Part of the profession concentrated on a narrow set of well measurable (i.e. “to what extent”) questions. Others chose a wider set of (i.e. “why”/“how”) evaluation questions in an attempt to better reflect the complexity of the real world. In this view, interventions are part of a causal package and only work in combination with other factors such as the cultural background of the beneficiaries, stakeholder behaviour, institutional settings, environmental context, etc. Building on this, over the last decade, evaluators have constantly been working on broadening the range of impact evaluation methods (Stern et al., 2012). Besides randomised controlled trials (RCTs) – the former “gold standard” of the development evaluation community (see also "RCTs and rural development - an abundance of opportunities") – other econometric, theory-based, case-based and participatory approaches have gained ground and experienced enormous improvements in the field of systematic testing procedures, a prerequisite for rigorous causal inference.

Beyond the increased variety of rigorous methods, the field of impact evaluation benefits from new forms of data collection and analysis which emerged in the digital revolution era.