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Women play a central role in rural economies, primarily through the agricultural sector. Yet these women face many barriers, including time poverty, lack of land ownership, fewer agricultural inputs, restrictive social norms, and less access to finance. The emergence of digital agricultural platforms has the potential to help rural women overcome these barriers and improve their livelihoods.
Digital agriculture platforms are a specific subset of AgTechs, defined as models that facilitate direct interactions between multiple users for the purpose of exchange. These platforms are built upon network effects—enabling multiple users on both sides of an exchange to interact, creating shared value for both platform providers and end users. The unique benefits created by digital platforms could be particularly helpful in leveling the playing field for women; however, platforms currently struggle to reach and engage this important customer segment.
In new research from CGAP, ISF Advisors and Value for Women, we look at how digital agricultural platforms can best integrate gender-forward practices, what the major opportunity areas are for creating shared value, and how donors and investors can support these efforts. This research builds on CGAP’s extensive work surrounding women in rural and agricultural livelihoods (WIRAL). In this blog post we summarize a few key findings, with a deeper dive into the opportunities surrounding sex-disaggregated data.
Digital platforms have the ability to disintermediate markets, connect multiple users, facilitate information sharing, and provide farmers with a digital financial footprint. These benefits could be especially useful for rural women in overcoming gender-related barriers. For example, the exchange of knowledge and information that are crucial to competitively participate in markets (e.g., prices) is often out of reach for women due to restricted mobility and social norms that keep them out of male-dominated spaces. Digital platforms could connect them to this vital information with far less friction.
Unfortunately, although the digital platform market has grown rapidly, these AgTechs are struggling to reach rural women. While women make up half of smallholder farmers in sub-Saharan Africa, they represent only 25% of AgTech users. Even when AgTechs do reach rural women, usage rates suggest that they are not sufficiently serving them.
Many platforms recognize this missed opportunity and are thinking more about gender—but are only beginning to translate that into concrete action. While there are some encouraging examples of gender-forward efforts, this area is largely not seen as critical to commercial success. Platforms are generally focused on the short-term challenges of achieving profitability and scale. But platforms that integrate long-term gender intentionality into their models could tap into a large opportunity if they implement the best practices proposed in this research.
In our research, as seen in the figure below, we lay out a curated list of best practices that platforms, and their investors and donors, can adopt—with the ultimate goal of creating shared value for platforms and the women that engage with them.
The two practice areas at the top of this figure serve as foundational best practices that influence a platform’s actions in the other four areas. Internal prioritization of gender in the organizational strategy, budget, policies, etc. is necessary to then enable external-facing best practices around marketing, customer targeting, product design, and providing income generating opportunities.
Building on this, we outline the four biggest opportunities for platforms to increase shared value for themselves and for rural women. As in the best practices, two of these opportunities revolve around establishing a strong internal foundation for platforms to drive commercial and gender outcomes—and ultimately become more gender-forward:
The other two opportunities center on increasing impact for women as customers and income earners:
In this blog post, we will take a deeper dive into the opportunities around sex-disaggregated data.
The collection and analysis of sex-disaggregated data is the typical starting point for increasing gender inclusion both within a company and in the external-facing products and services. A comprehensive business strategy that incorporates gender requires the ability to understand how many women a platform is serving, how well it is currently serving them, and the value women are generating.
Nearly all platforms interviewed collect basic sex-disaggregated data on their end users and their workforce, and nearly half of the providers that have agents on their platforms can also sex-disaggregate that data. However, the majority of platforms do not have a structured process for analyzing this data or taking action on those insights. Only one interviewed platform (CoAmana) seems to be collecting and leveraging sex-disaggregated data that enables it to better engage women customers. For others, there is a significant missed opportunity.
Many providers are aware of this opportunity, but 43% in our sample indicated that it is one of their top three challenges. With a more systematic approach to data collection, analysis, and decision making, platforms can leverage data for:
Importantly, platforms that implement this systematic data-driven approach can then quantify and showcase their impact to potential donors and investors. In fact, there are many entry points for donors and investors to influence platforms to become more gender-forward, especially at early stages of the business.
These entry points include:
Investor and donor support (and influence) will be crucial for platforms to overcome market barriers and failures that currently prevent them from investing fully in rural women.
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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.
Our 2021 report revealed a wide range of marketplace platform models operating in the agricultural sector. Broadly, we can divide them into three models:
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.
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:
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.
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:
The graphic below illustrates examples of in-platform financing within the sub-Saharan Africa agricultural market.
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.
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.
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:
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.
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).
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:
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).
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:
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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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.
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.
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?
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.
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:
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.
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).
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.
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.
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:
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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.
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:
We are also seeing bright spots of activity emerging across the landscape — from renewed attention to existing systems to new collaborations and innovations:
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:
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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