Systems are built to scale judgment, to make good decisions automatic and repeatable. But systems fail. Understanding why they fail is essential to building systems that do not.
Failure Mode 1: Complexity Exceeds Capacity
Systems grow features. Each feature makes sense in isolation. But collectively, the system becomes too complex to understand, maintain, or debug. When something breaks, no one knows why. When changes are needed, no one knows what else will break.
The solution is aggressive simplicity. Resist the urge to add. Remove features that are not essential. The myth of the perfect funnel is partly about this: the pursuit of optimization through complexity often degrades overall performance.
Failure Mode 2: Optimizing Proxies Instead of Goals
Systems are built around metrics. But metrics are proxies for what actually matters. When systems optimize the proxy instead of the goal, they can achieve excellent metric performance while delivering poor outcomes.
Attribution models lie in part because they measure what can be measured, not what matters. Optimization makes performance worse when it chases proxies that do not align with actual business goals.
Failure Mode 3: Brittleness
Systems work well under normal conditions but fail catastrophically when conditions change. The edge case that was not anticipated. The upstream dependency that changed. The assumption that was invalidated.
Robust systems expect change. They degrade gracefully instead of failing completely. They have fallbacks and monitoring that alert when assumptions are violated.
Failure Mode 4: Handoff Losses
Information is lost when it moves between systems or between people. The context that was clear in one system is missing in another. The nuance that was captured in the initial interaction disappears by the time action is taken.
Follow-up infrastructure fails frequently at handoffs. The lead that came in with rich context becomes a sparse record in the CRM. The urgency that was conveyed on the phone is lost in the task assignment.
Failure Mode 5: Incentive Misalignment
Systems are operated by people. If the system's goals do not align with the operator's incentives, the system will be subverted, gamed, or neglected. This is not bad behavior; it is rational response to incentive structures.
Marketing metrics drift from reality partly because the people measured on those metrics have incentives to make the metrics look good, regardless of whether the underlying reality improves.
Failure Mode 6: Maintenance Neglect
Systems require ongoing attention. Data quality degrades. Integrations break. Assumptions become outdated. Without active maintenance, systems drift from effectiveness into dysfunction.
The most common pattern: a system is built, it works well initially, everyone moves on to new projects, and the system slowly degrades until it becomes more burden than benefit.
Designing Against Failure
Resilient systems share certain characteristics:
- Simplicity: Fewer parts means fewer failure points
- Visibility: What is happening is observable and understandable
- Feedback loops: Problems surface quickly rather than accumulating silently
- Graceful degradation: Partial failure is better than total failure
- Clear ownership: Someone is responsible for system health
- Regular maintenance: Attention is scheduled, not assumed
The Human Element
Systems scale judgment, but they do not replace it. The best systems create leverage by handling the predictable, freeing humans to handle the exceptional. When systems try to handle everything, they fail in the exceptional cases that matter most.
Understanding where human judgment is still required, and designing systems that support rather than replace that judgment, is essential to building systems that work.