Many biological and chemical processes proceed through one or more intermediate steps. Statistical analysis of dwell-time distributions from single molecule trajectories enables the study of intermediate steps that are not directly observable. Here, we discuss the application of the randomness parameter and model fitting in determining the number of steps in a stochastic process. Through simulated examples, we show some of the limitations of these techniques. We discuss how shot noise and heterogeneity among the transition rates of individual steps affect how accurately the number of steps can be determined. Finally, we explore dynamic disorder in multistep reactions and show that the phenomenon can obscure the presence of rate-limiting intermediate steps.