Dealing with revisions is an important part of any short-term statistical (STS) process. This is especially the case when STS-estimates are based on a combination of a survey for the largest enterprises and administrative data (admin data) for medium and small enterprises. In such a system, admin data are structurally incomplete when the first estimates have to be made and this incompleteness leads to revisions when replacing these first preliminary estimates with later final estimates based on

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... a complete set of admin data. As NSIs (NSIs) have little control over the completeness of the admin data, it is important that revision analysis is carried out in order to monitor this effect. However, our analyses show that updates to the information from the large enterprises survey and corrections in the determination of the active enterprise population between the first preliminary and last final estimate are also important sources for revisions. Based on these observations, this paper describes three aspects of revision analysis. The first is revision analysis as a tool to understand the characteristics of the preliminary estimates. The second is revision analysis to suggest areas for improvement, either in a development stage or during current production. The third is to support NSIs when setting up revision policies for an STS-production process based on a combination of a large enterprise survey and admin data.