In the past decade, there have been increasing calls for greater use of real-world evidence (RWE) and data (RWD), with the explicit goal of enabling faster provision of effective medicines to patients in need. The push for decision makers to accept RWE is especially noticeable in the pursuit of regulatory approval, but RWE, particularly when used to estimate the relative effectiveness of interventions, is not always readily accepted by agencies responsible for reimbursement and pricing of new pharmaceuticals and, to a varying degree, is not accepted across jurisdictions. This lack of trust hampers the use of RWE despite a very large and growing literature base on the principles of how RWE should be used. In this article, we suggest an important part of the explanation of why this situation has arisen and make suggestions for its alleviation. Given that problems commonly arise that are particular to the question being asked and the data sources being used, general guidance on the principles of how to use RWD cannot cover all eventualities. Therefore, we are suggesting the creation of an archive, or repository, to record uses of RWD in support of decisions by funding bodies or their advisors. This article introduces a proposed, structured classification of decision types using RWE, around which evidence can be assembled in a curated source (RWD/RWE taxonomy) and thus facilitate judgments on when evidence is "good enough." This article is part of a series in a special issue of this journal that looks at the barriers to optimal use of RWE in health technology assessment and how to overcome them. We begin significantly to populate our "taxonomy" with examples in an accompanying article. We also propose recommendations for international standards of evaluating the acceptability of RWD governance practices.