Access to finance is a key challenge holding back smallholder farmers. This finance gap represents a business opportunity ripe for innovation. Data-sharing partnerships hold the potential for improving access to finance and delivering other important services to smallholder farmers that could improve their commercial performance and eventually create a valuable asset class.
Smallholder farmers currently face a financing gap of close to US$ 170 billion per year. As data becomes more accessible with the digitalization of agricultural value chains, tech-enabled data-sharing partnerships have emerged that can optimize service delivery and improve access to finance for smallholder farmers and their cooperatives. The sharing and integration of data among organizations can fuel new product innovation, enhance customer adoption and engagement, drive efficiencies, and support scaling-up of private sector enterprises. These partnerships can improve service delivery and create opportunities for farmers to boost farm productivity, performance, and profitability.
A common data-sharing partnership model involves agricultural value chain players that works closely with farmers or farmer collectives and a financial service provider that holds funds for agricultural finance. These value chain players include input providers, off-takers, aggregators, processors and agri-tech innovators that provide a range of services to farmers and their collectives. They are directly involved in agricultural activities, serving and supporting farmers to optimize their farming experience. Financial institutions include traditional institutions such as commercial and microfinance banks and a growing landscape of innovative fintech start-ups. They directly impact farmers’ financial lives by offering mechanisms for savings, credit and insurance that are legal and regulated.
As data becomes more accessible with the digitalization of agricultural value chains, tech-enabled data-sharing partnerships have emerged that can optimize service delivery and improve access to finance for smallholder farmers and their cooperatives.
When these value chain players share data with each other, they enable better access to finance for the farmers they serve, which helps financial institutions reduce the risks and costs associated with lending to the agriculture sector. For these partnerships to succeed, it is critical that all partners fulfil necessary conditions for privacy and transparency, such as adherence to data protection regulations, such as the General Data Protection Regulation (GDPR) in the EU, and having at least a basic data collection and data storage plan.
As a part of its technology practice, IDH, in partnership with Dalberg Design, conducted an innovation launchpad with Barry Callebaut and Advans Group in Côte d’Ivoire to identify how the organizations can optimize data sharing to enhance service delivery to farmers. The innovation launchpad identified common frameworks and solutions where they could partner to optimize data collection and the delivery of financial services to farmers and cooperatives in the cocoa value chain in Côte d’Ivoire.
Download “Innovations for data-sharing in agricultural partnerships” for full details on how similar coalitions can tap into these opportunities or read the summaries below.
Launchpad Learnings on Data Partnerships
Two immediate opportunities for data sharing partnerships emerged out of the innovation launchpad. These included improving farmer onboarding and improving cooperative due diligence processes.
Improving farmer onboarding
Various service providers seeking to serve the same set of farmers often see inefficiencies in the onboarding process if their processes are not aligned. For instance, different approaches to farmer data collection and onboarding often result in inconsistencies in data capture, which negatively affects the data quality, data redundancies, challenges in extracting and sharing data among enterprises, and time inefficiencies as enterprises merge and integrate data. The launchpad identified two innovations to improve farmer onboarding through data partnerships, these include:
- Establish joint data standards and adhere to them at the stage of farmer onboarding: Enterprises often have their own data standards which may differ and can lead to inefficiencies. In a collaborative service delivery model based on data partnerships, enterprises would align on data standards such as the definition of key data elements (e.g. common unique identifiers for the registered farmers), the type and format of the data corresponding to those data elements, and data quality standards specific to those elements. By aligning data standards, enterprises will save time when reconciling datasets from the two organizations, improve data quality over time, and facilitate the integration of the shared data in individual data systems.
- Integrate master data systems: Another approach to streamline farmer onboarding among enterprises is to establish automated integration among individual data systems. If data systems are integrated, the last version of any data point can be accessed at any point in time without the involvement of the other party who owns and manages the data. Additionally, through such arrangements, data sharing and usage are more secure and transparent, while database administrators still retain control over data access.
Improving cooperative due diligence
Cooperatives and other forms of farmer collectives allow service providers to serve a group of farmers rather than individuals. This helps them amplify their reach and impact in a manner that is commercially viable. An orchestrated approach to due diligence while partnering to serve cooperatives can reduce both the time required for lending and the lending risks. To improve cooperative due diligence processes, the launchpad identified two innovations for data-sharing partnerships:
- Develop and implement a common data collection template: When enterprises plan to collaborate in service delivery to serve the same farmer collectives, they should align on a common data collection template. Development of such a template could encompass shared lists of data fields to collect for the due diligence; shared definition and format for those data fields; as well as technologies to enable data collection and management. Since such a template would orchestrate data collection, it is necessary to evaluate the capacity building needs of data collection staff and ensure that all operate at a similar level.
- Initiate a process for cooperative segmentation and assessment: Typically led by the financial service provider, segmentation of cooperatives with well-defined thresholds can aid the due diligence process. This segmentation process can substantially reduce the number of data points to be collected from cooperatives in a lower risk segment. Some of the key criteria for segmentation could include the volume of the credit required by the cooperative; the total production of the cooperative; and previous loan and repayment history of the cooperative. This methodology can accelerate the due diligence process by reducing the time needed to review and analyze cooperatives that have established credibility.
There are many opportunities for data-sharing partnerships that can help close the finance gap and enable a flourishing smallholder sector. We believe that such partnerships could become the new norm when it comes to providing financial services that are customized specifically for farmers living in the most rural areas, who would otherwise be excluded. These partnerships, digital technologies and platforms have the potential to play a catalyzing role facilitating the identification of respective haves and needs, offers of bundled services, reduced operating costs by leveraging existing infrastructure and relationships, and shared risk, all of which can trickle down to smallholder farmers.
Download “Innovations for data-sharing in agricultural partnerships” for the full report.