There is a large potential for automation and optimisation of transports within quarrying and mining, but operational models and characteristics for this purpose are lacking. This paper aims to provide insight into cyclic transports and the parameters that affect energy consumption and productivity. Detailed operational data from machines has been collected and analysed through automatic logging of the machine’s internal communication network. The paper presents and discusses the characteristics of the operation identified, develops models for energy consumption and productivity, and discusses their relation for optimisation and automation purposes. A conclusion is that stochastic fluctuations in activity times need continuous real-time control for an optimisation system to be effective. The method used in the paper resulted in regression models for cycle energy cost and hauler fuel rate, which provide both correlation and significance, which is promising for future validation and use in energy optimisation control systems.