Project documentation is generally a valuable source of project knowledge. Consequently, established project management guidelines explicitly recommend a systematic analysis of such codified project experiences in order to identify lessons relevant for the planning of future projects. In practice, however, project managers are limited in their capacity to process this codified project knowledge due to the often very large stocks of project documentation. One solution for handling this extensive collection of documents could be the automated content analysis (CA) approaches currently growing in favor. Nevertheless, to date, no studies have been published that address and compare the efficacy of both automated and manual CAs for extracting lessons learned from project documentation. This raises the following questions: to what extent are automated CAs a viable solution for handling large stocks of textbased project documentation and how do they compare to the corresponding manual CAs? To answer these questions, an experiment was performed in which lessons learned were extracted using automated and manual CAs. A comparative evaluation was then made to further extend what is known about the efficacy of both automated and manual CAs. It became clear that the outcomes of the two methods do differ and that each has its potentials and limitations. This confirms the relevance of a further examination of these approaches to project management. Finally, the findings collected in this preliminary study have been used to derive propositions for subsequent studies.