Farm Management Information Systems
Definition
Farm Management Information Systems (FMIS) are ICT tools that help value chain actors, such as agribusinesses, streamline the collection, aggregation, and analysis of last-mile farmer data, including agronomic, transactional, and geospatial information. This data supports efficient farmer management and helps determine which services (such as inputs, certification, and training) should be provided to which farmers, in which locations, and at what time. FMIS can also be leveraged to manage and optimise sourcing activities.
Lead Actors
Off-taker; Trader
Target Demographics
Smallholder Farmers
Objectives addressed
Farmer related
Reduce farmer cost of production:
FMIS can deliver customised services, replacing the one-size-fits-all approach. For example, GAP training and input offerings can be tailored to farmers’ cropping calendars and regional conditions. This can help reduce cultivation costs. However, for this impact to materialise, information captured by the FMIS must be shared with farmers and/or translated into targeted service delivery by the company.
Improve yields:
An FMIS enables the delivery of customised services, moving beyond a one-size-fits-all approach. For example, GAP training and input provision can be tailored to farmers’ cropping calendars and regional conditions, which may lead to improved productivity.
Address gender inequalities:
Collecting gender-disaggregated data is critical for identifying risks and opportunities for women and designing targeted interventions. FMIS can support this process provided women are adequately reached during data collection.
Boost access to finance:
FMIS can create a unique user identification platform for farmers, recording their profiles, farm practices, and transactions. This builds a financial track record that can help farmers access services like loans and insurance. It also supports the development of credit profiles that third-party financial service providers can use to offer tailored financial products.
Improve market access:
FMIS can support procurement management and enable companies to communicate timely information to farmers on sourcing activities, such as offtake demand, aggregation timing, and logistics. This can improve farmers’ access to markets.
Business related
Reduce cost-to-serve:
Several mechanisms can reduce the cost to serve: (i) digital data collection enables efficient farmer profiling and management; (ii) FMIS-driven segmentation aligns services with farmers’ needs, which can reduce unnecessary cost associated with service provision that is not being adopted by farmers or that is not effective; and (iii) FMIS supports better planning, lowering operational costs.
Lower credit losses:
Companies offering inputs on credit or other financial services use FMIS to better manage loan applications and repayments. FMIS data (e.g., field size, crops) helps calculate input credit needs, estimate yields and harvest dates, and enables automatic loan deductions from harvest sales, reducing default risks. Additionally, FMIS tracks farmers’ credit histories, supporting more informed lending decisions.
Increase revenues:
FMIS can help increase sourcing and service revenues through: (i) improved supply forecasting for cost-efficient logistics and field staff allocation; (ii) automation of transactions and input loan calculations, which can boost efficiency; and (iii) targeted service provision, which may lead to higher service uptake (and service fee revenues) and potentially increased sourcing volumes, assuming production rises through more tailored support.
Reduce side-selling:
FMIS can enhance farmer engagement through more timely payments, clearer communication on expected offtake, and more targeted service provision. This may contribute to greater farmer satisfaction and can help reduce side-selling.
Address sourcing needs:
FMIS can help companies monitor farmer performance across volumes, quality, and consistency, while also identifying where additional support is needed. When equipped with a communication function, FMIS can also enable companies to share timely information with farmers on sourcing requirements, including expected volumes and quality standards.
Attract investment:
FMIS enables companies to track farmer performance, maintain a record of transactions, monitor expected sourcing volumes, assess working capital needs, and identify potential risks and opportunities. Together, these data sources can help de-risk future investments in the company.
Improve sourcing efficiency:
FMIS enables companies to forecast supply volumes, which can support more cost-efficient planning, including logistics such as the allocation of field staff, agents, and coordination of produce collection. FMIS can automate transactions and calculations for input loans and payments for harvested produce, which can further improve operational efficiency.
Strengthen organisational processes:
FMIS can automate transactions and calculations for input loans and payments, can reduce human error while increasing transparency and efficiency. It can enable faster, safer, and more transparent payments to farmers. FMIS can also be integrated with digital tools, such as electronic weighing scales and mobile payment systems, which may further enhance transparency and strengthen the security of payments during procurement.
Contexts Best Suited to
Perishable crops: where quality and oversight are key.
High-value crops: requiring traceability for certification or regulatory compliance (e.g., coffee, cocoa, EUDR).
Production systems with scattered smallholder farmers: where data is important given variability.
Areas with sufficient digital infrastructure: such as internet connectivity for data uploading.
Regions with basic rural infrastructure: to support data collection efforts.
High-value crops: requiring traceability for certification or regulatory compliance (e.g., coffee, cocoa, EUDR).
Production systems with scattered smallholder farmers: where data is important given variability.
Areas with sufficient digital infrastructure: such as internet connectivity for data uploading.
Regions with basic rural infrastructure: to support data collection efforts.
Key Risks
Organisational capacity risks: such as HR and skill gaps for implementation and maintenance, and competing internal priorities.
Social risks: including resistance to adoption, distrust, and data-sharing fatigue.
Regulatory risks: stemming from changes or uncertainty in data policies and regulations.
Exclusion risks: where underperforming farmers may be left out of service provision.
Technological risks: such as cybersecurity threats.
Social risks: including resistance to adoption, distrust, and data-sharing fatigue.
Regulatory risks: stemming from changes or uncertainty in data policies and regulations.
Exclusion risks: where underperforming farmers may be left out of service provision.
Technological risks: such as cybersecurity threats.
Environmental Impact
Positive:
FMIS can track farmers’ input use (water, fertiliser, pesticides) and application of Good Agricultural Practices (GAP), helping optimise resource use and reducing environmental impact. Monitoring geospatial data supports sustainable land use and discourages deforestation. Potential negative impacts, such as increased travel and logistics for data collection, can be minimised by leveraging existing networks like aggregation centres or group training sessions.
Ambition level
High
Time
Before an FMIS becomes operational, significant time is spent on planning (defining the value proposition, budgeting, selecting a provider), designing the system (identifying data fields, customising to the local context, building internal capabilities), and implementation (incentivising farmers to share data and training agents to collect it). Once in use, the FMIS requires ongoing maintenance, including continuous data collection and updates to ensure it remains effective and aligned with operational needs.
Investment Need
FMIS costs include software development or purchase, personnel for data collection and management, hardware, data transmission and storage, training, logistics, quality assurance, and value-added features like two-way communication, farm traceability, or IVR systems. Costs can be reduced by choosing off-the-shelf solutions, leveraging existing networks for data collection, using remote sensing data, and establishing data-sharing partnerships with actors who deliver complementary services to farmers based on shared data.
