Application of EVM to pressure equipment manufacturing


Work reported in this article covers recent developments in transforming a project-based organization from one with minimal formal project management structure to a business that is now being managed as a whole by its project focus. Changes were driven by the need to restructure the host organization so sufficient data streams became available for earned value management (EVM) analysis. The central challenge has been to make EVM function beneficially on a relatively small scale without imposing uneconomic burdens in data generation and management. Established EVM theories were applied—as described here—and shown to be adaptable to the small-scale manufacturing projects this research is investigating. Results from schedule forecasting have shown consistency in the various methods applied, though some proved more accurate than others. Conclusions suggest EVM has the flexibility to be successfully used as an option for the tracking of pressure equipment manufacturing projects. In addition, the structure to support EVM, and the data delivered by the method, displays capacity to benefit functional areas of the SME and deliver improvements in estimating and scheduling.


In recent years, more sophisticated project management concepts have been applied to project-based organizations (Cooke-Davies, Crawford, & Lechler, 2009) because of their ability to optimize an organization’s responses to the complexities projects typically introduce into a business environment (Maylor, Vidgen, & Carver, 2008). These concepts, coupled with the current changes in the Australian pressure equipment manufacturing sector, established the framework for this research. This article aims to offer some insight into the processes entailed in applying EVM to small pressure equipment supply projects for the Australian market. The investigation was initially targeted at using EVM to enhance management of single projects for major resource developers. Through EVM application it became apparent that the uptake of a wider array of project management theories could facilitate the general management of the schedule-intensive organization being investigated (Dixon, 2011).

Work reported here covers recent developments in transforming a project-based organization from one with minimal formal project management structure, to a business that is now being managed as a whole by its project focus. Changes were driven through the need to restructure the host organization so sufficient data streams became available for EVM analysis. In achieving this goal, it was found that the underlying approaches needed to manage the wider organization were converging toward many of the theories relating to project portfolio management, the project management office, matrix management and project management methodologies. These ancillary research threads, introduced through necessity to support EVM, have made a significant contribution to the “project management maturity” (Besner & Hobbs, 2008, p. S124) of the host business. System benefits were initially focused on the concept of multiple projects through the need for them to be “viewed as an integrated portfolio rather than a disjointed collection” (Dooley, Lupton, & O’Sullivan, 2005). Matrix management was also drawn into early system considerations by identifying layers of project authority and recognizing the need to have integration between the complexities of managing multiple projects within an organization that also needed traditional functional management to drive the operational processes (Kuprenas, 2003). The development of defined systems, addressing the varying project and business management needs, formed a crucial part of the maturity concepts discussed in much of the supporting literature.

Further advances in management strategies were developed through consideration of project context, clarification of a complicated project vs. a complex one, and “stakeholder salience” (Maylor et al., 2008, p. S23). Attempts to address these topics led to a realization that human factors also needed more attention in refining system design. A paper by Belout and Gauvreau (2004) discussing human resource management and project success was used to identify different approaches people have towards projects and the value placed on the tools they have to deliver their project. Drawing on the many inputs from the above literature, an overarching objective of the research was apparent: the EVM application (and its necessary sub-systems) needed to contribute positively to the concept of valuing the project experience (Carù, Cova, & Pace, 2004) by not only improving project management but also by reducing the “struggle” needed to get jobs out “right” and on time.


Research Context

The research is being undertaken through an industry partnership between L&A Pressure Welding Pty Ltd (LAP), an Australian Small to Medium Enterprise (SME); and the University of Technology, Sydney (UTS). The academic link is achieved through UTS’s Master of Engineering Research Degree program and was initiated by LAP’s general manager, partly in response to an internal discussion paper issued by Engineers Australia addressing the nation’s longer-term manufacturing challenges (Engineers Australia, 2008). Funding of the academic association is provided through an Australian Government initiative, the “Research Training Scheme Program,” while commercial support and data access is provided by LAP.

This amalgam of interests suggested that development of EVM should be undertaken from a first principles approach, using established EVM methods and applying these through customized spreadsheets. The reasons behind this approach, as opposed to adopting a commercially available tool, was to provide opportunity to tailor all aspects of the inputs and outputs to ensure existing business processes and culture could be integrated with the application objective. It was also foreseen that any outputs needed to be understood in every detail so EVM behavior may be better comprehended. In addition, the approach was seen as a means of being able to alter the application strategy and observe the effect on outputs.

