  Both in academic and industry-based research, online evaluation methods are
seen as the golden standard for interactive applications like recommendation
systems. Naturally, the reason for this is that we can directly measure utility
metrics that rely on interventions, being the recommendations that are being
shown to users. Nevertheless, online evaluation methods are costly for a number
of reasons, and a clear need remains for reliable offline evaluation
procedures. In industry, offline metrics are often used as a first-line
evaluation to generate promising candidate models to evaluate online. In
academic work, limited access to online systems makes offline metrics the de
facto approach to validating novel methods. Two classes of offline metrics
exist: proxy-based methods, and counterfactual methods. The first class is
often poorly correlated with the online metrics we care about, and the latter
class only provides theoretical guarantees under assumptions that cannot be
fulfilled in real-world environments. Here, we make the case that
simulation-based comparisons provide ways forward beyond offline metrics, and
argue that they are a preferable means of evaluation.
