This research is carried out within a semiconductor production plant of the firm STMicroelectronics. The company's Department of Information Technology (IT) is collecting huge databases of information about the information systems (IS), to store performance and activities variables, called metrics. However, their exploitation is under-optimized, because their systematic analysis is not the priority of IT professionals. In this context, we are willing to develop statistical tools, helping IT professionals (i.e. understandable by non-statisticians) to take advantage of this amount of information. We are particularly interested in two activities of the ITIL (Information Technology Infrastructure Library) Capacity Management process: IS monitoring and IS modelling. As the starting point, STMicroelectronics IT Department was manually monitoring a selected set of performance and activities metrics. This was time-consuming and inefficient: only a little part of the IS was under control and many exceptional IS activities were not detected. We implemented a statistical answer, built on a Holt-Winters based monitoring coupled with a robust standard-deviation estimator. This solution is already up and running and allows a fully automated monitoring of several hundred metrics. The modelling activity is aiming at evaluating the interactions between business and IS activities. STMicroelectronics is doing this work by rule of thumb, without any support from a quantified tool. We are currently working on developing such a tool, based on a multivariate statistical analysis of the available metrics. At the present time, we have already identified and quantified some interesting pat- terns, helping at understanding several interactions between the different layers (resource-application- business) of the IS. Beyond the answer to the ITIL process, we are also happy to see that this work really helps at developing a "statistical culture" within the IT Department: brainstorming meetings and presentation of our research results are developing a positive emulation about the use of statistics.