Agricultural Data Analytics

The agricultural sector has witnessed an immense transformation over the years; it has evolved from the stage where it relied entirely on the recommendations from fellow farmers to a modern, data-driven endeavour. Modern-fay farmers are capable of harnessing insights backed with a lot of historical data to derive a conclusive analysis of the crop to be planted and the method of cultivation that would be used. Data analytics is a crucial aspect of enhancing business operations in every industry and is now penetrating the age-old agricultural process. Agricultural data analytics help streamline irregularities and enhance efficiency in cultivation, irrigation, harvesting, supply chain management, and logistics to ensure that there are minimal to no risks involved while dealing with perishable goods.

Globally, “data analysis in agriculture is currently valued at 565 million USD, and the projected valuation by 2023 is 1256 million USD”. Did you know that the world population is expected to reach over 9 billion by 2050 and the Food and Agriculture Organisation (FAO) predicts a 70% growth in agricultural output will be needed to serve the projected demand? This has increased the demand for data analytics in agribusiness.

Australian agribusiness companies, wholesalers, growers, and farmers are enhancing their use of technology and data analytics to manage profitability, minimise wastage, and understand customer needs, crop yields, soil conditions, weather patterns, and more. Modern-day sensors, internet-enabled devices, software applications, and cloud data storage facilities allow a huge amount and different types of data to be captured, stored, manipulated and fed into decision-support tools to aid agribusiness decisions.

In this blog, we have enlisted a few advantages of using data analytics in agriculture.

How is Data Analytics Beneficial to the Agricultural Sector?

With precision agriculture and big data analytics evolving, farmers have shown an inclination towards data-driven solutions for agricultural problems due to the noticeable benefits it has shown over the years.

  1. Enhancing Productivity and Innovation: Farmers, agribusinesses, and growers must leverage data and innovation to enhance productivity to enhance both yield and profits. Technological benefits such as soil sensors, GPS-equipped tractors, and weather tracking provide an unprecedented visibility into operations and opportunities to maximize resources. Having access to real-time data, farmers can get access to information required about when, where and how to plant, starting from a granular level. 
  1. Greater Understanding of Environmental Challenges: Different environmental factors such as unpredictable weather, severe storms, drought, and changing insect behaviours due to weather are the factors that impact the agribusiness supply chain. Using data to understand and predict shifts in environmental conditions help farmers prepare for challenges and increase opportunities without wasting any resources. Hence, data analytics help farmers monitor the crop-health in real-time, create predictive analytics related to future yields, and aid farmers in making resource management decisions based on proven trends. 
  1. Minimising Waste and Enhancing Profits: For agribusinesses to remain profitable, they must continue to innovate and find ways to demonstrate real value which can be done by incorporating a data analytics strategy. Using real-time data, agribusinesses can get the ability to answer sales-related questions through data from one platform, creating the opportunity to make on-time, and evidence-based decisions. Also, they help gain pricing visibility that allows for profit-based decision making. Big data analytics also help uncover opportunities at the customer level and inform the sales team in order to enhance market share. 
  1. Enhancing Supply Chain Management: Since the current agribusiness value chain is still in its nascent stage, it is in need of enhancements to both communication and collaboration efforts. Precision agriculture technologies such as data analytics make it easier for farmers to trace their products through the supply chain which allows each farmer to communicate essential information to their retailers, distributors, and other key stakeholders regarding product offerings and services. 

How to Implement Data Analytics in Agriculture?

Gaining data insights, creating algorithms and inventing new technologies are in-trend. Shared information coupled with smart technology and ambitious innovation allows agribusinesses to achieve amazing accomplishments. Agribusinesses need to have the right tools to implement a data analytics strategy.

  1. Collect Data: Collecting data will help you aggregate them from a trusted, selected source and simplify operations by storing the data in a single and safe location. 
  1. Standardise Data: Bringing multiple data sets together in a single data structure will formulate the opportunity to run comparisons; track trends in real-time, and uncover patterns in the data to help identify new opportunities. 
  1. Clean Data: Having access to clean, accurate, and complete data, you can make data-driven decisions based on that data. 
  1. Enrich Data: You can improve forecasting and identify potential challenges by linking outside information such as weather data, local soil analytics, and insect tracks. 
  1. Analyse Data: Analysing data is essential for gaining value from the information you are collecting. Hence, you need to learn the tools available for establishing analytics ad ensuring they support the results you want to achieve.

Having access to the right technology and communication tools, you can consider a proper business strategy. To do so, you need to

  • Understand how a data analytics platform will support your overall business strategy.
  • Create an analytics vision and set target maturity levels for core processes.
  • Prioritise and create a strategic roadmap that includes both short-term and long-term goals.
  • Outline a blueprint of the resulting target design.

Wrapping Up,

Big data analytics as we know is an essential business strategy that helps businesses distinguish themselves from their competitors and boost their revenue. Using predictive analytics, big data provides businesses with customised recommendations and suggestions. Also, with big data gathering information from extensive sources and translating it into actionable information to enhance business processes and solve problems speedily, there have been real-time performance optimisations across the industry. Incorporating data analytics has constantly been transforming agriculture ever since its advent.

For a more detailed insight into data analytics in agriculture, browse the KG2 website. We are Australia’s largest independent farmer database that enables farmers and industry to leverage Australia’s most comprehensive agribusiness database for mutually beneficial outcomes.