Leveraging farmer household aspirations to target and scale agricultural innovations – an approach built on novel partnerships and methods

Project Timeframe:
Apr 2018 to Dec 2019

Related country(s)


80.000$ for 2018 part


CRP Grain Legumes and Dryland Cereals


ICRISAT | Cynefin Centre | Bangor University

Historically, agricultural researchers have failed to consider household aspirations in the design, targeting and dissemination of agricultural research. Most approaches implicitly assume that households want to maximize returns to,or outputs from, their agricultural activities, neglecting the fact that most households have multiple income streams which demand their attention. While the importance of these trade-offs and interplays has been acknowledged, there has been no significant research due, in part, to the lack of appropriate tools for understanding household aspirations. A new partnership between the World Agroforestry Centre (ICRAF), the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Bangor University and the Cynefin Center is using a novel approach for agricultural research that is shedding light on how multiple income streams interact and the role they play in determining household aspirations.

The Cynefin Center is focused on distributed ethnography and works on the understanding of attitudes and perceptions within populations, while ICRAF, ICRISAT and Bangor University bring a strong understanding of the agricultural sector in developing countries and the wider systems in which rural households are embedded. The combination of distributed ethnography tools and the deep understanding of the agricultural system in developing countries now allows the team to conduct ethnography at scale and thereby answer new research questions such as ‘why do households choose the income portfolio that they do and what are their aspirations that drive these choices?’.

The SenseMaker software that we are using is founded in distributed ethnography that goes beyond simple causal relationships and sees human behaviour as being affected by a variety of interacting elements that ebb and flow. People are invited to share a story based on their lived experience then, immediately and without guidance from the interviewer, proceed to interpret it using criteria designed using expert knowledge. Thus the power of interpretation is at the level of the subject; it is the respondent who provides the data and signifies what it means, rather than the data being mediated by experts. This method is thought to have advantages over traditional experimental methods where people ‘gift and game’ as they try to figure out what the researcher wants from them and perhaps manipulate their responses for their own ends.

This is the first study that will generate data on aspirations of households and the first time Sensemaker is being used in the agricultural development setting and, as such, is a proof-of-concept. Co-locating parts of this study with ongoing projects allows us to immediately link results to current efforts and to highlight the implications of our results for future research.

We will specifically target multiple people within each household to start exploring intra-household dynamics in the formation of aspirations so as to guide future work. We are targeting a mix of communities with varying degrees of exposure to opportunities for livelihood diversification to account for external influences on the aspirations of households. The three locations in Kenya chosen are Turkana (Loima), Meru (Timau), and Makueni (Kibwezi east, Kalawa). We are targeting 100 households in each of the three regions and two people per household (the household head plus one randomly selected household member, either the spouse or a youth aged between 16 and 25, in order to gain insights into intra-household differences).

The evolution of this research and the partnership will be easily relatable to other researchers exploring new ideas by maintaining an interactive timeline that includes the main milestones but also changes in lines of inquiry and methodology as we learn lessons along the way.

Principal Investigator: 
Kai Mausch