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Specialist vetting and capacity matching for live work

Specialist vetting should produce a current capability record that can be matched to a real assignment. Evidence of domain skill, language, security training and availability needs an expiry date and a clear review route before a worker is marked ready.

Composite reference architecture. A modelled operating system; no hiring or placement metric is represented as realised.

The operating problem

A résumé does not prove task readiness. Delivery teams need current evidence of domain skill, language, security training, availability and performance on the exact workflow.

How the workflow works

Match the project requirement to task-specific assessments and verified credentials. Keep availability separate from competence: a strong specialist can still be unavailable or overbooked. The capability record should show when each check was completed, what it covered and whether retraining or reassessment is due.

Case 10 Talent operations · specialist vetting and capacity matching: authorised inputs, validation, candidate work, human control, approved action, verified receipt, metrics and weekly review. The diagram labels exception and correction paths.Case 10 Talent operations · specialist vetting and capacity matching: authorised inputs, validation, candidate work, human control, approved action, verified receipt, metrics and weekly review. The diagram labels exception and correction paths.
Reference workflow. The human decision, exception route and feedback loop connect the source evidence to the intended outcome. Open the figure for the full canvas.

Where review and controls matter

A talent lead reviews identity concerns, accommodations and high-risk assignments. Weak proxies should not determine readiness. When early production quality disagrees with the assessment, review the assessment design as well as the worker's performance. Placement, retraining and holds need an explicit reason and an appeal path, so an old assessment does not silently exclude someone from future work.

Risk reference: NIST AI RMF.

What to measure

Use a fixed cohort and measurement window. Count numerator events only within the denominator's eligible cohort; sampled measures use the same audit sample for both terms. Record the source, exclusions and owner, and keep missing data visible. These definitions are proposed measurement contracts, not observed results.

Proposed operating measures
MeasureDefinition and unit
Time to verified capacityTime from approved staffing need to the required ready specialists becoming available; median and p90 days.
Match acceptanceProposed assignments accepted by both delivery owner and specialist divided by eligible proposed assignments; percent.
Early qualityAudited tasks passing the rubric during a fixed early-assignment window divided by audited tasks in that window; percent.
RedeploymentEligible released specialists placed in another suitable assignment within a fixed follow-up window divided by eligible released specialists whose full window has elapsed; percent.
Appeal resolutionAppeals resolved within the promised deadline divided by appeals due; percent. Report time and outcome separately.

A useful first pilot

Match a small project demand to an existing specialist pool, including expired credentials and overlapping availability. Review early task quality against the exact evidence used for placement.

Bring the workflow, its source records and the decision that needs an owner to a BergLabs pilot discussion.

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