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It can be seen that the project was actually under budget, relative to the amount of work accomplished, since the start of the project. This is a much better conclusion than might be derived from Figure 1. Figure 4 shows all three curves together — which is a typical EVM line chart. The best way to read these three-line charts is to identify the EV curve first, then compare it to PV for schedule performance and AC for cost performance. It can be seen from this illustration that a true understanding of cost performance and schedule performance relies first on measuring technical performance objectively.

This is the foundational principle of EVM. The foundational principle of EVM, mentioned above, does not depend on the size or complexity of the project. However, the implementations of EVM can vary significantly depending on the circumstances.

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In many cases, organizations establish an all-or-nothing threshold; projects above the threshold require a full-featured complex EVM system and projects below the threshold are exempted. Another approach that is gaining favor is to scale EVM implementation according to the project at hand and skill level of the project team. There are many more small and simple projects than there are large and complex ones, yet historically only the largest and most complex have enjoyed the benefits of EVM. Still, lightweight implementations of EVM are achievable by any person who has basic spreadsheet skills.

In fact, spreadsheet implementations are an excellent way to learn basic EVM skills. The first step is to define the work. This is typically done in a hierarchical arrangement called a work breakdown structure WBS although the simplest projects may use a simple list of tasks. In either case, it is important that the WBS or list be comprehensive. It is also important that the elements be mutually exclusive , so that work is easily categorized in one and only one element of work. The most detailed elements of a WBS hierarchy or the items in a list are called activities or tasks.

The second step is to assign a value, called planned value PV , to each activity. For large projects, PV is almost always an allocation of the total project budget, and may be in units of currency e. Assigning weighted values and achieving consensus on all PV quantities yields an important benefit of EVM, because it exposes misunderstandings and miscommunications about the scope of the project, and resolving these differences should always occur as early as possible. Some terminal elements can not be known planned in great detail in advance, and that is expected, because they can be further refined at a later time.

The third step is to define "earning rules" for each activity. These simple earning rules work well for small or simple projects because generally each activity tends to be fairly short in duration. These initial three steps define the minimal amount of planning for simplified EVM. The final step is to execute the project according to the plan and measure progress.

When activities are started or finished, EV is accumulated according to the earning rule. This is typically done at regular intervals e. In fact, waiting to update EV only once per month simply because that is when cost data are available only detracts from a primary benefit of using EVM, which is to create a technical performance scoreboard for the project team.

In a lightweight implementation such as described here, the project manager has not accumulated cost nor defined a detailed project schedule network i. While such omissions are inappropriate for managing large projects, they are a common and reasonable occurrence in many very small or simple projects.

Any project can benefit from using EV alone as a real-time score of progress. One useful result of this very simple approach without schedule models and actual cost accumulation is to compare EV curves of similar projects, as illustrated in Figure 5. In this example, the progress of three residential construction projects are compared by aligning the starting dates.

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If these three home construction projects were measured with the same PV valuations, the relative schedule performance of the projects can be easily compared. The actual critical path is ultimately the determining factor of every project's duration. Because earned value schedule metrics take no account of critical path data, big budget activities that are not on the critical path have the potential to dwarf the impact of performing small budget critical path activities.

This can lead to "gaming" the SV and SPI metrics by ignoring critical path activities in favor of big budget activities that may have lots of float. This can sometimes even lead to performing activities out-of-sequence just to improve the schedule tracking metrics, which can cause major problems with quality. In this way, the distorting aspect of float would be eliminated.

There would be no benefit to performing a non-critical activity with lots of float until it is due in proper sequence. Also, an activity would not generate a negative schedule variance until it had used up its float. Under this method, one way of gaming the schedule metrics would be eliminated. The only way of generating a positive schedule variance or SPI over 1. In addition to managing technical and schedule performance, large and complex projects require that cost performance be monitored and reviewed at regular intervals. In large implementations, the planned value curve is commonly called a Performance Measurement Baseline PMB and may be arranged in control accounts, summary-level planning packages, planning packages and work packages.

In large projects, establishing control accounts is the primary method of delegating responsibility and authority to various parts of the performing organization. Large projects require more elaborate processes for controlling baseline revisions, more thorough integration with subcontractor EVM systems, and more elaborate management of procured materials. The standard defines 32 criteria for full-featured EVM system compliance. Other countries have established similar standards. Additional acronyms and formulas include:. Proponents of EVM note a number of issues with implementing it, [11] [12] and further limitations may be inherent to the concept itself.

Because EVM requires quantification of a project plan, it is often perceived to be inapplicable to discovery-driven or Agile software development projects. For example, it may be impossible to plan certain research projects far in advance, because research itself uncovers some opportunities research paths and actively eliminates others. However, another school of thought holds that all work can be planned, even if in weekly timeboxes or other short increments.

Traditional EVM is not intended for non-discrete continuous effort. Traditional definitions of EVM typically assume that project accounting and project network schedule management are prerequisites to achieving any benefit from EVM. Many small projects don't satisfy either of these prerequisites, but they too can benefit from EVM, as described for simple implementations , above.

Other projects can be planned with a project network, but do not have access to true and timely actual cost data. In practice, the collection of true and timely actual cost data can be the most difficult aspect of EVM. Such projects can benefit from EVM, as described for intermediate implementations , above, and Earned Schedule. These risk profiles anticipate opportunities that may be revealed and possibly be exploited as development and testing proceeds. The published research resulted in a Technical Performance Management TPM methodology and software application that is still used by many DoD agencies in informing EVM estimates with technical achievement.

There is the difficulty inherent for any periodic monitoring of synchronizing data timing: This may limit EVM to a less tactical or less definitive role where use is combined with other forms to explain why or add recent news and manage future expectations. There is a measurement limitation for how precisely EVM can be used, stemming from classic conflict between accuracy and precision , as the mathematics can calculate deceptively far beyond the precision of the measurements of data and the approximation that is the plan estimation.

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The limitation on estimation is commonly understood such as the ninety-ninety rule in software but is not visible in any margin of error. The limitations on measurement are largely a form of digitization error as EVM measurements ultimately can be no finer than by item, which may be the Work Breakdown Structure terminal element size, to the scale of reporting period, typically end summary of a month, and by the means of delivery measure. The delivery measure may be actual deliveries, may include estimates of partial work done at the end of month subject to estimation limits, and typically does not include QC check or risk offsets.

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