Data-Driven Agriculture: The Future of Smallholder Farmer ... · input suppliers, agro-processors...
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DATA-DRIVEN AGRICULTURE The Future of Smallholder Farmer Data Management and Use DIGITAL FARMER PROFILES: THEN AND NOW A digital farmer profile is a profile that can capture comprehensive data on a farmer and their farm. It can be developed over time, provide real-time data flows between farmers and stakeholders, and it can be accessed simultaneously by multiple service providers such as financial service providers, input suppliers, agro-processors and farmer cooperatives. OBD=Out-bound dialing IVR=Interactive Voice Recording API= Application Programming Interface B2B=Business to Business B2C=Business to consumer e type of service provider does not necessarily determine what data they collect, how they collect it, or how it is used, but service provider models are an important starting point for understanding farmer profile data management. Farmers need to make decisions in critical moments. e aggregation of information from their profile data, remote-sensing data, satellite and weather data makes this possible. Big data is one promise that can bring fragmented data, resources and service providers together to support a farmer’s ecosystem. As digital management of farmer profile data becomes the norm, the farmer becomes only one of many sources of that data, and only one of its many users. More than 500 million smallholder farms worldwide play a significant role in food production and genetic diversity of food supply. Mobile technology, remote-sensing data and distributed computing and storage capabilities are changing how smallholder farmers are identified, understood and supported. DATA GENERATORS: SERVICE PROVIDERS Service providers who collect data on and from smallholder farmers fall into four main models. DATA CAPTURE, ANALYSIS AND USE Digital data capture is the starting point for developing a digital farmer profile ecosystem. Leveraging the three methods of data capture below increases the accuracy of profiles. DATABASE 1 3 Paper Surveys Digital Surveys Human-centered Design (Qualitative) National ID Registry Land Management PEOPLE FACILITATED (i.e., extensions agents, researchers) REMOTE SENSING OR CAPTURE Registration Usage Chatbots Crowdsourcing Phone-based Capture SMS OBD IVR Call Center GPS Phone Usage Transactions Passive Mobile Capture Mobile Phone Applications Satelitte Drones Sensors Weather Registry Facebook Phone Data Other Datasets 2 MOBILE PHONE DATA AND REVENUE FLOWS Changing methods of data capture are giving rise to new configurations within service provider models. KEY CONSIDERATION When assessing how to leverage farmer profile data USAID staff and Feed the Future partners should consider: Today, farmers provide data to service providers in exchange for support services. In the future, farmers might monetize their own data. All service providers should consider how to compensate farmers for their data. This can be a pathway to farmers’ financial sustainability and protect their privacy. • How are smallholder farmers defined? • What is the landscape of service provider models? • What is the technology environment for supporting digital capture, analysis and timely use of data? • What data is commonly collected, what are the gaps and is data being shared? • Are there farmer profile data sources that can be leveraged to build dynamic farmer profiles? • What farmer archetypes have been created by programs and can they be leveraged by other service? • What is the policy and legal environment for data sharing, consumer protection and privacy? • How is data shared post-project? • What may be the utility of the projects’ data assets for other service providers? • What investments by USAID and other donors can support the development of a digital data ecosystem for farmer profiles? 3 2 1 6 5 4 9 8 7 * 0 # NGO TA PROVIDERS GOVT. RESEARCH NGO / GOVERNMENT COMMERCIAL B2C Market Services B2B DONORS & INVESTORS FARMER SERVICES SERVICES SERVICES B2C INFORMATION SERVICES B2C MARKET SERVICES B2C FINANCIAL SERVICES B2C AGGREGATOR This product is made possible by the generous support of the American people through the United States Agency for International Development (USAID). The contents are the responsibility of FHI 360 and do not reflect the views of USAID or the US Government. For additional information digital agriculture technologies, including farmer profiles, please visit www.usaid.gov/digitalag EXTENSION AGENT SERVICE PROVIDER FARMER THEN NOW DIGITAL FARM DATA SATELLITE MOBILE PHONE DRONES WEATHER FARMER PLANTS/ ANIMALS APIs (financial services, other) SERVICE PROVIDER(S) EXTENSION AGENTS SENSORS (soil,water) DIGITAL FARM DATA PROJECT MANAGEMENT/ TECHNICAL ASSISTANCE 1 2 3 4 RESEARCH ENTITIES GOVERNMENT / NGO EXTENSION SERVICES COMMERCIAL SERVICE PROVIDERS (B2B AND B2C)
Transcript of Data-Driven Agriculture: The Future of Smallholder Farmer ... · input suppliers, agro-processors...
