How cells make decisions can be investigated using mathematical models. We describe a procedure to decide whether a model is compatible with steady-state data. This method requires no parameter values-- it is based on techniques from algebraic geometry, linear algebra, and optimization. Cellular decisions also depend on where they occur in the cell (e.g., nucleus or cytoplasm). We also find that cellular information processing can be altered by including spatial organization. Borrowing tools from chemical reaction network theory and dynamical systems, we show that the existence of distinct compartments plays a pivotal role in whether a system is capable of multistationarity.