Bridging The Agricultural Data Gap

5 Key challenges facing the agriculture data ecosystem.

Today, the world has over 600 million people that are hungry and do not have access to food. This accounts for 8.9% of the world population that is undernourished. The first thought that would cross your mind is a shortage of food supply. Today, the world is producing 20% more food than it has in all these years. Where is all the food going? Primarily, this is a problem with distribution and not production channels in the countries.

There are government bodies all around the world that have access to all the information. But, due to bureaucratic red tapes and a need to hoard this data to themselves, farmers all over the world do not have access to relevant data that can help them make smart decisions.

The challenges facing the agricultural sector today are manifold. The gap is getting bigger in a world where technology is making the world a smaller place. These are some of the challenges that the agricultural ecosystem faces today.

1. Tensions in the Data Ecosystem

World governments and agencies have access to food production estimates and food distribution information that would allow the farmers to increase or decrease their production. It would make their returns more valuable. But due to licenses and lack of transparency, it is difficult for farmers and startups to have accessible data that can help make informed decisions.

Due to technological advancement today, many agricultural apps relay information but not relevant information that meets the needs and wants of the farming community. This poses a major obstacle in utilizing data that can improve agri-operations all over the world.

2. Funding

Big data is an expensive technology that is constantly changing with the needs of the world and its customers. Due to the high volume and dynamic nature of data, funding from just government bodies would not be enough. In conjunction with private investors and companies, government bodies can fund the creation of big data technology that will allow relevant information to reach the right people.

3. Data science and serendipity

Technology and data go hand-in-hand. Today, consumers are more into healthy food that comes from organic and local resources. Before long-term investments in food retail can be made, the technology requires a buffer period to be tested with real-time supply chain conditions and thus data science be allowed to build and sustain. This includes investing in technologies such as moisture and temperature sensors, biometric sensing that allows for the collection of real-time data.

Using data analytics to draw out patterns for pricing models and weather reports will help farmers make well-informed and sustainable decisions. Companies such as DTN provide up-to-date and accessible data to farmers to better manage their businesses. SourceTrace has a unique advantage of delivering agri-tech to the last-mile even in the most remote non-internet fields. Timely data and information on the crop, weather and pest advisory are critical for farmers to ensure their crop is protected.

4. Data Quality

The data on agricultural value chains is not of the highest quality or relevant. The actual data about acreage, soil statistics, crop diversity, women in agriculture, and more are stuck in red tape and licensing issues. Many social impact networks like CGAIR with the aid of member farmers, national authorities and FAO have endeavoured to fetch, record and share data responsibly with the agri-food sector, however, they are a long way from their targets. The need for scientifically sound and comprehensive data is now more than ever. SMAG, a subsidiary of InVivo covering five agencies in France, has created a data crop algorithm that allows farmers to track the progress of their crops and give an estimated yearly yield which led to an increase in wheat production. They also cover data management with multiple vineyards, winery and cattle management customers across France.

Undoubtedly, data collection for farm/plot management, seed management, agricultural contract operations, and advisory is intense and varied. Currently, not being fed into digital systems barring a few organisations and food companies, limit their scope of GAPs to a geographical area. How do we extend agritech solutions that can be implemented globally?

5. Interoperability of Data and Global Standards

The issue that currently faces us in the agricultural industry is the lack of interoperability of information across different platforms and apps. Since each platform has a unique ecosystem on which it operates, the input of the same data in different platforms makes it a time-consuming task. Certain food producers are comfortable with SAP or an in-built MIS but are wary of digital transformation onto a cloud-based agritech platform. The fear usually arises from some common denominators such as data duplicacy, additional training requirements and management of two databases for the cooling period.

These problems can only be solved by creating a system of standards that can be applied across all platforms and several ecosystems. A singular platform that covers farm-to-table agri and food operations is the space where agritech is focused upon.

SourceTrace DataGreen provides comprehensive farm-to-fork data analytics in both mobile and web dashboards ensuring the technology makes reasonable sense to farmers and food companies.

These challenges can be overcome by investing in technology that gives farmers and various stakeholders access to unimpeded and relevant data. Creating standard operating procedures for interoperability of data across multiple platforms, and collaboration between private and government agencies to invest in more robust technologies so that the agricultural sector can grow. These solutions will allow farmers to make smarter and more informed choices about their business. These initiatives will play a massive role in the distribution of food and combating world hunger.

The 50×2030 initiative by FAO is a multi-partner program that is focused on closing the agricultural data gap by building survey programs at a national level to allow countries to analyze and interpret data to help them improve their agriculture and rural food sectors. Building a robust program that will allow policymakers and stakeholders to make informed decisions based on access to open, meaningful, and relevant data will help bridge the data gap in the agricultural sector.

SourceTrace's software solutions have been deployed across 37 countries and 4 continents already. We are on a mission to make agriculture and food systems more sustainable. Get in touch and we will extend our expertise and commitment to you.

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