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In our 2021 Agricultural Platforms in a Digital Era report, ISF presented a definition of “platforms” defined by two distinguishing factors: 1) they are built upon network effects, enabling multiple users on both sides of an exchange to interact, and 2) unlike traditional “pipeline businesses” they do not produce goods or services, but rather link users together to access goods and services. Since the publication of that report, there has been broad endorsement of our definition of “platforms” and of the need to coalesce around more specific descriptions of AgTech models. 

In this update, we look at marketplace platform models, which connect users with products or integrated products and services. This growing subset of Digital Platforms are well positioned to help smallholder farmers and agricultural small- and medium-sized enterprises (agri-SMEs) overcome many of the market barriers inherent in the sector.

Types of marketplace models

Our 2021 report revealed a wide range of marketplace platform models operating in the agricultural sector. Broadly, we can divide them into three models:

  1. Product marketplace: connects smallholder farmers to physical markets both to and from the farm, including farm inputs suppliers and various kinds of off-takers (processors, trader, retailers, consumers)
  2. Integrated product and services marketplace: facilitates access to a holistic, bundled offer to farmers. Similar to a product marketplace, but offering broader range of services to farmers
  3. Services marketplace: shared economy platform that links farmers to equipment and/or other service providers.

We outlined eight sub-categories under these models, which continue to be the prevailing types in the market as shown in this graphic:

However, recent landscaping of the sub-Saharan Africa market revealed some updates to how these sub-categories of platform models are emerging.  

  • Many/most digital platforms are not truly open marketplaces with a large range of product and service providers engaged. Rather, many involve small numbers of curated partners with single offerings in each category (e.g. Digifarm)  
  • Many digital platforms are having to invest heavily in enabling infrastructure (e.g. transport, logistics, warehousing, field forces) to make they models work for smallholder-anchored markets (e.g. AFEX’s sourcing network, Twiga’s upstream investment in primary production) 
  • Many digital platforms are also running more traditional pipeline business offerings alongside their digital platforms (e.g. Coamana; AFEX)  
  • Many digital platforms are starting as agriculturally-focused and then moving to multi-product category marketplaces to include a range of consumer goods (e.g. DeHatt; Pinduoduo)

Platform design & scaling

Compared to pipeline business models, the unique characteristics of platforms should make achieving scale easier, at least after the initial start-up costs. But platforms will still struggle to reach profitability given the difficulty of generating additional value for users—and the highly localized nature of the agriculture sector makes scaling profitability even more complex. In our 2021 report, we outlined five key design decisions that platform providers must consider:

  1. Who: target customer and problem solved
  2. Where: value chain and geographies
  3. What: service offering
  4. How to Engage: customer engagement model
  5. How to Monetize: revenue model

Recent analysis shows that most platforms are still struggling to make their economics work. This is leading many to run more direct B2B pipeline business offerings alongside their platform, while some are also still reliant on donor funding. Many platforms recognize that integrated credit is key (giving rise to the term AgFinTech), but they are struggling to raise and structure the right capital to support these offerings. In the sub-Saharan Africa market, successful platforms remain heavily reliant on agent networks to scale, even after achieving a product-market fit.

Finance offerings within platforms

Most marketplaces integrate payments as a form of financial services, and some—as mentioned above—are expanding their model to include provision of financial services. In our recent landscaping, we identified four specific forms of financing being offered within marketplace models:

  • Vendor financing provides financing for products and services sold on the platform
  • Input financing provides credit to smallholder farmers in the form of in-kind inputs (or cash for labor) at the beginning of the season, generally to be repaid at harvest
  • Asset financing focuses on productive assets often financed through innovative business models such as PAYGO
  • Insurance offers bundled insurance for products or services offered on the platform

The graphic below illustrates examples of in-platform financing within the sub-Saharan Africa agricultural market.

