Big data from small farms
Mark van Wijk, Romain Frelat, Randall Ritzema and Sabine
Douxchamps
ILRI@40 Livestock and Environment workshop
Addis Ababa, 7 November 2014

Farming systems analysis and HH modeling for:
- Finding structure in variability in farming
systems
- Understanding of systems functioning
- Targeting of interventions

However…
Typically we got stuck in in-depth site specific
studies
We did not deliver on the targeting promised:
What works where for which farmer?

Here…
1. Ongoing work on bringing together HH
level characterization data
2. Present a simple analysis of farm
household level food security that can be
used across many datasets

A key decision:
Go simple!!

From food self-sufficiency towards
food security

Keep the analysis simple enough to
be able to apply it across HH
characterization data collected in
different surveys!

Food crops
produced
Cash crops
produced
Off farm
income
Livestock
products
produced

Food crops
produced
Cash crops
produced
Off farm
income
Livestock
products
produced
Food
available
Consumed
Consumed

Food crops
produced
Cash crops
produced
Off farm
income
Livestock
products
produced
Cash
available
Food
available
Consumed
Consumed
Sold
Sold

Food crops
produced
Cash crops
produced
Off farm
income
Livestock
products
produced
Cash
available
Food
available
Consumed
Buy staple
crop
Expenses
Consumed
Sold
Sold

Food crops
produced
Cash crops
produced
Off farm
income
Livestock
products
produced
Cash
available
Food
available
Food
need
Buy staple
crop
Expenses
Household size
and composition
Consumed
Consumed
Sold
Sold

Food crops
produced
Cash crops
produced
Off farm
income
Livestock
products
produced
Cash
available
Food
available
Food
need
Buy staple
crop
Expenses
Household size
and composition
Consumed
Consumed
Sold
Sold
Food
security
ratio

Lushoto, Tanzania (CCAFS)

Rapid intervention analyses

First findings:
Agricultural based interventions will not get the poorest
20-60% of the smallholder farmers food secure
Alleviation of problems! Goats are an important entry
point

First findings:
The upper 20 – 50% is intensifying, and linking up to
markets
In mixed crop-livestock systems this group owns cattle:
interventions focusing on cattle productivity address
poverty but not so much food security

First findings:
20 – 60% of the farmers: agricultural interventions can
make a difference for getting farmers more food secure
In high population density areas with small farm sizes:
crop interventions can make this difference
In medium / low population density areas both livestock
and crop intervention can make this difference:
production/availability of enough fodder resources

Ongoing activities
1. Expand the database (also CA and SEA)
2. Test results (both the big FS numbers, but also
with farmers in field)
3. Adapt and apply mini-survey, on tablet
4. Super cheap survey instrument that is directly
linked to an analysis framework: produce rapid
results!

Ongoing activities
5. Implement gender component
6. With the mini-survey we fill gaps in the
database, but also set up some permanent
monitoring sites
7. For more in-depth analyses: use existing tools,
but also develop an ‘intermediate complexity
HH model’

Targeting
Can we identify robust interventions that cut across
systems and socio-economic scenarios?
(what works where for which group of farmers)
Can we upscale the strategies to quantify investment
needs in interventions?

Generate bottom up based information
to improve large scale impact assessment
exercises

Look at changing livelihoods: from that
perspective add to the land expansion /
intensification – land sharing / sparing
debates

Thanks!!