For SME manufacturing, EVM is seen as a useful device to have available, an opinion that is supported in Besner and Hobbs (2008). Accordingly, the application of EVM in a form that fits and improves the business operations and culture is a prime goal of this investigation. There is ample evidence for organizations to adopt many of the theories offered by project management literature; however, the value of these can only be realized if there are sufficient resources in the organization to drive the initial integration and assure upkeep. Frequently, however, SMEs such as LAP are human resource ‘poor’ and with this comes constraints on the actual value these theories can deliver to SMEs. Acknowledgment of this limitation has been central to this EVM application process mainly through considerations that address the issues of flexibility, control, fit and structure, all of which frequently appear in the literature (Aubiy & Hobbs, 2011; Kim, Wells, & Duffey, 2003).

Organization Background

Data for the research is being drawn from LAP. The organization grew from a small fabrication shop to a moderate-size design and manufacturing operation over the last 30 years. Its fabrication heritage has, until recently, dominated through what could be described as a “product-focused” culture. The past decade introduced design services, and with this, project scale and complexity began to grow. As a result the ad hoc approach to project management, which has largely been driven by Gantt charts and experience, no longer fits the project portfolio or strategic plans for the future.

Project Portfolio

At LAP, 25 to 35 projects typically run simultaneously throughout the year. Scope ranges from very small repair jobs to significant equipment supply for refinery upgrades and packaged contracts for resource developments. The diversity of projects and the presence of small jobs mean that project budgets range from a few thousand dollars up to approximately $8 million (AUD). Equally, durations can be from an immediate maintenance call out to a 24-month project cycle. The application of the research has been on projects that have a budget of approximately $60K and up, translating to about 10 weeks and up in duration. While the smaller projects are not of direct interest to EVM application, their presence in a portfolio impacts the finite resources available. These situations cause ripples in major project production and therefore have been taken into consideration when establishing the research methodology.



At the outset, in January 2009, the research targeted investigation of the potential of EVM as a tool for managing manufacturing projects of small to medium scale. Goals were aimed at measuring the methods performance in tracking and forecasting individual project progress. From this perspective, it was assumed that EVM would simply be plugged into randomly selected projects and the value EVM brought to the management process could be analyzed. During the first six months of investigation and trial application, it became apparent that the initial approach needed modification. Identified problems were thought to be related to the fact that business processes were not sufficiently developed to support EVM’s needs, particularly for building up detailed data sets. This observation was reinforced in a concluding statement by Kim, et al. (2003, p. 382) noting that ”…successful implementation of EVM, in terms of leading to better outcomes for projects, is not simply a matter of introducing the methodology into an organization. It must be associated with overall organizational approaches… and facilitating support systems.”

Limitations on being able to apply EVM in isolation changed the overall goals for the investigation from “EVM performance analyses” to a goal that includes “the EVM impact on an organization.” While the original objective of investigating EVM’s performance on small manufacturing projects remained a core output, it was obvious the adopted methodology for the research needed to include a much broader scope to achieve the objective of understanding and applying EVM to this project environment.

Overall methodology has been established from the basic guidelines provided by the Practice Standard for Earned Value Management (Project Management Institute, 2005) and the Australian Standard, Project Performance Measurement using Earned Value AS 4817 (Standards Australia, 2006), which covers budget, scheduling, time phase budget and distribution of value. Details of how each of these critical components is structured to achieve a balance between EVM requirements and its fit with the organization are noted in the following subsections.


The project budget (PB) and Budget at Completion (BAC) definitions and structure were modeled using the guidelines offered in AS4817. The Australian Standard was selected to maintain uniformity in the organization with respect to its ISO 9001 accreditation and offered a useful guide to project and business cost cells and their placement within these two budgets. Establishing how project allowances, business costs and contingencies were represented in the budget required significant effort in synchronizing these cost structures with the organization’s existing estimating and finance methods. An outline of the current budget dashboard illustrating the content of the BAC and the overall project budget is provided in Exhibit 1.

