The deployment of industrial robotic cells based on lean manufacturing principles enables the development of fast-reconfigurable assembly lines in which human and robotic agents collaborate to achieve a shared task. To ensure the effective coordination of the shared effort, each task must be decomposed into a sequence of atomic actions that can be assigned either to a single agent or to the combination of more agents, according to a defined metric. While task allocation is a general problem and has been discussed intensively in other fields, less effort has been devoted in industrial scenarios, involving mixed human–robot teams and in particular, to the factors that should be considered in allocating tasks among a heterogeneous set of agents in collaborative manufacturing scenarios. In this letter, we investigate the agent characteristics that should be considered in the task allocation problem of fast-reconfigurable systems in industrial assembly processes. First, we introduce a set of indices, namely task complexity, agent dexterity, and agent effort, to evaluate agent performance with respect to a task. Second, we propose an offline allocation algorithm that combines the performance indices to assign optimally the task to the team agents. Finally, we validate the framework in a proof-of-concept collaborative assembly of a metallic structure. The results show that the workload is shared through the agents according to their particular physical capabilities and skill levels. A subjective analysis of the proposed collaborative framework on 12 healthy participants also validated the intuitiveness-of-use and improved performance.