It is one of the most important indexes to evaluate the possibility of project financial recovery using Earned Value Management System (EVMS).

AACE – Association for Advancement of Cost Engineering 47th Annual Meeting
Orlando – Florida – USA – 2003
PMI College of Performance Management Measurable News Magazine
Arlington- Virginia – USA – 2003

Abstract

The objective of this paper is to present and discuss the main obstacles and benefits of the use of the Earned Value Analysis in projects, including factors to be improved and implemented during the project plan and actions to be taken while the project is accomplished and controlled. Also, through a real case study in civil construction field, the applicability of the technique is faced with a theoretical reference, in order to identify aspects of the applicability of the tool tested in case study. The results to be presented and discussed are subdivided in two parts:
The first one is about the different features of each business and its contribution for the success or failure in the implementation of the Earned Value Analysis, and the second is about the characteristics of similarity found in all businesses that together favor or not the use of the tool.

Earned Value Analysis as a Control Technique

Many studies about the applicability of the Earned Value Analysis have been made. THAMHAIN (1998) tried to evaluate the popularity of different practices of project management. Surveys were made with 400 professionals who work with projects (managers, directors, people in charge) in 180 projects in Fortune-1000 companies. They were asked about the popularity and value of different techniques of performance evaluation. As a result, he could see that the Earned Value Analysis is used by 41% of people who work with projects. It is more used than critical path method, QFD (quality function deployment) and Crashing, among others. The Earned Value Analysis is almost as popular as the net PERT/CPM.
Concerning the value of the technique, the results found for Earned Value Analysis are fitted in a layer of little value, staying below practically all techniques analyzed, what infers that the popularity of the technique doesn’t seem to show its applicability or value.
Trying to justify the low value proved by researchers, THAMHAIN (1998) states that little applicability found as a result in the studies made, can be attributed to different barriers, either being internal or from the environment. They are:

• lack of comprehension of how the technique works
• anxiety concerning the adequate use of the tool
• use of the tool requiring a lot of work and time consumption
• tools trimming creativity in the use of other strategies
• inconsistency of the tool in managerial procedures / businesses processes
• method of control as threat, concerning the freedom of the team
• vague and inaccurate purpose and its benefit
• high cost of its implementation
• unsuccessful prior experience in the use of other techniques
• low familiarity with the technique

WIDEMAN (1999) states that a project of great importance requires a unit of planning and control that has professionals capable of collecting the information and making the Analysis of Added Value, turning its applicability justifiable.
CHRISTENSEN (1998) states, in his studies about the applicability of Added Value in govern organizations in the United States, that the implementation of Earned Value requires a cultural change, which demands time and effort. This means to make sure that policies and knowledge are taught by the organization and by the project in order to quicken the work of the ones involved.
To Sparrow (2000), the Earned Value Analysis enables a supplementary value to the project because it offers a premature visibility of its results, in other words, it is possible to determine a tendency of costs and deadlines of the project in a certain phase of it, when there is still a possibility of implementation of corrective actions.
On the contrary, WEST & MCELROY (2001) agree that the Earned Value Analysis is an adequate tool for the generation of reports of work done, and not a managerial tool, since the control in real time of the project, using all parameters of analysis becomes unviable: “the Earned Value Analysis shows to the project team the performance obtained until then, and not the future forecast of the project.”
WIDEMAN (1999) supports that the technique is conceptually attractive, however it requires great efforts in its maintenance, therefore it needs a qualified team to understand and provide reliable information. He also states that many project managers don’t consider the analysis an appropriate cost-benefit ratio.
From those opposite points of view, we may imply that the Earned Value Analysis is a group of powerful intrinsic characteristics, wide and varied, like payment projection and forecasting. However, it is bound to find great difficulty in either data collection or in the low speed of information generation.
These considerations may mean that, if the data collection is made in adequate speed and accuracy, and the information is correctly compiled accomplishing the deadlines, the analysis has its applicability widely enlarged. Otherwise, it will not add much to the process of project control.
TERREL et al (1998) states that, in order to make the Earned Value Analysis effectively implemented, it is necessary to have the information about the resources clearly defined. A failure in obtaining these data, motivate the creation of inaccurate performance measurement baseline (PMB), distant from the real scenario.

