Title : Malawi’s national agriculture management information system ecosystem and opportunities
Abstract:
This paper is based on a case study on the implementation of Malawi’s first National Agriculture Management Information System (NAMIS). NAMIS is a comprehensive and integrated platform that is used to gather, manage, analyse, and disseminate agricultural data and information from the point of collection (farmers, markets) to the national level. It is integrated in the sense that it has tools for different agriculture activities and departments, like market data, farm inputs, post-harvest losses, animal health, production estimate surveys, fisheries, weather, and climate data. The aim of this paper is to identify opportunities that exist through the implementation of a national agriculture system. This is based on the premise that most research done in the Agriculture Information System (AIS) across Africa has focused on identifying challenges in their implementation, and mostly the findings are based on the implementation of single activity within the agriculture ecosystem, like market information or farm inputs only. Finding possibilities inside a digital intervention is essential to matching the needs of system users; this increases the likelihood that the digital solution will be accepted and used. Design and functionality decisions that appeal to people can be made with an understanding of these needs. We employed an interpretive approach to qualitative data analysis. Data was collected using interviews, focus group discussions (FDGs), and observation for a period of 12 months. Data collection was done across all levels in the agriculture ecosystem (national to block level). 8 interviews were done at the national and district levels, and 2 FDGs were conducted at the Extension Planning Area (EPA) level with 11 and 9 participants, respectively. The study identified these opportunities that have arisen due to the implementation of NAMIS. NAMIS provides for a learning platform in digital agriculture and ICT education. In most education institutions, the literature used in African contexts lacks contextualisation as it is mostly adapted from developed countries, which use their study cases. It also provides for a platform where African researchers can get practical data on different cross-cutting technologies like machine learning and AI, as the data could be made available for different research activities and as well on how to design software systems, adoption, and data use to improve the platform. NAMIS also provides an opportunity for cross-sectoral system integration and data sharing. For example, disease surveillance is important in human health, which is covered by the Ministry of Health, and animal health under the Ministry of Agriculture. As well, on human nutrition, mostly it is dependent on agriculture production and food availability at households, which is one of the components in the NAMIS platform. With such cross-cutting issues, it provides for an opportunity where decisions should be made from rich context data by combining different data sources.
