The Half-Life of Skill

Every leader I meet is racing to train people faster.

But almost no one asks the more important question —
how long does that training stay alive?

In physics, “half-life” measures how long it takes for a substance to lose half its energy.
In learning, our skills follow the same decay curve.

We’ve been measuring time-to-competence.
It’s time we start measuring time-from-competence.

The Hourglass Framework

Picture your workforce as an hourglass.

• Top half → Time-to-Competence — how fast people ramp up.

• Bottom half → Skill Half-Life™ — how slowly capability drains away.

Skill Durability Index
(1 / Time-to-Competence) × Skill Half-Life

Shorter ramp × longer relevance = higher ROI, lower turnover, greater adaptability.

What We’re Seeing on the Ground

Across sectors, half-life data is already visible:

• Technical skills decay in ≈ 2.5 years

• Power skills and leadership capacities last 7–10 years

• Micro-refresh programs extend retention 30–50 %

Each loop adds months of relevance for the same training spend.

Why It Matters

As AI accelerates change, the durability of human capability becomes the new competitive edge.

Speed alone isn’t strategy. Longevity is.

If your dashboards only track how fast people learn, you’re seeing half the picture.
The next advantage is in how long those skills stay alive.

Attribution

Skill Half-Life™ Framework developed by Lindsay Fitzpatrick (2025).
Quantifying skill durability in the AI economy.
Trace ID: FFL-SHL-2025-001