FLEMING & KOPPELMAN (1999) state, also that another difficulty factor is about an adequate work breakdown structure (WBS). If the work is subdivided in small packages of work, it will represent a high cost of control and a lot of paperwork. On the other hand, a badly stratified subdivision may represent an inaccuracy of data, concerning real costs and deadlines.
This confirmation may be proved in the low application of the Earned Value Analysis in technology and marketing areas, where the creative work is the variant in a scope previously defined, making its application limited and directly related to the stability of a defined scope, according to PETERSON & OLIVER (2001).
They state that, the more short-term projects grow, with reduced team and a generically defined scope, the more the Earned Value Analysis, according to Instruction 5000. 2R (DOD, 1997) and by ANSI/EIA 748, is not viable, due to inaccurate projections, consequence of a badly defined scope and to high costs noticed by the entrepreneurs.

Case Study

The company researched belongs to a sector of civil construction, which applies project management in a steady way. It is a segment that most invests in researches and new tools in this field. Furthermore, it is the only one on the market that admits publicly the use of Earned Value Analysis in its process of construction control.
This company is the 11th in the national segment of heavy construction. It is also part of the three biggest groups in the segment in the country and a leader in other segments of the economy, such as government work and telecommunications. It has been on the market for more than 50 years. Its turnover in 2001 was about US$200,000,000 with 80 engineers and about 4000 workers in its personnel.
Concerning the case study, everything started through a process of interview in which three professionals from the southeast business planning unit of the company, gave their opinion about the process in a wide and clear way. These professionals were the first ones to be interviewed, because they have developed the construction control system using the Earned Value Analysis.
After analyzing the issues discussed by the first interviewees, a new series of interviews was made, based on a new open line of interviews, with construction managers and the ones in charge of planning departments of each construction site. At this moment, the objective was to test the planning practices, analysis and gathering of data in different levels, aiming to find possible distortions, conceptual flaws, resistance and work style in the use of Earned Value Analysis in the construction sites.
In a third and final moment, the final result of the projects (deadlines and costs) was faced with the values computed for the Earned Value Analysis that were under the responsibility of the planning unit of the company. From that combination between interview results and the data available in the company, we tried to get evidence that could link the success or failure of the business to maturity in the use of Earned Value.
Concerning the evaluated construction sites, they were categorized by the company as medium-sized and average technique complexity constructions, which will be finished by the end of this work.

Results

The results to be presented and discussed in this section are about different characteristics of each construction site and its contribution to the success or failure in the implementation of the Earned Value Analysis. The second part is about the traces of similarity found in the construction sites and the general conclusions about the case study.
The results obtained in the process of interview and the combination of real data provided by the planning department, as seen before, were significantly different in each business.
From these different characteristics (Table 1), the main factors are presented and evaluated in each construction site, just like the final result concerning the fidelity of the results and the preliminary conclusions.
The factors evaluated have been presented in the discussion and analysis of each construction site, and they are: scope, deadlines and schedules, budget process, type of contract, type of client, partners and/or consortiums, organizational support, support by the client, geographic distribution of work, the presence of outsourced staff, use and knowledge of the indexes and models of projection provided by the tool.

Table 1 – Comparative analysis of the main characteristics of three construction sites evaluated.

