Which markets do Isolde and Emanuel target respectively? How do their respective business/revenue models align with their markets?
Isolde’s Siiquent targets hospitals and large diagnostics labs under tight reimbursement and capex constraints; a razor–blade model fits because placing instruments at (near) cost lowers purchase friction while predictable per-test/consumables charges map to how labs are reimbursed and budget. Emanuel’s Teomik targets research universities and institutes funded by grants with fewer regulatory hurdles; an instrument-margin model fits because PIs spend lump-sum grant dollars on high-spec equipment (status, capability) and run relatively variable, price-sensitive consumables thereafter. Both units provide high-touch services (training, workflow, expert support) that historically weren’t monetized—a misalignment that leaves value on the table. The occasional blur (clinical labs acting like research buyers, or vice versa) explains why a single revenue model struggles to stick, but the core fit remains: reimbursement-driven diagnostics → consumables economics; grant-driven research → instrument economics.
Pros and perils of a single revenue model vs. flexible way
Impose one model:
Pros:
- Cleaner pricing logic and simpler sales comp; easier forecasting and messaging.
- Reduces internal cannibalization and customer confusion from conflicting offers.
Perils:
- Market misfit: diagnostics (razor–blade, pay-per-test, reimbursement-driven) ≠ research (instrument-margin, grant-driven). Forcing one model risks breaking product–market–revenue fit.
- May squash useful adaptations like pay-per-test that built loyalty—while ignoring the need to manage its moral hazard.
Let it stay flexible:
Pros:
- Matches how customers actually buy in two distinct markets; preserves agility that created wins like pay-per-test and high-touch service.
- Adapts to blurred boundaries where some diagnostics labs now behave like research buyers.
Perils:
- Under-monetized services remain invisible if not intentionally priced.
- Can devolve into “random reactivity”—exceptions everywhere, internal competition, confused customers.
As the PM mediating a mandated merger, I’d run a four-phase, non-overlapping process that is collectively exhaustive:
(1) Set the ground rules by creating psychological safety and clarifying intent (we are optimizing customer value and sustainable margins, not picking political winners), then codify decision principles—segment fit, transparency, no orphaned customers, and margin discipline—so both sides share the same north star.
(2) Build a common fact base that describes the markets and economics without blame: segment definitions and jobs-to-be-done; instrument vs. consumables margins; attach rates; cost-to-serve for services; and quantified risks. This is especially important as in my past consulting job, one of my clients have two departments blaming each other for work in the grey area. To solve this, we can also execute some kind of shared KPIs and evaluation criteria to allign the parties.
(3) Design the operating model by segment using that evidence: specify which revenue model applies to which segment, price and package services explicitly, align sales compensation and messaging, and document exception policies; the output is a portfolio playbook rather than a one-size-fits-all scheme.
(4) Govern, pilot, and scale through a standing cross-functional council with clear RACI, monthly variance reviews, and 90-day pilots in selected geographies to test win rate, margin, NPS, attach rates, and service utilization before rolling out; if results diverge, iterate the playbook rather than reverting to ad-hoc flexibility.
