Knowledge on consumers and markets, technological innovations in ingredients and manufacturing highly define our success in the market. In Foods, first and repeated choices by consumers depend on several factors, which are described by the Quality Function Deployment (QFD) model. In QFD various quality tables represent the complex pathway from consumer values down to the supply chain. Vision is that scientists and product developers should be able to navigate through the information universe, linking information from consumer liking down to product attributes and to processing. To achieve this, information repositories of different worlds should be connected in a federated architecture, filling in bridging relationships by new models. In Home and Personal Care the consumer preference is much more driven by objective factors. Products in HPC tend to become more complex in order to exploit synergies between ingredients. To tackle this complexity research has focused on using modem, high volume appraisal methods comparable to the High Throughput Screening techniques. An example is the FAST formulation tool that was developed in the MSI formulation consortium. Considering the quantity and quality of our experimental data it is important to combine data from different experiments in a search for hidden knowledge, not present in the individual experiments. Data Mining tools like cluster analysis, neural Networks, Kohonen Maps and Generative Topographic Maps are excellent tools to extract such knowledge. Here it must be noted that performance is a balance between criteria such as stain removal and color protection under different conditions as well as price. We therefore use Multi Criteria Decision Making tools to optimize product formulations.