Farmer Value Creation vs Scale

Strength of Relationship 3/5

  • Strong relationship between driver and outcome variables
  • Results are largely consistent across analytical models used
  • Few limitations regarding sample or indicator

Key Messages

The scale of a smallholder-inclusive business model is the most impactful driver when it comes to farmer value created. FarmFit’s vision is one of business models able to operate in a commercially viable and effective manner at scale. However, FarmFit data strongly suggests that value created for farmers decreases significantly as business models expand to work with over 1,000 farmers.

This finding is crucial when seen in light of other FarmFit data analyses that show a link between higher scale and lower service delivery cost and higher direct cost recovery. In other words, while scale seems to be a key driver of improved business performance it may come at the detriment of the value delivered to farmers. This reinforces the need to develop and identify business models that are able to combine high investment, efficient distribution of resources, a strong return on investment for businesses and high value creation for farmers, at scale.

FarmFit data suggests that it is harder to create value for farmers at scale is due to:

  • Intensity and nature of service delivery.
  • Changing farmer profiles at scale.

Keep reading to find out more.

Understanding how scale relates to farmer value creation

The key challenge that the FarmFit Insights Hub is looking to crack is how to design smallholder-inclusive business models that combine efficiency, commercial viability, investability and scalability, with effectiveness in creating value at farm-level. Scale is a key driver for all three outcomes that are assessed in the Insights Hub. Unfortunately, when it comes to farmer value created, FarmFit data shows that larger-scale models struggle to deliver the same value to farmers that smaller-scale models do – and the difference is sizeable.

These results do not appear influenced by any other contextual or design drivers that the FarmFit Insights Hub has analyzed in detail: when disaggregating by any of the other key drivers, the results hold.

Finally, using rigorous machine learning methods, these results are not only validated, but even strengthened: FarmFit’s machine learning analysis shows scale to be by far the most impactful variable in relation to farmer value created. Machine learning methods, also showed scale to be by far the most impactful driver to decrease the cost to serve, further highlighting the tension between the impact on scale for business and famer outcomes.

Link to other outcomes

When looking at the relationship between Scale and the other two outcomes analyzed in this Insights Hub, we find that:

  • For Direct Cost Recovery from Service Provision, our data suggests that on average, larger-scale models recover a larger percentage of their service delivery costs to farmers. Click here for more details
  • For Service Delivery Costs, our data shows that smaller-scale models are associated with much higher service delivery costs. Click here for more details

The implications are crucial: scale is a key driver across all three outcomes analyzed in the FarmFit Insights Hub, but the impact of scale is not uniform. Larger scale is associated with higher cost recovery, lower service delivery cost, and less value creation. How to scale smallholder-inclusive business models while optimizing for all three outcomes is one of the key nuts to crack, and thus will be a feature of insights added to the Hub in the future.

In the following sections we dive deeper into possible explanations and nuances behind these results, as well as their implications.

Diving deeper: what do we think explains these results

Our quantitative and qualitative data suggests there are a number of compelling reasons explaining why business serving a larger number of farmers deliver, on average, less value to farmers.

  1. Intensity and nature of service delivery – As business models scale, the intensity with which services are delivered is reduced as the farmers-to-staff ratios increase significantly. In addition, larger-scale models are more likely to work with intermediaries for service delivery, helping them scale but often at the cost of reduced control and quality.
  2. Changing farmer profiles at scale – Smallholder farmers are often challenging to serve due to various reasons including small farm sizes, challenging economics, imperfect infrastructure. Businesses that are first set up are likely to work with relatively easier-to-reach farmers, for instance those that are closer to the business’ own operations or those farmers with whom the business has had longer and more secure sourcing relations. As business models scale, they are more and more likely to work with more farmers in more challenging circumstances, making it more and more difficult to achieve high value.

Clicking on each of the preceding reasons provides a longer overview of our thinking, including more supporting qualitative and quantitative insights.

Implications – so what does this mean for you?

Based on our findings till date on this topic, we see the following implications for different audiences:

Reflections on data limitations and further research

The Insights Hub is a living document which we are constantly updating with new data, new analysis, validation by our partners, etc. For the results on this page, we would like to emphasize the following:

Major caveats and limitations of our current approach 

  1. Absolute income uplift does not show proportional impact

Next steps that we have planned to update these findings in the near future  

  1. Control for measured and projected data
  2. Incorporate scale as an outcome indicator

Suggestions for additional research by our peers and partners

  1. Research innovations that can help scale, while maintaining or increasing farmer impact