Planning and managing the flow of work and value
What the syllabus expects
You must understand how work moves from demand to value, how to visualise it, and how to remove the constraints that slow it. Candidates should be comfortable with value stream mapping, Kanban and visual management, work-in-progress (WIP) limits, batch size and cadence, and priority-setting using capacity and demand data.
Concepts to know: the four flow measures - WIP, throughput, work item age and cycle time; Little's Law; queueing theory and the danger of running teams near 100 per cent utilisation; the Theory of Constraints five focusing steps; single-piece flow versus large batches; cadence and synchronisation of planning; and delivery metrics such as lead time for change, deployment frequency, change failure rate and time to restore.
Traps in questions
- Swap lead time (from request to delivery) with cycle time (from start of work to delivery).
- Believing WIP limits reduce output: they expose bottlenecks, shorten queues and usually improve throughput.
- "Maximise utilisation everywhere" is wrong - queues and waiting explode as utilisation approaches 100 per cent.
- Improving a non-bottleneck does not improve flow; elevate or exploit the constraint first.
- Confusing velocity-type internal measures with customer-facing lead time.
Worked example
A team has 20 items in progress and completes four per week. Little's Law gives an average lead time of 20 ÷ 4 = five weeks. If WIP is halved to ten and throughput holds, average lead time falls to about 2.5 weeks without anyone working faster. Rule of thumb: stop starting, start finishing - cap the work, watch the queue.