Geographic differences

The maturity of platform models varies greatly by region. The majority of large ag-focused platforms are headquartered in India and China and are operated by tech companies. Many of these models have already reached significant scale, including DeHatt, Gramophone, Pinduoduo, Tanihub, and Rural Taobao. These models have grown rapidly on the back of densely populated markets, with strong enabling market infrastructure and consumers who are used to e-commerce in other sectors. Of particular note is Pinduoduo, which launched in 2017 as an ag-focused marketplace and now has over 880 million active users.  

At this time, most marketplaces in Africa remain small in size. Kenya is a hub for marketplaces, including Digifarm and Copia who both have over 1M users, fueled by the prevalence of mobile money and the relatively flexible nature of regulators. Other players, such as Hello Tractor and WeFarm (social connectivity platform), are currently capitalizing on their achievements as true platform models to now offer diversified offerings. Altogether, Kenya and Nigeria are the top markets in the region, receiving 96% of AgTech venture funding.

In Latin America, AgTechs are primarily concentrated in Brazil (51%) and Argentina (23%), as shown in this IBD mapping from 2019. Marketplace growth in the region has largely been fueled by mature farming systems, relatively tight value chains, urban wealth, and relatively better logistics. A select few product marketplaces, such as Smattcom and Frubana, have expanded into multiple markets.

Overall, these regional differences reveal some interesting dynamics. In particular, the relative scale of platform models in China and India are due to three key enablers that hold lessons for other markets looking to scale: 1) density and formalization; 2) maturity of enabling systems; and 3) progressive regulatory environment.

Persistent challenges

Despite their growth, platforms still face large barriers in the agricultural market. The localized nature of the sector limits network effects and increases customer acquisition costs. To successfully scale, platforms need the correct monetization strategy. 

One of the most prevalent challenges of marketplaces is the physical capital associated with the exchange of value between users. Successful e-commerce platforms, such as Amazon, have employed backwards integration to bring their shipping and packaging logistics in-house. In the agricultural sector, this challenge is amplified by the weak infrastructure in rural communities and developing economies writ large. Platforms may have no choice but to build the infrastructure themselves—as was the case with AFEX in Nigeria, which built a network of physical storage and logistics throughout the country, including 113 warehouses.

The path forward

One way we can continue to improve outcomes for ag-focused digital platforms in emerging markets is to leverage lessons from more mature sectors and markets. For example, in the US, venture capital is largely flowing into companies that have a downstream link to consumers (e.g., GrubHub, DoorDash). The same holds true for the agricultural sector, in which some of the most successful models are product marketplaces with a direct consumer link, whether it be an end consumer or a restaurant/aggregator. Plant AG, for instance, is developing a “farm to plate” platform and plans to grow their own food to sell to consumers. They raised $800M in their early stage VC round in 2021.

In Europe, similarly, the biggest deals of 2021 centered around direct-to-consumer platform models, such as Gorilla ($1B), Fink Food ($750M), and Wolt ($530M). Investments in the overall food tech space tripled to $10B in 2021, while AgTech investments grew only slightly to $900M. Investments in Europe tend to be on a smaller scale than in the US, but with significant opportunity for growth.

These adjacent markets reveal some cross-cutting learnings for platforms in smallholder agricultural markets, including:

  1. The emergence of integrated credit is a widespread platform trend. Companies in the United States (FBN) and other sectors (SafeBoda) have introduced financing opportunities for both customers and workers, similar to what we observed in the shift to “AgFinTechs.”
  2. There is a strong focus on the end consumer. This can be seen in the successful capital raises of start-ups with direct consumer links. Furthermore, the introduction of financial services specifically for platform workers demonstrates that platform providers are treating their own workers as customers as well.

Overall, platforms continue to offer a major pathway to overcoming the scaling challenge in smallholder agricultural markets. More research and further clarification of definitions and models will help digital platforms unleash their full potential.

