Cost and resource estimation can be an challenging aspect of project planning for any industry. As the lecture this week pointed out, the planning phase involves going through individual tasks within the WBS structure to determine where to allocate costs and resources. Common pitfalls include estimating wildly off mark, assuming costs before the tasks are finalized, not accounting for risk and associated contingency plans, and failing to incorporate vacations or typical work week hours. While these oversights are basic in nature, they can have detrimental effects on the project. For example, an initial biocompatibility task that was budgeted out at a particular cost may require additional testing that would now be outside of budget constraints. This could lead the device to be gatekept by regulatory requirements to undergo further testing and ultimately lead to a failed project. How do estimation failures in the planning phase of a medical device project threaten the success of a project/product? Given employee vacations, holidays, and typical work weeks, how should PMs account for theoretical vs realistic employee resource allocation? Lastly, what do you believe is the most effective way to structure contingency plans for costs and resource estimates to protect against potential roadblocks?
As mentioned, estimation failures can be detrimental in the planning phase of a medical device since they can disrupt budgets and timelines but also the confidence of stakeholders. Compared to general engineering projects, medical devices have to meet strict verification, validation, and compliance requirements that must be addressed early to avoid costly results. Early activities such as biocompatibility testing and verification of risk mitigation are underestimated since they can affect the product from reaching regulatory submission, which can lead to a forced cancellation of the project. Failures can then cascade to outcomes such as increased labor costs, missed deadlines that delay other deadlines, and loss of confidence. Underestimating resource availability can also slow operations, especially if the key engineers are not available for documenting or testing.
In order to account for realistic resource allocation, a PM has to approximate productive hours instead of predetermined full-time hours. For example, a PM should assume that instead of there being 40 productive hours, a PM should take into consideration meeting times, company events, vacations, holidays, and unexpected interruptions, which can reduce productivity. Organizing contingency plans is most effective when there can be operational and project level activities. High risk tasks like clinical testing or regulatory review should have more mitigation mechanisms. Meanwhile, regular project reviews and checkpoints allow teams to make estimates and adjust plans early before the situation escalates. It is also essential to consider if it is better to distribute contingency plans for individual tasks or to just focus on contingency plans to maintain general flexibility on the project.
Including costs and resources in the risk management analysis can lower project estimates. Finding alternatives to different resources to mitigate risk can increase project success. Having a vendor when internal production issues arise, or training additional employees for coverage, are examples. Furthermore, setting aside a percentage of the project budget for risk is essential and may require the input of multiple department heads. The medical device's class is a factor in how much of the project budget should be allocated to risks. Class 1 medical devices may only need to maintain general flexibility for any setbacks. In comparison, class 2 or 3 medical devices that require clinical trials may favor task-based plans because they will make monitoring easier with a higher budget and more resources. Nonetheless, the project manager needs to understand what is available before making any commitments.
Estimation failures in the planning phase of a medical device project can severely threaten the success of a project because cost, project timeline, and regulatory compliance are connected. If tasks in the work breakdown structure like verification testing or biocompatibility testing are underestimated, the project may require additional testing that goes over the set budget or the timeline. Underestimating could also delay submission to the FDA or even pressure teams to rush validation tests, which would jeopardize the product quality and patient safety. Project Managers should account for realistic employee resource allocation by not assuming an employee is available 100 percent of the time for one project. One way that PMs can plan for this is to use a resource calendar that tracks the availability, allocation, and utilization of team members. An effective contingency plan that protects against potential roadblocks should combine time and budget buffers for high-risk tasks and a management reserve. A management reserve is an amount of the project budget withheld for management control intended to address unforeseen events that may happen in a project.
I agree that estimation failures can create bigger problems than just going over budget. In medical device projects, cost, timeline, and regulatory approval are all connected. If one part is underestimated, it can affect everything else. It can also create pressure on the team to move faster than they should, which increases risk.
For resource planning, PMs should not assume employees are available 100% of the time. Meetings, vacations, and unexpected issues always reduce productive hours. Planning for 70–80% capacity is more realistic and helps prevent schedule delays later.
For contingency planning, I think it works best to separate it into two parts. Add extra buffer to high-risk tasks like clinical or verification testing. Then keep a separate management reserve for true unknowns. This keeps the project flexible without overusing one large reserve.
Overall, building realistic estimates and small buffers early is much easier than fixing problems once the project is already off track.
One factor that has not been discussed is how learning curves can affect the cost and resource estimates. Many tasks in medical device development can involve processes that the team will be doing for the first time. This would require them to embark on a learning curve, which does not have an exact timeline if the task is very difficult and requires a lot of learning. The team might have to learn a new type of test protocol or a new regulatory pathway. The first couple of attempts might take more time and resources than later ones, but this curve must be accounted for by PMs when planning.
Documentation requirements can also cause delays that PMs should account for. Even if the technical work is done efficiently and quickly, the documentation process can take a large amount of time that the team cannot fully control.
I think information bottlenecks are the biggest challenges for resource planning. There are certain people who have critical knowledge on the design or testing process, and if tasks depend on this individual, the person is a bottleneck that slows down the entire process. A PM must reduce this risk by distributing knowledge much earlier in the project process. This can be done with documentation or cross training. Multiple team members that have critical knowledge will allow for multiple pathways for each item in the project, allowing for failsafes when one individual team member is falling behind.
Planning for regulatory iteration is another approach to contingency planning that hasn’t been mentioned yet. Regulators might request more data or clarification before approving the device, even if the testing was successful. The schedule will get delayed if it assumes that approval will happen right after the testing is successful. Allocating time and resources for a revision cycle will allow for a more realistic cycle with a proper buffer.
Do you think PMs should always assume at least one round of additional testing after submission, or would this make budgets unnecessarily high? Additionally, do you agree with multiple people having critical knowledge from cross-training, or do you think only the experts should handle critical tasks? How can AI be incorporated into the pipeline to prevent bottlenecks or other issues with schedule delays?
Estimation failures during the planning phase can threaten the project's success, as the project is more likely to have a higher burn rate, increasing the risk of running out of budget before project milestones are completed. Actual resource costs are higher than planned, and actual resource utilization can be lower despite these higher costs. Now in the execution phase, the cost of change increases when the team takes longer to identify or handle a defect. As project tasks are completed, it becomes more difficult to revise documentation, redo testing, or purchase alternative resources. These additional activities are common, but take more time, and can discourage stakeholders. If the project continues, the deliverables may worsen and fall below the organization’s standards. The learning curve discussed in the previous post can contribute to suboptimal outcomes because experimentation involves uncertainty. Considering additional rounds of testing early on can mitigate risk and is recommended. However, if possible, they can even be used for post-approval studies. Cross-training helps a lot with resource allocation. It depends on the organization as to whether they want backups for the experts. This is where personalities also come into play, including whether the experts are motivated to share their knowledge.