Impact pathways and genealogies

I have been working with three different organisations where the isssue of impact pathways has come up. Note the use of the plural: pathways. Network models of development projects allow the representation of multiple pathways of influence (whereby project activities can have an impact) whereas linear / temporal logic models are less conducive to this view. They tend to encourage a more singular vision, of an impact pathway.

In one research funding organisation there was a relative simple conception of how research would have an impact on peoples lives. It would happen by ensuring that research projects included both both researchers and practioners. Simple as it was, this was an improvement on the past, where research projects included researchers and did not think too much about practioners at all. But there was also room for improvement in this new model. For example, it might be that some research would have most of its impact through "research popularisers",who would collate and re-package research findings in user friendly forms, then communicate them on to practioners. And there may be other forms of research where the results were mainly of interest to other researchers.This might be the case with more "foundational" or "basic" research. So, there might be multiple impact pathways, including others yet not identified or imagined.

Impact pathways can not only extend out into the future, but also back into the past. All development projects have histories. Where their designs can be linked back to previous projects these histories can be seen as genealogies. The challenge, as with all genealogical research, is to find some useful historical sources.

Fortunately, the research funding organisation had an excellent database of all the research proposals it had considered, including those it had ended up funding. In each proposal the staff had added short lists of other previous research projects they had funded, which they thought were related and relevant to this project proposal. What the organisation has now is not just a list of projects, but also information about the web of expected influences between these projects, a provisional genealogy which stretches back more than ten years.

I have suggested to the organisation that this data should be analysed in two ways. Firstly, to identify those pieces of research which have been most influential over the last 10 to 15 years, simply in terms of influencing many other subsequent pieces of research. They could start by identifying which prior research projects were most frequently refered to in the lists attached to (funded) research proposals. This is very similar to citation analysis used in bibliometrics. These results would then need to be subject to some independent verification. Researchers' reports of their research findings could be re-read for evidence of the expected influence (incuding, but not only, their listed citations). They could also be contacted and interviewed.

The second purpose of a network analysis of past research would be to identify a sample of research projects that could be the focus of an ex-post evaluation. With the organisation concerned, I have argued the case for cluster evaluations, as a means of establishing how a large number of projects have contributed to their corporate objectives. But what is a cluster? A cluster could be identified through network analysis, as a groups of projects having more linkages of expected influence between themselves than they do have with other research projects around them. Network analysis software, such as UCINET, provides some simple means of identifying such clusters in large and complex networks, based on established social network analysis methods. Within those clusters it may also be of interest to examine four types of research projects, having different combinations of outwards influences (high versus low numbers of links to others) and inward influences (high versus low numbers of links from others).

Looking further afield it may of value for other grant making organisations to be more systematic about identifying linkages between the projects they have funded in the past, and those they are considering funding now. And then encouraging prospective grantees to explore those linkages, as a way of promoting inter-generational learning between development projects funded over the years.