Full waveform inversion of seismic data is often plagued by cycle skipping problems so that an iterative optimization method often gets stuck in a local minimum. To avoid this problem we simplify the objective function so that the iterative solution can quickly converge to a solution in the vicinity of the global minimum. The objective function is simplified by only using parsimonious and important portions of the data, which are defined as skeletonized data. We now present a mostly non-mathematical tutorial that explains the theory of skeletonized inversion. We also show its effectiveness with examples.