WINNER TAKES ALL

With network economies comes great power. And great music

My father’s Steinway ¾ grand piano. Vintage 1927. After a year at Juillard, he enlisted and served in Patton’s First Army. My grandfather bought it for him when he came back from Europe. My Dad eventually did a PhD in system science at UCLA and worked on navigation systems for things that still fly today. At age 97, he played Scarlatti by heart. Passed away on his 100th birthday taking a nap.

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Intro

This week: Network Economies: Part 7 of my 7-part series on the 7 Powers — winning frameworks TechBio companies use to build moats.

And no. I will not talk about RBnB, FB or LI.

If you missed previous parts:

Counter-Positioning: Founder–Market Misfit at Delve Health

Cornered Resource: Itay and Beyond (brain-on-a-chip)

Switching Costs: SAP and Flatiron Health

Brand Power: Selmer Paris and Caris

Process Power: Iktos — AI & Robotics Rewrite Drug Discovery

Scale Power: 3 ways to achieve scale - YES. SIZE MATTERS.

Let’s start with a quick refresher of the 7 Powers.

Helmer’s 7 Powers outline the ways companies create lasting advantages: Scale Economies, Network Effects, Counter-Positioning, Switching Costs, Brand, Cornered Resources, and Process Power.

Across these 7 Powers, one pattern repeats: winners don’t out-muscle competitors — they out-compound them.

Network effects examples often focus on social media and marketplaces —but some of the most defensible positions in TechBio come from infrastructure network effects where value compounds through data access rather than user transactions.

Today I’ll analyze the Network economies pattern in 2 companies: Steinway Pianos and Picnic Health.

We’ll study pattern recognition - and look for reinforcing loops in infrastructure where scale begets scale, even if it’s not a classic marketplace like RBnB.

Steinway is an example of cultural infrastructure and Picnic Health an example of data infrastructure.

Steinway: The 170-Year Cultural Network Effect Hiding in Plain Sight

Steinway was founded in 1853 — and it’s an example of one of the oldest, slowest-built network effects in modern culture. The company began as a German immigrant family hand-crafting instruments in New York. Steinway’s moat developed over decades: the world’s greatest pianists gravitated to Steinway, and Steinway formalized that into the Steinway Artist program. These were the original influencers long before Instagram — elite performers whose choices shaped the tastes of conservatories, concert halls, and competitions.

That prestige loop compounds to this day. Institutions buy Steinways to attract top talent; students learn on Steinways and imprint on their touch and tone; those students become the next generation of Steinway Artists. It’s an intergenerational cultural flywheel — identity formation masquerading as product preference.

Steinway demonstrates how standards-based network effects create compounding value through ecosystem coordination. Concert halls stock Steinway because artists demand it → artists trust venues with Steinway → next generation learns on Steinway → reinforcing loop.

From pop to Shostakovich to jazz.

From music infrastructure to clinical data infrastructure.

Picnic Health: The Participatory Data Network

Picnic Health built a network effect at the data infrastructure layer—not through social connections or marketplace matching, but through participatory data aggregation.

The flywheel works like this: Each new patient who consents → richer longitudinal dataset → better research matching capabilities → more trial opportunities available → higher patient lifetime value → more compelling recruitment pitch → attracts the next patient cohort.

This is fundamentally different from traditional clinical research networks. In conventional models, sites compete for individual studies, and patients enroll in discrete trials. Picnic creates a continuous participation model: patients don’t sign up for a single study—they contribute their complete medical journey, which becomes queryable for multiple research purposes over time.

Why this compounds super-linearly:

With 10,000 patients, Picnic can support basic cohort identification. With 100,000 patients spanning diverse conditions and treatment histories, they can:

• Match rare disease cohorts pharma couldn’t find elsewhere

• Track long-term outcomes across multiple health systems (critical for gene therapy safety monitoring)

• Provide real-world evidence that supplements—or in some cases replaces—expensive observational trials

Each patient’s longitudinal record becomes more valuable as the network grows, because researchers can identify more precise cohorts and track outcomes that only emerge at scale.

The mechanics that enable the flywheel:

On the patient side, Picnic operates as a personal health assistant—helping patients understand and navigate care with a complete picture of their health journey. Patients consent to share their medical records, and Picnic passively collects records from all providers they visit, creating a “Universal Patient Record.”

On the pharma side, Picnic automates data collection, cleaning, and structuring using Picnic AI—a domain-trained large language model. This AI produces comprehensive, chronologically merged medical histories for each patient, which can be aggregated (for those who opt in) into research-ready datasets.

The system captures data across the fragmented U.S. healthcare landscape without requiring providers to adopt new software. One patient’s 7-year journey might span a dozen different health systems—Picnic stitches that together automatically, something neither a single trial site nor a single EHR would easily obtain.

The economic advantage:

Traditional trials pay investigator sites for visits and manual chart reviews. Picnic’s approach leverages standard of care (which accounts for ~70-80% of needed data in many studies), eliminating most “source data capture” expenses.

Their LLM—trained on millions of real records—labels and interprets clinical text on par with or better than human experts, driving down the marginal cost of each additional patient record to near zero.

Why late entrants struggle to compete with Picnic Health

Once patients centralize their medical records with Picnic, there’s a meaningful switching cost: they’d need to recreate that Universal Patient Record elsewhere. Meanwhile, pharma partners build their research workflows around Picnic’s infrastructure, creating bilateral lock-in.

The result: a two-sided platform where patient participation directly increases pharma research value, which creates more research opportunities that attract more patients.

Outro

Infrastructure network effects—whether in music like Steinway or in clinical data like Picnic Health—both create defensible moats.

If you want the platform/social network paradigm:

Steinway Pianos is a social network for music and Picnic Health is a 2-sided platform for non-interventional research.

Network effects provide great power:

From jazz - Diana Krall and Herbie Hancock, are official Steinway Artists who perform exclusively on Steinway pianos to pop - Lady Gaga played on a Steinway in her music video for “Hold My Hand,” from Top Gun: Maverick.

From AstraZeneca to Sanofi to Vertex Pharmaceuticals.

This Week on Life Sciences Today

Briya Turns Healthcare Chaos into Cohort-Ready Intelligence

Briya is an Israeli clinical data infrastructure company using zero-knowledge proofs.

I sat down this week with David Lazerson, CEO of Briya, to unpack how his team is turning the messiest asset in healthcare—clinical data—into a reliable engine for research, repurposing, and trials.

Briya started in 2020 as an infrastructure play, tackling the hardest problem in medicine: patient data scattered across formats, systems, and compliance walls. The breakthrough came in 2023, when they realized customers didn’t want better pipes—they wanted better answers. That shift led to AIRE, an AI-powered research environment that harmonizes structured and unstructured data (including the ~⅔ of value buried in clinician notes) with scientific rigor.

Zero-knowledge proofs enable privacy-safe record matching. A distributed architecture ensures Briya never takes control of customer data. Pharma uses it for cohort design, repurposing, and due diligence—accelerating insights from months to hours.

The long game? A trusted network connecting pharma and healthcare organizations without ever owning the data.

Visit Briya here

You can see the episode here

About Me

I’m a 5X founder who learned hard lessons the hard way.

Today, I help TechBio companies maximize their channel revenue and navigate growth, team, and strategy.

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