actions if needed. Project managers use EVA by setting a performance measurement baseline, measuring actual work progress and costs, and calculating variances to analyze schedule and cost performance.
The document discusses key aspects of project cost management including cost estimating, budgeting, and control. It defines important terms like cost baseline, contingency reserve, estimate at completion (EAC), and performance indices. Formulas are provided for calculating things like cost variance, schedule variance, cost performance index, and estimate to completion. The cost management plan is highlighted as establishing guidelines for precision, units of measure, control thresholds, and reporting formats for cost activities.
This document discusses project cost management and control. It describes cost estimating, cost budgeting, and cost control as the three factors of project cost management. It defines key terms like planned value, earned value, and actual cost used in earned value management. Earned value management compares planned work to actual work completed and actual costs to measure cost and schedule performance. The document also discusses tools for cost control like estimate to complete, forecasting, cost variance, and cost performance index.
This document discusses project cost management. It explains that cost management includes planning, estimating, budgeting, and controlling costs to complete a project within the approved budget. Estimating involves developing cost estimates for project resources. Budgeting aggregates these estimates to establish a cost baseline. Controlling costs involves managing the baseline and variances using tools like earned value management. A surveyor plays a key role by supporting cost planning, estimating, monitoring budgets, and other cost control activities. Effective cost control is important for project success and company profitability.
Earned value analysis is a technique for measuring project performance and progress. It involves establishing a performance measurement baseline at the start of the project. Actual costs and schedule progress are measured against the baseline to calculate cost and schedule variances. These variances help identify issues early and estimate future project costs and completion dates. For example, an analysis of a robot production project found it was over budget by $150,000 and behind schedule by 25% after completing 3 of 4 planned robots. The estimated total cost was $600,000 if performance did not improve.
The document provides a cost management plan for the construction of a scrap tire recycling plant. It outlines the project's cost management approach, how costs will be measured using earned value management, the reporting format, cost variance response process, and cost change control process. It also includes the overall budget of $5 million for the project which is broken down into categories such as land procurement, architectural development, construction, project closeout, construction administration, and contingency surplus. The total projected cost is $4.98 million.
Basic Concepts of Earned Value Management.pdfElyes ELEBRI
Earned value management (EVM) combines measurements of project scope, schedule and costs. It provides accurate forecasts of performance problems and improvements in planning and controls. Successful EVM requires a good project plan, defined work values, and performance indicators. The 32 EVM guidelines established by ANSI are divided into organization, planning/budgeting, accounting, analysis/reporting, and revisions/maintenance. EVM introduces terms like earned value, variance, and indices to integrate technical, schedule and cost performance.
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1. Schedule and effort/cost variance which measure performance against baselines using earned value management.
2. Productivity and resource utilization which measure how efficiently resources are being used.
3. Change requests which should be tracked to monitor scope creep.
4. Quality and customer satisfaction metrics like defect density and resolution rates.
5. Gross margin which tracks overall project profitability.
Quality management tools like check sheets, control charts, Pareto charts, and scatter plots are also briefly introduced. The document emphasizes the importance of defining appropriate metrics and using metrics to drive continuous improvement.
The document discusses three key processes for managing project costs: cost estimating, cost budgeting, and cost control. It provides details on cost estimation methods like analogous estimating. Cost budgeting involves creating a cost baseline budget. Cost control tools like earned value management measure how well a project is adhering to the baseline budget through metrics like cost and schedule variance.
The document discusses three key processes for managing project costs: cost estimating, cost budgeting, and cost control. It provides details on cost estimation methods like analogous estimating and three-point estimating. Cost budgeting involves setting a cost baseline budget. Cost control tools like earned value management measure planned vs. actual costs and schedules to identify variances enabling corrective actions. Earned value charts and calculations like CPI and SPI are used to forecast final costs and identify if projects will finish over or under budget.
Project monitoring refers to tracking project metrics like team performance, task duration, and identifying potential problems to ensure a project is on schedule, budget, and scope. It clarifies objectives, links activities to objectives, reports progress to management, and alerts managers to issues. Project monitoring assesses results, improves planning, promotes learning, ensures accountability, and answers questions about task progress, unforeseen consequences, team performance, needed changes, and impact on results. Earned value analysis is a monitoring tool that compares planned, actual, and earned values to measure progress and performance through metrics like schedule and cost variances, and indexes. Regular reporting keeps stakeholders informed of project status.
