It is widely accepted that, as well as developing new Clinical Outcome Assessments (COAs) for clinical trials, using existing COAs to evaluate treatment benefit from the patient perspective is often a more pragmatic, time- and cost-effective strategy. However, the suitability of a COA (whether new or existing) is dependent on evidence of content and psychometric validity in a specific context and for specific concepts of interest. Determining which existing COA is most suitable based upon these criteria is particularly challenging when a large pool of instruments is available. For example, a recent MEDLINE search for COAs in head and neck cancer yielded more than 100 instruments. To shortlist from here, the logical next step is to review which COAs have been used (successfully and unsuccessfully) by sponsors in previous and ongoing trials. However, there is no clear guidance that explains how to identify relevant products or trials and what information to review to support measurement selection and ensure regulatory acceptance. Thus we outline an approach that is systematic, robust and pragmatic to support the selection of an existing COA for inclusion in upcoming studies. The Competitor Outcomes Landscape Analysis (COLA) methodology is a four-step approach: 1) identify relevant competitor drugs using a global clinical trial database, 2) review the Drugs@FDA database and the EMA’s European Public Assessment Reports to establish approval status and identify COAs included in labelling, 3) review FDA’s Drug Approval Packages to document regulatory decision-making and 4) identify COAs included in trial protocols for drugs in development. The COLA approach helps sponsors to select the most appropriate COA for studies in a specific population and disease area. We believe this framework allows for more confidence, transparency and credibility in the decision-making process and as such COLA is a systematic approach to support an optimal COA strategy.