Finding Structure in Flexibility
I really enjoyed this case because it captures a tension that exists in so many companies, and in product management too, between the clarity of structure and the freedom of flexibility. Isolde and Emanuel represent these two sides beautifully.
Two Markets, Two Models
Isolde’s market was large hospitals and diagnostic labs that needed reliability and compliance in gene-based diagnosis. Her business model mirrored that: a “razor-blade” model where she made money on consumables, not the machines. It worked perfectly for a market that valued predictability and regulation. Emanuel’s world, on the other hand, was full of research labs and universities chasing discovery, not efficiency. His model revolved around high-margin machines, constant innovation, and pricing that could shift with the academic or competitive landscape. His flexibility wasn’t laziness, it was a strategy to match a volatile market.
The real tension came when leadership wanted to impose a single revenue model on the merged unit. There’s something comforting about standardization, it’s one system, one strategy, one clear story to tell the market. But as Isolde and Emanuel argued, that kind of rigidity can kill adaptability. In fast-moving or complex B2B environments, customers’ needs evolve, and companies have to evolve too. The risk of flexibility, of course, is chaos aka “random reactivity,” as Peter put it. Without some unifying structure, you can lose focus and profitability, chasing every new demand without clear priorities.
Designing a Fair Process for Integration
If I were the PM asked to mediate the merger discussion, I’d approach it not by forcing a quick decision on the “right” model, but by designing a fair process for reaching one. I’d start by helping both sides map their value chains, where money actually changes hands, where customer pain points are highest, and where each model currently wins or loses. Then, I’d introduce joint customer journeys, finding overlaps in customer needs rather than differences in revenue streams.
Next, I’d workshop a hypothesis together. We’d define and test a few hybrid models through limited pilots, maybe a small segment of research labs trying a pay-per-test structure or a diagnostic client testing premium support as a paid add-on. The goal wouldn’t be to pick one model immediately, but to create data that informs the decision, rather than opinions. Ultimately, my job as a mediator wouldn’t be to decide who’s right, it’d be to design a process that makes both sides feel heard, keeps the customer at the center, and brings clarity without killing creativity.
