Information sharing

Information sharing is the deliberate disclosure of data between autonomous agents — firms, organizations, individuals, or computational systems — in order to reduce collective uncertainty and improve joint decision-making. In supply chains, information sharing typically means transmitting point-of-sale data, inventory levels, or demand forecasts upstream to suppliers who would otherwise infer demand from the distorted signal of orders. In distributed computing, it means sharing state, checkpoints, or partial results across nodes. In governance, it means transparency.

The practice is simple in principle and difficult in practice because information is power. To share information is to cede an advantage in negotiation, forecasting, and strategic positioning. The bullwhip effect is a canonical example of what happens when information is not shared: each echelon in a supply chain amplifies demand variability because it operates on local, distorted signals rather than on the shared reality of consumer behavior. The remedy — sharing point-of-sale data upstream — is technically trivial and institutionally costly.

The structural tension is that information sharing requires either trust (which is rare between competitors) or a dominant power asymmetry (in which the stronger party can demand transparency from the weaker). Where it succeeds, it transforms a loosely coupled system into a coordinated one. Where it fails, the system remains a market of adversarial optimizers, each maximizing its own objective at the expense of the collective stability that information sharing would have provided.