When managing medical device projects, understanding where our project stands in terms of schedule and budget is important. This is where Schedule Variance (SV) and Cost Variance (CV) come into play, both of which are key components of Earned Value Management (EVM). SV helps us assess whether the project is ahead or behind schedule by comparing the Earned Value (work completed) with the Planned Value (work scheduled). Similarly, CV allows us to evaluate how well the project is sticking to its budget by comparing the Earned Value to the Actual Cost (money spent).
While SV and CV are useful for keeping projects on track, they come with their own set of challenges. One major issue is that these metrics rely heavily on accurate initial planning and budgeting. If the foundational project estimates are off, both SV and CV can give misleading information. For instance, if a medical device project underestimated the complexity of the design process, the Planned Value might be set too low. As a result, even if the SV shows that the project is ahead of schedule, in reality, the team might just be progressing based on flawed initial assumptions. Similarly, CV's effectiveness can be compromised if unexpected costs arise, such as the need for additional compliance testing, which was not included in the initial budget.
These challenges underscore the need for upfront planning and flexibility in project management, especially in fields like medical device development where changes are frequent and compliance is important. Have you experienced similar challenges with SV and CV in your projects? How do you manage the discrepancies that arise from initial planning errors or unforeseen expenses?
In the medical device industry, a primary challenge is to identify, investigate, and resolve deviations in a compliant manner while avoiding significant changes to major design controls. Deviation Management, as defined by the FDA, addresses unexpected or planned events that deviate from approved projects, impacting operational specifications during the development, manufacturing, and testing of a device. Deviation Management involves planned deviations that can be anticipated in advance due to temporary changes in processes or procedures. Conversely, unplanned deviations, as the name suggests, occur unexpectedly without prior notice. These deviations can arise from equipment malfunctions, human errors, or unforeseen circumstances. Therefore, a prompt investigation is essential to identify any impact on the quality of the medical device. A key component of this process is effective communication, which should have been documented from the start of the project. This documentation helps identify any lack of coordination throughout the development phase, enabling the management of earned value assessments. As you become more engaged in the medical device industry, where do you believe costly mistakes tend to recur more frequently in terms of safety and quality compliance with regulations?
Using Schedule Variance (SV) and Cost Variance (CV) in medical device project management presents several challenges. First, SV and CV are often based on planned values that may not account for regulatory delays unique to the medical device industry. Second, frequent changes in design due to clinical feedback can distort earned value calculations. Third, SV might show progress even if critical regulatory milestones are delayed, giving a false sense of schedule health. Fourth, cost overruns due to compliance testing may inflate CV without indicating actual inefficiency. Fifth, integrating SV and CV with iterative development models like Agile is difficult, as traditional Earned Value Management (EVM) assumes a linear workflow. Sixth, accurate tracking of earned value requires detailed work breakdown structures, which may be hard to maintain amid rapid prototyping. Seventh, external factors such as FDA audits can abruptly alter cost and time expectations. Eighth, cross-functional teams working across R&D, quality, and manufacturing may interpret variances differently, leading to misaligned priorities. Finally, overreliance on SV and CV may cause managers to overlook qualitative risks, like user safety or human factor issues.
There’s a lot of great insight here, especially around how SV and CV can be distorted in the complex and evolving landscape of medical device development. One thing that’s helped in projects I’ve been part of is blending traditional Earned Value Management with more flexible, iterative approaches. Using a hybrid model—where we still track planned and earned value within Agile sprints or iterative phases, lets us stay responsive to real-time changes without losing sight of long-term progress. It’s also been helpful to balance these quantitative metrics with a strong emphasis on qualitative risks. Sometimes, a project can look healthy on paper with favorable SV and CV, but that doesn’t mean the design is safe or intuitive for users. We’ve tried to embed regular human factors and usability reviews alongside the usual project checkpoints to ensure we’re not overlooking those critical elements.
Lastly, we've started using more adaptive planning techniques like rolling wave forecasting to update our schedule and budget assumptions as we gather more data. It’s been a practical way to avoid letting early inaccuracies snowball throughout the project. Rather than locking everything in upfront, we plan in detail only for the near-term work and keep revisiting assumptions for later phases, making our variance tracking much more meaningful.
You make a great point about how important those early estimates are when it comes to using SV and CV effectively. I haven’t used these metrics myself yet, but it makes sense that if the original plan is off, like underestimating how long the design process will take—then the numbers can be misleading. I like how you mentioned that even if SV looks good, it doesn’t always mean things are going smoothly. It seems like it’d be helpful to regularly check in and update the original scope and cost estimates as the project moves along. I’m curious too, do any of you use specific tools or have a system to keep those baseline estimates realistic as things change?
