Having one's funding cut in the course of conducting a longitudinal study has become an increasingly real challenge faced by developmental researchers. The main purpose of the current work is to propose "post hoc" planned missing (PHPM) data designs as a promising solution in such difficult situations. This study discusses general guidelines that can be followed to search for viable PHPM designs within a given budget restriction. Illustrative examples across different longitudinal research contexts are provided, each showing how PHPM data designs can help salvage longitudinal studies when an unexpected funding cut occurs mid-study. With the illustrative examples, the article also shows how developmental researchers can conveniently identify viable designs using the R package "simPM."