Agricultural data refers to data gathered and assessed from various sources for the benefit, growth, and development of agribusinesses. It includes information relevant to the agribusiness operations in whatever capacity, intensity and area within the agricultural value chain and landscape. Such data ultimately provide the raw materials that need to be processed.
Processed data leads to information that helps businesses and organisations make informed decisions. Big data and analytics, on the other hand, essentially indicate data sets that are very large or complex, usually sourced from many different sources to be processed. They are dynamic, and large volumes are created by people, tools, and machines. Rather than being seen as a continuation of past information trends, it is an asset to every agribusiness, regardless of the size and scale of operation as it will change how companies do business, internally and externally. Big data and analytics have been researched to transform agribusiness start-ups in many ways. They are playing significant roles in optimising global food production and transforming agribusiness through increased profitability.
Agribusiness start-ups integrate technology into their model and operations to improve efficiency, sustainability, and profitability. Depending on the challenges or problems the agribusiness start-ups intend to provide solutions to. One of the ways technology has become relevant to them is to analyse big data into condensed and precise information required for the immediate short, medium, and long-term goals of the enterprises.
Big data is progressively becoming the foundation for modern agriculture and agribusiness operations according to N-iX. It offers operational relevance of such enterprises while providing direction to their identified vision and mission. Today, most if not all agribusinesses cannot do without big data.
The relevance of big data has progressed from a supportive position in terms of taking a secondary and alternative role for agribusiness enterprises to much deeper, foundational roles. This transition is hinged and motivated by technological advancements in agriculture. Cropin identifies that agribusiness operations can unravel insights, optimise their operations, and ensure a sustainable future by harnessing big data analytics.
Agribusiness operations span through the entire agricultural eco-system and identified value chains. In this article, the relevance of big data to agribusiness start-ups will be discussed.
Download the Ebook now
Big Data-based Decision System
Relevance of Big Data
- Better resource management
Agribusiness start-ups can use big data to plan and manage their resources more effectively. They can optimise their staff engagements by working with staff that are relevant to the goals and vision of the organisation rather than having many redundant hands. Furthermore, it helps them plan and manage their operations and scope. For example, data on weather and agro-climatic conditions can help producers plan for what commodities to grow and the calculated application days or rates required rather than a one-size-fits-all resource utilisation approach.
- Improved productivity and efficiency
Agricultural productivity is a measure of how efficiently an agricultural system produces outputs relative to the inputs it uses. Essentially, it measures the ratio of outputs to inputs in an agribusiness. Big data provides data that provides a rational and improved output to input as a result of working with information from data that gives a panoramic view of the agribusiness enterprise. For example, in producing an agricultural commodity like rice, cassava, maize, etc. farmers make better business decisions by providing accurate forecasts for crop yields and production while guiding the quantity, quality, and utilisation of inputs into the production. In the same vein, big data provides an opportunity to improve the efficiency of agribusiness operations. It reduces error, and second-guessing and allows for almost seamless operational hiccups.
- Real-time, smarter decision-making
Due to the influence of big data in helping to curate real-time information that can be utilised to make instant decisions, big data analytics and interpretations have been synonymous with instant, on-the-spot and smarter decisions. This is particularly a useful relevance of big data to the decision-making process of many start-ups.
Big Data Analytics
- Speedy operations
With the utilisation of big data, the operations, activities, and procedures for agricultural and food production and supply chains become essentially improved, faster and more efficient. Big data can help improve internal operations of agribusiness start-ups and their activities in their supply chains by analysing logistics and supply chain data.
- Accelerated research
Agribusiness start-ups require substantial data to process as it affects all the areas of their proposed operations where research is necessary to be conducted. Market, Operations, Sales, Product Development, Value Chain Analysis, and many more research focuses of agribusiness start-ups require the use of big data. Big data can help develop data and information that can speed up the research processes shortening the time for making decisions and taking forward-thinking steps. For example, the discovery of new crop varieties by processing large amounts of genetic and experimental data.
- Sustainable practices
Most start-ups are saddled with tasks and responsibilities that must be proven to be sustainable and innovative. Big data becomes relevant in helping to drive innovation in sustainable agribusiness operations and practices.
- Record purposes
Big data is fundamentally relevant in generating and keeping records that are instrumental to the growth and expansion of agribusiness start-ups and can help agribusiness start-up operators to create detailed records that can be used for various corporate essentialities.
- Gives corporate direction
Big data and analytics provide, reinforce, and in some cases chart new courses and directions for agribusiness start-ups. It clearly defines the proposed corporate vision and direction while constantly showing and helping to validate the directions of start-ups.
Conclusion
The relevance of big data and analytics cannot be over-emphasised in the operations of agribusiness start-ups. Agribusiness operations are evolving throughout the entire value chain as big data and analytics continue to play a dominant role in determining the direction, growth, and expansion strategies of start-ups. However, big data-driven decisions and analytics will further play crucial roles in agribusiness start-ups and their operations in the nearest future.
