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“Vivemos um ponto de virada no setor rural brasileiro: agora, a única forma eficaz de competir é por meio da tecnologia.” A fala é do coordenador do Centro de Agronegócio da escola de administração da Fundação Getulio Vargas (FGV-EAESP), Roberto Rodrigues, ex-ministro da Agricultura, Pecuária e Abastecimento. “Se antes o
With planting season upon us, it is the time of year to be thinking about the data that you are collecting as you go across the field, as it becomes increasingly important each year to make management decisions from.
When we look to the history of agriculture in several moments we had important changes that are remembered as… revolutions. Issues linked to technology, products, credit, cooperatives, labor, water, irrigation, genetics, environment, among others had their chance to write down their names in several moment of food and agriculture history.
The current revolution is related to data and will also leave its name in the history of agriculture. We are currently facing a situation where data is generated in almost all moments, by several different sources, and if we have the capacity to transform this data into good information, several opportunities will emerge creating winners in the food business. It is a race for the future of data generation and use of information, and no company can stay out of this process.
In this article, I separated the data revolution issue in food and agriculture in three parts, being the sources of data (1), the processing of data into information (2) and the use of information (3).
When we compare our lives now and ten years ago, we can easily perceive new sources of data registers, based in a much bigger use of technology in our activities. Data that can be used in food and agriculture is being constantly generated in:
ü Financial transactions, credits, assets, liabilities in Banks and other financial institutions;
ü Product and services purchase transactions;
ü Credit and debit cards usage and personal data;
ü Traffic of cars, tractors, combines and others, tolls and GPS information;
ü Interpersonal cooperation (as an example, Waze and other applications/systems)
ü Millions of sensors (speed, temperature, traffic, weight, size);
ü Hash tags, tweets and other movements;
ü Images and videos (uploads and downloads);
ü Website page views, comments, likes, dislikes and others;
ü Mobile phone traffic and usage;
ü Tracing information (traceability) from the supply chain (bar codes);
ü QR codes accesses;
ü Physical and virtual memberships, communities and clubs;
ü TVs, computers and other devices tracking information;
ü Insurances and other services (health, home, cargo);
ü Drones, satellites, images and others;
ü Weather, rain, temperatures…
These are just some examples of sources of billions of data being generated now. Much of these weren’t available several years ago, and now are suppliers of data. So the idea here in this first part, is to have access to data. If you have access to data, you are one step ahead.
The second topic is the capacity an organization has to filter, to select, to process, to aggregate and analyze,transforming the billions of data coming from very different sources in relevant information for the structuring the decision process. How to do it is the big question that is joining a interdisciplinary team of specialists in systems, in strategy, in data mining.
Finally, we come to the third topic that brings the opportunities to use all this data transformed in information for an organization. Several opportunities emerge that will allow improvements that can be captured by the first movers bringing competitive advantage:
ü More efficiency in targeting marketing efforts, as for new product and new service developments, communications and others;
ü Increase controls in the production processes and as a consequence, productivity;
ü These controls will allow better and anticipated diagnosis of bottlenecks;
ü Economy of resources (fertilizers, chemicals, seeds and others) via a much more precise agriculture. We can even think about “zero waste” agriculture.
ü More information allowing improvements in inter-firm cooperation and linkages;
ü Improvement in all types of projections;
ü Anticipation of macro-environmental impacts, with better previous signaling;
ü More controls allowing for even more efficient just-in-time operations, with less stocks and better management of inventories;
ü With more information and more monitoring, we can have a learning curve acceleration, reducing costs;
ü More efficiency in use of machinery;
ü Improve capacity of price monitoring and dealing with volatility in futures markets;
ü Information can also improve efficiency in buying resources needed for production;
ü Better decisions can be taken with more information available;
The challenges for the organizations are in all three parts of this article.
1 - How do we build access to data?
2 - How do we filter and process data into relevant information?
3 - How to use this information as a source for a continuous search of competitive advantage?
