Rogers, Bass, and Moore saw the shape. Zorthex measures the clock.
This is the perspective of an independent researcher with a background in the humanities. No institutional affiliation, no laboratory. Just a question that wouldn't let go — and the public data to begin answering it.
There are ideas that define a field so completely that we forget they were once radical. Everett Rogers published Diffusion of Innovations in 1962. Frank Bass added the mathematical architecture in 1969. Geoffrey Moore identified the structural gap that kills most innovations in 1991. Together, they gave us the language and the tools to understand one of the most fundamental questions in social and economic life: how do new things spread — and why do so many of them fail?
I want to start with gratitude. Before proposing anything new, it is worth understanding — precisely — what these three thinkers actually built. Because the more carefully you read them, the more you realise that what looks like a limitation is often a deliberate choice, made with the tools available at the time.
Rogers did not treat time as background. He made it the third of four explicit elements in his definition of diffusion — a definition so precise it has survived sixty years without revision:
Diffusion is the process by which an innovation is communicated through certain channels, over time, among the members of a social system.
Time enters his framework in three distinct ways: through the innovation-decision process (how long an individual takes to move from awareness to adoption), through innovativeness (how early or late a person adopts relative to others), and through the rate of adoption (how fast an innovation spreads through a system).
This is a sophisticated treatment of time. But it is time as experienced by individuals inside a social process — relative, qualitative, endogenous. Rogers measures how long people take to decide. He does not — and with the tools of 1962, could not — measure how long a phenomenon takes to become visible to the world outside.
Bass took Rogers' sociology and gave it a differential equation. In his 1969 paper, time becomes the independent variable: dN/dt — the rate of change of cumulative adopters with respect to time. For the first time, diffusion had a mathematical clock.
His formula is elegant precisely because of what it assumes: that diffusion is continuous, driven by two stable internal forces — innovators (p) and imitators (q) — and that the system is closed. The wave builds from within. Word of mouth does the work. The curve is smooth.
Bass was not naive about this. He knew his model worked best for consumer durables — televisions, washing machines, the products he studied. He was building a tool for a specific problem, and he built it brilliantly.
Geoffrey Moore gave us the most honest map of why innovations fail. Not because they are bad. Not because the market doesn't need them. But because there is a structural gap — the Chasm — between the Early Adopters who buy on vision and the Early Majority who buy on proof.
The pragmatists don't care about potential. They care about references. They want to see someone like them, in a company like theirs, who has already solved the problem and lived to tell the story. Without that reference, the wave breaks before it reaches the shore.
Moore's insight was surgical: the visionaries are not credible references for the pragmatists. They speak different languages, they measure success differently, they buy for different reasons. And so, after the initial excitement of the early market, sales stall. The chasm opens. Most innovations never cross it.
Here is the thing none of them could observe: they had no way to distinguish between a phenomenon that exists and a phenomenon that is visible.
In 1962, in 1969, in 1991, there was no population-scale, real-time instrument for public attention. You could survey. You could interview. You could study sales data after the fact. But you could not watch the moment of transition happening.
Today we can.
Search volumes, encyclopaedic pageviews, citation frequencies in specialist versus generalist sources — these are instruments Rogers, Bass, and Moore never had. And what they reveal, across decades of documented cases, is a pattern that their models do not capture.
For years — sometimes decades — a phenomenon lives entirely within a specialist layer. The technical community knows it. Experts write about it. The knowledge passes from hand to hand, carefully, like a candle sheltered from the wind. Bass's imitators are there, but they imitate only within the specialist network. Rogers' Early Adopters are active — but their activity is invisible to the general public. Moore's chasm sits open, waiting.
Then something arrives. Not the critical mass of imitators Bass modelled. Not the word of mouth Rogers described. Not the peer reference Moore prescribed. An external event — a regulation, an institutional mandate, a policy trigger — arrives and changes the regime entirely.
This is not a refutation of Rogers, Bass, or Moore. It is a distinction they could not make with the data available to them.
All three models assume that diffusion is driven by forces endogenous to the system — communication between adopters, imitation of innovators, peer references among pragmatists. Time, in all three frameworks, is shaped by internal social dynamics.
What the data now shows is that for entire categories of phenomena — cybersecurity, cryptography, AI governance, financial infrastructure, regulated markets — time is shaped by forces exogenous to the system. A regulation does not spread through word of mouth. It arrives. And when it arrives, it does not accelerate an existing curve. It switches the regime.
This distinction matters practically. If you are an investor, a strategist, or a policy maker trying to understand when a phenomenon will break through to the mainstream, the Bass model tells you to watch the imitator network. Moore tells you to watch the reference base. In policy-driven domains, both watches are the wrong ones. The signal is not inside the network. It is outside it — in the regulatory calendar, in the institutional pipeline, in the structural gap between when a norm exists and when it becomes operationally binding.
That gap is now measurable. Not as a prediction — Zorthex does not forecast. But as an empirical observation: how long, across documented cases, has that gap historically been? What regime is a given phenomenon in? How far along the specialist attention curve has it travelled before the trigger arrives?
Rogers wrote before the internet. Bass wrote before digital markets. Moore wrote before platforms and network effects reshaped entire industries overnight. All three built their models in a world where noise was limited by the friction of communication.
Today the opposite problem exists. Communication is instantaneous and global. Noise is everywhere. Every technology is announced, hyped, declared revolutionary, and buried — sometimes within the same news cycle.
In this environment, the ability to distinguish signal from noise is not just analytically useful. It is the difference between acting on evidence and acting on narrative.
Time — systematically measured, empirically grounded, stripped of hype — becomes the most valuable variable of all. Not time as Rogers described it, the duration of individual decision processes. Not time as Bass modelled it, the continuous accumulation of imitators. Not time as Moore implied it, the undefined wait before a reference base forms. But time as the distance between operational reality and public visibility. Time as the measure of how long a phenomenon can exist before the world decides to look at it.
That distance — that lag — is what Zorthex measures.
It is built on the foundation Rogers, Bass, and Moore laid. It could not exist without them.