Archana SinhaContact

Case study — 01

Data Monetization or Problem Solving?

What if the best data product starts with a customer problem?

For this product, it was both. I started with a provider problem: how to make clinical data exchange with external organizations easier and more scalable. I led the strategy and launch of the first provider–payer use case, using existing clinical data capabilities and an ecosystem partner to create a scalable commercial data service.

Context — US healthcare technology companyRole — Senior Product Manager, product ownerAnonymized
(a)

Providers shouldn't have to manage a growing web of data connections.

Providers need to exchange clinical data with multiple external organizations — starting with payers and potentially extending to other data-requester workflows.

The product challenge: reduce point-to-point complexity while making exchange reliable, scalable and commercially viable.

Fig. 01 — Fragmentation today
US healthcare provider
Payer A
Payer B
Payer C
Other external requesters

…and the list keeps growing

Every new requester adds another connection the provider must manage.

(b)

One problem first. A platform for what comes next.

I prioritized provider–payer clinical data exchange as the first use case, while designing the product around reusable capabilities that could support additional data-requester workflows over time.

Fig. 02 — Broad opportunity → first use case → platform
  1. 01

    Broad opportunity

    Clinical data + platform capability across many possible buyers

  2. 02

    Provider–payer exchange

    The first high-value use case — acute enough to matter, narrow enough to ship

  3. 03

    Reusable platform → future use cases

    Payers · legal · disability / SSN-related · pharma / life sciences

Future opportunity areas: payers · legal · disability / SSN-related workflows · pharma / life sciences. High level only — not all launched.

(c)

I didn't build another point-to-point integration.

I designed an ecosystem model combining the healthcare technology company's clinical data capabilities with a healthcare data connectivity partner, enabling scalable exchange with external payers.

Fig. 03 — The ecosystem model
US healthcare providers
Clinical data platform — normalisation, consent, audit
Healthcare data connectivity partner
Multiple US healthcare payers

One integration for the provider; reusable capabilities in the middle.

US Healthcare Provider → Clinical Data Platform → Healthcare Data Connectivity Partner → Multiple US Healthcare Payers

Less provider-specific connectivity management. More scalable exchange.

(d)

Three PM decisions

01

Prioritize

Start with provider–payer exchange rather than attempting every potential market.

02

Partner

Leverage external connectivity capabilities rather than building the entire network internally.

03

Productize

Turn the initial solution into reusable platform capabilities and a recurring Data-as-a-Service offering.

(e)

Solving the problem created a new commercial product.

Once the exchange model was established, I led commercialization across business case, pricing strategy, partner model, phased rollout, GTM and customer readiness.

The result: a recurring Data-as-a-Service offering.

Fig. 04 — Problem → Product → Platform → Commercial service → Launch → Scale
  1. 01Problem
  2. 02Product
  3. 03Platform
  4. 04Commercial service
  5. 05Launch
  6. 06Scale
(f)

From 0→1 product to commercial platform capability.

300+

Initial provider customers

~1,000

Provider organizations supported

Millions

Patient records supported

Commercial Launch

New data-services business model

The initial product solved a provider–payer problem while establishing reusable capabilities for broader healthcare data services.

Solve the customer problem first.

Build the platform so the solution can scale.

Then monetize the value you create.

Anonymized case study. Company, partner, customers, pricing and commercial mechanics are intentionally omitted.

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