• No se han encontrado resultados

Su regulación en la Ley Ordinaria Tributaria

PRINCIPIO DE LEGALIDAD 3.1 Definición de Legalidad:

3.6 Su regulación en la Ley Ordinaria Tributaria

Increasingly, enterprises have been able to generate at least some revenue (Figure 26). Based on the CTA-Dalberg survey data, of the 175 respondents, an estimated 70% of African D4Ag solutions generated some earned revenue – a number lower than the likely 80%+ of D4Ag enterprises in Africa that are revenue- seeking.276 The remaining organisations were

either entirely donor- or government-funded entities or were very-early-stage start-ups that

Figure 23 D4Ag solutions by number of registered farmers

Solutions (ranked ordered by size from 1 to 390) 0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 millions

Registrations are concentrated by geography; the majority are in East Africa.

The top 20 solutions, each with more than ~400k registered users,

Western Africa Users HQ: 145 Focus: 162 3.1M 4.3M Solutions Eastern Africa Users HQ: 124 Focus: 146 21.0M 21.8M Solutions Southern Africa Users HQ: 43 Focus: 46 3.9M 5.8M Solutions Central Africa Users HQ: 18 Focus: 20 0.60M 0.85M Solutions 27 solutions headquartered in the G5 Sahel, account for 573k users. Another 33 solutions have users in the region.

Registered users

Solutions by primary region

Never generate revenue Will generate revenue Generating revenue Financial access 31 29 1 1 Advisory services 71 4 7 82 Market linkages 68 4 3 75 Supply chain 33 4 2 2 2 39 Data systems 25 29

Figure 24 Regional breakdown of D4Ag solutions

solutions and registered users (millions) by sub-region of HQ and sub-region of primary focus, EOY 2018)

number of survey respondents by use case

did not yet report revenue streams. In a few cases, non-revenue-earning solutions were in-house (i.e. non-monetised) digital platforms from agribusinesses or MNO solutions that derived value indirectly without revenues (e.g., ‘free’ farmer information services that generate value through improved customer retention and stickiness but do not generate direct D4Ag revenues). Around 80% of the revenue-generating enterprises had several revenue streams.277

Of the revenue-generating firms in the survey sample, 26% reported running profitable and sustainable businesses that could survive without donor long-term subsidies, a figure that is within range of earlier D4Ag sector overviews.278 Most D4Ag enterprises are thus

largely supported by grants and still have a way to go before they are sustainable and scalable. This profitability number may seem disappointing but is not unexpected. Only 40% of the commercial enterprises in the CTA-Dalberg databases have been in operation longer than three years, which is often seen as a reasonable benchmark for time to profitability for tech start-ups and, more broadly, new small and medium-sized businesses.279 This share of profitability among

start-up enterprises is also in line with early- stage start-up investor expectations in Africa.280

Sector economics are improving and the share (and number) of profitable enterprises is growing. While there are no baseline data with which we can make a comparison, anecdotal evidence from interviews suggests that these results are significantly higher than what was common even a few years ago in terms of the share of D4Ag solutions that are profitable. Extrapolating to the overall sector, even assuming very high levels of new business failure (e.g., 50–75% failure rate over three years), these numbers suggest that the number of profitable and thus potentially investable D4Ag actors could double from ~75 D4Ag solutions today to over 150 in 2021.281

There is also a clear trend of rising annual D4Ag enterprise revenue per farmer. Self-

reported D4Ag enterprise revenues, expressed in annual revenues per registered farmer, tend to be highest for market linkage enterprises. Aggregating across survey, desk research, and interview data, and rounding for convenience, we see ~€25 average revenues for market linkage solutions per registered farmer annually (€3–45 range), in comparison to ~€5 for advisory and information services (€1–9 range), ~€4 for digital financial services (€0.5–7 range, and ~€4 for supply chain management solutions (€1–7 range).282

As the sector pivots to a greater focus on market linkage (or rather market linkages bundled with other services) from solutions focused more on advisory services – something that we heard universally in our interviews but are unable to demonstrate empirically in the absence of comparable historical data – one would expect that average sector revenues would rise quickly.

A small but growing number of players have already started developing business models that can generate up to €90 in annual per farmer revenue. Achieving these types of revenues requires multiple revenue streams and extensive product bundling, i.e., characteristics of emerging D4Ag ‘super platform’ models. To generate such economics D4Ag actors must essentially become active agriculture value chain participants, taking a share of both agricultural input costs and off-take value as compensation for their digital intermediation. This approach can work well when D4Ag solutions are able to successfully consolidate fragmented value chains by removing other intermediaries (e.g., digitally linking farmers to retailers for the post-harvest sale in ways that bypass last-mile village agents and traders), reducing value chain ‘leakage’ (e.g., using digitised logistics and just-in-time market linkage to significantly reduce post-harvest losses) or, in an ideal state, capturing both of these effects. The substantial surplus value created can then be shared in ways that leave both the farmer client and the D4Ag intermediary with dramatically improved

Revenue generation example – N-Frnds In Rwanda, N-Frnds understands the tremendous value of data for both banks and farmers and has built a viable business model around it. The company leverages the data it records on transactions between farmers and off-takers to link farmers to banks to facilitate lending opportunities. Smallholder farmers pay nothing for the service; instead, N-Frnds charges banks a small acquisition fee for every loan extended to N-Frnds’ network of farmers. In this way, N-Frnds’ business model targets businesses that are able and willing to pay for these data, as opposed to farmers who would be unlikely to use the service if they had to pay for it.

economics. The D4Ag enterprise can then further supplement such revenues with ancillary revenue streams such as inancial services fees/interest or even data monetisation revenues.

