Technology right but too early is a recognisable pattern, one that repeats more often than most strategy teams admit. General Motors built a mass produced electric car in 1996 and it was gone within three years, roughly a decade before anyone believed there was a real market for one. The engineering was not the problem. The timing was.
Technology Right but Too Early: Right Idea, Wrong Decade
Technology history is full of the GM EV-1’s cousins. TIME’s retrospective on failed technology lists the EV-1 alongside the Palm Pilot, which established mobile computing habits years before smartphones capitalised on them properly, and Google Glass, which collapsed under privacy concerns in 2015 yet correctly anticipated a wearable, always-on computing layer that is only now becoming normal. None of these products failed because the underlying idea was wrong. They failed because the infrastructure, the culture, or the regulation around them had not caught up yet.
Gartner has spent years mapping this exact pattern through its widely used Hype Cycle. Its own methodology description explains that after initial enthusiasm, interest wanes as early implementations fail to deliver, a phase it calls the trough of disillusionment, before mainstream adoption eventually takes off in what it terms the plateau of productivity. The technology itself rarely changes much between those two phases. What changes is everything around it.
The healthcare version of the same story
I have watched this pattern up close in health information exchange. The idea that a patient’s clinical record should follow them between hospitals, clinics and specialists is not new, and the technical building blocks for it have existed for a long time. What has taken decades is the surrounding work: data standards, consent frameworks, incentive structures and clinical trust.
The scale of that lag is visible in the data. ONC’s own hospital interoperability data shows that seventy per cent of non-federal acute care hospitals were engaged across all four interoperability domains, sending, receiving, finding and integrating outside data, by 2023, up from forty six per cent in 2018. Real progress, but only forty three per cent of hospitals were doing this routinely rather than occasionally, and independent hospitals lagged system-affiliated ones by more than thirty percentage points. The concept was right in the 1990s. The plateau is only now coming into view.
The clearest recent sign of that plateau arriving sits outside hospitals altogether. The Social Security Administration announced in February 2026 that it is joining the national TEFCA health data exchange network, with its connection still in testing and go-live expected by early spring of 2026. The goal is plain: faster access to the clinical records needed to decide the roughly two million disability claims SSA receives each year, trading a mailed records request for a direct query. A federal benefits agency pulling medical history on demand, rather than waiting weeks for paper, is not a new ambition. It took three decades for the surrounding exchange infrastructure to become something an agency with no stake in healthcare delivery could actually plug into.
What this means for anyone building ahead of the curve
Working on a national digital healthcare transformation programme now, the lesson I carry from this history is patience without complacency. Being early is not the same as being wrong, but it does mean the work is not finished once the technology exists. It means building the standards, the governance and the trust that let adoption actually happen, often years after the announcement that made the technology look inevitable.
The organisations that eventually win with an early idea are rarely the ones who invented it first. They are the ones still building the supporting infrastructure, quietly and without much recognition, when the market finally catches up to the reason the idea existed in the first place.