Agent Bullwhip Effect

Problem

When each agent optimises its own node against a demand spike, their reorders synchronise: a small bump at the stores becomes a large coordinated order upstream, which causes supplier stockouts that ripple backward through the network. The amplification does not come from any agent failing or hallucinating — each is doing its job correctly — it comes from the agents' collective decision policy reacting to the same signal at once. The more agents and the tighter their coupling to demand, the larger the swing, and the variability the network creates is the agents' own, not the customers'.

Solution

Recognise that a network of locally-optimising agents can amplify the very signal it reacts to, and design against it at the system level rather than per node. Add explicit demand-signal dampening so a spike at one node does not translate into a full synchronised reorder upstream, and coordinate or stagger the agents' ordering so they do not all react in lockstep. Measure and separate the variability the agents' policy introduces from the variability inherited from real customer demand, and tune the policy to minimise the former. The control lives in the collective ordering policy and its damping, not in any single agent's local optimisation.

When to use

• Recognising this failure when a network of replenishment or ordering agents amplifies a demand signal into upstream surges and stockouts.
• Reviewing a multi-agent supply chain where each node optimises locally with no system-level damping.
• Diagnosing supplier stockouts and overstock swings larger than the underlying customer demand change.