While the cost structure for generating these revenues varies dramatically depending on solution type, there is evidence that some companies are able to achieve 30–40% gross margins. We certainly do not expect all businesses to achieve this level of revenue or margin, but the data indicate that with extensive revenue bundling, strong economics are achievable. This is already a major leap forward from a time when D4Ag solutions centred on advisory services, as that model is marked by low per-farmer revenues and typically razor thin margins.

Important business model shifts account for the high share of revenue-generating enterprises in the D4Ag space. By and

large, digital service providers have learned that farmers will rarely pay for digital products and services – and especially advisory services, where it can take time for farmers to realise

benefits (and even if they do realise benefits, they may not attribute the benefits to the advisory service). There are signs of emerging willingness on the part of farmers to pay for market linkage solutions where results are more immediate. Overall, while 70% of revenue- generating enterprises have user payment revenue streams, user payments do not appear to constitute the majority of their revenue.

Because of the challenges of generating revenue from farmers, organisations have oriented themselves to generate their revenues from other businesses, even if the final service is to the farmer.

Such B2B payment models allow for a range of payment streams from players with greater ability and willingness to pay than the smallholder farmer. These models include monetising data and fee for service. FSPs often partner with banks and other FSPs rather than work directly with farmers, while supply chain management enterprises partner with larger agribusinesses. For example, Tulaa relies on commissions from farmer market linkages and related transactions. Farmforce, meanwhile, enables off-takers (processors or agribusinesses)

Solutions farmers (million)Addressable Annual revenue per user(min) (max) Total addressable market (million)(min) (max)

Advisory services 250 1 €1.00 €9.00 €250 €2,250

Financial access 73 2 €3.00 €14.00 €219 €1,022

Market linkage 73 2 €3.00 €50.00 €219 €3,650

Supply chain management 73 2 €0.50 €9.00 €37 €657

Total (assuming no digital constraints)7257,579

Total factoring in connectivity constraints

Conservative scenario: (39% of smallholder farmers have mobile subcriptions)3 283 2,956

Less conservative scenario: (70% of smallholder farmers have access to phone in household)4 507 5,305

Figure 26 Estimated total addressable market calculations

Notes:

1 Assumes that every smallholder farmer is part of addressable market for advisory services subscriptions (i.e., possible to have multiple subscribers from family for one farm) 2 Assumes that farms or households are a relevant unit for market sizing as multiple subscrption for the same product unlikely or impossible

3 Sub-Saharan Africa farmers with unique subscriptions in 2018 (~39%, estimated based on 44% unique subscriber rate in the region and 1.3 ratio of urban to rural connections based on

GSMA data)

to access, monitor, and manage a large number of farmers for a fee paid by the off-taker.

Overall, we estimate that the total addressable market (TAM) is a maximum of €5.3 billion, depending

on key assumptions around the number of addressable farmers, average revenue per user (ARPU) by use case (see Figure 26 and additional information on these calculations in Annex 3: Methodology) and constraints around smallholder farmer connectivity. 283, 284, 285 These ranges are wide primarily for

two reasons. First, the ARPU by use case varies significantly: individual enterprises within a use case have widely varying business models and few reliable examples with data points exist today. In our estimates we have therefore applied the highest and lowest ranges based on available estimates from enterprises themselves. Second, there are no reliable estimates of smallholder farmer ownership of mobile phones, and there are multiple ways to arrive at such a figure. As with ARPU, we similarly applied a range of the most

conservative estimates (smallholder farmers with unique mobile phone subscriptions) to less constrained estimates (households owning at least one mobile phone) in order to arrive at a directional estimate.

At the lowest end, the TAM is somewhere between ~€0.3–0.5 billion. These figures apply the lowest end of ARPU for each use case. They are likely to underestimate the TAM because the ARPUs underlying this calculation are likely more representative of the lowest performers in the market, rather than an average. At the highest end, the TAM is approximately €5.3 billion, assuming the highest ARPUs for individual use cases as well as limited constraints around phone ownership (i.e., if a smallholder family owns at least one phone, family members are able to use D4Ag services and are therefore part of the addressable market). These figures are likely to be overestimates; only a handful of companies are achieving the highest end of ARPUs (though in a few cases like market linkages, there are examples of companies

Figure 27 Known and estimated earned revenue by primary use case

3M Tracked revenue 26M 6M 18M 3M 54 39

Estimated sector revenue 21 9 3 3 ~€107M Market linkage Macro agri-intelligence Advisory & information services

Data intermediary Financial access

Supply chain management ~€127M average

(€110–145M range) revenues by use case

€, EOY 2018

outperforming our current range) and household ownership of a phone is likely not fully indicative of ability to access D4Ag services. Still, these figures provide useful bounds and suggest that the likely TAM is somewhere between the midpoints of the conservative and less constrained estimates (i.e., €1.6 billion and €2.9 billion). As the sector evolves and more data points emerge, the range of estimated values for the addressable market will likely become narrower and more precise.

The D4Ag sector likely generated about €110–145 million in revenue in 2018,286 a small fraction (6%) of the total

addressable market.287 This figure includes

commercial enterprises (including financial service providers), NGOs, and MNOs, but excludes governments and agribusinesses. We do not include governments because they typically do not charge users or frame

success in terms of revenue – and while D4Ag solutions do reduce agribusinesses’ costs and/ or increase their revenues, these benefits do not come from user payments – and agribusiness data are difficult to access publicly. Taking the midpoint of the revenue range (€140 million) and the midpoint of total addressable market (€2.3 midpoint estimate, €1.6–2.9 billion range depending on which constraints to connectivity one assumes), we estimate that market penetration today is 6% (between 4–8%).

Evidence of results is