Protein phosphorylation is a reversible post-translational modification known to regulate protein function, subcellular localization, complex formation, and protein degradation. Detailed phosphoproteomic information is critical to kinomic studies of signal transduction and for elucidation of cancer biomarkers, such as in non-small-cell lung adenocarcinoma, where phosphorylation is commonly dysregulated. However, the collection and analysis of phosphorylation data remains a difficult problem. The low concentrations of phosphopeptides in complex biological mixtures as well as challenges inherent in their chemical nature have limited phosphoproteomic characterization and some phosphorylation sites are inaccessible by traditional workflows. We developed a sequential digestion method using complementary proteases, Glu-C and trypsin, to increase phosphoproteomic coverage and supplement traditional approaches. The sequential digestion method is more productive than workflows utilizing only Glu-C and we evaluated the orthogonality of the sequential digestion method relative to replicate trypsin-based analyses. Finally, we demonstrate the ability of the sequential digestion method to access new regions of the phosphoproteome by comparison to existing public phosphoproteomic databases. Our approach increases coverage of the human lung cancer phosphoproteome by accessing both new phosphoproteins and novel phosphorylation site information.