Budget Structure

Exhibit 1 – Budget Structure

Following several trials it was observed that a portion of the material and services consumed required cost fields that could be customized for each project. There were then a series of services common to all projects which lent themselves to a fixed description approach along with the consumable allocation. The final group identified was associated with human effort, including shop labor, engineering and quality management. Determining the content and the quantity of fields provided within each of these BAC groups required significant integration with estimating and purchasing processes to determine the number of variable fields to be available as well as what fixed description fields need to be offered.

The three remaining fields of company, contingency and profit were simple enough to identify; however, the calculations behind the values assigned provided more challenging. Net Profit was taken directly from the estimators “quote work sheets” and did not pose difficulty in identifying a value; however, stripping out overhead contribution and management reserve was not as simple. The overhead contribution field required agreement between the EVM cost model and regular accounts to ensure the fixed cost per hour, assigned to the projects estimated hours, would contribute enough to the company’s operational costs. “Contingency” calculations were initially focused on capturing “uncertainty margins” within the quote work sheet; however, the need to simplify the system’s user effort eventually led to the ‘contingency’ value displaying the balance of the contract value after subtracting the BAC, overhead contribution and net profit. Using this field as a balancing cell enabled it to absorb rounding errors and any unsustainable discounting which may have occurred during tender negotiations.

During the development of the budget and testing its flexibility to fit different project scenarios it was found that the suggestion by Kim, et al. (2003) to build flexibility “within a framework of general guideline” had proven to be beneficial. Once established, the flexibility offered by this approach made the actual application of this budget tool a much simpler process and has resulted in it becoming a standard practice for the organization. It is now applied even to projects that are considered too small for EVM. The reason for its broad uptake is in part due to its interaction with other functional managers outside the direct project management process.

Project schedules (Gantt charts) were an existing part of the organization’s culture, typically required by clients for projects of a size relevant to this investigation. As part of the restructuring undertaken due to this research, preparation of preliminary scheduling was transferred to the project management office. Final baselines are still set by the project engineers and are usually issued to the client within one to two weeks of receiving an order. Although initial scheduling responsibilities were transferred from the project engineer as a direct consequence of the research, the organizational culture applied to the process remained intact. The importance of retaining normal practices was seen as a way of ensuring there was minimal disruption to the flow of work and to also be sure of capturing normal schedule methodology due to the dependency EVM outputs have on schedules baselines.

Items manufactured by these projects are often assembled from large sections of raw materials to make equipment such as pressure vessels and heat exchangers. Individual materials can be a significant portion of the project’s BAC and frequently require long lead times relative to total project durations. The main components of these projects are relatively simple and identifiable, and are therefore suited to the work break down structure (WBS) process. Deliverables are typically considered to belong to one of six groups, those being engineering, quality assurance (QA), procurement, fabrication, testing / treatment and packing / dispatch. Through experience it has been found that the accuracy of the overall project duration, represented by the schedule, benefits from further break down of the work packages into their elements when preparing a schedule.
In contrast to the simplicity of the finished product, the manufacture and build sequence can become complicated as quality and process limitations constrain the process. The practice of breaking down the work packages when scheduling has advantages in ensuring the project scope and build sequence is well planned in advance of manufacturing. The downside of this process, though, is that it can create a lengthy and complicated schedule, diminishing its value as a communication tool when reporting progress. It also leads to difficulties in the EVM application when assigning estimated labor costs with actual work package activities and scaling these to a suitable time phased budget.

Time Phase Budget
The design of the present Time Phase Budget (TPB) was achieved over approximately a 12-month period through trial and error on varying projects. The main issue in developing its interface, from an organizational perspective, was achieving a balance in the number of fields needed to represent the budget and schedule feed documents. To date, the best arrangement for these fields has been to consider three main cost inputs: Engineering / QA and Administration (the indirect labor contribution); Purchasing and Subcontracting (the materials and services); and Manufacturing (the direct shop labor).

