EVM Forecast Accuracy: Navigating Variance and Trends

Earned Value Management (EVM) is a project management technique that combines measurements of scope, schedule and cost to provide an accurate assessment of a project's performance. By utilizing EVM, project managers are able to create realistic forecasts that enable stakeholders to compare the actual performance of a project against its original baseline.

EVM incorporates several key metrics including planned value (PV), earned value (EV) and actual cost (AC). PV represents the planned or budgeted cost of completing work at a specific point in time, while EV represents the actual value of work completed to date. AC represents the actual cost incurred to complete the work. By analyzing these metrics, project stakeholders can clearly understand whether a project is on track, behind, or ahead of schedule and cost.

One of the main benefits of utilizing EVM to create realistic forecasts is that it allows project stakeholders to compare the performance of a project against the project baseline. This enables them to identify any deviations and take corrective actions as necessary. Additionally, EVM allows stakeholders to make better decisions by analyzing trends and using advanced analytics.

Having accurate forecasts is important so that project stakeholders can gain better visibility into the progress and performance of a project. This enables them to make informed decisions and take proactive measures to keep the project on track. Furthermore, it increases the likelihood of project success by minimizing risks and ensuring that the project is delivered within budget and on time.

Overview of Variance Analysis and EVM Key Indicators

In project management, it is crucial to have a comprehensive understanding of a project's performance to ensure its success. Variance analysis and the use of key indicators both play a vital role in analyzing project performance and allowing managers to make informed decisions and take corrective actions when necessary.

Tracking cost and schedule variances provides a straightforward indicator of problems or opportunities. Tracking variances over time shows trends that can indicate where corrective actions or adjustments to schedule or budgets/forecasts are required. Variance analysis and reporting can also serve as a good mechanism to communicate project status to stakeholders.

The purpose of EVM key indicators is to provide a holistic view of a project's cost and schedule performance. These indicators enable project managers to determine the project's health, identify potential issues or risks, and monitor progress towards achieving project objectives. They serve as a benchmark for measuring project progress, helping managers to stay on track and make timely adjustments.

Some of the main indicators used in EVM include Cost Performance Index (CPI) and Schedule Performance Index (SPI). These are two widely-used metrics that compare project performance against baseline expectations. Variance analysis allows project managers to compare planned versus actual performance to identify discrepancies and take corrective actions. The To Complete Performance Index (TCPI) helps predict the future performance needed to achieve project objectives. Additionally, Key Performance Indicator (KPI) trends provide insights into the overall project performance and progress over time.

Introduction to EVM Metrics

EVM integrates the scheduling, cost control, and performance measurement of a project, providing a comprehensive view of its overall status.

As we introduced earlier, EVM compares the actual value of work completed with the planned value of work and the actual cost incurred. Comparing these metrics provides insights into project performance. This is done using various performance indexes such as SPI and CPI.

SPI provides a measure of whether or not a project is on track to finish on schedule by measuring the schedule efficiency of the project, while the CPI is used to determine the cost efficiency of the project.

Calculating Project Outcomes Using EVM

Future project performance is likely to follow historic performance, so our objective is to utilize indexes to access project efficiency and leverage this data to validate the forecast. Predicting project outcomes using Earned Value Management involves several steps. Here is a step-by-step guide on using EVM metrics to assess project performance and progress:

