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Queuing Intuitions

Why It Matters

"We have enough capacity on average" is not enough. Variability creates queues even in systems that seem adequately resourced.

The Key Move

Ask not just "is average capacity sufficient?" but "what's the variability in arrivals and service?" As utilization approaches 100%, wait times go to infinity. The relationship is non-linear - going from 80% to 90% utilization hurts more than 70% to 80%.

Classic Application

Emergency rooms. Average patient load may be well below capacity, but variability in arrivals (Friday night vs Tuesday morning) creates periodic overwhelming.

Surprising Application

Calendar management. If you're scheduled at 90% capacity, any variance (meetings running over, unexpected requests) cascades into delays. Slack isn't laziness - it's buffer against variability.

Failure Modes

  • Planning for average demand without accounting for variability
  • Treating high utilization as automatically good
  • Ignoring that queuing dynamics differ by queue discipline (FIFO, priority, etc.)

Go Deeper

Hillier and Lieberman's "Introduction to Operations Research." Any queuing theory text.