This document outlines a training program on project performance tracking, analysis, and reporting presented by Supreme Management Consultants. The two-day program will cover key topics such as performance indicators, developing and analyzing project objectives, benchmarking, measuring and monitoring performance, reporting, research methods, baselines, and information management systems. Fundamental concepts like defining projects, performance management, the project management triple constraint, life cycle, and performance cycle will also be discussed. Techniques like earned value management, control charts, and post-project evaluation will be examined.
Cost management involves planning, estimating, budgeting, and controlling costs to complete a project within budget. Common cost estimating techniques include analogous, parametric, and bottom-up estimating. Earned value management is used to measure project performance by comparing planned, earned, and actual costs and schedules.
This document discusses project monitoring and control. It defines monitoring as tracking key parameters like cost, schedule and risks throughout the project duration. Control is defined as comparing actual performance to the baseline plan and taking corrective actions. The document outlines the project control process and tools used like tracking Gantt charts and control charts. It also discusses topics like baselines, earned value analysis, updating estimates and using software like MS Project for project execution and control.
This document provides an overview of project cost management for an IT project management course. It defines key cost management terms and processes including cost estimation, budgeting, and controlling costs. It discusses tools for cost estimation like analogous estimates, bottom-up estimates, and parametric modeling. It also explains earned value management (EVM) as a tool for cost control, defining terms like planned value, earned value, actual cost, and calculating values like cost performance index (CPI) and estimate at completion (EAC).
Abstract— Execution of engineering projects are tracked against critical metrics such as safety, quality,
delivery cost and inventory. Earned value is a key parameter that helps in assessing delivery (schedule) and cost.
Static shows that 70% of projects are over budget behind schedule, 52% of all projects finish at 189% of their
initial budget and some, after huge investments of time and money, are simply never completed. The rest of this
paper gives a perspective on monitoring project health by Earned value analysis.
The Project Management Process - Week 9 Performance ManagementCraig Brown
The document discusses project performance management and monitoring. It describes establishing a project baseline and monitoring system to track performance against the baseline over time. Key aspects covered include defining data collection, analysis and reporting processes, using tools like Gantt charts and control charts to monitor schedule and cost performance, and integrating scope, time and cost using earned value management.
The processes from the PMBOK® Guide — Sixth Edition are separated into colors according to their respective knowledge areas. Only the main connections are shown in this process flow.
See related content at https://ricardo-vargas.com/pmbok6-processes-flow/
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Nesta versão simplificada do fluxo, as entradas, ferramentas e técnicas e saídas não estão listadas.
Veja conteúdo relacionado em https://ricardo-vargas.com/pt/pmbok6-processes-flow/
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O documento descreve a ferramenta MTA (Milestones Trend Analysis), que analisa a evolução dos marcos de um projeto através de um gráfico. O MTA representa os marcos por cores ou símbolos e analisa padrões como linhas normais, crescentes, com mudança de tendência, divergentes, decrescentes ou em zig zag para identificar desvios no cronograma. O documento também menciona um programa para aplicar o MTA e finaliza promovendo outros conteúdos sobre gerenciamento de projetos do autor.
Brief introduction to the milestones trend analysis tool.
Listen to the related podcast: http://www.ricardo-vargas.com/podcasts/understading-the-milestone-trend-analysis-mta-part-1-of-2
Le flux de processus répresenté est basé sur les figures du Guide PMBOK. Seules les liaisons présentées dans les figures cités sont répresentées dans ce flux.
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Earned Value Probabilistic Forecasting Using Monte Carlo Simulation
1. EARNED VALUE
PROBABILISTIC
FORECASTING USING
MONTE CARLO
SIMULATION
Accepted for publication at
AACE - Association for Advancement of Cost Engineering 48th Annual Meeting
Washington – DC – USA – 2004
Revista Brasileira de Gerenciamento de Projetos
Curitiba – PR – Brazil – 2004
2. 2 Earned Value Probabilistic Forecasting using Monte Carlo Simulation
Abstract
The aim of this article is to present a proposal of interconnection between mod-els
and probabilistic simulations of project as possible ways to determine EAC
(Final cost) through Earned Value Analysis. The article proves that the use of the
3 main models of projection (constant index, CPI and SCI) as the basis of a trian-gular
probabilistic distribution that, through Monte Carlo simulation will permit
associate and determine the probability according to the accomplishment of
budgets and costs of the project.
