Direct Cost Recovery from Services vs Scale

Strength of Relationship 4/5

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

Key Messages

FarmFit believes that an important component of any successful smallholder-inclusive business model is that it is able to operate at scale. This allows the model to reach large numbers of farmers and to be of a sufficient size to operate efficiently and attract commercial financing. FarmFit data on direct cost recovery from service delivery broadly supports this thinking; larger-scale models recover, proportionally, a lot more of their costs by charging farmers than smaller and medium scale models. At the same time, our data suggests the opposite might be equally or even more true: increasing direct cost recovery helps business models reach larger scale.

The story behind the data, however, is very nuanced. Three main findings are highlighted in this section:

  1. Reverse causality: Cost recovery as a pathway to scale.
  2. Value chain dynamics: High cost recovery regardless of scale. 
  3. Farming and business models allowing high cost recovery at smaller scale. 

Keep reading to find out more.

Understanding how scale relates to cost recovery

Inherent in FarmFit’s thinking on building better smallholder-inclusive business models is the importance of scale; models need to reach a minimum size to be efficient and investable, and able to work with a greater number of farmers. Data on direct recovery of service costs supports this, as we see that large-scale models recover a lot more of their costs by charging farmers.

The differences are substantial; scale seems to be positively correlated with direct cost recovery. These results are validated using rigorous machine learning methods. (Read more.)

However, there remains quite some spread in the results and the nuance behind the data is important. Whilst, overall, the data strongly suggests that large-scale models are associated with higher direct cost recovery, there are unexpected insights when diving deeper. These are as follows:

  1. Contexts exist in which scale appears not to matter
  2. There are specific types of business models that are able to have high cost recovery even at small and medium scale
  3. Cost recovery might be a driver of scale rather than vice versa.

These patterns are explored further below.

Link to other outcomes

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

  • For Service Delivery Cost, our data finds that the cost of service delivery and scale are inversely related; small-scale models are much more costly on a per-farmer basis than large-scale models. Click here for more details
  • For Farmer Value Created, FarmFit data shows that smaller-scale models create a lot more absolute value for farmers than medium and large-scale models. Click here for more details

In the following sections we take a closer look at possible explanations and nuances behind these results, as well as their implications.

Diving deeper: what might explain these results?

Our quantitative and qualitative data suggests there are a few compelling reasons explaining the pattern behind these results.

  1. Reverse causality: Cost recovery as a pathway to scale – Higher cost recovery can be a driver of scale, in particular in contexts where heavy subsidization of smallholder services is widespread
  2. Value chain dynamics: High cost recovery regardless of scale – Within certain value chain dynamics, cost recovery can be high regardless of scale.
  3. Farming and business models allowing high cost recovery at smaller scale – Specific farming and business models – such as block farms – allow high cost recovery at small and medium scales. This helps explain some of the outliers apparent in the data

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 to date on this topic, we see the following implications for different audiences:

Reflections on data limitations and further research

The Hub is an interactive resource that 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 out current approach

1. Direct cost recovery is not always a goal of business models

Next steps: Updating our findings

1. Incorporate scale as an outcome indicator

Suggestions for additional research by our peers and partners

1. Research innovations that can help scale