cbf7c04c7d6714e4017364296850059f_400x400-2Today we have a guest article from Peadar Coyle. Peadar is an Irish Data Scientist who is based in Luxembourg. You can check out his personal blog on this link and find him on Twitter here.

I recently came across this article in Wired about how ‘big data’ is revolutionising the food industry, and this got me thinking about what value my profession of ‘data science’ could bring to the food industry. So I did a bit of research, and spoke to some friends.

We already see the rise of apps such as Gobble, ChefSteps and Blue Apron which are startups providing either dinner kits, electronic equipment and/or meal advice. These startups also have data-science teams working on a range of problems such as demand forecasting, product analytics and customer analytics. So clearly at one end of the supply chain we’re seeing a lot of activity.

What about the other ends of the supply chain?

We can all agree that farmers face increasing pressure to grow more food on existing fields at lower cost and with less environmental impact. These challenges will become even more important in light of COP21.

In late 2013 Monsanto acquired the Climate Corporation. Climate Corp’s analytics technology provides localised weather statistics to help farmers improve productivity. Data is sourced from third parties that track weather patterns on a region-by-region basis. Climate’s software collects, manages and analyses the weather data, looking for patterns. As a data analyst specialist I find a lot of interesting open source tools in the Python Data community coming out of Climate, such as the excellent X-ray library.


Monsanto plans to integrate this technology with its FieldScripts software. FieldScripts helps farmers maximise planting by varying the amount of seed they apply to a patch of land. The software marries Monsanto’s intelligence about genetically modified hybrids with soil data characteristics provided by farmers themselves. This data is then mashed up with the seed and farm data.

Models are then built using a predictive component that makes spatial yield forecasts which help to maximise yield. I would call this a fine example of “decision management software” and we’ve already seen this in FinTech from companies such as Nutmeg who leverage algorithms to provide decision support for portfolio allocation. This works in much the same way – only in farming your portfolio is your crops!

Over a year ago, Monsanto acquired Precision Planting Inc. for $250 million. Precision Planting developed software that used spatial analytics to optimise how far apart and how deep into soil seeds should be planted. The company claims it can improve yields by 7%. or 5 to 10 bushels per acre. Its algorithms are accurate to within 10 square meters.

With these acquisitions and work done in-house, Monsanto is becoming a data-driven enterprise and this was mentioned recently at its shareholder meeting.

Monsanto CEO: Data Science key part of long-term growth

This is part of a larger trend – we’ve already seen the rise of Big Data and decision management technologies in finance, e-commerce and transportation. We’re going to see it influence competitive advantage in the food industry.

So if you’re a manager or executive working in that space you should take ‘big data’ very seriously.

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