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Data is growing in importance across all sectors, including agriculture. With the advent of new digital technologies and innovative business models, the amount of available data and potential use cases are increasing. Agricultural and Fintech innovators that recognize this trend are utilizing data in new ways, from creating digital platforms to delivering new, data-enabled services. Many are also exploring data partnerships, combining the power of multiple datasets to create greater impact for smallholder farmers.

In a new case study, ISF Advisors examined 33 engagements between Mercy Corps’ AgriFin program and 14 partners across four different countries. We found that around a quarter of the portfolio of AgriFin engagements—spanning various use cases—featured a strong data-sharing component. Underpinning many of these engagements are complex negotiations about how data sharing can unlock service delivery and enable different social and commercial outcomes for different players.

By analyzing these 33 engagements, we have uncovered lessons about the common barriers faced by data-sharing arrangements. In distilling these lessons, we hope to provide practical guidance and tools for overcoming these barriers to the broader ecosystem of actors involved in optimizing data sharing for agriculture.

The promise and role of data sharing in agriculture

Smallholder farmers’ remote location and lack of linkages to global markets have traditionally hindered robust data collection. But the penetration of mobile phones and other digital technologies into rural areas has made data collection and sharing significantly easier in recent years. New technologies such as drones, satellites, and sensors have also expanded data collection options.

Simultaneously, private companies are increasingly seeing farmers as potential customers and are turning to data to expand their understanding of this market segment. By entering into data-sharing partnerships, these companies can leverage combined datasets to develop new, tailored products for smallholder farmers, integrate farmer risk scoring, and optimize customer interactions. Some companies are even utilizing combined datasets to create entirely new business models where data itself is the commodity, sold directly to customers or to businesses that want to know more about their customers.

Despite the increasing use of data in agriculture, it is still in a nascent stage of development. At a foundational level, practitioners don’t even have a common data taxonomy to talk about what agriculture data is—making it difficult to learn from what others are doing. Additionally, many investments into new data-enabled platforms, models, services, and systems are still working out how to operate profitably at scale. Data-sharing engagements, while promising, tend to lack sophistication on several levels: 1) the types of data being shared (limited primarily to demographic data); 2) the format of data sharing (primarily static reports); 3) the level of analysis applied to the data (primarily simple analysis at the farmer level; and 4) the types of data-sharing agreements (primarily bilateral).

Barriers to effective data sharing

As might be expected in such complex arrangements involving a variety of actors, analysis of early data-sharing partnerships shows a range of barriers. Factors like the type of partners, type of data, use case for the data, and country where data is shared typically shape which barriers a partnership will face.

Looking at the AgriFin portfolio, we can see that the primary barriers to establishing a data-sharing agreement can be classified as:

  • Cultural (e.g., the company’s leadership or established internal data-sharing practices);
  • Capacity (e.g., the skills, technology, and experience each partner brings to the table);
  • Commercial (e.g., example, the cost of data and how partners treat intellectual property and/or competition in the data space);
  • Reputational (e.g., how partners think about the riskiness of sharing personal data); and
  • Regulatory (e.g., national data policies and legal jusdictions).

Even for organizations that recognize the potential of data in agriculture, these barriers can prevent them from effectively assessing the business case for investment within different regulatory environments. Once a data-sharing agreement is created, the barriers tend to shift. For example, many organizations don’t have a dedicated team working on the engagement, which can lead to delays in sharing data. Data-sharing agreements also suffer when the partners don’t have on-the-ground staff members who understand how to work with disaggregated farmers.

Certain barriers are more apparent with certain types of partners. For instance, government and nonprofit actors often face skill and capacity barriers, while financial service providers often contend more with cultural and regulatory barriers. While each use case is unique, we have distilled a common taxonomy of reference barriers and a mapping of where they’re most likely to show up in different partnerships (see full case study for more detail).

