Introduction

The rise of AI, and controversy about its best (or any) use, is the most recent demonstration of how technology for generating and communicating evidence continues to grow at a dizzying pace. Support for those taking ‘evidence- based’ decisions can now come from a plethora of sources including pseudo- evidence from lobbying, interest groupings and disparate sources within social media. Evaluation evidence, where it exists, will be just a part of the perhaps numerous influences open to decision- makers.

Evaluation evidence may consequently struggle to have its voice listened to. Even well- placed evidence may struggle to be heard against more palatable or louder voices. Purposeful evaluators need to avoid cynicism that this is naturally the case. As a leading opinion former in medical science recently put it to the author: ‘Evidence [in public policy] may take time, effort and persistence to make its mark, but good evidence will eventually get there.’ This chapter focuses on how to optimise opportunities for making that mark; it draws unapologetically, and heavily, on the author's own experience and practice.

Improving use and utility

The practice of systematic evaluation, in many areas of public policy, has been boosted by ideas of ‘evidence- based’ decision-making which emerged from ‘evidence- based medicine’ in the 1980s. In the later 1990s, this began to be applied to other areas of public policy, notably in the UK, Australia and parts of Europe, and was a central tenet behind the creation of the UK's ‘What Works Centres’. Yet, despite the policy rhetoric and an extensive academic literature exploring and categorising what is ‘evidence-based’, evidence continues to find itself facing competitors who may have more pull on decision- makers (Figure 15.1).