The ESSnet on Quality of Multisource Statistics – also referred to as Komuso – is part of the ESS.VIP Admin Project. The main objectives of that latter project are (i) to improve the use of administrative data sources and (ii) to support the quality assurance of the output produced using administrative sources. The aim of the ESSnet is to produce quality guidelines for National Statistics Institutes (NSIs) that are specific enough to be used in statistical production at those NSIs. The guidelines are expected to take the entire production chain into account (input, process, and output). They also aim to cover the diversity of situations in which NSIs work as well as restrictions on data availability. The guidelines will list a variety of potential indicators/measures, indicate for each of them their applicability and in what situation it is preferred or not, and provide an ample set of examples of specific cases and decision-making processes. The first Specific Grant Agreement (SGA) of the ESSnet lasted from January 2016 until April 2017. The second SGA started in May 2017 and lasts until mid-October 2018. A third and final SGA is planned to start mid-October 2018 and end mid-October 2019. Work Package (WP) 3 of the ESSnet focuses on developing and testing quantitative measures and indicators for measuring the quality of output based on multiple data sources and on methods to compute such measures and indicators. Examples of such quality measures and indicators are bias and variance of the estimated output. Methods for computing these and other quality measures and indicators often depend on the specific situation at hand. Many different situations can arise when multiple sources are used to produce statistical output, depending on the nature of the data sources and on the kind of output produced. Therefore we have identified several basic data configurations for the use of administrative data sources in combination with other sources, for which we propose, revise and test quantitative measures and indicators for the accuracy, timeliness and coherence of the output. In this paper we discuss WP 3 of Komuso and some of the results obtained. Section 2 describes the approach taken in WP 3. Section 3 gives some examples of quality measures and methods to compute them. Section 4 concludes this paper with a brief discussion.