OBJECTIVES: T&M studies are designed to collect observational data to quantify efficiency-related outcomes, mainly staff-time and consumables associated with medical interventions. Our aim is to describe scientific and operational challenges that were observed when implementation a T&M study alongside a clinical trial. METHODS: T&M-method involves repeated observations of pre-identified tasks associated with a process in order to measure task durations to estimate total process time. As part of a multi-centre T&M study run as a sub-study to a clinical trial, we identified key design parameters that drive robustness as well as process elements that are critical factors to successful operational conduct. RESULTS: T&M-endpoints are to be carefully selected to align with their final use as inputs in e.g. economic models. As part of a trial that investigates time for a new route of administration (subcutaneous as alternative to intravenous), it is important to discuss with staff the applicability of task descriptions, with local CRF adjustment justifiable if providing more accurate time measurements. Trial protocol determines number and timing of observations, leading to sample size restriction and potentially extended study period. In the absence of clear guidelines on T&M study classification, regulatory processes are to be well understood, and absence of patient interaction clearly stated. Initiation of T&M-sub-study together with First-Patient-In is crucial to avoid losing valuable observations. Sites prefer to be given options for selecting observers, but ideally observers are external to the care unit (within or outside the hospital) and are competent and available during study period. As sites are inexperienced with T&M-method, streamlined communication and focused training proved crucial. CONCLUSIONS: T&M-methodology is associated with important design and operational challenges that must be identified early on to guarantee a scientifically robust design and operational feasibility, with the ultimate aim to produce valid efficiency-related data in support of economic analyses.