  This paper presents ongoing research focused on improving the utility of data
protected by Global Differential Privacy(DP) in the scenario of summary
statistics. Our approach is based on predictions on how an analyst will use
statistics released under DP protection, so that a developer can optimise data
utility on further usage of the data in the privacy budget allocation. This
novel approach can potentially improve the utility of data without compromising
privacy constraints. We also propose a metric that can be used by the developer
to optimise the budget allocation process.
