Using data to professionalise farmer organisations

AMEA is a global network whose members and partners support millions of farmers to professionalize their business organisations. They work with all kinds of farmer-led small and medium enterprises (SMEs): cooperatives, associations, and farmer-led businesses like input retailer shops. Strengthening their capacities enables these organisations to access higher-value markets, inputs, and finance. This allows them to improve their services for members or customers.  

How can data be used to improve farmers’ access to finance and make agri-SMEs more professional?

Data-driven improvement processes are an essential foundation for agri-SME growth. In our experience, data can be harnessed at two levels: capacities and performance. Capacities include business and financial management, human resources management, members services delivery, and organisation governance, among others. Data on capacities demonstrates to agri-SMEs and their partners what areas of improvement and investment are possible. This helps inform business development plans. As for performance, data indicates how well the capacities are being executed and how much improvement is needed. Both of them help agri-SMEs to develop and access finance, as partners see the improvements already achieved as well as needed.  

AMEA promotes a standardized approach which includes assessment tools that are benchmarked to IWA29, the ISO guidelines for the characteristics of a professional farmer organisation. These assessments allow agri-SMEs to understand their strengths and weaknesses in relation to their planned growth. It also allows technical assistance to be targeted to address the weaknesses. This data also enables prospective financiers to decide whether to take these agri-SMEs into their intake process. The Bankability Metrics, a standardized set of indicators to help unlock  finance for farmers and their agri-SMEs,  is an example of how this can be put into practice. The Metrics are currently being piloted by AMEA members AGRA and SCOPEinsight.

What makes it difficult to collect data on agri-SMEs, and how could such difficulties be overcome?

Our experience is that there are many difficulties such as logistical challenges (size and dispersion of agri-SMEs and members/customers, availability of enumerators/assessors, availability of appropriate tools and technologies, etc.) and investment challenges (costs and cost-efficiency of collecting data, lack of preparedness or literacy of agri-SMEs, etc.). Legal challenges are increasing, too, as data ownership and privacy laws are tightened up. Finally and critically, there is also the farmer fatigue challenge. Farmers and agri-SMEs are regularly subjected to many assessments, which can lead to farmers seeing very little value in the process. This can mean the data collected is inaccurate and misleading. Also, farmers and agri-SMEs may not use it for their own improvement.

To overcome these challenges, AMEA believes action is needed to build a system rather than a loosely coordinated collection of projects. Therefore, AMEA works towards the creation of conducive ecosystems where actors understand the value of harnessing the power of data and create a sense of empowerment, negotiation power, and agency for agri-SMEs. The building of an ecosystem would also ensure that data governance requirements can be managed more effectively. 

These ecosystems are what we call AMEA Local Networks, which are currently active in Uganda, Ethiopia, Kenya, Ivory Coast, Honduras and Peru. They are networks in the very sense of the word: local platforms where members and partners can discuss priority areas for acting. In Uganda, for example, the network facilitated the launch of a National Cooperative Database.

Why is data ownership important for agri-SMEs?

Over the last decade, there has been a movement to recognize an individual’s right to their data: We should not unknowingly have our data extracted and shared for other people’s benefit.  In many countries, there are no or scant rules and protections addressing this. In principle, there should be no reason not to apply the same rules and protections to farmers and agri-SMEs.  AMEA therefore promotes tools which recognize these rights and supports debate about how to improve the way in which members and partners engage with farmers and agri-SMEs.

Data ownership is also critical to enable farmers and agri-SMEs to develop greater empowerment and agency in the value chains they operate. Increasingly, agri-SMEs would appreciate the value of this data in enabling access to finance, developing new business opportunities, and meeting legal obligations. This is already being seen in many member and partner projects, as evidenced by the AMEA case studies. For instance, AMEA member Cordaid’s  STARS program supported financial service providers (FSPs) to use an Agricultural Credit Assessment Tool (ACAT), which equips non-agricultural credit staff to assess finance risk in select agricultural value chains. ACAT works best when farmer organisations (FOs) have credible data to provide to FSPs. This was partially addressed by the introduction of a Harvest Tracking Tool. Also, AMEA members IFC, IDH, Cordaid, and Glimmer all used SCOPEinsight tools, which enabled agri-SMEs and RuSACCOs to plan their next phase of development.