DATA-DRIVEN AGRICULTUREThe Future of Smallholder Farmer
Data Management and Use
DIGITAL FARMER PROFILES: THEN AND NOWA digital farmer profile is a profile that can capture comprehensive data on a farmer and their farm. It can be developed over time, provide real-time data flows between farmers and stakeholders, and it can be accessed simultaneously by multiple service providers such as financial service providers, input suppliers, agro-processors and farmer cooperatives.
OBD=Out-bound dialing IVR=Interactive Voice Recording API= Application Programming Interface
B2B=Business to Business B2C=Business to consumer
The type of service provider does not necessarily determine what data they collect, how they collect it, or how it is used, but service provider models are an important starting point for understanding farmer profile data management.
Farmers need to make decisions in critical moments. The aggregation of information from their profile data, remote-sensing data, satellite and weather data makes this possible. Big data is one promise that can bring fragmented data, resources and service providers together to support a farmer’s ecosystem.
As digital management of farmer profile data becomes the norm, the farmer becomes only one of many sources of that data, and only one of its many users.
More than 500 million smallholder farms worldwide play a significant role in food production and genetic diversity of food supply. Mobile technology, remote-sensing data and distributed computing and storage capabilities are changing how smallholder farmers are identified, understood and supported.
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DATA GENERATORS: SERVICE PROVIDERSService providers who collect data on and from smallholder farmers fall into four main models.
DATA CAPTURE, ANALYSIS AND USEDigital data capture is the starting point for developing a digital farmer profile ecosystem. Leveraging the three methods of data capture below increases the accuracy of profiles.
DATABASE
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1 3
Paper SurveysDigital Surveys
Human-centered Design(Qualitative)
National ID Registry
Land Management
PEOPLE FACILITATED(i.e., extensions agents,
researchers)
REMOTE SENSING OR CAPTURE
RegistrationUsage
ChatbotsCrowdsourcing
Phone-basedCapture
SMSOBDIVR
Call Center
GPSPhone UsageTransactions
Passive MobileCapture
Mobile Phone Applications
Satelitte
Drones
Sensors
Weather
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*0
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*0
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RegistryFacebook
Phone DataOther Datasets
DATABASE
2MOBILE PHONE
DATA AND REVENUE FLOWSChanging methods of data capture are giving rise to new configurations within service provider models.
KEY CONSIDERATIONWhen assessing how to leverage farmer profile data USAID staff and
Feed the Future partners should consider :
Today, farmers provide data to service providers in exchange for support services. In the future, farmers might monetize their own data. All service providers should consider how to compensate farmers for their data. This can be a pathway to farmers’ financial sustainability and protect their privacy.
• How are smallholder farmers defined?• What is the landscape of service provider models? • What is the technology environment for supporting
digital capture, analysis and timely use of data? • What data is commonly collected, what are the gaps
and is data being shared?• Are there farmer profile data sources that can be
leveraged to build dynamic farmer profiles?
• What farmer archetypes have been created by programs and can they be leveraged by other service?
• What is the policy and legal environment for data sharing, consumer protection and privacy?
• How is data shared post-project? • What may be the utility of the projects’ data assets for
other service providers?• What investments by USAID and other donors can support the
development of a digital data ecosystem for farmer profiles?
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98
7
*0
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*0
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NGO
TAPROVIDERS
GOVT.
RESEARCH
NGO / GOVERNMENT COMMERCIAL
B2CMarketServices
B2B
DONORS & INVESTORS
FARMER
SERVICES
SERV
ICES
SERVICES
B2CINFORMATION
SERVICES
B2CMARKETSERVICES
B2CFINANCIALSERVICES
B2CAGGREGATOR
This product is made possible by the generous support of the American people through the United States Agency for International Development (USAID). The contents are the responsibility of FHI 360 and do not reflect the views of USAID or the US Government.
For additional information digital agriculture technologies, including farmer profiles, please visit www.usaid.gov/digitalag
EXTENSION AGENT
SERVICE PROVIDER
FARMER
THEN NOW
DIGITALFARM DATA
SATELLITE
MOBILEPHONE
DRONES
WEATHER
FARMER
PLANTS/ANIMALS
APIs(financial services, other)
SERVICEPROVIDER(S)
EXTENSIONAGENTS
SENSORS(soil,water)
DIGITALFARM DATA
PROJECT MANAGEMENT/ TECHNICAL ASSISTANCE1
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RESEARCH ENTITIES
GOVERNMENT / NGO EXTENSION SERVICES
COMMERCIAL SERVICE PROVIDERS (B2B AND B2C)