As we can see, after analyzing table 1, we may conclude that the implementation of construction site one was successful and of construction site three was a failure. Both results are not necessarily product of an isolated factor, but from lots of linked factors.
It is not possible to conclude that the unsatisfactory results found in construction site three are linked to the existence of a consortium or to an inadequate geographic distribution of work. This failure is a consequence of a group of many unfavorable characteristics, which contributed to unexpected results.
On the other hand, evaluating construction sites one and two, we find characteristics in construction site two that are significantly closer to those in construction site one. However, the main difference found was the lack of detailing of scope, which consequently made the budget process unsatisfactory. We may conclude that it was one of the main factors that made the results different (see Table 1).
Similarities have been found in all three projects evaluated. They are related to the process of interview and obtained results.
Initially, we may conclude that there are factors linked to the organizational structure and to the management model of the company that could affect directly the fidelity of results. Therefore, it is necessary to investigate deeply about the influence in organizational structure in the use of the tool.
Also, concerning organizational aspects, the ones in charge of construction sites planning, questioned the need of a high number of indexes, and mentioned that the determination of performance indexes was redundant.
A preliminary evaluation of these considerations, allows us to conclude, at first, that the Earned Value Analysis as we can see in all of the three projects, may show a high use of excessive indexes, superior of the management potential of a construction site. That could make the construction site impossible, result of low priority in the process and unnecessary use of indexes.
The opinion of the interviewees about the real value of the tool was unanimous. They all agree that the Earned Value Analysis is a great step for the improvement and introduction to a more modern mechanism of construction site control. This would confirm the first result of THAMHAIN’S (1998) study about how popular the technique is, however, in the same study (THAMHAIN, 1998), they all agree that the conditions of market and the necessity of a quicker generation of results, made the dedication to the use of the tool, difficult, proving the low value of the technique presented in the study of THAMHAIN (1998).
According to prior quotations, we can also see that in all three cases, there was an active participation of the planning departments of the business unit. However, this participation was different in each construction site. We can imply that the success of construction site 1, concerning the implantation of the tool, is directly linked to a strong presence of the professionals of planning department.
Therefore, we may conclude that, very often, the efforts of the construction site team are divided in many different groups, and the team dedicates to the tool, directly used by top executives to evaluate the businesses. As a result, the dedication to other competitive tools is ignored or left behind, as seen in Earned Value Analysis in projects two and three.
In construction site one, this process inverted. In this project, the Earned Value Analysis was the main mechanism of construction site control. It gathered all the necessary support to be successful. Finally, we may conclude that the case study proved the characteristics of the projects that favor the use of the tool and the use of others which show to be difficult in the process.
It was also proved that the implementation of the Earned Value Analysis is a complex process that involves several aspects, since the kind of business until its organizational structure, its scope, its geographic distribution and the relationship with the client, among others, that deserve a more detailed study.

