Isolde’s Siiquent targets hospitals and large diagnostic labs performing gene-based diagnosis, using a “razor-blade” revenue model where machines are sold at cost while profits come from consumables like reagents and test kits. This aligns perfectly with her market because customers face strict regulatory requirements and receive fixed reimbursements from insurers, allowing Siiquent to price consumables just below reimbursement rates and position itself as a revenue generator.
Emanuel’s Teomik targets research labs and universities conducting genomics studies, profiting from premium-priced patent-protected instruments rather than consumables. This works because research institutions have larger equipment budgets, aren’t constrained by the same regulations, and value cutting-edge tools for prestigious publications, while commodity compounds yield slim margins.
Imposing a single revenue model offers strategic clarity, prevents internal competition (like Teomik undercutting Siiquent), enables better forecasting, and avoids unintended consequences like the pay-per-test model’s moral hazard where customers waste materials. However, it risks rigidity in dynamic markets and ignores that different customer segments have fundamentally different needs – hospitals care about regulatory compliance and reimbursements while research labs prioritize innovation and performance. The flexible approach enabled innovations like pay-per-test billing that won customer loyalty and allows rapid competitive responses, but creates “random reactivity,” internal cannibalization, scaling challenges, and makes accountability difficult. The core tension is whether flexibility itself is a strategic advantage or simply undisciplined execution.
As mediating PM, I’d focus on evidence-based resolution rather than executive decree with a rigid structure – which is what both Isolde and Emanuel came to a consensus on. Similar to the steps we have been taking in class, it would be essential to start by establishing shared success metrics and map customer journeys to identify clear goals and alignments. This is done by conducting data-driven analysis by segmenting customers by actual needs, calculating true profitability including hidden costs, and looking at competitors. Additionally, running pilot tests and customer interviews, offering customers both models to reveal preferences and willingness to pay. Then building on this, we can work on our market segmentation, looking at metrics such as TAM/SAM/SOM for both Siiquent and Teomik’s market, and see where their market differs and overlaps. After doing this, we can design approaches for overlapping markets and aligned sales compensation – allowing both Siiquent and Teomik to serve both their respective and overlapping markets. This way, we can find a way to bring these two companies together – not having to pick or choose one business model to overshadow the other, but understanding that both can exist at the same time and continue serving their respective interests.