The Engineering /QA and Administration field offers five rows for input and has been set up as an independent and flexible cells group. The work descriptions applied to these are designed to represent the key activities within the schedules engineering and QA deliverables and to also carry across any administration allocations that have been included in the budget. Flexibility was applied to this group because its contribution to the overall project budget is typically small. The flexible approach also assisted user function as it was found that the physical delivery of these activities were frequently not clearly definable in terms of “being finished.” This was due to projects generally being executed under a concurrent engineering strategy which saw critical engineering completed to schedule while supplementary detail (not affecting progress) lagged for some time after the planned completion. Although the work in this field is best described as discrete effort, its entire completion is not a pre-requisite to achieving progress. For the purposes of applying EVM, the effort put into Engineering/QA is typically assigned to tangible deliverables that directly affect progress and is measured using a fixed formula of 0/100 (Project Management Institute, 2005, p. 11). An example of this would be ‘calculations and general arrangement details submitted.’ The approach has simplified the allocation of earned value for the user and is believed to realistically represent progress in an area that has an ‘on and off’ impact on manufacturing.

The Purchasing and Subcontracting field has been set up to display the description entered into the three groups (15 cells) making up the material and services BAC. Unlike the Engineering and QA, material and service descriptions are established through interaction with the estimators’ quote work sheet and BAC, rather than the schedule content. As this field delivers a large portion of the project’s budget, it was considered important to limit flexibility and user input while increasing control over alignment between the budget and the time phasing fields. It has been found that materials are best treated as discrete effort and assigned 100% of their value on delivery into the factory. This allocation method is in line with the prescribed method from PMI (2005, p. 9-11). Services are considered as sub-contracted activities of tangible product. The value of these is typically high in proportion to overall material budget and usually extends over several measurement periods. Through several trials and taking user effort into consideration, it was found that the best means of allocation was using a weighted milestone as suggested by PMI (2005, p. 9-11) and dividing the budget value equally over the planned duration periods.

The Manufacturing field represents the direct labor value provided in the budget. Establishing a methodology to bring together the single line “shop labor value” from the budget and the decompressed schedule activities presented several difficulties. Initially it was necessary to determine the number of cells that would provide adequate scale to EVM while not making it overly difficult for the user to allocate earned value as progress was made. Through trails and interaction with estimating, it was determined that nine “work description cells” offered a good balance between detail, user effort and alignment with existing estimating practices when dealing with pressure vessel and exchanger projects. The next step was to develop a logical approach to bring together the single budget allowance and the multiple schedule activities. Initial attempts were based on using an approximated percentage of the budget value for each cell description. The content of the cell descriptions were based on tangible milestones in the manufacturing process and that used by estimating to summarize pressure equipment scope. Although this percentage allocation worked, it was susceptible to user opinion, which transposed to differed planned value curves under testing conditions and suggested that this method was unable to deliver consistency. The approach also required a high degree of product knowledge and was unable to provide any firm alignment with the schedule. In the context of the investigation, these issues were seen as significant in establishing a system that needed to be robust for both industry application and academic validation.

Considering dependencies between the TPB and schedule, and also looking at the difference between the time values of work effort vs. actual scheduled durations, an alternative method of allocation was derived. From the initial trials, it was found that the method of applying milestone activities to the nine flexible “work description cells” (WDC) functioned well, providing sufficient opportunity to distribute project scope into relatively even segments over the manufacturing process. Allocation was then approached by grouping the many scheduled activities into one of the nine WDC. This typically resulted in three or more scheduled activities representing a single WDC listed in the TPB. Labor values from the budget can then be transferred through a pro rata method to the decompressed TPB - WDC content.

Exhibit 2 provides a tabulated example of how the method expands the WDC, assigns labor value based on scheduled work, and then re-compresses it for easier use in EVM application. This approach secures representation of the schedule in terms of specific activities and their planned duration, and maps this with a portion of the budgeted value for labor. The process has eliminated the original reliance on user approximation and simplified the process of cost assignment to the TPB. Using this method it is possible to compress a very detailed schedule from an extensive list of activities into the TPB’s nine rows while maintaining a structure that has the necessary degree of logic to achieve consistency needed.

Labor Budget Allocation Example

Exhibit 2 – Labor Budget Allocation Example

Project Data Capture
Collecting accurate data on project progress has been an important part of this investigation and evolved from a research function to a process that also added value to the organization for future use in understanding and managing other processes. To support EVM it was necessary to collect data relating to the three main cost fields identified by the TPB. The need to meet research standards in data collection required higher sample rates of “frequency and granularity” (Project Management Institute, 2005, p. 4) than might normally be needed for projects of this nature. Exhibit 3 summarizes the activities that are being used to feed EVM for this investigation and the sample rates applied.