Conclusions

From this paper, we may conclude that the Earned Value Analysis is a powerful tool in the control of performance evaluation. However, most of the projects have insufficiently detailed scope, staff with little experience in the use of the tool and a natural dissociation in the control of costs and deadlines. These elements make the results questionable to a necessary effort.
We may also conclude that the results are not very obvious in short-term basis. They will only be evidenced in future phases of the project, especially in cost reduction of operations and rework.
As a third conclusion, we may see that, in projects of clearly defined scope, or in contracts with price and work established, the Earned Value Analysis shows a favorable cost-benefit ratio. Other element that might favor the application of the tool is the qualification of project teams in the use of the tool and the organizational support, which allows the tool to be simplified to meet the specific needs of the project and the organization.
To sum up, the combinations of the conclusions obtained from the analysis of the theoretical reference, with the case study are shown as follows.
Nature of the project – the application of the Earned Value Analysis can be considered more successful in projects of clear and tangible objectives, with a detailed scope, simple and direct. This type of project presents better results in the use of the analysis, as evidenced in the case study (construction site one). Projects with incomplete final products or services, or projects that involve aspects of creativity that make a precise plan impossible, show high inviability in the use of the technique. Since the planning has not been established, the date of performance can be determined (construction sites two and three).
Scope definition – from empirical evidence obtained from the evaluated construction sites and based on theoretical discussions presented in the theoretical reference, we may imply that the facility or difficulty concerning detailing and specification of scope, permits the tool to be favored or disfavored, since a tangible scope, controllable and detailed provides better specification of the work to be made. Consequently, it facilitates the process of measurement of real and added values. The establishment of tangible, controllable and detailed scope is a process that comes from the nature of the project and from the model of business established (contract, type of client, etc). Therefore, a strong dedication to the process of development of the scope improves results in the use in the Earned Value Analysis.
Informality in management and resistance to changes – we can see in the case study that the informality in the control of project is high, and resistance found in the implementation of a new model of control exists and cannot be ignored. This resistance is associated to a perception that the planning work and control rise in an unjustifiable way, when using the tool. Trying to associate both factors, ANTVIK (1998) states that the resistance comes from a cultural process of informality in the control of projects. In this way, it is implied that it is necessary to create a different work of management of changes, for example the training of management of projects, workshops, an efficient support of the professionals of this area, with prizes and bonuses. Everything aims to minimize the resistance found in the implementation and to favor the project environment.
Attractively and value of the technique – Based on the evidence of the case study and on researches presented on theoretical reference, we can say that the Earned Value Analysis is considered by the ones who have already used it or known it, as attractive and complete. However, this fact is not true, concerning the use of the technique. The interviewees and several authors that were cited and in this theoretical reference agree that the technique demands a strong effort that, if not analyzed widely, should not have good results. This consideration justifies the results presented on the research of THAMHAIN (1998).
Training – The Earned Value Analysis suggests a cultural change in the process of projects control, therefore people who have experience in dealing with the tool are really necessary in this process. Moreover, it is also necessary a process of intense training, in order to reduce the resistance to its implementation that comes originally from a low technical knowledge of the tool.
Organizational support – The way an organization implements the tool, influences directly the results. As seen empirically in the case study, the construction site one, that had an organizational support, provided by specialized resources, had better results in terms of application. However, the organizational support, has a cost that has to be determined and accounted, otherwise the obtained results might be distorted.

References

ANTVIK, L. C. S. (1998). Earned value Management – a 200 Year Perspective. Long Beach: 29th Annual Project Management Institute Seminars & Symposium.
CHRISTENSEN, D. S. (1998) The Cost and Benefits of the Earned value Management Process. Acquisition Review Quarterly.
DOD (1997). Earned value Management Implementation Guide. Washington: United States of America Department of Defense
FLEMING, Q. W. & KOPPELMAN, J. M. (1999). Earned value Project Management, 2nd Ed. Newton Square: Project Management Institute.
PETERSON, C. D. & OLIVER, M. E. (2001). EV-Lite – Earned value Control for Fast Paced Projects. Nashville: 32th Annual Project Management Institute Seminars & Symposium.
SPARROW, H. (2000). EVM = Earned value Management Results in Early Visibility and Management Opportunities. Houston: 31st Annual Project Management Institute Seminars & Symposium.
TERREL, M. S., BROCK, A. W., WISE, J. R. (1998). Evaluating Project Performance Tools – A Case Study. Long Beach: 29th Annual Project Management Institute Seminars & Symposium.
THAMHAIN, H. J. (1998). Integrating Project Management Tools with the Project Team. Long Beach: 29th Annual Project Management Institute Seminars & Symposium.
WEST, S. M & MCELROY, S. (2001). EVMS: A Managerial Tool vs. a Reporting Tool. Nashville: 32th Annual Project Management Institute Seminars & Symposium.
WIDEMAN, R. M. (1999). Cost Control of Capital Projects and the Project Cost Management Systems Requirements. 2ª ed. Vancouver: AEW Services e BiTech Publishers.

AACE – Association for Advancement of Cost Engineering 48th Annual Meeting Washington – DC – USA – 2004
Revista Brasileira de Gerenciamento de Projetos Curitiba – PR – Brazil, 2004

Abstract

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 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 according 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 budgeted 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 project. 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.

