Engagement Leadership · Control room
Capacity & Resourcing Planner
SIMULATEDVerified Jul 2, 2026Thirty people, five short — but only in three skills. The heatmap shows where the portfolio is over-allocated; the toggles show what hire, contract, or upskill each does to the date and the cost. This one is personal — it mirrors a 31-resource intelligence mapping I ran.
7 FTE short in skills
+10 wk vs plan
base team
Over-allocated skills
Skill utilization · demand ÷ capacity
demand 9 · capacity 6 · 150%
demand 7 · capacity 5 · 140%
demand 4 · capacity 4 · 100%
demand 4 · capacity 5 · 80%
demand 5 · capacity 6 · 83%
demand 6 · capacity 4 · 150%
Tick mark = current capacity line. Bars past it are over-allocated. Hire = +6 wk / $18k·FTE · Contract = +1 wk / $28k · Upskill = +4 wk / $8k (draws on slack).
Bottleneck: ML Engineering
Steering-committee takeaway: Capacity plans fail on skills, not headcount. Thirty people ≠ thirty people.
Resume echo — a direct mirror of the 31-resource AMEX intelligence mapping; the most personal instrument on the site.
How this is built
Utilization = demand ÷ effective capacity per skill. Resolving a gap adds its shortfall as capacity; delivery slip = the worst gap's overflow (unresolved) or its resolution lead time (resolved). Monthly cost = base team + Σ(gap × resolution rate).
Stack: Next.js (static) + shared design system; deterministic client-side.
Limitations: skills are aggregated pools, not named individuals; upskill assumes the slack is transferable. It exposes the skill-shaped bottleneck and the trade, not a resource-levelled schedule.