Diagnose bottlenecks with context
Course overview · 4 min reading + 12 min practice, estimated
Principles and method
A large queue can result from high inflow, low capacity, poor inputs or a deliberate hold. Inspect cases before prescribing automation. Compare arrival rate, completion rate and work in progress over a suitable period. Little’s Law relates average work in progress, throughput and time under stable conditions with consistent boundaries; do not apply it mechanically to a changing or mixed process. Ask which decision or resource constrains flow and what evidence supports that hypothesis. A dashboard should lead to investigation, not automatically assign blame to the person owning the stage.
Worked example
Twelve applications wait for review because a hiring manager changed the brief, not because the recruiter stopped working. The action resolves requirements before adding reminder automation.
Put it into practice
Investigate a fictional queue using inflow, outflow and three case notes.
Use fictional information and keep your work in your own notes.
Compare your approach: self-review guidance
Identify at least two plausible explanations and the next evidence needed. If the process is unstable, describe the trend rather than presenting a steady-state formula as a precise prediction.
Sources and further reading
Original Academy teaching and fictional examples. These references provide context, not endorsement. Edition 2026.09; updated 2026-09-24.
- CIPD: Recruitment
Professional context for the recruitment lifecycle.
- MIT: Little's formula and queueing systems
Technical background for interpreting work in progress, throughput and flow time.