Current Drawbacks of EVM at the Program Management Level

Concerns regarding Earned Value Management (EVM) practices on the Program Management level are often under-estimated. This article will start by explaining the importance of cost and schedule variances on the program management level (you should be familiar with these PMP® materials), rationalize why CPI and SPI can often be exaggerated on the Program level, and some of the good practices that organizations should adopt so that EVM calculations result in correct analysis for Program Managers to make optimal decisions that maximize the benefits passed back onto the stakeholders.


We will start with the simple cost and schedule variances.  Variances, in general terms, are the differences between a program’s management plan and the program’s actual performance. From independent projects’ standpoint, you are correct when you specified that cost and schedule variances greater than zero indicate “good” project performance progress (below budget and ahead of schedule). However, on the program level, negative variances are not always unfavourable. For benefits to be realized from a program and pass onto the stakeholders, we need to look at the interrelationships and interdependencies between the component projects in more detail, hence the variances and its implications are not always as straightforward as independent projects.  For example, if a component project is over budget due to the hiring of extra SME’s, in which the project is now being completed more rapidly and with higher quality, which translates to faster benefit realization to the program stakeholders, then the negative cost variances might be favourable in this case.  The same can be said about schedule variances, component project being early doesn’t always mean the program benefits are passed onto the program stakeholders early, and doesn’t always mean it’s a good thing.  For example, quality could have been less than expected, possible excessive overtime might have decreased employee morale and their future productivities when passed onto operations, and maybe decreased project/program scope result in compromised benefit realization upon program closure.  Understanding the reasons behind the cost and schedule variances helps program managers identify the causes and take corrective measures when necessary in order to maximize the realization of program benefits going forward.
CPI is a measure of the cost efficiency relative to the performance of tasks and completion on those tasks. In order for us to analyze why CPI is greater than 1, we not only need to look at our internal methodologies in calculating EVM measures, it is also critical to consider external factors that influence these measures. Below are a few examples of external risk factors that could influence our CPI calculation.  (Note that CPI = EV/AC):

  • External Market Conditions: if we have a fixed-price contract but due to favourable market conditions the price per unit of the material we need for our project/program reduced in pricing.  The budgeted cost of work performed (EV) remains at the contractual price, however, the actual cost of work performed (AC) is less due to the reduction in unit pricing of the material, resulting in positive CPI. This change is CPI is most likely temporary as opposed to long-term and systematic.
  • Centralized Shared Services: using the same fixed-price contract example, if the organization undergo restructuring and centralized services such as HR or procurement, reducing the actual cost of purchasing the materials we need and/or increase in labor efficiencies, positive CPI may result since our contractual budgeted cost remains the same. This CPI influence would most likely be long-term and systematic.
  • New Governmental Regulations: if new gov’t regulations stipulates the use of a new standardized IT/software for our program and its component projects, causing a revision increase in our original budgeted cost (EV), while the actual material and labor costs remains the same.  This could influence our CPI calculation to result above 1.  This CPI influencer could be short-term or long-term.

Standards and policies on how to measure task completion needs to be created and implemented organizational-wide and consistent across component projects of the program. Some common approaches to task completion criteria are (Source: PM Guru – EVA):

  • The best approach is to have detailed tasks planning with a percentage of PV assigned to each item or milestone within the task.  A complete WBS is critical.  As soon as that item is complete the amount of EV has been earned.
  • “0-100” technique: In this approach, no EV credit is allowed for a task until the task is complete. This is a good approach for short and discrete tasks, such as “place purchase order”.
  • “50-50” technique: In this commonly used approach half of the EV is credited to a task once the task is started and the other half is credited once the task is complete. This is usually done when the task is relatively long and will span multiple reporting periods.
  • “30-70” technique: This approach is good to use when the task has an uncertain estimate, such as software debugging. There is the recognition that work is underway, but the emphasis is on the completion of the task.

Even though the above few task completion criteria and techniques can ensure the EV be measured as accurately as possible, some risk factors can still falsely exaggerate the earned value at the program level.  Factors such as the work being done, the cost of the work, and the time allocated to the completion of that work can all have impacts on program performance, and hence, the EVM analysis.  For example, if each component project uses the data from one particular reporting period only, instead of looking at the measures across multiple periods, systematic variances could easily be overlooked as a one-time variance, and whether the variance is positive or negative, when extrapolated onto the program level, there will be exaggerated effects on the stakeholders when it comes to benefit realization.  Program managers may interpret the EV analysis wrong, and therefore unable to provide the necessary corrective actions to fix the ongoing issues to close the variance gaps (if any).  Overall, accuracy in EVM analysis and the program managers’ abilities to take into account the risk factors that may influence the interpretation is critical when optimizing the relationship between a program’s costs and its realized benefits, so that stakeholders and sponsors can make informed decisions based on the most updated and consistent EVM information.

Written by: Jenna Chou, PMP

November 26, 2016



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