If you take a look to the mobile phone siting beside your newspaper or your computer now, or the one that you are using to read this story and imagine how did it look like ten years ago and how many industries it substituted allowing you to do several activities in just one device, imagine what will happen with all this information available for food and agribusiness decision makers. Another revolution…
The author is professor of strategic planning and food chains at the School of Economics and Business, University of Sao Paulo, Brazil (www.favaneves.org) and international speaker. Author of “The Future of Food Business” and other 50 books published in 8 countries and in China, “The World on the Tongue”.
(Opinions of the writer in this blog don't represent those of China Daily.)
O Desafio Agronegócios é um grande desafio da sociedade identificado e proposto em conjunto por empresas líderes conectadas ao movimento 100 Open Startups. As grandes empresas abaixo têm interesse em colaborar com startups na busca de soluções para este desafio. Saiba mais e conecte-se submetendo a sua proposta.
Descrição do Desafio: O Brasil possui liderança no segmento de agronegócios, principalmente nas atividades voltadas à agricultura (cultivo da terra), pecuária (criação de animais) e bioenergia. O setor, porém, enfrenta desafios principalmente relacionados à falta de investimentos em infraestrutura (logística, maquinário e outros), mudanças climáticas e ataque das lavouras por pragas. A tendência de inovação no setor caminha no sentido da transgenia e melhoramento genético, mas as empresas atuantes no setor também têm buscado novas soluções ligadas à alimentação de animais, diagnóstico, matérias-primas industriais, plataformas de inteligência de dados para tomada de decisões e outros.
Oportunidades para startups:
Tecnologias para aumento de produtividade considerando a cadeia agrícola/pecuária como um todo (ex: logística, industrial, comercial, tecnologias de preservação e prolongamento da qualidade dos alimentos); Tecnologias para manutenção da saúde animal (vacinas, diagnósticos, inseminação etc); Tecnologias em sementes e em transgênicos (bioengenharia, biologia molecular); Defensivos agrícolas e sistemas para controle de pragas (químicos ou biológicos); Tecnologias em fertilizantes e manejo de fertilidade (químicos ou biológicos); Bioenergia (ex: tecnologias a base de etanol, biodiesel, biomassa, subprodutos do esgoto e outros); Agricultura de precisão, sensores, novas máquinas e equipamentos, sistemas de operação remota, que promovam a mecanização rural. Serviços:
Plataformas tecnológicas e aplicativos para interação com o usuário (orientação, acesso à informação, consulta a especialista, etc); Sistemas que promovam inteligência analítica (analytics) e melhoria de processos industriais ou de negócios; Sistemas que promovam o maior acesso ao microcrédito e seguros.
That’s the cream of the crop when it comes to agricultural technology. It’s more precise, more efficient and collects more data. Farmers can utilize so much of this to get a great yield … if the unpredictability of nature allows (it always throws some curve ball, doesn’t it? That’s the nature of the beast called “farming.”)
Todd Janzen, attorney at Plews Shadley Racher & Braun LLP in Indianapolis, grew up on a Kansas grain and livestock farm and now practices law in the at the intersection of ag and technology. In this guest post, Todd addresses the question Does Your Co-Op Own Your Farm Data?
Trimble continues to innovate its premier, highest functioning in-cab display, the TMX-2050. In terms of in-cab computing solutions for the agriculture market, companies like Case IH, Topcon, Trimble, John Deere and Raven spent the past 12 months mostly tweaking and adding capabilities to make their displays more modular, more automated and more customizable to the end user. “I like to think the off-road industries tend to follow trends of the on-road or automotive industry,” says Mike Gomes, vice president of business development, Topcon Precision Agriculture. “And that’s what we’re seeing within in-cab computing; guys want to view multiple screen views with more features and have the capability to make machine specific adjustments with a single touch.” Topcon did, however, release a new display in the last few months with its 8-inch X25 display, which debuted back in December, just in time for the winter trade show circuit. X25 is the mid-range display to compliment Topcon’s “X”
Gary Wagner is a 34-year farm-data veteran who’s taken data analysis to the next level to improve his profits. He uses two to four key data layers to identify soil productivity zones and yield patterns. Scrupulous attention to data accuracy ensures meaningful data and conclusions.
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