1. Collect Data: Gather project data such as planned value, actual cost, schedule progress and cost forecasts from project plans, budgets, and reports.
2. Calculate EV: Determine the value of work completed by comparing the actual progress against the planned schedule and milestones.
3. Calculate Schedule Variance (SV): SV measures the difference between the earned value and the planned value, indicating if the project is ahead or behind schedule. SV = EV - PV. Positive SV indicates ahead of schedule, while negative SV suggests a delay.
4. Calculate Cost Variance (CV): CV determines the difference between the earned value and the actual cost, revealing if the project is over or under budget. CV = EV - AC. Positive CV indicates being under budget, while negative CV indicates going over budget.
5. Calculate SPI: SPI measures the project's efficiency in terms of time. SPI = EV / PV. SPI > 1 demonstrates a faster pace, while SPI < 1 implies slower progress.
6. Calculate CPI: CPI evaluates the project's efficiency in terms of costs. It shows the efficiency rating of the budgeted cost of the work performed. CPI = EV / AC. CPI > 1 (good) indicates the performance outpaces actual cost of the work; CPI < 1 (bad) indicates the actual cost of the work outpaces performance.
7. Calculate TCPI: TCPI estimates the performance required to meet remaining project goals concerning budget. TCPI = (BAC - EV) / (BAC - AC). If TCPI > 1, the remaining work needs to be completed more efficiently to meet the budget.
8. Calculate TCPI eac: TCPI eac is an indicator of the validity of the forecast. TCPI eac = (BAC – EVcum) / (EAC – ACcum). If TCPI eac > 1, then resources are being utilized efficiently for the remainder of the project; otherwise, improvements are needed.

If TCPI eac is very different from CPI, the forecast may need to be updated with a more realistic value.

Price and Usage Variance

Knowing if the cost variance to date is due to the resources costing more than budgeted (a price variance) or if it is taking more hours than budgeted (a usage variance) is an important factor to understand when creating a forecast. There is more information about determining the price/usage variances in our Variance Analysis guide.

If the resources are costing more than budgeted, then you need to change the forecast rate. The remaining hours are then multiplied by the new rate to calculate the new forecast costs.

If the work takes more hours than budgeted, the remaining hours must be changed. If the TCPIeac is very different than the CPI to date, then a good method to factor the remaining hours is to use the CPI:

EAC = 1/CPI (BAC - EV) + AC

This formula multiplies the remaining budget by 1/CPI and then adds the actual costs to date. This assumes the remaining work will have the same CPI as the cumulative to-date CPI. Using factors to multiply the remaining is typically called a statistical forecast. There are a number of different statistical forecast methods. This method includes the Schedule Performance Index (SPI) and it often calculates the worst-case scenario:

EAC = 1/(CPI*SPI) (BAC - EV) + AC

Calculating multiple statical forecasts will give you a range from best-case scenarios to worst-case forecasts.

Forecast Accuracy Levels and Improvement Techniques

Forecast reliability is vital for effective project planning, resource allocation, and decision-making. Several variables can impact forecast quality, so let's review them and discuss options for improvement.

Firstly, data quality plays a crucial role in forecast accuracy. Poor data quality, such as incomplete or inconsistent data, can lead to inaccurate forecasts.

Secondly, the choice of forecasting techniques and models can significantly affect accuracy levels. Organizations must select appropriate forecasting methods based on their industry, historical data patterns, and future requirements. Different industries may require different forecasting approaches, such as time series analysis, regression analysis, or qualitative techniques.

Estimating budgets accurately helps organizations allocate resources effectively, control costs, and ensure the project's financial feasibility. It is important to consider past experience, industry benchmarks, and potential risks to help improve accuracy.

To validate forecast accuracy and compare details to similar projects, performance indexes are useful tools. They provide standardized metrics to evaluate and benchmark forecast accuracy. These metrics enable organizations to assess their performance against industry standards and identify areas for improvement.

Improvement techniques for forecast accuracy and budget estimation include continuous monitoring and evaluation, incorporating feedback loops, using advanced analytics and machine learning algorithms, and employing expert judgment. By adopting these techniques, organizations can enhance their forecasting capabilities and achieve more accurate predictions and budget estimations, leading to improved project outcomes and better resource management.

In the dynamic landscape of project management, accurate forecasting is crucial to achieving successful outcomes. Earned Value Management is a powerful technique for harmonizing project scope, schedule, and budget, empowering project managers with a robust predictive toolset. Deltek Cobra is the trusted industry leader in cost and earned value management. By analyzing metrics like planned value, earned value, and actual cost, Deltek Cobra enables project managers to forecast cost variations and take timely corrective actions, guiding projects toward efficient cost management and enhancing the likelihood of success within budgetary constraints.