Related Podcasts
♫♫Earned Value Project Man-agement
http://rvarg.as/bk
♫♫Monte Carlo Simulation
http://rvarg.as/bi
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Project Schedule and Cost
http://rvarg.as/15
♫♫4 Different Indexes to Forecast
the Project Final Cost Using the
Earned Value Analysis
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♫♫Understanding the Difference
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3. ricardo-vargas.com 3
Earned Value Analysis
Earned Value focuses on the relation between actual costs and the work done in
the project within a certain time limit. The focus is on the performance obtained
in comparison to what was spent to obtain it (FLEMING & KOPPELMAN, 1999a).
Earned Value can be defined as the evaluation between what was obtained ac-cording
to what was truly spent and to what was planned to be spent, in which it
is suggested that the value to be earned initially by an activity is the value bud-geted
for this activity. As each activity or task of a project is accomplished, that
value initially budgeted for the activity, now builds the Earned Value of the proj-ect.
In order to formalize the concepts mentioned before, based on the norm ANSI/
EIA 748 of the American National Standards Institute, a specific terminology was
made up, based on data of the forecasted cost, real cost and earned value.
The 3 elements of the Earned Value Analysis
A project that will be controlled through the Earned Value Analysis needs to be
planned through the management basic principles, applicable to any kind of
project.
Exhibit 1 evidences these management processes. Firstly, the work to be done
is defined. In a second moment, the schedules and budgets are developed. The
measurement and evaluation of the results of Earned Value are then, determined
and compared to the planned values.
4. 4 Earned Value Probabilistic Forecasting using Monte Carlo Simulation
10
10
10
12
8
6
6
20 4
4
20
40 10
10
20
20
SCOPE DEFINITION SCHEDULE DEVELOPMENT
AND COST BUDGETING
PERFORMANCE
MEASUREMENT
Data
de
Status
Linha de
Base
(BCWS)
Custo
Real
(ACWP)
Valor
Agregado
(BCWP)
Exhibit 1 – Planning and monitoring system using Earned Value Analysis (ABBA, 1998).
Likewise, the PMI (2000) shows, in its process of planning (Exhibit 2), a detailing of
processes of planning according to the same steps mentioned by ABBA (1998), in
which the scope definition of the project (Scope Definition – 5.3) is prerequisite
for schedule development (Schedule Development – 6.4), for resource allocation
(Resource Planning – 7.1) and for cost budgeting (Cost Budgeting – 7.3). Based
on the conclusion of these processes, the project plan is developed (Project Plan
Development – 4.1).
SCOPE
5.3 – Scope Definition
TIME
6.1 – Activity Definition
SCOPE
5.2. Scope Planning
COST
7.1 – Resource
Planning
TIME
6.2 - Activity
Sequencing
TIME
6.3 - Activity Duration
Estimating
RISK
11.1 - Risk
Management Planning
COST
7.2 - Cost Estimating
TIME
6.4 - Schedule
Development
COST
7.3 – Cost Budgeting
INTEGRATION
4.1 – Project Plan
Development
Exhibit 2 – Planning processes (PMI,2000).
BCWS (Budget cost of work scheduled) is the value that points out the part of
the budget that should be spent, considering the cost of baseline of the activity,
5. ricardo-vargas.com 5
attribution or resource. The BCWS is calculated as the costs of baseline divided in
phases and accumulated until the date of the status, or current date. It is the cost
originated in the budget.
During the execution, the monitoring of the progress of the project is made
through the comparison between the real results obtained and the ones fore-casted
by the project in the BCWS. In this moment, the Earned Value of the work
(BCWP) is evaluated, as well as the appropriation of real costs (ACWP).
BCWP (Budget cost work performed) is the value that points out the part of the
budget that should be spent, considering the work done up to the moment and
the cost of baseline for the activity, attribution or resource. The BCWP is also
called Earned Value.
