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From the perspective of study management, research is surprisingly lacking on two of the major challenges for planning and performing content analysis: determining the sample size (i.e. number of objects to code) and the required number of coders to hire. The optimization of both of these numbers will ultimately determine how efficiently available resources are used. This study contributes to the methodological discussion on coding by identifying and conceptualizing the role of learning effects with respect to the coding task and by highlighting the importance of considering the coding process when managing a content analysis. We present empirical evidence for the existence and impact of learning effects on coders' coding speed. Accordingly, study management should take account of learning effects when determining the sample size and number of coders. We also provide an illustrative example of how learning effects can impact the results of pretests. [ABSTRACT FROM AUTHOR]