Case Study
MedTech Startup Systems Design & Management
Ignacio Rodriguez de Castro
The MedTech industry is a rapidly evolving sector that encompasses a wide range of healthcare technologies, including diagnostic, therapeutic, monitoring, and surgical devices. BREATHEBAND, a wearable device designed to anticipate asthma attacks in children, represents a promising innovation within this industry. However, its development and commercialization are fraught with uncertainties, including regulatory hurdles, market demand variability, and cost fluctuations.
Managing uncertainty is a critical challenge in the MedTech industry. Traditional deterministic planning approaches often fail to account for the inherent variability in factors such as regulatory costs, market demand, and manufacturing expenses. This can lead to inaccurate financial projections and an increased risk of project failure. BREATHEBAND’s success hinges on effectively navigating these uncertainties
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Motivation
Asthma remains a critical public health issue, affecting millions globally and posing a particular challenge for children. In the United States alone, approximately 5 million children are diagnosed with asthma, making it the most common chronic disease among youth. For parents, the risk of an unexpected asthma attack—especially when they’re not nearby—can be a constant source of anxiety. Despite the prevalence of paediatric asthma, no current solutions on the market offer comprehensive monitoring capabilities that integrate patient-specific health indicators and real-time environmental data. (Clinical unmet need, page 11)
Methodologies
- Stochastic Planning: “To manage uncertainty, randomized or stochastic planning methods use probability distributions to model different possible outcomes… This helps organizations develop risk-mitigation strategies, optimize resource allocation, and improve resilience in unpredictable environments.” (Systems Design & Management Under Uncertainty, p. 13)
- Monte Carlo Simulation: “This statistical method randomizes a significant set of simulated system performances and classifies them according to their value… we can obtain a distribution of results with their frequency or probability percentage and a target curve.” (Systems Design & Management Under Uncertainty, p. 13)
Insights
- Uncertainty Management: “The MedTech industry is inherently uncertain, with factors like regulatory costs, market demand, and manufacturing costs varying significantly.” (Lessons Learned, p. 31)
- Value of Flexible Options: “Incorporating flexible options, such as adjusting product pricing or canceling the project under unfavorable conditions, can significantly mitigate risks and enhance profitability.” (Lessons Learned, p. 31)
- Power of Simulations: “The power of simulations, such as the Monte Carlo one, to simulate uncertainty-prone scenarios.” (Lessons Learned, p. 31)
- Market Research & Customer Insights: “Thorough market research is essential for understanding customer needs and sentiments, which can inform product development and pricing strategies.” (Lessons Learned, p. 31)
Training
Relevant lectures:
- Real options analysis
- Monte Carlo simulation
- Sensitivity Analysis
- Multidimensional evaluation