The way of measurement of Earned Value, or BCWP, is directly linked to the way
the project was planned. Without an adequate planning, the measurement of
performance has little or no applicability.
HARROFF (2000) and FLEMING & KOPPELMAN (1999) subdivide the measure-ment
of Earned Value (BCWP) in different methods:
1. Milestone with weighted value: The control cell is converted in 2 or
more marks where each one of them is defined by a partial delivery of the
work, generating, consequently, a specific cost. The sum of the costs of
accomplishment of each one of these marks is the cost of the item.
2. Fixed formula by CAP: It is the method that divides CAP in 2 parts that,
if summed up, complete 100% of the work. In general, the most used
formulas are 25/75, 50/50 and 75/25. The formula 25/75 separates the work
in 2 points: the first point is accomplished immediately at the beginning
of CAP (25% of costs are already accounted); the other 74% are accounted
when the work is finished. The formula 50/50 points out that 50% of costs
will be accounted at the beginning of the work and 50% at the end.
3. Percent complete: This method attributes to each element of a certain
percent complete (between 0 and 100%) to each control cycle. This
percentage is multiplied by the forecasted cost, aiming to determine the
part of the budget already done.
4. Equivalent units: It is a method that calculates the Earned Value based
on the units produced or made by individual elements of costs, applied
in repetitive works or where the elements are defined in terms of direct
consumption of resources.
It is common sense in all Earned Value reports that there is not only one method
able to fulfill all kinds of work. Most of the times, companies should allow the use
of more than a mechanism of Earned Value calculation.
In this article we decided to choose the use of percent complete as a way to de-termine
Earned Value (BCWP), due to its popularity and user-friendliness. The
6. 6 Earned Value Probabilistic Forecasting using Monte Carlo Simulation
percent complete is being more used in projects because it is easy to use and it
is a standard entry mechanism for earned values in many project management
software.
On the other hand, it brings a huge obstacle in its use, which is the strong subjec-tivity
in its evaluation. It is influenced directly by the evaluator’s perception. Since
the data entry relies on the individual perception, the percent complete method
can be threatened by clients’ pressure or by management staff, and as a conse-quence
it could harm the results obtained. In order to minimize those problems,
some companies have been using internal evaluation procedures of percent
complete. The use of Earned Value in projects leads to more precise estimates.
The actual costs (ACWP) are measured and evaluated by the project team that
is in charge of accounts payable and receivable or by the finance department of
the same company. The team is supposed to report the real cost of the project
until the dead line (status) in a specified accounts plan, defined by the controller’s
department of the enterprise.
ACWP (Actual cost of work performed) presents the actual costs resulting from
the work already done by a resource or activity, until the status date, or actual
date of the project, due to financial data. When those 3 parameters are defined,
the analysis of results is obtained based on the correlation among the values
found for ea ch one of them in a certain status date.
Cumulative Cost
BCWP
BCWS
ACWP
ACWP
BCWS
BCWP
Status
Date
Time
Exhibit 3 – Graphic example of BCWS, BCWP and ACWP within a time length.
7. ricardo-vargas.com 7
Project Evaluation and Development of Projections
with the Earned Value Analysis
The correlation among the values of BCWS, BCWP and ACWP allows the verifica-tion
of the results of the project and continue the evaluations and future projec-tions
of final costs
In order to relate between BCWP and the parameters BCWS and ACWP there are
the following indexes:
A) SPI (Schedule Performance Index) – Division between the Earned Value (BCWP)
and the planned value in the baseline (BCWS). The SPI shows the conversion rate
of the forecasted value in Earned Value.
BCWS
SPI BCWP =
(equation 01)
When the SPI equals 1 it means that the planned value was integrally earned to
the project. When the SPI is less than 1 it means that the project is being done in
a lower conversion rate than the forecasted one. In other words, the forecasted fi-nancial
amount to be earned in the period defined couldn’t be obtained, and the
project is late. When the SPI is superior to 1, it means that the project is earning
results faster than expected, in other words, it is advanced.
B) CPI (Cost Performance Index) – Division between the Earned Value (BCWP) and
the actual cost (ACWP). The CPI indicates which the conversion is between the
actual values used by the project and the earned values in the same period.
