Hook
Local wins can be global losses.
Problem
Teams often optimize their own part of the pipeline without considering the full system. This can increase throughput locally while creating queues, rework, or delays elsewhere.
Why it matters
System throughput is limited by its constraint. The theory of constraints reminds us that the slowest step sets the pace. When you optimize locally, you can shift pain downstream and make overall delivery slower.
Signals you are here
- Team metrics are green but delivery is slow
- Upstream output overwhelms downstream capacity
- Queues grow at a single stage
- More coordination meetings are needed to move work
Anti-patterns
- Per-team KPIs that ignore end-to-end flow
- Maximizing utilization instead of throughput
- Automating steps that just create more backlog
- Blaming downstream teams for delays
Try this
- Align on system-level metrics (lead time, throughput)
- Map the value stream and fix the constraint first
- Reduce handoffs and shared queues
- Design cross-team goals and shared ownership
Example
A build team speeds up builds by 50 percent, but releases slow down because testing becomes the bottleneck. Instead of pushing builds faster, they invest in automated testing and the system throughput improves.
Reflection prompt
Where did a local improvement make someone else's work harder? Fix that connection.
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