The University of the Andes aims to innovate in university philanthropy. For this reason, it designed and implemented a model that can predict the probability that people with certain characteristics will contribute to a philanthropic cause. Using data on people who have contributed to causes over a 20-year period, the model produces descriptive analytics by collecting, organizing, and systematizing information on potential philanthropists. The model performs an iteration process that updates the data through the university's architecture. Connecting directly to the data sources, the model analyzes the prospects and how likely they are to donate. Predictive analytics has been fundamental in prospecting. The Commercially Viable Prospects (CVP) indicator was built to analyze the annual behavior of prospects. The indicator reveals how many people made it through contact, cultivation, solicitation, and donation processes and then decided to contribute to a philanthropic cause, commit to it, or defer their decision. The model makes it possible to define strategies to cultivate donors, generates opportunities for donors that are highly contactable and have a high probability of donating, and analyzes predictive variables. In addition, the model helps strengthen long-term relationships with the university community.
From the Judges
Strong materials make this entry a useful reference for other organizations looking to model data. The entry included a report, a PowerPoint slide deck, and a dashboard. The team recognized communication as an import part of model deployment. They were strategic in leveraging and building upon the results.
