Albert and James explore what the new EU funding for experimental innovation support means for innovation agencies and evidence.
Back in 2015, the Canadian Prime Minister publicly released, for the first time, his instructions to all his ministers. Among these instructions, entitled mandate letters, one was particularly relevant to experimentation. It was addressed to the President of the Treasury Board of Canada, and it stated:
Recent years have seen a growing interest and increasing uptake of experimental methods in government. Around the world, we see a growing number of governments taking up experimental approaches to tackle complex issues and generate better public outcomes.
There is growing public concern about the challenges the economy of the future presents. From automation to rising inequalities, governments are looking for ways to tackle these issues while rekindling growth rates that have been, in many advanced economies, sluggish.
Embarking on a journey of policy experimentation might be easier with just a first small step… Keen to encourage a culture of experimentation amongst policy makers, IGL has been examining the barriers that prevent its adoptions – finding that these include a reluctance to disrupt the status quo, fears of a backlash if ‘lotteries’ are used to allocate support or simply that evaluation is considered too late.
What prevents government agencies from making a greater use of randomised controlled trials (RCTs), as well as evidence to inform their policies? Last summer we set out to answer this question, and to try and tease out which barrier is the most important. In this blog we present the results from our survey.
IGL is undertaking a study on the barriers that prevent organisations from using randomised controlled trials to evaluate programmes and, more generally, using evidence to inform policies. Take part in our survey to give us your perspective.
As more and more governments attempt to base their policies on sound evidence, randomised controlled trials - the 'gold standard' in evaluation - are gaining a stronger role in determining which policies work. But are they really the best way to tell us which policies should be used? This blogpost explores how to improve our ability to learn and better design things that work.