How data analytics is transforming agriculture

 

Data analytics is a critical part of improving business operations in every industry. An organization can utilize data analytics to improve decision-making, analyze customer trends, track customer satisfaction and identify opportunities for new products and services to meet growing market needs. By integrating information and systems to gather data across the business, organizations are able to gain real-time insights into marketing, product demand, sales and finances.

With the world population expected to reach more than nine billion by the year 2050, The Food and Agriculture Organization (FAO) predicts a 70-percent growth in agricultural output will be needed to serve the projected demand. This driving force has greatly increased the interest in and utilization of data analytics in agribusiness.

Analytics Driving Agribusinesses

The precision agriculture market continues to evolve, allowing farmers to embrace data-driven solutions. While the future opportunities for data analytics in agriculture is limitless, there are already strong benefits emerging, such as:

Increasing innovation and productivity. To increase both yield and profits, agribusinesses, farmers and growers must leverage data and innovation to improve productivity. With the benefits of technology, including soil sensors, GPS-equipped tractors and weather tracking, there is now unprecedented visibility into operations and opportunities to maximize resources. When farmers have access to real-time data, they gain the information needed to know when, where and how to plant, down to a granular level.

Greater understanding of environmental challenges. Unpredictable weather, severe storms, draught and changing insect behaviors due to weather are all environmental factors that impact the agribusiness supply chain. However, utilizing data to help navigate shifts in environmental conditions can help farmers prepare for challenges and maximize on opportunities, all without wasting resources. Data analytics can help farmers monitor the health of crops in real-time, create predictive analytics related to future yields and help farmers make resource management decisions based on proven trends.

Reducing waste and improving profits. To remain profitable, agribusinesses must continue to innovate and find ways to demonstrate real value. Through the incorporation of a data analytics strategy, agribusinesses gain the ability to answer sales-related questions through data from a single platform, creating the opportunity to make timely, evidence-based decisions. They also gain visibility of pricing, which allows for decisions to be made based on profitability. Additionally, the right analytics will uncover opportunities at the customer level and inform the sales team in order to increase market share.

Improving supply chain management. The current agribusiness value chain is very siloed and in need of improvements to both communication and collaboration efforts. The transformative impact of precision agriculture technologies, like data analytics, make it easier for farmers to trace their products through the supply chain. This allows each farmer to communicate valuable information to retailers, distributors and other key stakeholders regarding product offerings and services.

Getting Started

The ability to gain insights from data, create algorithms and invent new technologies continues to move forward at an astounding speed. The combination of shared information, smart technology and ambitious innovation can accomplish amazing feats for the agribusiness industry. To take advantage of data analytics and create a competitive advantage, it is important to consider the strategy and long-term goals of this endeavor. First, an agri organization must have the right tools in place before a data analytics strategy can be implemented:

  • Collect data. This will allow you to aggregate data from your trusted, selected sources and simplify operations by storing the data in a single, safe location.
  • Standardize data. The ability to bring multiple data sets together in a single data structure will create the opportunity to run comparisons, track trends in real-time and uncover patterns in the data to help identify new opportunities.
  • Clean data. Ensuring your data is clean, accurate and complete will give you confidence to make decisions based on that data.
  • Enrich data. Having the opportunity to link to outside information – weather data, local soil analytics, insect tracking – will allow you to improve forecasting and identify potential challenges.
  • Analyze data. The ability to analyze data is critical to gaining value from the information you are collecting. Learn the tools available for establishing analytics and make sure they support the results that you want to achieve.

Once the right technology and communication tools are in place, it is time to consider business strategy. Here are the key steps to take prior to rolling out a data analytics platform:

  • Understand how the data analytics platform will support the overall business strategy of the organization
  • Develop an analytics vision and set target maturity levels for core processes
  • Prioritize and develop a strategic roadmap that includes short-term and long-term goals
  • Develop a blueprint of the resulting target architecture

 

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