  The overwhelming volume of data generated and indexed by search engines poses
a significant challenge in retrieving documents from the index efficiently and
effectively. Even with a well-crafted query, several relevant documents often
get buried among a multitude of competing documents, resulting in reduced
accessibility or `findability' of the desired document. Consequently, it is
crucial to develop a robust methodology for assessing this dimension of
Information Retrieval (IR) system performance. While previous studies have
focused on measuring document accessibility disregarding user queries and
document relevance, there exists no metric to quantify the findability of a
document within a given IR system without resorting to manual labor. This paper
aims to address this gap by defining and deriving a metric to evaluate the
findability of documents as perceived by end-users. Through experiments, we
demonstrate the varying impact of different retrieval models and collections on
the findability of documents. Furthermore, we establish the findability measure
as an independent metric distinct from retrievability, an accessibility measure
introduced in prior literature.
