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PurposeThe widespread application of radio frequency identification (RFID) tags in supply chains is said to cause enormous data volume problems that could render RFID event‐driven supply chains unmanageable. An unbiased and quantitative understanding of the characteristics and extent of these data volume problems is necessary to identify and remove adoption barriers. This paper aims to address the issues.Design/methodology/approachThe paper presents a simulation study based on a real‐world scenario that reveals quantitative characteristics of the data volumes problem in an RFID‐enabled supply chain and discusses its implications.FindingsThe results suggest that data volumes will be much lower than currently assumed by practitioners. Thus, this work can be seen as a first basis for eliminating unjustified adoption concerns regarding data volumes complexity. However, it finds that the data volume problems bear still significant challenges for researchers and developers of RFID infrastructures with real‐time decision‐making applications.Research limitations/implicationsThe simulation study is based on a single product case study of a retail supply chain in Europe. Since a simulation is always a simplification of the real world, the results need to be interpreted carefully in different contexts. The nature and extent of the problem might vary across different products, industries and geographic regions.Practical implicationsResearchers, end‐users and solution providers might use our paper as a guideline how to approach and quantify the data volume problem in their particular case. Moreover, the result data can be used to benchmark and optimize RFID applications.Originality/valueThis paper is one of the first scholarly works that analyze RFID data volume problems in supply chains with a quantitative methodology.