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Blog Post
15 January 2018

Know your numbers: Kenyan agricultural transformation needs stronger data systems

Photo by Olu Eletu on Unsplash.

In Kenya, nearly 70% of people reside in rural areas, and almost 80% of the rural population rely on agriculture for a living or sustenance. Like much of Sub-Saharan Africa (SSA), Kenya faces two interrelated challenges: widespread rural poverty and the risk of rising food insecurity. These are then in turn affected by population growth and climate change, which exacerbate the already low agricultural productivity.

Clearly, addressing these challenges will not be possible without agricultural transformation and smart rural development.

An agricultural transformation is a process by which a low productivity subsistence farming agro-food system leaps towards a more efficient, commercialised, market-responsive production.

Like most countries in SSA, Kenya is blessed with a wide diversity of agro-ecological zones, allowing for cultivation of nearly any crop and livestock. Kenya also has access to the world’s second-largest fresh water body, Lake Victoria, and borders the Indian Ocean, meaning access to fish is abundant. An agricultural transformation in Kenya is possible, and overdue. Yet Kenya’s natural endowment is underused.

Explaining the status quo

Kenya has no lack of regulations, policies, strategies and development plans aimed at facilitating agricultural transformation. However, despite a wealth of high-quality research available, policies and strategies have not been implemented; several factors needlessly holding back the transformation.

One factor is the fact that rural land is fragmented into very small holdings. It is a result of an annual population growth rate of 3.2%, combined with unclear land policies and limited investment in small and medium enterprises. This in turn is holding back mechanization and economies of scale in production. Smallholders also tend to cultivate a portfolio of crops, with little knowledge about what market demands or what the best farming practices are, which compromises productivity.

Climate change and land degradation are also important obstacles to agricultural intensification in Kenya, but have not been given sufficient attention in planning and resource allocation. Meanwhile, comparing to many other countries, irrigation development is slow only 19% of the irrigation potential of at least 540,000 ha has been utilised.

The missing numbers

It is legitimate to wonder whether the current agricultural policies and strategies are well informed. A key issue is data. Using quality, up-to-date agricultural data is vital for decision making and policy development. It is also needed to ensure transparency, and to attract the right investments.

Middle-income agriculture-dependent economies, such as Kenya’s often have the poorest data both with regard to quality and scope. The excuse being, resources to direct into improving statistical quality for informing policies are limited and that there are more urgent outstanding priorities.

Meanwhile, agricultural data in Kenya is top heavy, particularly when it comes to open data sources. Even though the Kenya National Bureau of Statistics (KNBS) provides macro-level trends, such as; agriculture contribution to GDP, or incomes from some food crops, there are few or no disaggregated statistics, at household or farm level or data disaggregated by gender. There are also other important gaps in the data; for example, the percentage of households owning title deeds or household capacity to respond to climate change.

Better household level data and other lower-level data would be particularly important, not least because of the predominance of smallholders, who have various farming strategies.  Often such data is in fact being collected, but by different organizations working in isolation and with different methodologies, which means the data is not being coordinated or processed centrally by the KNBS.

There are also budget constraints in Kenya, meaning there is often a trade-off between depth and breadth of data collection, as noted in the Strategic Plan for Agricultural and Rural Statistics for Kenya, (SPARS; 2015–2022).

Another challenge is poor availability and access. Most of the data holders in the agricultural data ecosystem, including the smallholder households, are unwilling to share information due to concerns about attribution, intellectual property, commercial sensitivity or security.

Thus, most agricultural stakeholders in Kenya currently only have access to agricultural data from open sources such as the World Bank database, ministry and country databases, FAOSTAT and the KNBS, which have limited datasets.  And even when the data is freely accessible, effective dissemination or communication is not in place.

All that said, it is promising that Kenyan government announced it will finally carry out an agricultural census in 2025, and recently hosted a roundtable meeting for the World Programme for the Census of Agriculture 2020.

George Oketch Achola is a farmer preparing the new bean varieties for market.

Making the change

There is clearly a need for improvement in the gathering, accessibility and use of agricultural data in Kenya. Given the diversity of data that should be (and sometimes is being) collected to support the development of the agricultural sector in Kenya, coordination will be an essential function. As the mandated national statistical body, this is clearly a role for the KNBS. The global strategy for agricultural and rural statistics provides a framework for facilitating this coordination and developing a bare minimum of agricultural data required by the various stakeholders.

At the level of data gathering, this would mean identifying research gaps and priority research questions for different stakeholders. KNBS should develop methodologies and build the capacity of local stakeholders to apply them, in order to ensure consistency between data gathered in different areas and subsectors.

KNBS could also oversee the creation of an open agricultural data repository, where all stakeholders can make their data freely accessible.

Finally, there is a compelling case for developing the capacities of institutions and individuals to analyse, interpret and use data. This would help farmers and other agricultural stakeholders to make better decisions, plans and investments. It should also help with ensuring the quality of data generated.

However, at the end of the day, it is important to keep in mind that activities around data generation and sharing should be a means to an end: data is important, but the right type of data that fits the purposes of agricultural transformation in Kenya is essential. And as observed by Stephen Few in his “Show me the numbers” book: “Numbers have an important story to tell, they rely on you to give them a clear and convincing voice.”

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