Empowering effective data sharing

Research and learning about how to effectively use data in different agricultural use cases and partnership models is quickly accelerating. For example, donor-funded programs like AgriFin are working with providers to test new service delivery models, using data as a key enabler. In the broader ecosystem, a number of open data initiatives—such as GODAN and GEOGLAM—are establishing much-needed standards, open datasets, and enabling resources for different actors.

Our case study takes stock of what has been learned so far about effective data sharing within AgriFin’s portfolio. In addition to the lessons on barriers noted above, the case study contains the following tools:

  • Reference taxonomies that distill how the AgriFin program considers key dimensions of data within data-sharing partnerships;
  • A data readiness tool that provides a holistic way of assessing organizational readiness to start working with data internally or in data-sharing partnerships; and
  • A data-sharing agreement process that distills the common steps, barriers, and learnings from the AgriFin program.

Our hope is that these tools can be used broadly by the agricultural community in understanding why data is important and how you can use it to improve the lives of smallholder farmers.

For more information, download the case study.

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The future is digital

We may not know what specific digital technologies and business models will win the day, but it is clear that the evolution of financial services around the world is now inextricably linked to the growth and development of digital products and processes.

Over the past three years, ISF and Mastercard Foundation Rural and Agricultural Finance Learning Lab (the Lab), among others, have conducted research on FSPs’ experiences and perspectives on digitization. In our survey of 47 Financial Service Providers (FSPs) around the world, 64% had already hired external consultants for digitization and 71% indicated that they probably or definitely will hire another specialist within the next two years. Those percentages were higher than any other category of business development services. Other FSPs indicated that they were building the capability in-house, choosing to develop systems internally.

And while the business case for digitization is preliminary, the Lab found positive impacts and perceptions in their own survey of 23 select FSPs in Africa. Though a small sample, their results showed a correlation between high levels of digitization and FSP profitability, and over 95% of the FSPs in their study indicated that they believed that digital tools would eventually increase their profitability.

But both surveys also indicated that FSPs considered the cost of digitization and data system development to be a primary barrier to uptake. Unsurprisingly, donors have stepped in with financial support to help extend the benefits of digitization to cost-constrained organizations that serve the rural poor.

Given the scale of attention and funding that is focused on digitization for FSPs in developing countries, we believe it is time to step back and consider how these investments should be structured to avoid distorting the market for digital services and make effective use of scarce donor funding. The question is no longer if digitization should be developed, but how it can be developed to have the greatest impact.

Build or buy: Understanding options for digitization

When an FSP decides to digitize, there are a range of options available, from building products and capabilities in-house, to hiring external digitization contractors to develop client-specific systems. These types of solutions can be mixed and matched to address a range of functional requirements—core banking, client registration and management, credit assessment, and more.

From an FSP’s perspective, the crucial considerations are strategic, financial and operational fit with the business. As in most markets, there is a general trade-off between affordability and customization. The more ‘bespoke’ a system, the higher the development and maintenance costs will be. From a functional perspective, building highly tailored systems internally will be required for organizations with a heavily tech-centric business model or operating in environments that have highly specific digital requirements (including strict privacy laws, regulations impacting FPS’ customer engagement processes, etc.). However, many FSPs could be better served by contracting with third-party providers, which can provider lower-cost options via standardized systems, with customizable modules and services a la carte when necessary.

So why does internally built digitization persist to such a high degree? In working with their partners, the Lab identified two main concerns that drive FSPs to rely on internal development of these systems. First, there is no ‘one size fits all’ system that will meet all FSPs’ needs to the same extent. There must be a minimum level of product customization and integration to successfully support an FSP’s digitization. Currently, many of the third-party providers are start-ups themselves, struggling to provide this necessary minimum support. Second, many FSPs simply don’t know where to look for third-party providers that meet their specific needs. And FSPs struggle with how to realistically assess their options given that providers’ track records are so limited—often there is no tangible proof of a product’s impact, just vague promises.

