When Coordination Is Avoidable: A Monotonicity Analysis of Organizational Tasks

Ju takes a question that organization theorists have circled for decades — when does coordination actually change the outcome rather than merely consuming resources? — and gives it a formal answer borrowed from distributed systems.

The key move is mapping Thompson's 1967 taxonomy of task interdependence onto monotonicity, the distributed-systems criterion for whether new information can invalidate prior conclusions; if a task is monotonic, no agent needs to wait for another before acting.

The empirical sweep across 65 APQC workflows and 13,000+ O*NET occupational tasks is unusually grounded for a theoretical contribution, and the finding that 24–57% of coordination spending may be structurally unnecessary reframes the perennial complaint about meeting overhead as a solvable design problem.

For product directors running multi-disciplinary teams or managing AI pipelines, the monotonicity criterion offers a precise diagnostic: decompose work into units, test for non-monotonicity, and treat coordination as a tax that should be levied only where logically unavoidable.

The paper is strongest as a bridge theorem — connecting organizational theory, formal methods, and applied AI governance — rather than as a standalone empirical study, which gives it durability beyond its 2026 data.