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 pre-requisite 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).

Exhibit 2 – Planning proccesses (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, 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 forecasted 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 measurement 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 fulfil 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 determine Earned Value (BCWP), due to its popularity and user-friendliness. The 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 subjectivity 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 consequence 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 each one of them in a certain status date.

Exhibit 3 – Graphic example of BCWS, BCWP and ACWP within a time length.

Project evaluation and development of projections with the earned value analysis

The correlation among the values of BCWS, BCWP and ACWP allows the verification of the results of the project and continue the evaluations and future projections 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.

(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 financial 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.

(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)

(equation 03)

B) ETC (Estimated to Complete) – financial value necessary to complete the project. 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).

(equation 04)

Exhibit 4 – Earned Value forecasting of final deadlines and final costs (GEROSA & CAPODIFERRO, 1999).

Indexes used for projection od project final costs

The generic formula for the remaining estimated cost is function of a performance factor

(equation 05)

where BAC is the final budget of the final project and index is the performance index of the project.

The performance index is determined by the combination of the Cost Performance 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 according 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.

(equation 06)

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 performance 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 natural tendency to work with CPI indexes inferior to 1, this estimate is commonly called Realistic Estimation or more probable.

(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 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 projects, 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.

(equation 08)

When the 3 ways of Estimated at completion is determined, a probabilistic model is applied in the dada, 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 possible 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 number 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

(equation 09)

where X is the variable analysed and F is its density of probabilities function.

Since the exact determination of the integration xF(x) is rather complex, the simulations permits an approximate form of results with less complexity.

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.

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 determined 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 triangular 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.

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.

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 simulation are determined, as well as the number of iterations and repetitions of simulation 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.

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.

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”.

Exhibit 12 – Percentage distribution of final EAC of Project “Simulation”.

According to prior data, we can assume for sure (about 90% of certainty), for example 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 interval between $57,858 and $90,792, according to what is shown in the following exhibit.

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 determinist vision of the final costs elaborated for the project, without the additional effort in its construction.

As mentioned in the study of CHRI STENSEN (1993), there isn’t an agreement in order to define which forecast model presents the best precision and applicability. 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 scenarios.(DOD, 1997).

Determine the estimate for the final cost that reflects the best professional judgment 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 projects, since the most adequate final EAC for the project is no longer an isolated 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 produced 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.

Abreviations

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

References

ABBA, W. F. (1998). Defense Acquisition Reform and Project Management. Long Beach: 29th Annual Project Management Institute Seminars & Symposium.

CHRISTENSEN, D. S. (1993). Determining an Accurate Estimate at Completion. Vienna: National Contract Management Journal.

DOD (1997). Earned Value Management Implementation Guide. Washington: United States of America Department of Defense

FLEMING, Q. W. & KOPPELMAN, J. M. (1999). Earned value Project Management, 2nd Ed. Newton Square: Project Management Institute.

GEROSA S. & CAPODIFERRO C. (1999). Earned value Management (EMV) Techniques form Engineering and Prototype Production Activities. Philadelphia: 30th Annual Project Management Institute Seminars & Symposium.

GREY, S. (1995). Practical Risk Assessment for Project Management. West Sussex: John Wiley & Sons.

HARROFF, N. N. (2000). Discrete Versus Level of Effort. Milford: NNH Enterprise.

PMI (2000). A guide to the Project Management Body of Knowledge. Newton Square: Project Management Institute.

PRITCHARD, C. L. (2001). Risk Management: Concepts and Guidance. 2ª Ed. Arlington: ESI International.

IPMA – International Project Management Association Global Congress
New Delhi – India – 2005 (accepted for publication)
PMI Global Congress Europe
Prague – Czech Republic- 2004 (accepted for publication)

Abstract

The objective of this paper is to present the main components of the development of a project team, the motivational characteristics inherent to the team work and an interrelation proposal between the earned value analysis and team development through the SPI and CPI indexes obtained by the tool and team development models and the compensation and reward in the project, allowing to reduce the evaluation subjectiveness of the human resource in the project.

