The increasing use of multivariate models both as part of the control strategy in commercial (bio)pharmaceutical production as well as for process monitoring calls for an efficient strategy for model development and model life cycle management. The traditional approach to develop multivariate models based on spectroscopy involves manual data management such as selection and transfer of spectroscopic data, import into modeling software and selection/exclusion of data. That is followed by addition of reference data, alignment of time stamps and import into the modeling software. 90% of the time required to construct a multivariate model is spent on data preparation. It was decided to develop a solution to automate these steps to prepare (stage) the data required for model development, reducing the time required to prepare a typical set of batch data to about five minutes. A second tool was developed to automatically optimize data pretreatment parameters and spectral range for PLS models. Both tools allow our scientists to invest their time into more value-added activities.