In the fast-paced world of product management, prioritization is key to ensuring that the most important tasks get the attention they deserve. However, when you're a product manager in a heavily regulated industry such as digital health or medical devices, the traditional methods of prioritization must be adapted to meet stringent safety, privacy, and security regulations. In this blog post, we will explore some of the traditional prioritization methods used in product management and discuss how to modify them for use in regulated industries.
This method classifies tasks into four categories: Must have, Should have, Could have, and Won't have. It’s simple and effective for most industries, allowing teams to focus on what’s essential for the product launch.
The Kano Model helps prioritize features based on customer satisfaction. It categorizes features into five groups: Must-be, One-dimensional, Attractive, Indifferent, and Reverse. This model is particularly effective for enhancing user experience.
RICE stands for Reach, Impact, Confidence, and Effort. It’s a quantitative approach, giving a more objective view of what features or tasks should be prioritized based on their potential impact and the resources required. I take this and combine it with the Value & Effort method, plotting Reach & Impact on one axis and Confidence & Effort on the other. It helps in quickly identifying quick wins and major projects.
Before modifying any prioritization method, it's crucial to have a deep understanding of the regulatory landscape. This includes being aware of compliance requirements, safety standards, and privacy laws applicable to your product.
A thorough understanding of the reimbursement landscape is also essential. This includes knowing how healthcare providers get reimbursed for using your product, which can dramatically influence product adoption.
In regulated industries, compliance should be treated as a 'Must have' in the MoSCoW method. No matter how attractive or desired a feature is, if it doesn’t meet regulatory standards, it cannot be part of your product. Why not just take it at risk? Best case scenario, the lack of the feature is identified by the regulator or other third party and it lengthens your time to approval. Worst case scenario, you end up hurting someone.
Reimbursement is a trickier one. For a CT scan or radiosurgery, reimbursement will be a crucial factor. For direct to consumer products like CPAP masks or mobile ECG monitors like the AliveCor Kardia, is it enough that the product is FSA or HSA eligible?
In the context of medical devices or digital health, the Kano Model's 'Must-be' category should include features that ensure patient safety and data security. This might mean prioritizing encryption features or stringent data validation processes over user-experience enhancements. Similarly, features that simplify the reimbursement process, align with payer requirements, or enable FSA/HSA eligibility can significantly enhance customer satisfaction.
RICE is where we see the most opportunity to play with prioritization factors. Traditionally, RICE is defined as follows:
Reach: This factor estimates how many people (or units) will be impacted by the task or feature over a certain period, usually a month. Reach should be a numerical value, such as the number of users affected.
Impact: Traditionally, Impact measures the effect that the task or feature will have on each person or unit. It is usually assessed on a scale (like 0.25, 0.5, 1, 2, 3), with higher numbers indicating greater impact. This scale is subjective and depends on the specific goals and metrics of your project or organization. I like tweaking this to equate to impact on conversion rate.
Confidence: This factor is a percentage that reflects your confidence in your estimates of delivering on time.
Effort: Effort is an estimate of the total time required to implement the task or feature, often measured in person-months or person-weeks. It accounts for all the work that your team needs to put in.
When applying RICE in regulated industries, there is an opportunity to incorporate regulatory & reimbursement as follows:
Reach: Rather than making this a straight quantity of units, incorporate reimbursement and HSA eligibility.
Impact: Incorporate reimbursement and HSA eligibility into your scale, playing with the weighting.
Confidence: Incorporate into your scale ease of regulatory approval. Is your product truly novel and will require Regulators to re-think their approach to the product category? For example, surgical robots back when scalpels were the only available tool.Or is it a relatively well-worn path, like applying cooled RF to a new tissue?
Effort: Create a fuller picture by incorporating multiple dimensions like technical complexity, resource constraints, dependencies, testing & QA, documentation, and prototyping into your effort analysis. Creating your own effort scale like the below could be used to supplement the time estimate.
By adjusting the RICE components, the resulting Value (Reach times Impact) & Effort (Confidence times Effort) matrix more easily shows shifts in the time & resource needs for compliance or reimbursement effort. This can be very impactful when you take into account that FDA and other Regulatory Authorities also have a priority scale for evaluating new products & changes to existing products.
Adapting traditional prioritization methods to fit the needs of regulated industries like digital health and medical devices is not just about adding an extra layer of complexity. It’s about integrating a mindset where safety, compliance, security, and reimbursement are not afterthoughts but integral parts of the product development process. By doing so, product managers can ensure that their products not only meet customer needs but also adhere to the highest standards of quality and regulatory compliance. This balance is critical for success in these industries.