The fact is, the third-party provider market is not sufficiently developed to fulfill every FSP’s needs, and in-house systems will continue to play a crucial role for many organizations. But we suggest that the longer-term benefits of a robust service ecosystem for digitization deserve additional consideration, especially from donors that are impacting how this market develops around the world.

Donor objectives: FSP success and social return on investment

Imagine a world in which every company built their own email program. While early electronic communication may have been developed internally out of necessity, the maturation of the market clearly depended on a robust set of specialist providers. Lower marginal cost, specialized but widely available innovation, the development of skill nodes within the economy, and the ability to communicate between organizations were all bolstered by third-party providers meeting the needs of multiple organizations.

Digitization of FSPs is developing along a similar trajectory—though the need for strict privacy and security protocols adds an additional, and very challenging, dimension to the story. To date, many of these systems have been developed internally out of necessity. And currently, many donor-funded digitization projects focus on supporting the development of in-house systems and capabilities. As discussed above, there are benefits to this approach under specific conditions—digitization as part of the core business or specific digital requirements. However, is this approach to funding the right one if long-term impact and a vibrant digital ecosystem are the goals?

The case for considering two markets with digital investments

In this context, donors’ investments have the ability to shape the development of an FSP’s individual digitization service AND the digitization service market overall. In-house development contributes to an individual FSP’s capabilities and systems, but this type of internal, bespoke investment can present distinct downsides for the long-term impacts of digitization.

  • First, when funding internal digitization projects on an individual basis, donors are foregoing economies of scale. Many of the systems currently being developed internally will be duplicative, meaning that donors are paying to develop the same or similar functionality multiple times. By directing funding towards third-party providers instead, donors have the potential to drastically increase the functionality that each dollar buys by avoiding scenarios in which each FSP is ‘reinventing the digital wheel’.
  • Second, in-house development of digital systems results in ‘quarantined innovation’, where advances in digitization cannot easily spread through the market. There is also a paradoxical ‘downside of success’—when an individual FSP develops a highly successful product, the proprietary nature limits the impact of the innovation. And in the event that an individual FSP fails or abandons a system, the donor-funded digitization investment goes to waste. In contrast, if donors actively direct funding towards third-party providers they support a model of ‘distributed innovation’. The development of skill nodes and publicly available digital products broadens the scope of impact, and the rise of a robust service ecosystem offers the long-term potential for services at lower marginal cost.
  • Finally, many donors actively profess an interest in data sharing and collaboration, which is hindered by the development of idiosyncratic systems. Widely adopted third-party systems offer the potential for interoperability and seamless data transfer that is unlikely with bespoke systems.

A call for a new donor mindset

Given donors’ active role in shaping the development of this market, ISF believes that there is call for proactive and careful consideration of how digitization funding is spent. At the core of this new mindset is a realization that, in supporting the move to digital, donors should be in the business of building two markets for long term impact – FSPs’ themselves AND a vibrant technology provider market.  Practically, this approach requires a few additional steps in grant making to ask more specific questions, including:

  • Does an in-house technology solution limit the potential impact relative to a more commercially available technology? [The economies of scale opportunity]
  • Does this underlying technology have potential to support many FSPs throughout the ecosystem, to create new innovations over time, and what will be lost if the venture fails? [The quarantined innovation dilemma]
  • Is there a broader data opportunity related to the technology that calls for a different ownership structure or access agreement? [The data opportunity]

While FSPs themselves will often push for an in-house solution to enhance their competitive advantage, donors have a broader opportunity to hedge against failure and open up more impact opportunities from replication, connected system innovation, and interoperable data.

Early movers

Some donors and actors are already incorporating these opportunities into their granting and investment priorities.

Mojaloop (previously the Level One Project, funded by the Gates Foundation) is an open source software that offers an interoperable payments platform to anyone in financial services. The intent of the project is to level the playing field for companies seeking to enter or expand the digital payment space by reducing the need to ‘reinvent the digital wheel’ for payment processing and to facilitate a connected ecosystem that allows seamless transfers across many actors within the payments ecosystem—in other words, the economies of scale opportunity and the data opportunity.

