Skills intelligence in manufacturing: why a generic taxonomy cannot staff a plant
Manufacturing capability depends on verified skill, equipment, site, authorisation, recency, and availability—not a generic taxonomy alone.
by Skills Intelligence
Analysis
Field notes
Methodology, deep dives, and field notes on building skills intelligence.
Why internal talent marketplaces do not create mobility
Matching people to opportunities is not the same as moving talent. A practical guide to release rules, incentives, capacity, evidence, and outcomes.
by Skills Intelligence
The skills-based organization will not kill the job
Jobs still govern employment, pay, budget, and accountability. Skills should increase the resolution of job architecture—not replace it.
by Skills Intelligence
Skills intelligence governance: who owns the taxonomy, evidence, and decisions?
Skills governance is about authority over meaning, evidence, models, workflows, corrections, and outcomes—not taxonomy housekeeping.
by Skills Intelligence
The skills intelligence maturity model: six stages from spreadsheet to decision system
A six-stage maturity model that measures which workforce decisions an organisation can safely improve—not profiles, features, or taxonomy size.
by Skills Intelligence
Skills intelligence dashboards: 12 metrics that matter
A decision-grade skills dashboard must connect evidence, capability gaps, action, and outcomes. Here are 12 metrics—and the vanity metrics to avoid.
by Skills Intelligence
AI skills intelligence: why inference is not evidence
AI can discover skills at scale, but an inferred skill is only a hypothesis. A practical framework for evidence, validation, governance, and decision rights.
by Skills Intelligence
How to evaluate a skills intelligence platform
A vendor-neutral framework for evaluating skills intelligence software by data quality, ontology depth, validation, workflows, governance, and outcomes.
by Skills Intelligence
What is skills intelligence? A practical model for AI work
A practical guide to skills intelligence: how it differs from inventories, taxonomies, analytics, and platforms, and how evidence becomes decisions.
by Skills Intelligence
Signal vs hype: what 414 AI terms reveal about operational maturity
What 414 AI terms reveal about hype, operational maturity, and the difference between laws, standards, protocols, and corporate policies.
by Skills Intelligence
AI job exposure: what a 78-role model can—and cannot—tell us
An editorial model of AI exposure across 78 role profiles: how to read net pressure, where the signal is useful, and why it is not a jobs forecast.
by Skills Intelligence
Why skill taxonomies cannot sequence reskilling: build a learning DAG
A practical guide to prerequisite graphs: edge strength, cycles, data contracts, pilot metrics, and evidence for defensible learning pathways.
by Skills Intelligence
What three AI research runs can—and cannot—validate
How the GenAI 2026 Skills Atlas uses 0/3–3/3 model agreement as a provenance signal, why disagreement matters, and where expert evidence must take over.
by Skills Intelligence