The Government of the Republic of Korea has implemented an ICT-based agricultural data management system through digitalization and a human capacity building program, which allows innovative data collection, analysis, and sharing in 6 ASEAN member countries. Through this, the governments have improved the paperless work process on agricultural statistics, accumulating the data and human resources for enhancing food security in the ASEAN region.
To respond effectively and efficiently to secure food security, providing accurate data and information on agricultural production and distribution at the right time is essential. Many developing countries are currently collecting that data manually using either paper or Excel, which can disrupt the accurate and timely work process on agricultural statistics data collection.
In this context, the Government of Korea has implemented a cooperation project with ASEAN Food Security Information System (AFSIS) Secretariat under ASEAN+3 Ministerial Meeting on Agriculture and Forestry (AMAF+3). As a result of the project implementation from 2014 to 2020, an ICT-based agricultural data management system, called National Agri-food Information System (NAIS), has been established in 6 ASEAN member countries: Laos, Cambodia, Indonesia, Philippines, Vietnam, and Myanmar. NAIS contributes to creating an innovative and timeliness work environment via digitalization of statistics data collection process and capacity building program for local government workforces.
The objective of the project is to enhance the ASEAN national/regional competency to respond to its food security promptly by creating an environment for ICT-based data collection and monitoring on national strategic agricultural data.
The project is three-phased that includes an action plan and information system development, and a human capacity building program in each phase:
1) PHASE 1 (2014~2017): NAIS system development for agricultural production data collection such as production volume, yield, and production area through the online web system.
2) PHASE 2 (2018~2021): NAIS system improvement for agricultural distribution data collection such as food stock, price, export, and import. The data collection is not only on the web but also is accessible and collectible in mobile connection in response to the high variability of data on agricultural distribution. Also, it is improved to provide the gathered data to the public for the greater good of autonomous supply and demand conditions by allowing farmers and consumers to make their own price decision.
3) PHASE 3 (2022~): Food security forecasting model development based on remote sensing technology (Pilot)
In the overall analysis of the project implementation, an ICT-based agricultural data management system, 'NAIS,' creates a new work process on agricultural data collection, which directly contributes to work efficiency and cost reduction. As the traditional manual data collection has transformed to an ICT system that enables paperless data collection, the data collection time has reduced up to 27% after Phase 1 and 40% after Phase 2 on average. Furthermore, the local government budget for data collection has reduced up to 27% after Phase 1 and 30% after Phase 2 on average.
Significantly, Indonesia has delivered an outstanding performance in terms of work efficiency and cost reduction. In 2016, bimodally divided bureaucracy on statistics collection into Ministry of Agriculture and Statistics Offices of Indonesia became unified through NAIS system to collect data on sugarcane, a national strategic crop of Indonesia, at the national-public level. Then, it added the scope of sugarcane data collection in private distribution channels in 2020, which manages a comprehensive agricultural value chain in both public and private sectors from production to processing and distribution. As a result, the data collection time has reduced to 71~80% in both Phase 1 and 2, showing the highest level of time-saving among 6 ASEAN member countries.
Also, a preliminary pilot project was implemented to develop the Food Security Forecasting Model (FSFM) for phase 3 of the project. Through this, satellite image processing and utilizing systems have been created. It also proposed a production forecasting model through sugarcane production monitoring, data analysis, and site inspection in three pilot areas.
Last but not least, the human capacity building program comprises local training and invitational training in Korea, targeting to focus on policy decision-making and work performance increase on food security and agricultural ICT area. Through the seven years of capacity building program operation, a total of 1,574 local government officials successfully enhanced their work competency in the workplace.
What Makes Your Project Innovative?
The NAIS system is an innovation in agricultural data collection and sharing because:
1) It is universally applicable as a standard model for ICT-based agricultural data collection and management from one’s innovation to another. The framework and modules can provide a customized tool for each nations’ different needs in data governance. Thus, the system applies identified measures to solve identified problems and adopt individual nations’ preferences and special requests such as strategic crop or scope of the system application at the sub-project unit level.
2) It enables accurate, timely, and eco-friendly agricultural data collection through ICT-based information systems that depart from the previous manual, inaccurate, and delayed data collection method. The real-time and accurate agricultural data assists reliable policy decision-making to respond to the food security of the nation/region more effectively and efficiently.
What is the current status of your innovation?
1) Project phases 1 and 2 have been completed in 5 countries except for Myanmar from 2014 to March 2020. Myanmar's project phase 2 was expected to be implemented in 2021 but is temporarily suspended due to the national emergency of Myanmar.
2) A comprehensive analysis of the overall project performance, including beneficiary interviews, was conducted from December 2020 to March 2021.
3) Project phase 3 is expected to launch in 2022, and EPIS has developed the master plan in March 2021. The AFSIS Secretariat submitted the letter of intent to Korea for project phase 3 implementation from 2021.