LenddoEFL (an Omidyar Network investee) and First Access (a Mastercard Foundation Fund for Rural Prosperity Innovation Competition winner) both offer credit scoring platforms for financial institutions seeking to serve underbanked people at lower cost—addressing the quarantined innovation dilemma by developing services that actively seek to serve FSPs around the world.

Other initiatives are aimed at addressing FSPs’ concerns about finding a trusted service provider. FinForward, a partnership between FMO (the Dutch Development Bank) and FinConecta (a Fintech company), offers a proprietary market platform “dedicated to accelerate the digitization of the financial industry in Africa by connecting African Financial Institutions (FIs) and Mobile Money Providers (MMPs) with Fintech companies worldwide.” Similarly, the ASEAN Financial Innovation Network (AFIN), a collaboration between the Monetary Authority of Singapore (MAS), the International Finance Corporation (IFC), World Bank Group and the ASEAN Bankers Association (ABA), has launched APIX—an open-architecture API platform for collaboration between FinTechs and Financial Institutions. Both these initiatives offer financial institutions easy access to a pre-vetted community of Fintech service providers (“marketplace” functionality) and a low-cost, low-risk environment to prototype and test potential systems (“sandbox” functionality).

Learning from other markets

As donors and ecosystem actors shape this nascent market, it is helpful to remember that this is not completely new territory. Digitization and specialist third-party service providers have been developing in many other markets around the world, providing us with valuable sources of learning.

In the early days of microfinance, donors were quick to fund the development of bespoke core-banking systems to accommodate the unique requirements of this new form of lending.  However, after a period of in-house replications of specialized software, a more sustainable and specialized vendor market emerged that built and maintained microfinance-specific core banking systems for the industry.  Part of that shift was facilitated by CGAP, which in the mid-2000s created an Management Information Systems (MIS) fund, which paid for MFI needs assessments. CGAP also facilitated access to quality vendors via an online library of pre-reviewed core banking systems providers, thus addressing the same type of concerns that current FSPs have around finding trusted vendors.

The digital health sector, while highly diverse across countries, has started to coalesce around a core set of software solutions and third-party providers. In the private sector, the challenges of standardization, interoperability, and quality have been largely addressed. In the cost-constrained public sector, and developing country consumer-facing sector, many digital health data collection systems have been built off 2-3 foundation software builds. One such example is OpenMRS, an open source electronic medical records system developed by a non-profit collaborative network of universities, NGOs, and software companies, funded by USAID and the Rockefeller Foundation. And in the specific market for client-facing data collection, there are a set of third-party providers, both non-profit and for-profit, leading the field, including CommCare, Medic Mobile, Ona, and Aether/Gather.

Just imagine…

Imagine a rural finance market where companies provide digital solutions to all players in the market with the sophistication of technology providers such as Salesforce, PayPal, or Oracle.  Suddenly farmer registration, integrated payments solutions, credit scoring, and integrated insurance bundles would be a matter of integrating into value chains rather than spending years creating the technology from scratch.

These opportunities, at this crucial stage of product development, makes considering two markets such an important conversation to have.  Rather than defaulting to siloed internal systems, is there an alternative that could spur the evolution of a supporting technology market to innovate solutions for longer-term, more systemic impact? Often, we think there is!

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In 2016, our landmark report Inflection Point identified a series of enablers to help close the USD 50 billion smallholder financing gap and unlock growth in smallholder finance. To no surprise, market transparency and availability of market data were some of the most critical. To close the financing gap, providers and practitioners need to make more customer-centric decisions, understand how to build more sustainable business models, and identify the effectiveness of different smallholder solutions. Yet, without transparent markets and reliable data, stakeholders across the value chain are unable to make smart decisions on how to improve smallholder financial solutions.

