The power of a data-driven agriculture sector


Have you heard of the new mining industry?

Agriculture is usually looked upon as a sector where techniques and wisdom are passed down from one generation to another. But issues related to global problems today such as climate change, rising population, depletion of farm acreage, and the need for self-sufficiency are driving countries to look for better ways to increase productivity. This gap is now being addressed effectively by technology and it has emerged as a game-changer.

By harnessing the power of big data and analytics techniques, remote sensors, cloud technology, drones, GPS, satellite mapping, precision machinery, and even the use of artificial intelligence, the agriculture sector of many countries is able to achieve significant improvements in productivity and sustainability despite limited viable farmlands and resource constraints.

The global population is expected to reach 9.8 billion by 2050 according to United Nations estimates. To address the food requirements of the ever-growing population, we need to step up our crop production significantly. Unfortunately, rapid urbanization and climate change have claimed much of what used to be farmlands in most countries including the Philippines. Antiquated farming techniques have also affected farm production.

Policymakers and industry leaders are turning to agricultural technology for solutions. Let us take a closer look at how technologies such as IoT,  analytics, and cloud computing can help tackle this challenge.

Data collection is seen as the initial step needed to effectively implement innovative technologies in the sector. Without data, it would be like working in the dark and not knowing where to start. IoT devices such as sensors plugged into farming equipment and drones as well as on the fields and plants aid in the collection of important data from the ground.
The use of analytics and cloud technology would then come to play once we have large amounts of vital data made available. Analysts would now be able to integrate the collected data with other available information such as weather data to generate patterns and insights. With this information, issues such as operational inefficiencies and problems related to soil quality are easily predicted even before they occur. Big data will help ensure that farmers will have the necessary insights to make good operational decisions and do not have to depend anymore on favorable natural forces.

The value of data analytics is very much underrated in the agriculture sector today. By collecting and analyzing data from a variety of sources, farmers can make better decisions about crop selection, planting, irrigation, storage, and pest management. This can lead to increased yields, reduced costs, minimum wastage, and improved sustainability.

Analytics can be used to analyze historical data on crop yields, weather patterns, and soil conditions to help farmers select the best crops to grow in a given area. It can help determine the optimal time to plant crops, based on factors such as weather conditions, soil moisture, and pest infestations thus ensuring that crops are planted at the right time and in the right conditions, which can lead to increased yields.

In places where water is a major constraint, analytics can be used to monitor soil moisture levels and weather patterns to help farmers determine the optimal irrigation schedule. This can improve water utilization and improve crop yields. Similarly, predictive analytics can identify early signs of plant diseases, enabling farmers to apply timely treatments and prevent significant crop losses. To help ensure sustainability, analytics can be used to track the environmental impact of agricultural practices. This information can be used to identify areas where practices can be improved to reduce environmental impact.

Analytics can transform the entire agricultural supply chain, a critical issue in countries like the Philippines. This can be achieved by improving logistics, distribution, and quality control. Farmers can gain insights into transportation routes, storage conditions, and product shelf life by analyzing data from farm to fork. Real-time monitoring of storage conditions ensures that perishable products are maintained at optimal temperatures, reducing spoilage and increasing marketability.

The use of analytics in the agricultural sector is not without challenges as far as the use of big data and analytics is concerned. Agriculture players need to understand the power of analytics to help increase productivity and profitability. The availability of usable data is also often a challenge in agriculture because data collection can be expensive and time-consuming. The lack of skills among farmers and agricultural professionals can also be a challenge to the adoption of analytics.

Market reports say that the adoption of analytics in agriculture has been increasing consistently and is expected to reach US$ 1.236 billion by this year. As seen in other countries, analytics have the potential to play a major role in improving agriculture productivity in the Philippines. This could be a critical prescription for ensuring food security in the country. (

(The author is an executive member of the National Innovation Council, lead convenor of the Alliance for Technology Innovators for the Nation (ATIN), vice president of the Analytics and AI Association of the Philippines, and vice president, UP System Information Technology Foundation.)