Collaborations & Partnerships
1) AFSIS Secretariat: operates ASEAN Food Security Information System and related international cooperation projects. Hosts international meetings to discuss regional food security among 10 ASEAN member countries.
2) Local Government Officials: Define requests on NAIS system development, Inspect development outputs, Provide administrative supports
3) Korean ICT Companies: Develop and customize NAIS system in each nation; supports system monitoring and data integration for AFSIS Secretariat.
Users, Stakeholders & Beneficiaries
1) System users: 9,586 local government officials responsible for agricultural statistics in 6 ASEAN member countries are the direct users of the systems.
2) Beneficiary: 49,745 local government officials of the Ministry of Agriculture and related organizations in 6 ASEAN member countries and international organizations can get more accurate and timely data. More widely, more than 620 million ASEAN people may be affected by the enhanced regional food security.
Results, Outcomes & Impacts
ICT-based agricultural data management system, “NAIS,” has directly contributed to work efficiency and cost reduction. According to the survey results answered by local focal points officers, as the former manual data collection method has transformed to a paperless ICT system, the data collection time has reduced by 27-40% on average. Furthermore, the local government budget for agricultural data collection has been reduced by 20-30% on average.
The project has also implemented intensive human capacity-building programs for 1,574 local government officials in the last seven years, leading to improved policy decision-making and technical skills in food security, agricultural statistics, and ICT.
Those trained officials are fostering the NAIS system's utilization. The click rate of the NAIS system indicated 299,466 in 2020, which is increased by 2,116% compared to the last year. Also, the number of data input showed 8,545, which is increased by 214% during the same period.
Challenges and Failures
In the beginning, most government officials did not fully understand ICT-based data management. Lack of understanding and experience on ICT application caused a significant obstacle in communication when designing the project with the governments during the initial phase of the projects.
Thus, the project included capacity-building programs as an indispensable component to help local government officials' complete understanding of the NAIS system and its utilization.
1) Local training: officials related to agricultural statistics took practical training sessions to make full use of the new/upgraded National Agricultural Information Systems (NAIS).
2) Invitational Workshop: ASEAN government officials’ participated in training courses and workshops in Korea. It includes lectures, field trips, in-depth discussions, and action plan development, which helped improve their knowledge and skills in policy decision-making in agricultural ICT and Food Security.
Conditions for Success
The conditions for the success of the project should include:
1) Internet accessibility to secure stable online agricultural data collection for local government officials at the national level.
2) Political supports and intents of the local governments to adopt new methodologies of agricultural data collection for national statistics management and administration.
3) Human resources with ICT knowledge for determining the requests for system development and sustainable operation of the NAIS system.
4) Governments' commitment and financial support for consistent use of the system and additional local training.
The project has been implemented by the method of sub-project units in each country. Certainly, it provides an environment for sharing knowledge and experience with other participating governments in annual workshop meetings.
It is in this context that the project targets to replicate one’s identified innovation to another. It applies identified measures to solve identified problems and thoughtful concerns to reflect each nation’s different circumstances and work process through customization at the sub-project unit level.
Also, it is expandable to other nations by applying customized models among project phases at the provincial, national and regional levels.
The lessons learned through the project are:
1) ICT can play an important role as an innovative measure in the agricultural sector in developing countries. Progress in agricultural informatization and data accessibility will lead to the enhancement of regional food security. In response to a new era of digitalized innovation, the world should provide more technical and financial supports in this area.
2) Human resources development on data accessibility and ICT application is not an option but a critical component for the success of an ICT system. Even an excellent information system would be worthless without the people who fully understand, utilize, and maintain the system. That is why it is strongly recommended that sufficient investment in human resources should come along on both working- and managing-level personals.
Due to the COVID-19 situation, food security issues have become more critical. In response to this, the third phase of this project will launch pilot projects to establish forecasting models for each countries’ strategic crops. Improved production monitoring will support proper responsive actions to food security issues.
Although Korea is playing a role in the planning and coordination of the project, EPIS will share all the results with the six participating countries and the AFSIS Secretariat.
The list of the participating organizations is as below:
- AFSIS Secretariat
- EPIS, Ministry of Agriculture, Food, and Rural Affairs, South Korea
- Center for Agricultural Data and Information Systems, Indonesia
- Center for Agricultural Statistics, Lao PDR
- Ministry of Agriculture, Forestry, and Fisheries, Cambodia
- Philippine Statistics Authority, Philippines
- Center for Informatics and Statistics, Vietnam
- Ministry of Agriculture, Livestock, and Irrigation, Myanmar
- Implementation - making the innovation happen
- Evaluation - understanding whether the innovative initiative has delivered what was needed
- Diffusing Lessons - using what was learnt to inform other projects and understanding how the innovation can be applied in other ways
3 September 2021