When Coordination Is Avoidable: A Monotonicity Analysis of Organizational Tasks

Abstract

Organizations devote substantial resources to coordination, yet which tasks actually require it for correctness remains unclear. The problem is acute in multi-agent AI systems, where coordination overhead is directly measurable and routinely exceeds the cost of the work itself. However, distributed systems theory provides a precise answer: coordination is necessary if and only if a task is non-monotonic, meaning new information can invalidate prior conclusions. Here we show that a classic taxonomy of organizational interdependence maps onto the monotonicity criterion, yielding a decision rule and a measure of avoidable overhead (the Coordination Tax). Multi-agent simulations confirm both predictions. We classify 65 enterprise workflows and find that 48 (74%) are monotonic, then replicate on 13,417 occupational tasks from the O*NET database (42% monotonic). These classification rates imply that 24-57% of coordination spending is unnecessary for correctness.