Presentation by Bruno Tran, Grain Postharvest Scientist, National Resources Institute, University of Greenwich Session: TechTalk for Ag. on 7 Nov 2013 ICT4Ag, Kigali, Rwanda

1. A mobile technology (M-Tech) pilot
for the
Zambian Food Reserve Agency
Emerging innovations

2. Abstract
A mobile technology (M-Tech) pilot for the
Zambian Food Reserve Agency
This pilot tests an electronic replacement to the paper-based forms used traditionally by the FRA. The pilot
covers information on quantity of maize purchased and stored temporarily at collection points, quantities being
shipped to the district depot, quantity and quality arriving at the depot, and feed-back to collection points. Data
entry is done on customised and automated Excel spreadsheets on Android-powered tablets. The spreadsheets
are synchronised daily with a cloud-based master copy, and a customised dashboard is available at the district
depot and national FRA headquarters. In this pilot, we test the technology, hardware and software, the required
users’ skills and the overall useability of the solution.
•
What is the technology being used?
a) Device(s): Samsung Galaxy Tab 7”
b) Service delivery: Web based synchronisation over mobile network
c) Format of content delivery: Customised and automated spreadsheets
d) Platform: Android and MS Excel
•
Specific challenge(s) addressed within the field of agriculture and rural development: Purchase and stock
management for a national strategic reserve requires a rapid flow of accurate information that is impossible
to achieve with current paper-based forms. This pilot tests the assumption that real-time (or near-real-time)
flow of data from rural collection points to central depots and back for timely quality feed-back, will allow the
FRA to improve its processes and procedures towards better quality of maize in store, reduced food losses
and improved financial management. This approach would be equally adapted to large private sector
purchases in the commodity sector.

3. Maize in Zambia

4. Smallholder maize production
with quantities purchased by the FRA:
2,500,000
90%
Small Holder Production
FRA Purchase
Tonnes of Maize
70%
% purchased by FRA
2,000,000
80%
60%
1,500,000
50%
40%
1,000,000
30%
20%
500,000
10%
0
0%
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012

5. Losses
FRA procures up to1.5 million tonnes of
maize
30% losses

7. Pilot project
•
•
How does the FRA lose this much maize?
What can be done about it?

8. FRA operations
SCP
•
•
•
•
SCP
SCP
Satellite storage
•
•
•
•
•
Community ownership
Improved facilities
• Cleaning area
• Fence
Successful fumigation
Improved checks
Improved Stock Taking
Depot storage
District
Depot
SCP
Transport to Depot
SCP
•
•
Farmers only (traders directly to depot)
Compulsory sieving
Quick quality checks at purchase
Planned daily intake (raffle?)
Province
Management &
Monitoring
•
•
Improved
information flow
Decentralised
responsibilities
Province
Timely information (SMS)
Timely movement of bags
Farmers bring bags to Satellite
•
•
•
•
Organised deliveries
Improved checks
Successful fumigations
Improved process for
data collection and
monitoring
National
Management &
Monitoring
•
•
Improved
information flow
Decentralised
responsibilities
Lusaka

9. Mobile Stock Management
Management Information System:
Maize purchase points
Maize storage depots
Real Time information
Monitor high stock levels
Query missing stock
Monitor quality of stock
Feedback issues to buyers

11. M-Tech at SCP

12. The data

13. Lessons Learnt
Technological issues
• Web-based synchronization technology for
rural areas
• Touch-screen tablet technology usage in
rural setting
• Support technologies: battery chargers
• “Real-time” availability of management
information

14. Lessons Learnt
Human Resources issues
• Skill levels: email, touch-screen
• Motivation to use new technology
• Sustainability of approach
Requirement for continuous, high level support

15. Conclusion
M-tech Pilot for the Food Reserve Agency
• FRA buys and stores large quantities of maize
• But experiences high levels of losses
• Real-time Stock control, Transport data and Quality
data
• Android Tablets and sync over mobile network
• Cloud based dataset
• Technically successful
• But very demanding in human resources