Need for fodder production data in ASALs

Food security, a key pillar of the ‘Big Four Agenda’, is, for the arid and semi-arid lands (ASALs), synonymous with the livestock sector, to which is pegged the success of the other three pillars — education, health and housing.

Halfway in the Jubilee agenda, let us review the ASALs’ performance on the fodder front. Counties such as Laikipia, Nyandarua and Narok have been committed to growing and conserving fodder, mainly hay.

With a combined land mass of 30,710 square kilometres (according to the individual counties’ websites) — Laikipia 9,462 km², Nyandarua 3,304 km² and Narok 17,944 km² — they not only produce hay for own consumption, but also sell it in Nairobi and central region.

Laikipia is also the fallback county for its pasture-deficient neighbours — and this often has its attendant security issues.

But do they achieve their full potential in hay production? What is their total production in 2019? What is the year-on-year growth rate?

At this rate, can they satisfy the demand for meat and milk in, say, 2035?

BUSINESS MODEL

Hay growing in Kenya is more on a ‘me too’ copycat trend devoid of data, market research, or quality standards, and with the utopian belief that, with minimum effort, one can make big money.

But such a business model is neither resilient nor economically scalable.

Counties should deploy fodder data models that can forecast the national hay demand for longer periods than our five-year electoral cycle, taking into account factors such as population size and growth and national income levels.

Since the efficacy of the model will depend on the data, it’s important that models are made by experienced teams.

The counties can then use their hay production data — mainly collected at cess points or at farm level — to strategise on meeting future fodder demand.

The unique factor for the ASALs is the availability of expansive land — an advantage in that mechanisation can be effectively deployed, achieving economies of scale.

MARKET TARGETS

But it becomes self-defeating with the tendency to look at hay production in absolute yields instead of maximising production per acre.

By using production data, counties can know if they will meet their market targets by increasing acreage or improved management practices.

This would also avoid duplication of projects by donors and development agencies.

Clear production data and targets would give the counties an in-house tool to monitor if the projects meet their fodder objectives.

Combining their production data and the national hay demand models can help the counties to know if and when they would have excess hay, for which they can then start thinking about the lucrative export market, especially in the Gulf countries.

Data models can also help private investors to not only make informed decisions, but also formulate a business plan when seeking finance.

BENCHMARKING

The counties with credible and easily accessible data are more likely to be preferred by investors.

Lastly, credible fodder data models can be used in benchmarking and appraisals within the county and externally when ranking regions nationally.

In today’s food production world, working without data is as good as flying blind. Taking advantage of data could be the low-hanging fruits that can reposition the ASALs counties to be the fodder barns of Kenya.

Ms Munene is the manager, Lukuai Hay Farm, Laikipia. [email protected]