ACWP
CPI BCWP =
(equation 02)
When the CPI equals 1, it means that the value spent by the project was integrally
earned to the project (project within the budget). When the CPI is less than 1, it
means that the project is spending more than forecasted until that moment. If
the CPI is superior to 1, it means that the project costs less than forecasted until
that moment. When CPI equals 1, it means that the project is according to the
forecasted budget until the reference date. According to project forecasting, the
following terminology is used:
A) EAC (Estimated at Completion) – finance value that represents the final cost of
the project when concluded. It includes the actual costs (ACWP) and the rest of
estimate values (ETC)
8. 8 Earned Value Probabilistic Forecasting using Monte Carlo Simulation
EAC = ACWP + ETC (equation 03)
B) ETC (Estimated to Complete) – financial value necessary to complete the proj-ect.
It is calculated according to mathematical models to be presented.
C) VAC (Variation at Completion) – difference between the budgeted cost (BAC)
and the projected final cost (EAC).
VAC = BAC − EAC (equation 04)
Cumulative Cost
Time
BCWP
BCWS
ACWP
BAC
ACWP
BCWS
BCWP
Status
Date
EAC Projection Using
CPI
EAC
BAC
VAC
Exhibit 4 – Earned Value forecasting of final deadlines and final costs (GEROSA &
CAPODIFERRO, 1999).
Indexes Used for Projection of Project Final Costs
The generic formula for the remaining estimated cost is function of a perfor-mance
factor
Índice
ETC BAC − BCWP
=
(equation 05)
where BAC is the final budget of the final project and index is the performance
9. ricardo-vargas.com 9
index of the project.
The performance index is determined by the combination of the Cost Perfor-mance
Index (CPI) with the Scheduled Performance Index (SPI), according to
what is described next, in its usual cases.
ETC through the constant deviation index (optimistic)
It assumes that the rest of the work to be done by the project will be done ac-cording
to the original plan and that an occurred deviation will not represent a
tendency of degeneration or recovery of the forecasted budget.
This estimate is commonly called the Optimistic Estimation, because, the indexes
CPI and SPI are usually less than 1, therefore permanence in the plan turns out to
be a good result.
EAC ACWP ETC ACWP BAC BCWP
BAC BCWP
Índice
ETC BAC BCWP
Índice 1
= + = + −
= −
−
=
=
(equation 06)
ETC through costs performance index (realistic or more probable)
It assumes that the rest of the work to be done by the project will follow the
same finance performance obtained until this moment, through the costs per-formance
index (CPI).
A negative or positive tendency obtained up to the moment in terms of CPI, will
project the same tendency for the final costs of the project. Since, there is a nat-ural
tendency to work with CPI indexes inferior to 1, this estimate is commonly
called Realistic Estimation or more probable.
CPI
EAC ACWP ETC ACWP BAC BCWP
CPI
BAC BCWP
Índice
ETC BAC BCWP
Índice CPI
−
= + = +
−
=
−
=
=
(equation 07)
ETC through future scheduled cost index SCI (pessimistic)
It assumes that the rest of the work (future) to be done by the project will follow
the finance projection determined by the cost performance index (CPI), as well
as the scheduled projection determined by the scheduled performance index,
generating the scheduled cost index SCI.
This procedure aims to catch a natural human tendency of recovering the time
10. 10 Earned Value Probabilistic Forecasting using Monte Carlo Simulation
wasted, and this try means to spend more resources to do the same work planned
before. The SCI index is strongly applicable in EAC projection in case of late proj-ects,
and with forecasted costs overspent. The product SPIxCPI makes up the
strictest index in order to determine the EAC.
Since there is a natural tendency to work with CPI and SPI indexes inferior to 1,
this estimate is usually called Pessimistic Estimation.
SPIxCPI
EAC ACWP ETC ACWP BAC BCWP
SPIxCPI
BAC BCWP
Índice
ETC BAC BCWP
Índice SCI SPIxCPI
−
= + = +
−
=
−
=
= =
(equation 08)
When the 3 ways of Estimated at completion is determined, a probabilistic model
is applied in the data, in order to allow verification, in a desired reliability degree,
which is the projected final cost for the project.