What tools could enable farmers or agri-SMEs to collect and control their own data?

AMEA promotes the use of assessment tools as part of our peer-reviewed Toolbox.  We recommend that the ecosystem supporting farmers and agri-SMEs use these tools as part of an integrated approach to generate large-scale data.

The AMEA Toolbox continues to evolve, and we have recognized the need for data to be collected and used for decision making at different levels. This is why AMEA has supported projects in Ethiopia and Uganda, where databases are established and used at policy and agri-SME levels. This recently led to the launch of the first ever digitized database of cooperatives in Uganda. This data is collected through a SCOPEinsight Rapid Assessment process, which enables any district commercial officer or development project assessor to collect basic performance data on a cooperative within two to three hours. They can then examine this cooperative’s performance and compare it to others. This data should allow for more tailored, coordinated support to cooperatives.  At the same time, the project supported in-depth SCOPEinsight BASIC assessments of selected cooperatives, which allows those cooperatives and their partners to understand their business capacity and decide how to improve their performance. These assessment processes and use of the data require the consent of the cooperatives. The tools for enabling agri-SMEs to own their data are already in place.

The question of whether agri-SMEs should collect their own data is a live debate in AMEA. Users of SCOPEinsight tools would probably say that there would be a high risk of exaggerating and distorting data if agri-SMEs performed self-assessments. However, the cost of independent assessments is obviously higher than self-assessments, and perhaps agri-SMEs would have a greater ownership of their data if they did the assessments themselves. 

In both scenarios, we need to ensure we have tools that are standardized. That is the purpose of the IWA29, which will now be developed into a full International Standard. We also need to ensure the data collection process is using technology that enables farmers and agri-SMEs to easily access and use their data. These challenges to adopting new technology should not be underestimated but this clearly provides an opportunity for young farmers and business leaders.

One last point. AMEA promotes peer reviewed tools that have proven to be effective. However, the best tools are useless in the hands of a person who does not have the required skills and expertise to operate them. The training of enumerators and assessors is therefore critical.

What learnings could impact-focused companies working with smallholders draw from your experiences?

AMEA commissions case studies, which are collated into Annual Learning Reports. The most recent Report noted that there was very little evidence of data being owned by the farmer organisations (FOs) or used by the FOs to secure new markets or finance. The data appears to be used primarily for determining training needs and monitoring FO development. The reasons for this are: 

• The cost of the process (time and money), which led some organisations to adopting a sampling approach instead 
• Concerns about the credibility of the assessment data (although this could be expected to be controlled by the users of the tool) 
• The data only providing a partial picture of bankability 

This could be explained by another finding: “Even the more capable FOs are relatively weak and fragile. This often means that it is the off-takers and financial service providers who have the most credible data on FOs, and this data is part of their competitive edge and thus remains protected. FOs therefore often have their data extracted, rather than owning and using data for business development.”  

However, as noted by IDH in their paper  “How to Best Use Primary Farm-Level Data for Impactful Smallholder Engagement Models,” this lack of data also makes it difficult for private sector to really understand farmer needs.

What trends do you foresee for agri-data management in the future?

The learnings we have generated through our global network suggest that there is a clear demand for a better agri-data management system. However, there are still many challenges to be overcome.  Due to the mismatch between demand and supply, we expect all stakeholders to invest significantly in data management systems over this decade.  The question is whether this evolution in the generation and use of data will empower all stakeholders or entrench current power imbalances.  

AMEA will continue to promote approaches that produce inclusive business outcomes such that value is created and shared throughout the value chain. As indicated in our Annual Learning Report, AMEA believes in the development of systems that promote the most effective approaches and tools. By narrowing down on these approaches, we will generate data that is relatable and useful for decision making for all agri-business stakeholders at all levels.