Since the publication of this study, we’ve seen improvement in market data transparency, creating opportunity to unlock access to finance for smallholders. While this improvement is significant, particularly around transparency for demand-side and impact data, there is a notable gap in data transparency for supply-side needs.

  1. Supply-side data is crucial for providers to better understand the competitive landscape and features of effective business models. With granular-level data, providers can understand what competitors are doing to serve smallholder farmers, understand a product’s value proposition, and identify which solutions have proved financially sustainable and how. However, there are three critical challenges providers face in regards to supply-side data: (1) there is a limited number of efforts aggregating data on market actors, (2) those that are aggregating data, often fail to provide enough granularity for it to be valuable and (3) providers themselves are often unwilling to share data publicly on their business model given competitive market risks
  2. Demand side data is fundamental to understanding an actor’s target client and developing customer-centric products. To effectively provide financial solutions for smallholders, providers must gather and analyze data to understand who their target customer is and how to better serve them. For example, CGAP’s Smallholder National Survey data helps providers understand how to segment smallholders and build solutions that address the needs of each segment. Organizations like CGAP are doing an exceptional job at making demand-side data available, however, there needs to be a more concerted effort around making the data usable for a given audience.
  3. Impact data is critical for providers to assess effective interventions in terms of farmer impact. For instance, evaluation studies by J-PAL and IPA allow providers to understand which smallholder financial products have the greatest impact on farmer livelihoods.  Research institutions and think-tanks tend to play a heavy role in gathering and sharing impact related data, however, smaller on-the-ground organizations often lack the resources to implement impact measurement activities at scale, particularly rigorous impact evaluations. Additionally, few organizations are aggregating and collecting sector-wide evidence to compare impact evidence across different institution types.

Bringing data transparency to the next level

Making credible, relevant, and quality data accessible is only one piece of the puzzle. To really reap the benefits of these data sets and unlock growth in agricultural and smallholder finance, data providers need to make the data not only accessible but, most importantly, usable. For example, the Lab is working with partners to think through how to make demand-side data usable for FSPs to better design products. This might include hosting workshops with potential users to explore data use-cases, organizing data “hackathons”, publishing case studies that highlight the business case for data, and developing how-to-guides for data usage. Additionally, to catalyze these efforts in data transparency, each stakeholder has a specific role to play:

  • FSPs and DSPs can increase market transparency and user access by partaking in relevant databases – such as the Smallholder Finance Explore. This requires engaging with the data available, building their team’s capacity, and sharing information on their solutions.
  • Funder and donors should support the development and maintenance of market databases as a public good to ensure improved market transparency is accessible for organizations at every stage; as well as data capacity building within organizations to ensure they are able to benefit from new data sets.
  • Think tanks, researchers, practitioners can celebrate and communicate the progress of data resources to speed up uptake and usage from a variety of users.

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In 2013 ISF developed a first of its kind global view of the technical assistance (TA) landscape for smallholder farmers. This initial briefing note described a highly fragmented USD8 billion a year industry – where 70% of resources were channeled through public extension systems, 20% through donor funded programs, and 10% through the efforts of large multinational companies. As part of this research, ISF developed a typology of existing programs in the technical assistance landscape (see figure 1) with updated size estimates and wiki features.

ISF’s 2014 follow up briefing note Rethinking technical assistance to unlock smallholder financing identified a gap in the way that these different forms of technical assistance were helping to facilitate access to finance for smallholder farmers. At that time, only 3% of funding for agricultural technical assistance went toward helping providers develop financial solutions for farmers. Despite slow movement, there have been positive changes in the last five years, along with encouraging spots of activity across the technical assistance landscape.