Monte Carlo Simulation
“Monte Carlo” was a nickname of a top-secret project related to the drawing and
to the project of atomic weapons developed by the mathematician John von
Neumann. He discovered that a simple model of random samples could solve
certain mathematical problems, that couldn’t be solved up to the moment.
The simulation refers, however, to a method in which the distribution of possi-ble
results is produced from successive recalculations of the data of the project,
allowing the construction of multiple scenarios. In each one of the calculations,
new random data is used to represent a repetitive and interactive process. The
combination of all these results creates a probabilistic distribution of the results.
The feasibility of produced distribution relies on the fact that, for a high num-ber
of repetitions, the model produced reflects the characteristics of the original
distribution, transforming the distribution in a plausible result for analysis. The
simulation can be applied in schedules, costs and other project indexes.
Mathematically the result of the simulation becomes a reasonable approximation
for the original data. In an infinite number of repetitions, we could define that
∫
+∞
−∞
Re sults = . xF(x)dx
(equation 09)
where X is the variable analyzed and F is its density of probabilities function.
11. ricardo-vargas.com 11
Since the exact determination of the integration xF(x) is rather complex, the sim-ulations
permits an approximate form of results with less complexity.
A B E
C
D
Start Finish
Forecast of Final Cost
%
Exhibit 5 – Construction of model of distribution of costs and activities or work packages
making up a final distribution from random data of the project (PRITCHARD, 2001).
Execution of the Simulation
The execution of the simulation assumes that all data of SPI, CPI and EAC’s have
already been determined for each activity or work package, according to what
was evidenced in the project example shown as follows.
Exhibit 6 – Project example using the simulation.1
1 In this paper all the case
study data are displayed in
Brazilian Portuguese, as the
original article.
12. 12 Earned Value Probabilistic Forecasting using Monte Carlo Simulation
NAME
%
COMPLETE BUDGET BCWS BCWP ACWP CV
Simulação 41% R$ 50.000,00 R$ 41.200,00 R$ 35.100,00 R$ 37.400,00 (R$ 2.300,00)
Desenhar requerimentos 100% R$ 4.000,00 R$ 4.000,00 R$ 4.000,00 R$ 5.000,00 (R$ 1.000,00)
Preparar dados 50% R$ 4.000,00 R$ 3.000,00 R$ 2.000,00 R$ 5.000,00 (R$ 3.000,00)
Obter ferramentas 25% R$ 6.000,00 R$ 6.000,00 R$ 1.500,00 R$ 3.000,00 (R$ 1.500,00)
Desenhar solução 100% R$ 12.000,00 R$ 12.000,00 R$ 12.000,00 R$ 10.000,00 R$ 2.000,00
Comprar equipamentos teste 100% R$ 15.000,00 R$ 15.000,00 R$ 15.000,00 R$ 13.500,00 R$ 1.500,00
Dados de teste completos 0% R$ 0,00 R$ 0,00 R$ 0,00 R$ 0,00 R$ 0,00
Construir ambiente de testes 10% R$ 6.000,00 R$ 1.200,00 R$ 600,00 R$ 900,00 (R$ 300,00)
Aguardar chegada equipamento 30% R$ 0,00 R$ 0,00 R$ 0,00 R$ 0,00 R$ 0,00
Testar 0% R$ 3.000,00 R$ 0,00 R$ 0,00 R$ 0,00 R$ 0,00
NAME SV CPI SPI EAC CONSTANT EAC CPI EAC SCI
Simulação (R$ 6.100,00) 0,94 0,85 R$ 52.300,00 R$ 62.500,00 R$ 100.100,00
Desenhar requerimentos R$ 0,00 0,80 1,00 R$ 5.000,00 R$ 5.000,00 R$ 5.000,00
Preparar dados (R$ 1.000,00) 0,40 0,67 R$ 7.000,00 R$ 10.000,00 R$ 12.500,00
Obter ferramentas (R$ 4.500,00) 0,50 0,25 R$ 7.500,00 R$ 12.000,00 R$ 39.000,00
Desenhar solução R$ 0,00 1,20 1,00 R$ 10.000,00 R$ 10.000,00 R$ 10.000,00
Comprar equipamentos teste R$ 0,00 1,11 1,00 R$ 13.500,00 R$ 13.500,00 R$ 13.500,00
Dados de teste completos R$ 0,00 - - R$ 0,00 R$ 0,00 R$ 0,00
Construir ambiente de testes (R$ 600,00) 0,67 0,50 R$ 6.300,00 R$ 9.000,00 R$ 17.100,00
Aguardar chegada equipamento R$ 0,00 - - R$ 0,00 R$ 0,00 R$ 0,00
Testar R$ 0,00 - - R$ 3.000,00 R$ 3.000,00 R$ 3.000,00
Exhibit 7 – Initial basic data of simulation and determination of the 3 models of
EAC (optimistic, pessimistic and realistic).
