The multiple domains of development covered by the SDGs present a practical challenge for governments. This is particularly acute in highly resource-constrained settings which use a sector-by-sector approach to structure financing and prioritisation. One potentially under-prioritized solution is to implement interventions with the potential to simultaneously improve multiple outcomes across sectors, what UNDP refer to as development ‘accelerators’. An increasing number of accelerators are being identified in the literature. There are, however, challenges associated with the evaluation and implementation of accelerators. Firstly, as accelerators have multiple benefits, possibly in different sectors, they will be undervalued if priority setting is conducted sector-by-sector. Secondly, even if their value is recognised, accelerators may not be adopted if doing so clashes with any of the multiple competing interests policymakers consider, of which efficiency/social desirability is but one. To illustrate the first challenge, and outline a possible solution, we conduct a cost-effectiveness analysis comparing the implementation of three sector-specific interventions to an accelerator, first using a sector-by-sector planning perspective, then a whole of government approach. The case study demonstrates how evaluating the cost-effectiveness of interventions sector-by-sector can lead to sub-optimal efficiency rankings and overlook interventions that are efficient from a whole of government perspective. We then examine why recommendations based on a whole of government approach to evaluation are unlikely to be heeded. To overcome this second challenge, we outline a menu of existing and novel financing mechanisms which aim to address the mismatch between political incentives and logistical constraints in priority setting and the economic evaluation evidence for cost-effective accelerators. These approaches to financing accelerators have the potential to improve efficiency, and in doing so, progress towards the SDGs, by aligning political incentives more closely with recommendations based on efficiency rankings.