The early adopter investment paradox: the service may disappear, the record should not

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A new app often becomes useful only once it has gathered lots of data and lots of users. The first users do that work: they enter their information, learn how the thing works and trust that the effort will pay off one day. Yet they are exactly the ones who lose the most if the app is shut down, because their work stays locked inside a service that no longer exists. I propose turning this around: the earlier someone joins, the less they should have to invest, and the data they enter should be theirs, in an open format that survives even if the service dies. My example is the records of a pet or another animal: the service may disappear, the animal’s history should not.

The early user builds the service and carries the risk

A service needs its first users’ time, data and trust to build its future value. At the same time, those very first users carry the greatest risk that their investment never pays off.

User value is benefits minus every kind of input

In a simple model, the value a user gets is:

V_user = B₀ + Σ (t = 1…T) pₜ · Bₜ − (P + S + M + L + R)

where

• B₀ is the immediate benefit,
• Bₜ is the future benefit at time t,
• pₜ is the probability that the service is still usable at time t,
• P is the price of the service,
• S is the work spent on onboarding and entering data,
• M is ongoing maintenance work,
• L is the lock-in and switching cost and
• R is the provider continuity risk.

Early on, almost every term works against the user

In the early stage the immediate benefit B₀ is often small, the onboarding work S large and the continuity probability pₜ uncertain. In practice the user pays and works to build the service’s database before the service has any meaningful network value.

Three known phenomena in one user

The early-user penalty is the sum of three known phenomena:

Early-user penalty = cold-start penalty
                   + relationship-specific investment
                   + provider continuity risk

• Cold-start penalty: the network is least valuable precisely to its first users. Tech investor Andrew Chen has written a whole book on the phenomenon, The Cold Start Problem (2021) (a16z).
• Relationship-specific investment: the data and work a user puts into a service raise the value of that particular relationship and can increase switching costs. The concept comes from transaction cost economics, where such specificity exposes the investor to hold-up by the other party (IDEAS/RePEc).
• Provider continuity risk: the user carries the risk that the startup or service will no longer exist when the data should be delivering its greatest benefit.

The earlier the user, the smaller the investment

For early users we should do the opposite of what happens now: the earlier the user, the smaller their investment should be.

Seven ways to push the inputs down

• free basic use
• automatic data import
• an open, documented format
• complete export
• clear provenance for every piece of data
• user ownership and control of the data
• the death of the service does not make the record unusable

Then the price P approaches zero, the work S shrinks, lock-in L approaches zero and the continuity risk R shrinks. The service-specific continuity probability pₜ loses its importance, because the data keeps its value elsewhere.

The investment moves from provider asset to user asset

In a closed model, the user’s investment becomes the provider’s asset. In an open model, it becomes a user-owned, portable asset. As a by-product, something bigger emerges:

many portable records → open data commons → network value

The network effect then rests not on lock-in but on compatibility.

The value of the open model to an early adopter

V_early adopter = immediate utility
                + portable future value
                + network upside
                − minimal onboarding cost

The question shifts from the startup to your own record

The user no longer has to ask: “Should I invest in this startup?” Instead they ask: “Should I build a portable digital record of this thing for myself?” If the answer to the second question is yes, whether the provider still exists ten years from now becomes much less important.

Applying it to animal data: the service as an interface to the owner’s record

In an animal service, a user could

• bring their own animal into the system,
• automatically fetch existing public data,
• add their own documents and information,
• see the origin of every piece of data,
• publish whatever they choose as open data,
• keep private documents hidden and
• export the animal’s entire history in an open format.

The service then does not primarily “own the animal’s profile”; it acts as an interface to a portable record that the user owns. The core line: The service may disappear. The record should not.

Novelty

I searched with terms such as local-first software, user-owned portable data, data portability, pet health record app export, animal health data interoperability and, in Finnish, KoiraNet public health data.

The principle is known and well articulated

• Local-first software. The 2019 essay by Martin Kleppmann, Adam Wiggins, Peter van Hardenberg and Mark McGranaghan sets out seven ideals, two of which are the core of this idea: data survives even if the service is shut down (“The Long Now”), and the user retains ultimate ownership and control (Ink & Switch).
• Solid. In Tim Berners-Lee’s Solid protocol, users’ data lives in their own “pod”, and applications are merely interfaces to it (Akamai/Linode).
• Portability rights and tools. Article 20 of the EU’s GDPR gives the right to receive the personal data you provided in a machine-readable format (gdpr-info.eu), and the Data Transfer Initiative, backed by Apple, Google and Meta, builds transfer tools between services (DTI).

In animal data the pieces exist but separately

App stores are full of pet health diaries, and some offer export. Pasu, for example, produces a PDF of the health history and a backup as a zip file, but mentions no open structured format (App Store). Public animal data exists too: the Finnish Kennel Club’s KoiraNet publishes individual dogs’ pedigrees, health screening results and trial and show results for anyone to see (DogWellNet). Continuity risk has also materialised: Tractive bought the Whistle pet trackers from Mars, and Whistle devices stopped working at the end of August 2025 (Invoxia). I found no information on whether users’ accumulated history survived the transition.

The difference is the combination and the early-adopter angle

I found no animal service that combines automatic fetching of public data, the owner’s own documents, per-item provenance, a choice between public and private, and full export in an open format. I searched the App Store, the general web and sources on animal health data interoperability. The novelty is therefore twofold: bringing local-first and Solid principles to the animal record, and a framing in which portability is not just consumer protection but specifically a way to remove the early-user penalty and to build network effects on compatibility.

Theoretical value

I estimate the value for animal data only. The general principle applies to almost every service, but it cannot be reduced to one sensible number.

Without the idea, AI handles data entry but not disappearance

In the next few years AI will make reading vet PDFs, vaccination certificates and invoices almost automatic, so the onboarding work S shrinks anyway. In the EU the right to export is already law. What remains without the idea is a problem AI does not solve: when a service shuts down or the user switches, the accumulated history disappears or is left as a pile of PDFs that no other service understands. The idea’s value comes from this difference.

Fermi estimate: roughly $15–420 million a year

• Users: 234 million × 5–20% ≈ 12–47 million households.
• Losses per year: 12–47 million × 10–20% ≈ 1.2–9.4 million cases.
• Time: 1.2–9.4 million × 1–3 h × $20 × 50% ≈ $12–280 million.
• Unnecessary repeats: 1.2–9.4 million × 5–10% × $50–150 ≈ $3–140 million.
• Total: roughly $15–420 million a year.

This excludes the network value of an open data commons, such as research use, which I could not estimate credibly. This is an order-of-magnitude estimate, not a forecast.

What moves it most is how many people keep records in a service

The range spans more than a factor of ten mainly because I found no figure for how many pet owners use a separate health record service. The other big factor is the baseline: if vet chains’ own portals and the EU export right cover most of the history anyway, the idea’s added value falls to the low end of the range.