Data Driven Agriculture: Forging Ahead
If it cannot be measured, it cannot be done. If it is not known, then it never occurred. Data and information management are synonymous to salt in food. We cannot over-emphasize the need of having correct and updated data and information management and dissemination as an enabler towards sustainable agricultural practices. Information is processed data and therefore quite a fundamental resource in implementing agriculture policies, strategies and business plans.
The resounding case scenario of broker farmers being paid for supplying maize to the National Cereals and Produce Board while the actual maize producers cry foul play is painstaking evidence of lack of proper data on land under production, a wanting farmer registry and lack of proper planning once again due to lack of data.
The main achievement of the Big 4 Agenda on Food and Nutrition Security will be realized with the attainment 100% food and nutrition security 2022. The key priority areas towards achieving food and nutrition security will be on increasing access to agricultural inputs, expanding irrigation schemes, implementing programs to support smallholder farmers, fisher folk and pastoralists to sustainably produce and market various commodities, and supporting large scale production of the specific staple crops as per the region. The recent report by the Kenya National Bureau of Statistics 2018 indicates that the Agriculture Sector contributes to approximately 31.5% to the Gross Domestic Product and thus employing over 70% of the Kenyan population both directly and indirectly. Now you know that agriculture contribution to the GDP is not an exaggerated or generic figure that frequent a variety of speeches and causes confusion as to which is which.
Data on soil profiling is rather archaic and this provides opportunity for soil scientists to carry out soil surveys, though it’s quite a lengthy process. The danger on relying on old age data here is rather obvious given that the climatic conditions, fertilizer effect on soils and soil formation processes have altered the composition of the soil profile down the years. Land is a major factor of production and the need to focus on proper soil management practices is quite dire given that productive land is slowly being encroached through human settlement and urbanization. Data will help in proper planning, evaluation and identification of most appropriate conservation measures and monitoring of soil management activities to measure effectiveness, and efficiency.
Another data set that needs to be enhanced is data on production as per the agricultural value chains be in under crops, livestock, fisheries or animal production. There is need for data on farmers and acreage of farm and then the quantity of production of the various commodities they sell. This calls for one on one verification visits to the actual farmer and farmland to ensure accuracy and integrity in the statistical analysis process. Another gap in agricultural statistics is data on production potential of the different agricultural regions. The production potential should be established with consideration to innovations, skilled extension service provision, application of science and technologies that enable progressive transformation in the agriculture sector.
Data is of great use by policy makers in informing their policy making processes by portraying the actual state of the sector and the significant issues and where the policies have overlooked fundamental aspects in the entire agriculture value chain. The information should be up to date and a reflection of the actual farming scenario from the actual farmers.
Data generated by research institutions should be made easily accessible to the common citizen so as to guide the design thinking process of any persons involved along the agricultural value chain. For example, use of antibiotics in animal breeding procedures tends to promote generation of cancerous cells in the human body once the humans ingest animal products for example meat. This should inform the animal breeders, the extension personnel teaching on animal breeding, farmers, food safety and standards management organizations and the final consumers of the animal products. Data on ongoing agricultural services offered by the numerous agribusiness start-ups, companies and even donor agencies should be collated and readily available for benchmarking across the stakeholders and further building of synergies where the institutional deliverables are inter-related.
The agriculture value chain is multi-sectoral in nature; bringing various sectors such as energy, infrastructure, environment, manufacturing, health care, textiles just to name a few into play in ensuring food and nutrition security. This is in full recognition that other aspects of data collection and analysis such as infographics to enhance data visualization, use of Information Technology such as Geo-spacial Planning just to mention a few must be factored in to revolutionize statistics in agriculture. It is therefore of great urgency that the statistical capacity of the agriculture sector as a whole be polished and rock-solid foundations be established. This will promote transparency, knowledge-driven agricultural practices and eliminate the issue of Kenya having sound policies with poor implementation structures.