Large vs small business in ag retail


In 2018, Proagrica surveyed the US ag retailer community, reaching out to over 5,000 businesses in the sector, to better understand key issues affecting profitability, growth, and the extent to which data and analytics are implemented into their current systems.

Proagrica’s report refined the data to focus on the responses from both larger and smaller businesses, setting the turnover split at $201m. Businesses with a revenue of over $201m had some noticeably different concerns and outlooks in specific areas, than businesses with a lower revenue – what were the differences, and what conclusions can we draw?

The key difference showed that the larger the business, the more likely that business will place a high value on their data usage and connectivity – both between their internal systems and those of business partners – and will have invested accordingly. Only 27% of larger business rated their use of data and analytics as working conspicuously below standard, compared to 43% of smaller businesses. It’s likely that many larger businesses engage with their data as a matter of necessity. Their larger size requires analytic solutions that ensure productive management of their more diverse and complex internal systems.

Many of the pain points for businesses align between larger and smaller businesses, as one would expect. For example, pressure from generic providers is an almost identical pain point between both groups. However, some differences do stand out.

The difficulty in managing manufacturer programs to growers ranks significantly lower as a pain point for larger businesses – by a gap of almost 10%. Business satisfaction also rates higher in several operational functions due to larger businesses’ investment in their data systems: timely payment from customers, efficient customer engagement and retention all deliver satisfaction rates 10% above smaller businesses.

Larger businesses placed much more value on the customer benefits granted by data optimization. When ranked between 1 and 5, where 5 is “substantial value”, improved customer services have a mean of 3.77 out of 5 for all respondents combined. However, larger businesses rate as 3.95 – far higher than the average and that of smaller businesses. This demonstrates a greater appreciation that optimized systems provide value for customers, not just for businesses. In a turbulent market, growers are seeking to cut input costs and brand loyalty has less sway over customers as a result. Larger businesses are positioning themselves smartly, offering services that make their offering a valuable one.

The term “big data” is still prevalent. A recent paper highlighted two consistent perceptions in the agriculture discourse[1]:

  1. Big Data is for Big Farming
  2. Big Data is for everybody

Mathias Golombek, CTO of US-based Exasol, recently spoke out on the outdated term, and suggested that smart data usage is the new standard mode for successful businesses.[2]. Large and small businesses both list common pain points – effective inventory management, generic providers, and high staff turnover for example – but they differ in their utilization of data & analytics.

There are challenges to be faced, certainly, but the advances taking place will benefit the whole supply chain. Farmers will use their data to apply the right products, at the right rates, and at the right time; distributors will use data to source inputs and to position them in the market properly; manufacturers will use data to improve the way they manufacture and recommend the use of their products.

More and more retailers are beginning to recognize the role data connectivity can play in developing their business models. Retailers that are rethinking their strategies and actively seeking improved system solutions are better placed to weather setbacks and, crucially, capitalize on the shifting requirements of their customer base.

[1] “Is big data for big farming or for everyone?”, Aysha Fleming, Agronomy for Sustainable Development, June 2018



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