From a complete database, the function of distribution of probability is deter-mined
for the 3 EAC data, building the medium EAC as a result of distribution, as
shown at table below.
The function of density of probability used in the simulation will be the triangu-lar
distribution. This distribution is determined based on its minimum value, its
more probable value and its maximum value. This function is probably the most
direct and simplest among distributions (GREY, 1995), requiring only 3 points in
its built.
13. ricardo-vargas.com 13
Probability
Cost Forecast
EACCPI
EACSCI EAC1
Exhibit 8 – Function of density of triangular probability for EAC.
Using the simulation software @Risk, we could determine the final EAC from the
function RiskTriang (EAC1, EAC cpi, EAC sci), making up the results evidenced at
table below.
NAME
EAC
CONSTANT EAC CPI EAC SCI EAC EAC
Simulação R$ 52.300,00 R$ 62.500,00 R$ 100.100,00 =RiskOutput() R$ 71.633.33
Desenhar requerimentos R$ 5.000,00 R$ 5.000,00 R$ 5.000,00 =RiskTriang(E16; F16; G16) R$ 5.000,00
Preparar dados R$ 7.000,00 R$ 10.000,00 R$ 12.500,00 =RiskTriang(E17; F17; G17) R$ 9.833,33
Obter ferramentas R$ 7.500,00 R$ 12.000,00 R$ 39.000,00 =RiskTriang(E18; F18; G18) R$ 19.500,00
Desenhar solução R$ 10.000,00 R$ 10.000,00 R$ 10.000,00 =RiskTriang(E19; F19; G19) R$ 10.000,00
Comprar equipamentos teste R$ 13.500,00 R$ 13.500,00 R$ 13.500,00 =RiskTriang(E20; F20; G20) R$ 13.500,00
Dados de teste completos R$ 0,00 R$ 0,00 R$ 0,00 =RiskTriang(E21; F21; G21) R$ 0,00
Construir ambiente de testes R$ 6.300,00 R$ 9.000,00 R$ 17.100,00 =RiskTriang(E22; F22; G22) R$ 10.800,00
Aguardar chegada equipamento R$ 0,00 R$ 0,00 R$ 0,00 =RiskTriang(E23; F23; G23) R$ 0,00
Testar R$ 3.000,00 R$ 3.000,00 R$ 3.000,00 =RiskTriang(E24; F24; G24) R$ 3.000,00
Exhibit 9 – Function of density of triangular probability determined for the final EAC.
When we build the function of density of probability, the parameters of simula-tion
are determined, as well as the number of iterations and repetitions of simu-lation
and other information. In this article 50,000 iterations were made.
The number of iterations is important to determine the quality of the results,
therefore, the more iterations are made, the more the function of final density
gets closer to the original functions. However, this kind of process requires a long
execution time, even for fast computers that are able to make the simulation in
high speed.
SUMMARY INFORMATION
Workbook Name eva.xls
Number of Simulations 1
Number of Iterations 50.000
Number of Inputs 9
Number of Outputs 1
Exhibit 10 – Simulation data.
14. 14 Earned Value Probabilistic Forecasting using Monte Carlo Simulation
SUMMARY INFORMATION
Sampling Type Latin Hypercube
Simulation Start Time 20/1/2004 13:26
Simulation Stop Time 20/1/2004 13:27
Simulation Duration 00:00:55
Random Seed 1102974243
Exhibit 10 – Simulation data.