The paper presents a brief report about the team development and compensation policies, as well as an introduction to the earned value concept aiming to align the approached concepts.

Team development in projects

The project human resources area is one of the PMBOK Guide 2000 (PMI 2000) knowledge areas that the manager and project team have requested more attention.

As reported in the Guide, the Project Human Resources Management includes the processes required to make the most effective use of human resources involved with the project. It includes all project stakeholders: sponsors, customers, individual contributors and others.The main processes are described below and Exhibit 1 provides an overview of the processes according to each project phase.

Organizational Planning – identify, document and assign project roles, responsibilities and the reporting relationships.

Staff acquisition – make the required human resources be designed and work in the project.

Team development - develop individual and group skills to increase project performance.

Exhibit 1 - Human Resources Management Processes distributed throughout the project phases.

These processes interact with each other and with the process in the other knowledge areas. Each process may involve effort from one or more individuals or groups depending on the needs of the project.

The team development approached in this paper involves the increase of the capability of the involved parties to contribute individually, as well as the increase of people capability to work as a team.

The individual growth (managerial and technical) is the basis required to develop the team becoming it crucial to the success of the projects and, therefore, becoming the key for the organization to accomplish their goals.

According to FITZ-ENZ (2000), each organization and each project are led by a combination of strengths and internal and external factors. These factors are the ones that make the organization unique, describing collectively how and why the organizational processes influence on the performance improvement.

The internal factors are the ones determined by the own organization and project goals, while the external objectives are those determined by external business environment in which the company and projects are inserted (Exhibit 2).

Exhibit 2 – Performance change factors

According to FLANES & LEVIN (2001) performance problems that impede the team members to perform their activities successfully can be divided in:
→    Problems related to technical competency
→    Problems related to relationship and communication
→    Problems related to time management and work habits

Due to the above problems, it is fundamental to have an impartial and objective performance evaluation process that besides addressing the mentioned problems, it allows improvements in the individual skills, improvements in the team behavior and improvements not only in the individual competencies but also in the team ones.

This impartial model directly reduces the subjectiveness of the performance evaluation and increases the team motivation according to the Adam’s Equity Theory (VERMA, 1995), as people get motivated when they are treated in equity, impartial and fair way.

Professional compensation (reward)

Some of the main tools available to increase performance are the compensation and reward policies that according to PMI (2000) are the formal actions that promote or reinforce desired behavior. To be effective, such system should make the link between performance and reward clear, explicit and achievable.

According to PARKER, MCADAMS & ZIELINSKI (2000) the reward models are designed to create a focus on specific goals or celebrate and reward individuals or teams with diversified performance. To them, the reward models should meet individual, team and organization needs, according to the model showed in Exhibit 3.

Exhibit 3 – Reward policies and bonuses (PARKER, MCADAMS e ZIELINSKI, 2000)

To SHUSTER (2000) the bonuses always need to satisfy the individual and the team. If a team satisfaction is neglected to satisfy an isolated individual, this process naturally generates dissatisfaction and demotivation. Thus, higher reward can only be gotten when high team and individual performances are achieved, as per Exhibit 4.

Exhibit 4 – Team and individual performance extent (Based on Shuster, 2000)

Earned value is focused on the relation between incurred actual cots and the work performed in the project in a given time period. The focus is on performance obtained in comparison to what was spent to get it. (FLEMING & KOPPELMAN, 1999).

Earned value is the evaluation between what was actually spent and what was budgeted, proposing that the value to be earned initially by an activity is the value budgeted for it. As each activity or task of a project is performed, the initial budgeted value for the activity starts to constitute now the Earned Value of the project.

