Retrievability is an important and interesting indicator that can be used in a number of ways to analyse Information Retrieval systems and document collections. Rather than focusing totally on relevance, retrievability examines what is retrieved, how often it is retrieved, and whether a user is likely to retrieve it or not. This is important because a document needs to be retrieved, before it can be judged for relevance. In this tutorial, we explained the concept of retrievability along with a number of retrievability measures, how it can be estimated and how it can be used for analysis. Since retrieval precedes relevance, we described how retrievability relates to effectiveness - along with some of the insights that researchers have discovered thus far. We also showed how retrievability relates to efficiency, and how the theory of retrievability can be used to improve both effectiveness and efficiency. Then an overview of the different applications of retrievability such as Search Engine Bias, Corpus Profiling, etc. was presented, before wrapping up with challenges and opportunities. The final session of the day examined example problems and techniques to analyse and apply retrievability to other problems and domains. This tutorial was designed for: (i) researchers curious about retrievability and wanting to see how it can impact their research, (ii) researchers who would like to expand their set of analysis techniques, and/or (iii) researchers who would like to use retrievability to perform their own analysis.