EVM Data Feeds and Measurement Frequency

Exhibit 3 – EVM Data Feeds and Measurement Frequency

Live Project Interface
After the first trial it was evident the method could be used on the projects in question and would benefit the organization. However, the extent to which EVM should be embedded in the organization raised questions over the decision to actively use it and report its outputs as a project tool while the research was being conducted. There were several areas of concern, particularly whether there was sufficient clarity in the systems, processes and established tools to allow others to be trained in its application without requiring vast knowledge of the method’s background. Other concerns were related to how EVM and its support systems would interact with the short-duration, high-material component and the tight schedule of the project setting. A final consideration (noted after observing initial results) was the dependency of EVM outputs and the schedule baseline accuracy and the project-build sequence. The net effect pointed to the importance of better understanding the organization’s normal practices and project trends so EVM outputs could be understood within a known context. Many of the above issues were addressed in Kim, et al. (2003, p. 378-381), all of which foreshadowed a need for sensitivity in how EVM should be introduced and supported in the day-to-day operations of the organization. For these reasons it was agreed that the actual uptake of the method into the organization should not occur until after the research, system structure and tools were finalized. This decision was based on the objective of being able to make a formal transition to an EVM system by presenting a positive, well-defined and integrated method, requiring minimal input by project staff but offering clear benefits over the existing time-based tracking method. Despite the decision to not manage projects with EVM directly during development, the research is still utilizing schedules, plans, data and events from live projects to feed “very real” project scenarios into the development process, allowing results to be analyzed against actual outcomes and hopefully building a robust system for the future.

Sample Projects

Project Dimensions and Setup
Data collection, implementation and organization strategies discussed in this work have been built around the single host organization and observations from numerous projects undertaken since 2009. Actual EVM outputs discussed in this paper are taken from two similar projects and discuss the methods employed to build up the EVM data, the curve generated and their response to date relative to actual project outcomes. The two projects are identified as A001 and A005; they were both medium–size, thin wall (16mm) carbon steel pressure vessels requiring an internal surface treatment in addition to the normal fabrication effort in vessel manufacturing. Exhibit 4 summarizes the dimensions of the two projects.

Sample Projects Data Summary

Exhibit 4 – Sample Projects Data Summary

Both projects have been set up using data captured as described in the above “Project Data Capture” discussion and entered into the EVM workbook as described under “Methodology” shortly after the completion of the project. In addition, A001 was originally set up and updated in parallel with the project's manufacture, using the initial trial method where an approximation of labor value per TPB activity was assigned based on experience. It was found there was little difference in the EV outputs between the two methods used on project A001. In addition, the curves themselves for A001, A005 and several other projects, not discussed here, appeared to represent their respective projects ‘actual progress’ with acceptable accuracy for the application being sought by this investigation.

Data collection and TPB entry has been based on a weekly frequency in both cases; however, the EVM workbook has been set up to compress the weekly data into fortnightly and monthly measures so further observations can be made about output results with respect to frequency. Established EVM calculations for performance analysis and forecasting have been prepared from those offered in the Practice Standard for Earned Value Management (Project Management Institute, 2005, pp. 15-22), Earned Schedule calculations were prepared from the method presented in (Lipke, Zwikael, Henderson, & Anbari, 2009, pp. 401-402) while supplementary forecasting methods draw on analogies made between forecasting final costs and the time based schedule variances offered by (Henderson & Lipke, 2006, pp. 27-28). These concepts were coupled with estimate at completion equations offered by (Project Management Institute, 2005, p. 21). To date, interest has been in the standard EVM curves: PV, EV and AC and the schedule variance (time) curve SVt. Schedule duration has been the focus of forecasting investigation, which coincided with initial research goals of having the ability to predicting end dates with some degree of objectivity. (The EVM workbooks have been setup with cost forecasting equations as detailed in the above citation for future investigation, but are not discussed in this paper.) Abbreviations used in calculations and curve legends are summarized in Exhibit 5 for reference:

Abbreviations and Terms

Exhibit 5 – Abbreviations and Terms

All forecasting outputs presented here are based on the method of ES and SVt. This approach was chosen over the schedule variance, as described in PMI’s Practice Standard for Earned Value Management (2005, pp. 17-18), due to ES gaining recognition as a more robust approach to measuring time variance. However, for the purpose of research, the Practice Standard methods have been built into the EVM spread sheet for reference in later work but are not of concern to this discussion. Final forecasting durations have been displayed as a percentage of IEACPF over the project ADR resulting in graphs that converge to 100% as the forecast duration closes in on the final project duration. Equations presented in Exhibit 6 have been used in calculating the IEACPF values that are displayed over the ADR in the forecasting plots in Exhibits 7 and 8.

Forecast Equations

Exhibit 6 – Forecast Equations

The following EVM / SVt and forecasting graphs show projects A001 and A005 using the weekly frequency cycle only. The SVt curve has been overlaid on the EVM plot using a second axis (RHS), as it was found useful to be able to visualize the difference between the PV and EV curves as a time measurement. The forecast duration graphs illustrate the best option for the IEACt,IF curve, which is influenced by the factors used in CPIf & SPIf that weights the result toward the cost or schedule performance.

Project A001 Results from Weekly Frequency

Exhibit 7 – Project A001 Results from Weekly Frequency

Project A005 Results from Weekly Frequency

Exhibit 8 – Project A005 Results from Weekly Frequency

The weekly frequency cycle has been found to be the most informative for internal communication of a project’s progress; it also provided the best fit for the organization’s production planning functions which are also carried out on a weekly basis. However, the forecast outcomes of these projects can change dramatically in a few days if resources are utilized across shift work or they can perform tasks in parallel if access constraints permit. Fortnightly and monthly reporting displayed less erratic curves; therefore, it is believed these frequencies would be more suited to reporting to clients on anticipated delivery dates.
Forecasting curves under the weekly cycle can become quite noisy;
the fortnightly and monthly frequency eliminates this occurrence, the peak values are typically retained. Weighting the long Form IF equation toward SPIf, for both of these projects improved the outcome of this curve while other curves are not influenced by this option. At this stage, the influence of these factors requires further work to explore relationships between project duration, schedule and cost forecasting over various project life cycles. An observation from A005 (and numerous other projects) indicates SVt frequently shows a marked change nearing the end of the project, i.e., the project has a “remarkable” recovery. From an EVM calculation viewpoint this translated to an increasing error in SVt as the project progresses, while CPI, although outside this discussion, has shown extreme error at the beginning of a project and good forecasting from approximately 50% of the ADR to completion. The combination of these two front-end and back-end deviations may be contributing to the continual poor performance of IEACt,IP, which uses the product of these two indices, whereas the other methods are not as dependent on the combined values.

As noted in the previous paragraph, many of the projects display remarkable recoveries in their closing stages. As EVM has not been used in actually live-tracking the projects at this stage, it is believed these recoveries are indicating an industry propensity to increase effort as the project gets close to completion and a firm end date can be determined by “gut feel” and driven by tangible constraints such as meeting clients’ plant shutdown deadlines or heavy transport arrangements. These observations are supported by the experiences of the principal author over the past 10 years in delivering projects to this industry, where projects frequently travel late with respect to the schedule and then recover within sight of the end to finish close to the initial planned duration time. By mapping these projects and visualizing the forecasting, it is possible that there is an underlying issue present in the organization with respect to scheduling culture. Looked at in another way, there is perhaps too little time being allowed at the front end, precipitating the “late” trend followed by too much time at the back end which EVM is seeing as a recovery, when in fact EVM has been able to illustrate the normal project and manufacturing cycle. It is acknowledged that more work is required on these aspects; however, it is conceivable that EVM data could be used to develop a scheduling method that better represents an organization’s performance culture as well as tracking projects as it is intended to do.


