Quantum readiness: a 30-day feasibility pathway
Category: Advanced Computing & Quantum Readiness · 7–9 min read · 2026-01-10
Quantum readiness is less about rewriting your models, and more about clarifying which parts of your workflow could benefit from emerging computational paradigms — and which parts should remain classical for the foreseeable future.
A low-regret 30-day pathway
Days 1–7: relevance screening
- List the top 3–5 decision bottlenecks (time-to-solution, uncertainty, optimisation cost, data constraints).
- Identify where the bottleneck lives: solver, preprocessing, calibration, optimisation, or decision governance.
Days 8–20: mapping
- Map problem classes (optimisation, sampling, inverse problems, ML workloads) to plausible future approaches.
- Identify what would be required for adoption (data, validation anchors, governance, skills).
Days 21–30: decision memo
- Write a one-page memo: what matters now, what to watch, and what to ignore.
- Define a “no-regret” capability step (education, small pilots, partnerships) aligned with your context.
Key warning sign
If the work is framed as “we need quantum because it’s faster,” the project usually becomes vendor-led and unfalsifiable. Readiness should be framed as capability planning under uncertainty.
Want a readiness memo tailored to your workflow? Send 3–5 lines and we’ll propose a path.