An electrolyte is placed under an applied potential - what happens next? This question of electrochemical reactivity seems simple on its surface. However, the answer of what intermediates, products, and byproducts will form, as well as how they will form, is immensely challenging to predict. Traditional theoretical methods have either used intuitively guided mechanistic calculations (e.g. density functional theory) that abstract away competition between reactions or dynamical simulations (e.g. ab initio molecular dynamics) that are computationally intractable beyond extremely short time scales. Recently, we have taken a new approach: using data-driven reaction networks to automatically explore electrochemical reactive landscapes. In this talk, we will present an end-to-end methodology to answer questions of reactivity in complex environments. Drawing from recent studies of solid electrolyte interphase (SEI) formation in lithium-ion batteries, we will describe how to generate and analyze reaction networks, leading to insights regarding both formation mechanisms of experimentally identified products as well as the prediction of novel SEI components. We will then illustrate how individual mechanisms obtained via reaction networks can be combined to understand reactive competition using kinetic Monte Carlo simulations. The methodology that we describe has potential not just to expand our understanding of battery chemistry, but of electrochemical reactivity in general.