In Industry 4.0 (I4.0), the role of the operator is essential to ensure the execution of working activities. Despite the implementation of the new I4.0 technologies, still motor activities require the execution of repetitive movements, such as in the pick and place or manipulations tasks. Consequently, there is still a need to evaluate the difficulty associated to repetitive movements, by considering movements executed, and the stochastic nature of agents (e.g., operator, cobot, robot). The aim of the present work is to propose a novel measure able to quantify the agent’s motor difficulty by observing its motor behaviour. To reach this goal, Index of Difficulty (ID) measures available in the scientific literature are firstly analysed and their capability in quantifying the motor difficulty of an agent in performing a general repetitive motor task is evaluated. Then, the proper ID candidate is selected, and a new ID model is proposed as a valuable tool to express the motor difficulty of an agent in accomplishing a general repetitive motor task. Preliminary experimental results highlight that the proposed ID has great potentials in different fields of application since it can be applied to any motor task, and to any ‘moving’ agent. In industrial contexts, the evaluation of agents’ motor difficulty is of practical interest for both production and ergonomics, paving the way to a range of new applications and promising research directions.