This thesis is about statistics' contributions to industry. It is an article compendium comprising four articles divided in two blocks: (i) two contributions for a water supply company, and (ii) significance of the effects in Design of Experiments. In the first block, great emphasis is placed on how the research design and statistics can be applied to various real problems that a water company raises and it aims to convince water management companies that statistics can be very useful to improve their services. The article "A methodology to model water demand based on the identification of homogeneous client segments. Application to the city of Barcelona", makes a comprehensive review of all the steps carried out for developing a mathematical model to forecast future water demand. It pays attention on how to know more about the influence of socioeconomic factors on customer's consumption in order to detect segments of customers with homogenous habits to objectively explain the behavior of the demand. The second article -related to water demand management, "An Approach to disaggregating total household water consumption into major end-uses" describes the procedure to assign water consumption to microcomponents (taps, showers, cisterns, washer machines and dishwashers) on the basis of the readings of water consumption of the water meter. The main idea to accomplish this is, to determine which of the devices has caused the consumption, to treat the consumption of each device as a stochastic process. In the second block of the thesis, a better way to judge the significance of effects in unreplicated factorial experiments is described. The article "Proposal of a Single Critical Value for the Lenth Method" analyzes the many analytical procedures that have been proposed for identifying significant effects in not replicated two level factorial designs. Many of them are based on the original "Lenth Method and explain and try to overcome the problems that it presents". The article proposes a new strategy to choose the critical values to better differentiate the inert from the active factors. The last article "Analysing DOE with Statistical Software Packages: Controversies and Proposals" review the most important and commonly used in industry statistical software with DOE capabilities: JMP, Minitab, SigmaXL, StatGraphics and Statistica and evaluates how well they resolve the problem of analyzing the significance of effects in unreplicated factorial designs