Proximate commuting is a potential employer-based travel-demand management program under which large, decentralized employers reassign each voluntary participant to a job location (with the same employer) closer to the participant's residence to reduce commuting distances. Key to determining proximate commuting's feasibility and potential success are the identification and estimation of its commuting benefits. A model for quantifying the distance and time savings of proximate-commuting programs is presented. It relies on stated preference information regarding an employee's willingness to proximate-commute. Potential commuting savings are modeled as originating from two distinct sources. First, savings can stem from mutually beneficial job exchanges that are estimated using optimization tools. Second, due to job vacancies occurring over time, savings can result from future employee relocations to closer branches. Because predicting future job vacancies is inherently stochastic, savings from future vacancies are estimated using optimization tools on scenarios created by a Monte Carlo simulation. The model is implemented and tested using data from self-administered survey questionnaires distributed among all tellers of a single banking institution in Bogota, Colombia. Results suggest immediate savings of 1,700 h/year and average savings of more than 8,000 h after the second year of program implementation. These results highlight the fact that accommodating people's desires for shorter commutes at negligible cost is possible and suggest a cautiously optimistic outlook for proximate commuting. Future research should focus on proximate-commuting implementation issues, such as employer adoption, middle management's role, and employee satisfaction after relocation.