The application of EVM to this manufacturing organization and its pressure equipment projects has produced many benefits. While initial goals were set on project-specific activities, the dependencies of EVM on the wider organization were the catalysts for the main improvements seen to date. To achieve the necessary data streams with the accuracy needed for EVM to function reliably, considerable tightening of the project management processes was required. In addition, better interface management between estimating, project and accounts was necessary. To achieve these structural changes, the theories of project portfolio management have clarified the contract management and estimating roles and framed the project engineering function for individual jobs. Even without running EVM as a tracking tool on current projects, the tighter control and availability of data streams coupled with the central portfolio methodology has reformed the production management function of the organization. The weekly review of production is now driven by the portfolio office, where priorities are established based on current work. The data streams capturing shop labor are also funneled into this resource matrix and published across the organization on a weekly basis. The data is also utilized in preparing a monthly shop load model. The transparency and continual project updates have helped in raising the profile of project performance and encouraging continual improvement in production control and management.

A prominent benefit from this process has been unifying the costing structure of the business in response to the transparency of project financial performance delivered by EVM. This has flowed into improvements in tendering and risk management. Benefits are in the form of building up a detailed library of project history that has the potential to greatly improve tendering accuracy while reducing the effort and cost of the function. EVM formatted data, forming part of the budget tool created for the system, has provided access to labor profiles for projects and is now being coupled with the shop loading from production to gain an overview of a project’s peak labor period with respect to the project cycle time and the shop load. These tools are helping the organization to improve its initiation/integration phase by being able to check if a project can be offered at a delivery that suits the client and fits the organization’s existing work load.

Although there was a level of expectation that EVM when applied to pressure equipment manufacturing would be focused on individual project benefits, it has been found under this application the benefits are much greater than expected because of its influence on the organizations structure. Due to the spread of the EVM system into these ancillary functions in this example, it is evident there is much work to be done on understanding and valuing EVM as a management tool for SMEs that are project oriented, as well as investigating the behavior of EVM in managing and tracking short duration manufacturing projects.



Aubry, M., & Hobbs, B. (2011). A fresh look at the contribution of project management to organizational performance. Project Management Journal, 42(1), 3-16.

Belout, A., & Gauvreau, C. (2004). Factors influencing project success: The impact of human resource management. International Journal of Project Management, 22(1), 1-11.

Besner, C., & Hobbs, B. (2008). Discriminating contexts and project management best practices on innovative and noninnovative projects. Project Management Journal, 39(S1), S123-S134.

Carù, A., Cova, B., & Pace, S. (2004). Project success: Lessons from the Andria Case. European Management Journal, 22(5), 532-545.

Cooke-Davies, T. J., Crawford, L. H., & Lechler, T. G. (2009). Project management systems: Moving project management from an operational to a strategic discipline. Project Management Journal, 40(1), 110-123.

Dixon, G. (2011). Service learning and integrated, collaborative project management. Project Management Journal, 42(1), 42-58.

Dooley, L., Lupton, G., & O’Sullivan, D. (2005). Multiple project management: A modern competitive necessity. Journal of Manufacturing Technology Management, 16(5/6), 466-482.

Engineers Australia. (2008). Manufacturing - Engineers Australia Discussion Paper (Internal Distribution Only): Engineers Australia.

Henderson, K., & Lipke, W. (2006). Earned schedule: An emerging enhancement to earned value management. CrossTalk, 26-30.

Kim, E., Wells, W. G., & Duffey, M. R. (2003). A model for effective implementation of earned value management methodology. International Journal of Project Management, 21(5), 375-382.

Kuprenas, J. A. (2003). Implementation and performance of a matrix organization structure. International Journal of Project Management, 21(1), 51-62.

Lipke, W., Zwikael, O., Henderson, K., & Anbari, F. (2009). Prediction of project outcome: The application of statistical methods to earned value management and earned schedule performance indexes. International Journal of Project Management, 27(4), 400-407.

Maylor, H., Vidgen, R., & Carver, S. (2008). Managerial complexity in project-based operations: A grounded model and its implications for practice. Project Management Journal, 39(S1), S15-S26.

Project Management Institute. (2005). Practice standard for earned value management. Newtown Square, PA: Project Management Institute.

Standards Australia. (2006). Project performance measurement using earned value AS 4817-2006. Sydney, Australia: Standards Australia.

© 2011, David Fox, Mary Walmsley & David Eager
Originally published as a part of 2011 PMI Global Congress Proceedings – Dallas, North America



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