After the implementation of a new regulation, which imposes some changes on products or consumer behaviours, it is important to know if the impact is in line with the expectations or not. To assess this impact the best method is to compare the figures before and after the implementation and to show the significance of the change. Sometimes, conclusions are rapidly drawn up from few data in order to show a potential positive impact and to justify the regulatory development. Often, these conclusions are based on a short period of time consisting in the comparison of the two consecutive years before and after the implementation. However, this comparison can only show a difference between two years but cannot in any circumstance lead to the conclusion on an effect of the new regulation. Indeed, a solid conclusion can only be claimed if a thorough study of data over a long period of time is performed taking into account the controlled (e.g. trend, seasonality) and random variations. In this paper, we show the important factors that should be taken into account and the techniques for extracting an underlying pattern of behaviour in a time series (trend analysis). Examples on the impact on new regulations will also be discussed (e.g. LIP regulation).