Exploring the PICSA approach with financial institutions in Kenya

Participatory Integrated Climate Services for Agriculture (PICSA) (https://research.reading.ac.uk/picsa/) is a highly successful participatory extension approach, developed by researchers at the University of Reading. It has proven to be an exceptionally effective method of supporting farmer innovation in over 20 countries across the world. 

PICSA makes use of historical climate data, forecasts and farmers’ knowledge of what works in their own context with participatory planning methods to help farmers make informed decisions about their agricultural practices. 

The climatic data component of PICSA relies on the ability of the local partners, often the national meteorological services, to analyse historical daily climatic data to provide the local climate information for their country. 

IDEMS provides support for local partners to work with climate data in a number of PICSA implementations, including in Lesotho as mentioned above.

The International Fund for Agricultural Development (IFAD) funded the University of Reading for a project to investigate the potential of using PICSA with financial service providers (FSP). IDEMS, with in country partners, took the lead on a scoping study that interviewed six FSP already working with IFAD, to investigate how climate risk could be better modelled for FSP and how their activities and interests could align with the PICSA approach.

We are now in the process of setting up a workshop where the FSP will be trained in the PICSA approach based on the priorities identified during discussions with them. 

We are excited by this important work because we believe in the PICSA approach and the way it uses climate data as a way of contributing to people making more informed decisions, in some cases changing opinions and mind sets and ultimately empowering farmers to tackle problems that are within their control. 

Extending PICSA to engage with FSP, by working towards a better understanding of risk using climate data and models, has the potential for not only improving the work of FSP, but also helping reduce farmers to better manage their risks.