In order to formalize the mentioned concepts based on instruction DOD (1997) and on norm ANSI/EIA 748 of the American National Standards Institute, a specific terminology was created based on forecasted and actual costs, as well earned value. The basic three elements of the earned value analysis are:

BCWS (Budget cost of work scheduled) is the value that indicates the budget portion that should be spent, taking into account the activity budget base line cost, allocation or resource. BCWS is calculated as budget base line cost divided into phases and cumulative up to the status date, or current date. It is the budgeted cost.

BCWP (Budget cost of work performed) is the value that indicates the budget portion that should be spent, taking into account the work performed up to the moment and budget base line cost for the activity, allocation or resource. BCWP is also called Earned Value.

ACWP (Actual cost of work performed) value that shows actual costs incurred from the work already performed by a resource or task up to the status date or project current date from financial inputs.

Once these three parameters are determined, the outcome analysis is obtained based on the correlation between values found for each one in a given status date (Exhibit 5).

Exhibit 5 – BCWS, BCWP e ACWP graphic example throughout the time for a given project

The correlation among BCWS, BCWP and ACWP values allows to rate project outcomes and to proceed evaluations and future final cost forecasts.
To treat the ratio among BCWP and BCWS and ACWP parameters, there are the following indexes:

A) SPI (Schedule Performance Index) – Division between the Earned Value (BCWP) and the budgeted base line cost (BCWS). SPI shows the conversion rate of the budgeted value in the Earned value.

SPI equals 1 indicate that the budgeted value was completely earned to the project. SPI lower than 1 indicates that the project is being performed at a conversion rate lower than scheduled, that is, the financial amount scheduled to be earned in the period was not achieved and the project is late. SPI higher than 1 indicates that the project is earning outcomes in a speed higher than scheduled, i.e., it is advanced.

B) CPI (Cost Performance Index) – Division between the Earned Value (BCWP) and the actual cost and (ACWP). CPI shows the conversion between the actual values spent by the project and the earned values in the same period.

CPI equals 1 indicate that the value spent by the project was completely earned to the project (project in the budget). CPI lower than 1 indicates that the project is spending more than scheduled up to the moment. If CPI is higher than 1 indicates that the project is costing less than scheduled up to that moment.

Human performance index and professional evaluation models

In order to allow the team evaluation ad project professional it was developed a new index called Human Performance Index (HPI). This index consists of the relationship between the CPI and SPI allowing the creation of an index that evaluates the accomplishment of the schedule and budget of the activities executed by the resource simultaneously.

In developing this paper, it was studied several types of relationship between indexes (sum, average, product, etc.), however, as the nature of the two indexes differs from the complete percentage of the project, it was chosen the composition of the indexes with complete percentage, where the participation of schedule performance index in the beginning of the project is higher than the cost performance index, while at the end of project occurs an inversion in the participation of indexes, once the SPI tends to 1 (BCWP → BCWS) with the termination of the project.

The resulting formula is

Where    CPI = Cost performance index
SPI = Schedule performance index
%C = Project complete physical percentage

Exhibit 6 observes it the participation of the indexes in the HPI composition along the project.

Exhibit 6 – Participation of the indexes according to project complete percentage

From the creation of this index, it is required to evaluate the HPI´s not only the individual work outcome but also the team work in which the resource is integral part of the project as a whole, creating a final HPI that is the weighed average of these three indexes as it is presented below:

Where

CPI_Individual = Cost performance index of the work packages where the evaluated resource was involved
SPI_Individual = Scheduled performance index of the work packages where the evaluated resource was involved
CPI_Team = Cost performance index of the team work packages of which the evaluated resource is participant
SPI_Team = Schedule performance index of the team work packages of which the evaluated resource is participant
CPI_Project = Cost performance index of the project
SPI_Project = Schedule performance index of the project
Weight_Individual = Constribution of resource HPI in the HPIFinal
Weight_Team = Constribution of team HPI in the HPIFinal
Weight_Project = Constribution of project HPI in the HPIFinal
%_C = Project complete physical percentage

HPI_Final can be obtained from different strategies starting from a strong focus on individual outcomes up to a balanced focus among the individual, team and project. Follows a model of weight composition for different focuses

Exhibit 7 – Example of a proposal of weight distribution for the HPI resource composition

It is important to emphasize that the resource, team and project HPI´s are not obtained from CPI and SPI´s work packages, but from the sum of the BCWS, BCWP and ACWP’s resource activities and later from the formula application, CPI=BCWP/ACWP and SPI = BCWP/BCWS.

