Informal network actors can help spread knowledge and promote organizational learning
The Sustainable Development Goals established ambitious goals that spurred organizations to consider new outcomes outside their traditional remit.
The paper in Nature Sustainability is here: https://go.nature.com/2qzviRu
After talking to my co-author, we think this might be a good opportunity to highlight the results in the community. The conservation sector, in particular, faced an opportunity and challenge to integrate economic development, public health, and other non-nature outcomes into their programs and strategies. This is especially difficult when organizations are large (e.g., over 1,000 staff), geographically distributed (e.g., operating in multiple countries), and work on a variety of topics (e.g., restoration, protection, sustainable agriculture) in a diverse set of biomes (e.g., grassland, tropical forests). But this is the reality faced by many large environmental non-governmental organizations (ENGOs). ENGOs seek to be as efficient and impactful as possible, and finding ways to adapt their programs and strategies to meet the demands of the changing political, economic, social, and natural environment is paramount.
This is where our research comes in. We set out to investigate efficient and effective methods for diffusing innovations within an organization. Top-down directives for change are often unpopular and expensive, so we sought alternatives. Informal networks offered an appealing alternative, as social network theories have posited some informal network actors can play a significant role in diffusion and organizational learning. Informal “boundary spanners,” crossing internal organizational boundaries, seemed especially promising. But testing this is challenging. First, a researcher must have data on, or at least an approximation of, the informal network. Second, that network must be nearly complete to be usable. Researchers using network surveys may be challenged by low response rates, which results in fragmented networks. This makes it difficult to identify boundary spanners and other important nodes. Finally, in an ideal situation it is important to minimize the risk of multiple treatments – that is, because networks by definition are links between people, it is possible that a person may get “treated” (by receiving experimental information) more than once.
We overcame these challenges in our study. We demonstrated how administrative data systems can be used to map the informal network and identify important network actors. Further, we found informal boundary spanners can significantly amplify organizational learning, even when there was no indication that they were more likely to adopt the innovation they were diffusing. We also found evidence suggesting this diffusion activity may lead to longer-term behavioral changes aligned with the innovation.
A clear next step is to take this research and inform policies and strategies within The Nature Conservancy (the organization studied). But it is also critical to share it with our colleagues in similarly large, geographically dispersed, and flatter organizations who may also be grappling with ways to leverage informal network actors to diffuse innovations for organizational learning. As policies and agendas become increasingly integrated, ENGOs and other large NGO actors must adapt to meet these challenges, and informal boundary spanners may be able to help.