Electrospray ionization mass spectrometry (ESI-MS) is a ubiquitously used analytical method applied across multiple departments in biopharma, ranging from early research discovery to process development. Accurate, efficient, and consistent protein MS spectral deconvolution across multiple instrument and detector platforms (time-of-flight, Orbitrap, Fourier-transform ion cyclotron resonance) is essential. When proteins are ionized during the ESI process, a distribution of consecutive multiply charged ions are observed on the m/z scale, either positive [M + nH]n+ or negative [M - nH]n- depending on the ionization polarity. The manual calculation of the neutral molecular weight (MW) of single proteins measured by ESI-MS is simple; however, algorithmic deconvolution is required for more complex protein mixtures to derive accurate MWs. Multiple deconvolution algorithms have evolved over the past two decades, all of which have their advantages and disadvantages, in terms of speed, user-input parameters (or ideally lack thereof), and whether they perform optimally on proteins analyzed under denatured or native-MS and solution conditions. Herein, we describe the utility of a parsimonious deconvolution algorithm (explaining the observed spectra with a minimum number of masses) to process a wide range of highly diverse biopharma relevant and research grade proteins and complexes (PEG-GCSF; an IgG1k; IgG1- and IgG2-biotin covalent conjugates; the membrane protein complex AqpZ; a highly polydisperse empty MSP1D1 nanodisc and the tetradecameric chaperone protein complex GroEL) analyzed under native-MS, denaturing LC-MS, and positive and negative modes of ionization, using multiple instruments and therefore multiple data formats. The implementation of a comb filter and peak sharpening option is also demonstrated to be highly effective for deconvolution of highly polydisperse and enhanced separation of a low level lysine glycation post-translational modification (+162.1 Da), partially processed heavy chain lysine residues (+128.1 Da), and loss of N-acetylglucosamine (GlcNAc; -203.1 Da).