Analysis of the Results
After doing the simulation, the product generated is a distribution of probability
of final EAC of the project, called “Simulation”, evidenced in the following exhibits. Distribution for Simulação / EAC/N2
Values in 10^ -5
Values in Thousands
0
1
2
3
4
5
6
Mean=71633,34
50 62,5 75 87,5 100
5% 90% 5%
61,1023 85,079
15. ricardo-vargas.com 15
Distribution for Simulação / EAC/N2
Values in Thousands
0,000
0,200
0,400
0,600
0,800
1,000
Mean=71633,34
50 62,5 75 87,5 100
5% 90% 5%
61,1023 85,079
Exhibit 11 – Distribution for the final EAC of the Project “Simulation” with an interval of
confidence of 90% and cumulative distribution for the final EAC of the Project “Simulation”.
%TILE VALUE %TILE VALUE
5% R$61.102,32 55% R$71.753,30
10% R$62.673,17 60% R$72.871,88
15% R$63.868,52 65% R$74.055,95
20% R$64.892,36 70% R$75.366,22
25% R$65.850,78 75% R$76.773,88
30% R$66.776,27 80% R$78.350,77
35% R$67.728,09 85% R$80.126,48
40% R$68.686,84 90% R$82.236,36
45% R$69.675,42 95% R$85.078,99
50% R$70.702,85
Exhibit 12 – Percentage distribution of final EAC of
Project “Simulation”.
According to prior data, we can assume for sure (about 90% of certainty), for ex-ample
that the projected final cost will be between $61,102 and $85,078.
These intervals could be altered in order to determine more or less precision. For
example, assuming a certainty of 99% regarding the values, we obtain the inter-val
between $57,858 and $90,792, according to what is shown in the following
exhibit.
16. 16 Earned Value Probabilistic Forecasting using Monte Carlo Simulation
Distribution for Simulação / EAC/N2
Values in 10^ -5
Values in Thousands
0
1
2
3
4
5
6
Mean=71633,34
50 62,5 75 87,5 100
,5% 99% ,5%
57,8581 90,7921
Exhibit 13 – Distribution for the final EAC of the Project “Simulation” with an interval of
confidence of 99%.
Conclusions
The use of Simulation Monte Carlo with the data of final EAC of the project, can,
in an associated way, contribute to a probabilistic vision and not a deterministic
vision of the final costs elaborated for the project, without the additional effort
in its construction.
As mentioned in the study of CHRISTENSEN (1993), there isn’t an agreement in
order to define which forecast model presents the best precision and applicabili-ty.
However, many studies have been made in order to compare many models for
the costs estimated in a certain project or group of projects, after its conclusion,
aiming to identify which models are more precise and in which phases of the
project they are applicable, as well as to associate a certain type of project to a
certain index.
The need of estimates and costs projections is mentioned and characterized by
DOD (1997) in Instruction 5000.2R in 1997 in 2 criterion.
Start with an estimate area for the final cost, reflecting the best and worst scenar-ios.(
DOD, 1997).
Determine the estimate for the final cost that reflects the best professional judg-ment
concerning costs. If the contract is at least 15% complete and the estimate
is less than the calculated using the accumulated performance index, give an
explanation (DOD, 1997).
However, none of these studies provides a probabilistic treatment for the proj-ects,
since the most adequate final EAC for the project is no longer an isolated
17. ricardo-vargas.com 17
value and turns out to be a values area with certain probabilities, as suggested
in this article.
As a suggestion for new works, the next step will be to evaluate the results pro-duced
in the simulation with the real results of concluded projects in order to
determine the precision of data obtained, aiming to produce cases associated to
the simulation model applied to EMVS.
Abbreviations
ACWP – Actual cost of work performed
BAC – Budget at completion
BCWP – Budget cost of work performed
BCWS – Budget cost of work scheduled
C/SCSC – Cost/Schedule Systems Control Criteria
CAPs – Cost Account Plans
CPI – Cost Performance Index
CV – Cost variation
DOD – United States of America Department of Defense
EAC – Estimated at completion
EMVS – Earned Value Management Systems
ETC – Estimated to complete
EVMS – Earned value Analysis
PMBOK® - A guide to the Project Management Body of Knowledge
PMI – Project Management Institute
SCI – Scheduled Cost Index (SPIxCPI)
SPI – Scheduled Performance Index
SV – Scheduled variation
VAC – Variation at completion
18. 18 Earned Value Probabilistic Forecasting using Monte Carlo Simulation
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