Protecting personal data is essential to guarantee the rule of law1. Due to the new Information and Communication Technologies (ICTs) unprecedented amounts of personal data can be stored and analysed. Thus, if the proper measures are not taken, individual privacy could be in jeopardy. Being the aim to protect individual privacy, a great variety of statistical dis- closure control (SDC) techniques has been proposed. Amongst many others, k-anonymity is a promising property that, if properly achieved, can help protect individual privacy. In this paper, we propose a new post-processing method that can be applied after a k-anonymity algo- rithm, being the aim to lessen the errors resulting from the aggregation of data. We show that our method can be extended to work with many other SDC techniques and we provide some experimental results which em- phasise the usefulness of our proposal.