In response to the urgent-need for analysis software that is capable of handling data from targeted high-throughput lipidomics experiments, we here present a systematic workflow for the straightforward method design and analysis of selected reaction monitoring data in lipidomics based on lipid building block. Skyline is a powerful software primarily designed for proteomics applications where is it widely-used. We adapted this tool to a 'Plug and Play' system for lipid research. This extension offers the unique capability to assemble targeted mass spectrometry methods for complex lipids easily by making use of their building blocks. With simple yet tailored modifications, targeted methods to analyze main lipid classes such as glycerophospholipids, sphingolipids, glycerolipids, cholesteryl-esters and cholesterol can be quickly introduced into Skyline for easy application by end users without special bioinformatics skills. To illustrate the benefits of our novel strategy, we used Skyline to quantify sphingolipids in mesenchymal stem cells. We demonstrate a simple method building procedure for sphingolipids screening, collision energy optimization and absolute quantification of sphingolipids. In total, 72 sphingolipids were identified and absolutely quantified at the fatty acid scan species level by utilizing Skyline for data interpretation and visualization.