2018 Inspire Challenge pitch, at annual convention of CGIAR Big Data in Agriculture, October 3-5, 2018, Nairobi, Kenya.

1. SEEING is
BELIEVING

2. Seeing through a farmer’s eyes

3. Weather
Data
Smartphone Pictures
from Farmers
Crop
Profiles
Satellite
Images
Soil
Data
+ + + +
Personalized
Advice

4. Does PBA increase ownership and take-up of advisory?
0.64
0.50
0.14
1.14
0.82
0.32
0
0.2
0.4
0.6
0.8
1
1.2
1.4
All advice Advice provided through
IVR and PBA
Advice provided through
PBA only
Knowledgescore(0-5)
***
***
***
Note: The comparisons between bars are based on tests of means between groups. *** indicates statistical significance at the 1 percent level.
‘N.S’ indicates lack of statistical significance at conventional levels.
98%
6% 20% 0%
87%
11%
24%
6%
0%
20%
40%
60%
80%
100%
Use of recommended
weedicides
Reported damage
due to weeds
Use of recommended
pesticides or
fungicides
Reported damage
due to pests or
disease
***
N.S
N.S N.S
PBA improved knowledge of recommended practices PBA did not have a strong effect on adoption of recommended
practices
Control (50 villages)
PBA (75 villages)
PBI + PBA (75 villages)

5. Can PBA complement insurance?
3.9
225.4
351.3
0
100
200
300
400
500
PBA only PBI only PBA+PBI
Willingnesstopay(in
Rs.)
***
Higher willingness to pay for bundled product
reveals synergies between insurance and advisories
8% 9%
26%
N.A
2.6
5.7
0
1
2
3
4
5
6
0%
20%
40%
60%
80%
100%
% extremely satisfied with
program
Average no. of repeat
pictures taken per site
Numberofpictures
%oftotalrespondents
Control PBA PBA+PBI
***
*
Providing PBI improves farmer engagement and
satisfaction with advisory service
Participants recognize PBA helping minimize risk better
than other sources
Note: The comparisons between bars are based on tests of means
between groups. *** indicates statistical significance at the 1 percent
level.
95%
81%
0%
20%
40%
60%
80%
100%
Personalized advisories
from PBA
Generic advisories from
other sources
%farmersreportingadvisories
helpedminimizerisk
***

6. Picture greenness helps identify crop growth stage, enabling personalization and increasing value
and timeliness of advice
Note: ‘Gcc’ stands for green chromatic coordinate, with its value normalized by the maximum gcc for the site. See details in Hufkens et al.
(2018)

7. 4
Scale-Up Plan
STATE OF HARYANA (0.74 million)
Scale-up model: Commercial, retail approach1
STATE OF ODISHA (1.77 million)
Scale-up model: Link with digital crop registry2
3 STATE OF TAMIL NADU (0.6 million)
Scale-up model:
Link with digital
crop registry
Scale-up model:
Link with
PlantWise
ALL INDIA
Scale-up model: Couple with national
insurance scheme (PMFBY)
4
3
1
2

8. Importance of the issue
Improving food security
and resilience from
climate change,
potentially reaching up to
4.1 million smallholders
Scale-UpPotential
Benefits for adopters
Tangible, high-quality
risk management
services; large potential
to improve profitability
and resilience
Ease of adoption
Easy to understand,
user-friendly protocol
with direct farmer
engagement, leveraging
their own smartphones
Credibility and
observability of innovation
Rigorous evaluation
identified key synergies in
our approach, leading to a
committed consortium for
scale up
Enabling environment
Large national insurance
scheme, with strong
existing incentives to
provide low cost, high
quality insurance
Benefits for
value-chain
Improved monitoring,
reduced risk, and lower
costs across the value
chain

9. Thank you!
bigdata.cgiar.org