Integration and coordination: Significant new trends

The integration of TA with other services – particularly financial – promises to be more effective than TA alone.  And we are seeing significant new trends across three key areas:

  • Greater focus on food systems and the role of the private sector: Overall, the design and implementation of technical assistance has experienced a significant shift from a value chain development view to a market systems view.  While this has always been core to certain types of technical assistance (e.g. certification, pre-competitive platforms) the market systems approach is becoming more mainstream and leading to more integrated technical assistance models. Examples such as Technoserve’s success with an integrated approach in their Coffee Initiative of East Africa, have been the focus of the last number of Global Forum for Rural Advisory Services global partner meetings.
  • Greater coordination around key commodities: The rise of multi-stakeholder initiatives in key crop areas such as cocoa (Cocoa-Action), palm oil (Roundtable on Sustainable Palm Oil), tea (the Ethical Tea Initiative) and coffee (the Global Coffee Platform) are bringing new levels of market insight and coordination to the design of technical assistance in key producing countries.
  • Stronger investment in TA and other support to financial service providers (FSPs): Led in part by The MasterCard Foundation’s USD175 million portfolio of grant investments in rural and agricultural finance, a new wave of programs are providing business development services (as well as sharing research and development costs) to support FSPs interested in serving smallholders. Foundation programs working with a range of local providers to develop and test financial solutions for farmers include Agrifin AccelerateAGRA FISFAPICCO STARSKiva, and the Fund for Rural Prosperity. Other efforts include CGAP’s partnerships with financial institutions to pilot new approaches for smallholder families, and the agriculture efforts of Financial Sector Deepening Africa (FSDA),

New epicenters of activity

We are also seeing bright spots of activity emerging across the landscape — from renewed attention to existing systems to new collaborations and innovations:

  • Re-energization of public extension systems: Ethiopia and Rwanda are creating a new standard for what government led programs can achieve, while countries such as Nigeria and Honduras are laying out bold new plans to try to re-energize their extension systems through training and involving a new wave of younger agro-entrepreneurs.
  • New donor efforts: The USAID-funded Developing Local Extension Capacity project and less formal Transforming Extension Initiative are new collaborations by major donors to develop and coordinate transformative efforts at scale.  These programs are important platforms for driving new approaches through traditional farmer outreach and training models.  In addition, a consortium of donors and implementers have formed an interest group for promoting digital technology for agricultural extension.  They include the World Bank and the Gates Foundation, which has developed a comprehensive new ICT4Agriculture strategy with a major focus on technology in rural advisory services.
  • Digital technology for extension: A growing number of digital service providers, over 200 enterprises and projects globally, are enabling organizations to deliver TA in innovative ways – from changing how traditional rural advisory services are delivered, to developing new participatory models, and finding ways of tailoring advice for farmers through precision technologies like remote and in-field sensors and much more timely and granular weather data. For instance, Digital Green is rapidly scaling its approach of applying video technology and intensive data collection to empower information extension and farmer-to-farmer training. In Ethiopia, the Agricultural Transformation Agency’s agricultural helpline is reaching millions of farmers each month with a new interactive voice response service. A new wave of tech firms such as Arifu and Farm Radio International are transforming the provision of advice to farmers from the ground up.

Fulfilling the promise of technical assistance: Action steps

As these developments show, progress has been made on many of the key recommendations from ISF’s research in 2013. However, we see a number of key areas where more continued concentration is needed:

  • Stronger focus on mainstreaming climate smart agriculture and nutrition, in addition to gender, as core parts of technical assistance programming.
  • Focus on sharing and pooling of data in ways that respect competition. Over time this will be an important way of standardizing metrics and measurement of results.
  • More focus on the potential of technology. There are exciting glimpses of potential, but those serving smallholders can make better use of the transformative potential of technology in delivery of TA. For instance, in the Learning Lab’s digitalization study, FSPs who had begun their digital journeys were still unlikely to have digitalized support services for farmers (stay tuned for digital service provider landscape data from the Lab).

The smallholder ecosystem model of Inflection Point identifies technical assistance providers as key players in the enabling environment for smallholder finance. While the landscape has evolved slowly, new developments and epicenters of activity mean that we are better positioned than ever before to help close the financing gap and improve livelihoods of the rural poor.

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