Livestock husbandry aims at managing the environment in which animals are reared to enable them to express their production potential. However, animals are often confronted with perturbations that affect their performance. Evaluating effects of these perturbations on animal performance could provide metrics to quantify and understand how animals cope with their environment, and therefore better manage them. Automation of body weight (BW) and milk yield (MY) measurements in dairy herds is increasingly widespread in commercial farms. BW and MY dynamics over reproductive cycles can together be informative about animal health status and effects on potential performance. The goal of this study was to use a differential smoothing approach on both MY and BW time series of dairy cattle to extract quantitative features of the profiles of perturbations. Daily MY and BW records from 491 primiparous Holstein cows from 33 commercial French herds were used. These cows were not involved in experiments and did not experience any particular controlled challenge. Perturbations were solely expected to occur at a standard level in commercial farms, e.g., mastitis decreasing milk production, diarrhea decreasing digestive tract contents, nutritional disorder enhancing body reserve mobilization. After the fitting procedure, 2711 deviations were detected in MY time series and 1539 were detected in BW time series for all cows. Fifty-seven percent of these deviations were detected in the same period (±10 d) in both MY and BW time series. Clustering methods were applied on all individual deviations and identified contrasted types of cows in terms of responses to perturbations. These responses involved either only MY, or only BW or both. Results suggest that combing various individual dynamic measures can be of great interest to obtain reliable estimates of robustness components in large populations