Example

In order to illustrate the index development it has a project composed of twenty different work packages to be performed by five resources in two teams. The resources 1, 2 and 3 belong to Team A and the resources 4 and 5 to Team B, respectively.
In Exhibit 8 there is the distribution of the resources in the work packages.

Exhibit 8 – Resource distribution to be used in the work packages

In a given moment of the project the package performance inputs were evaluated, obtaining the figure 9 with BCWS, BCWP and ACWP inputs for each work package

Exhibit 9 – Example of data collected for a project with determined BCWS, BCWP and ACWP

From the overcome crossing of each package with resources used in them, it was obtained the HPI of each one of the resources, as well as the HPI of each one of the teams and the total HPI of the project according to Exhibit 10.

Exhibit 10 – Project and resource HPI outcomes

Observing that each resource belongs to a given team, there are the following individual results, shown in exhibit 11.

Exhibit 11 – HPI results of each resource

From the combination of the results of exhibit 11 with the ones of exhibit 7, there are the final HPI of each resource from the individual, team and project focus and the balance focus among the three parameters, obtaining the exhibit 12.

Exhibit 12 – HPI results of each resource

From these values it can be analyzed the outcomes of each one of the resources and its contribution for the project and team outcome, as per example, it is shown in the exhibit 13.

Exhibit 13 – Comparative graphic of the focuses among the individual, team and project for the 5 evaluated resources

In this example, it is observed that the resources 1 and 3 showed a performance lower than their team and project; the resource 2 showed a higher individual performance, however, in analyzing its team, its performance was damaged by weak performance of resources 1 and 3. Resources 4 and 5, they had high performance, increasing this way the performance of Team B.

The project performance was lower than the 4 and 5 resources performance and Team B because the members of Team A lowered the global performance by their weak individual performances.

Conclusions

The main objective of this paper was to present an evaluation proposal of the human resources and teams through more direct mathematical model than the subjective evaluation by the project manager. Besides, bonuses and reward policies may be directly connected to the indexes causing more transparent mechanism of the distribution of project outcomes.

However, some cautions have to be taken in using this kind of evaluation. First, when the executer is not the responsible for the budget accomplishment, he/she can have his/her performance compromised by weak performance of the procurement team, as an example.

Secondly, this mathematical model may not be deterministic, i.e., the only one to represent the truth of the work outcome of the project resource, once they are completely mathematical, they may not evidence subjective human aspects inside the team work.

References

DOD (1997). Earned value Management Implementation Guide. Washington: United States of America Department of Defense

FITZ-ENZ, J. (2000). The ROI of Human Capital: Measuring the Economic Value of Employee Performance. New York; AMACOM.

FLANES, S. W. & LEVIN, G. (2001). People Skills for Project Managers. Vienna: Management Concepts.

FLEMING, Q. W. & KOPPELMAN, J. M. (1999). Earned value Project Management, 2nd Ed. Newton Square: Project Management Institute.

PARKER, G., MCADAMS, J. & ZIELINSKI, D. (2000). Rewarding Teams: Lesson from the Trenches. San Francisco: Jossey-Bass.

PMI (2000). A guide to the Project Management Body of Knowledge. Newton Square: Project Management Institute.

SHUSTER, H. D. (2000). Teaming for Quality: The Right Way for the Right Reason. Newton Square: Project Management Institute.

VERMA, V. K. (1995). Human Resource Skills for the Project Manager vol. 2. Upper Darby: Project Management Institute.