Last Monday, Leticia Gonçalves, President of Monsanto for Europe & Middle East, presented at the Women in Data Science (WiDS) Madrid in Spain – it is a conference that brings together women from the technological, business, institutional and social fields. The conference aims to not only inspire female talent in technical disciplines but also to explore the latest data science innovations and applications in Spain and Europe. The following is a short Q & A with Leticia.
What led you to participate in the WiDS congress?
I think it is a great opportunity to connect with leaders of the technological and scientific sector, and to understand how companies are incorporating digital transformation in their businesses; thanks to the application of new technologies and data science.
In addition, it is also an opportunity to learn about innovations and opportunities in the digital world. At the same time, I have been able to share developments that we are carrying out in Monsanto.
How is Monsanto tackling data science in their business operations?
Data science has been in the center of our company’s transformation in the last few years especially in R&D, supply chain and commercial functions.
We use data analysis in the discovery phase of our R&D to drive many of our technology platforms, including RNAi technology, greenhouse automation, metabolomics and automated screening.
When our research scientists plant trials to see how a seed performs in the field, our technology makes recommendations on where to plant to obtain the best outcomes. Throughout the growing season, our mobile tools and smart devices collect data on what is being planted, where it is being planted and how it is being managed. Then, during harvest, our technology streams and analyses yield data directly from the combine.
We are using data science to create an end-to-end supply chain and commercial transformation with improved strategies, processes, tools and systems by using data science to create efficiencies and better customer experiences.
What benefits can the application of these technologies have in the global supply chain?
The global supply chain has benefited quite successfully from the analysis to improve its own efficiency and processes, being critical for the success of our enterprise. It has the task of taking each seed, or each unit or byte of the raw material with which we work and converting them to a more useful form.
An example of a technology that has worked very well for us is climate-smart logistics, where we established what we call the Transportation Management Solution (TMS). This includes a combination of real-time monitoring, automation of processes, analytics-based decision making and standardisation of tools and processes. This allows us to consolidate some routes and optimise the efficiency of others.
In Brazil alone, the first year helped us reduce our total vehicles’ travel in kilometres by more than 2.25 million. Our corresponding reduction in carbon dioxide emissions exceeded 2,500 tons and the implementation of TMS has been so successful that the supply chain is rolling out the programme around the world.
How does data science contribute to more sustainable agriculture?
Farmers have the important task of sustainably addressing a growing food demand in an environment of increasingly limited resources. Each crop is different, and each field or piece of land is unique. However, using our digital tools throughout the year, we can help farmers make the most appropriate decisions to optimise the use of key resources such as water, land or energy.
In this way, we help farmers to face their challenge of being able to produce more from every drop of water, square metre of land or unit of energy. It is what we call “precision agriculture”.
What social impact does data science have on agri-food production?
We cooperate with farmers, regardless of the size of their farms, large or small, as all farmers face the same challenges; and aim to be profitable and sustainable in their operations. Smaller farmers need as much precision as possible in their field management, and access to digital tools is neutral with respect to the size of their farms.
In addition, we partner on data management to seamlessly collect, store and visualise critical field data — monitor and measure the impact of farmers’ agronomic decisions on crop yields, and manage field variability through elaboration of personalised fertilisation, irrigation and sowing plans for farmers’ fields.
How can data science socially help agriculture in EU countries?
The rural development policy of the European Union (EU) helps rural areas of the EU meet the wide range of economic, environmental and social challenges of the 21st century. Data Science, applied to agriculture in Europe, fits within EU priorities.
Some of these are to promote economic development in rural areas, foster the transfer of knowledge and innovation in agriculture, or promote innovative farm technologies, risk management, resource efficiency and support the shift towards a low-carbon and climate-resilient economy in the agricultural sector.
For example, in Spain we are currently involved in a pilot programme with a cooperative of small farmers within an irrigated area in the province of León. The goal is to bring our DEKALB SMART® digital tools to their farms so that the technology can help their maize crops.