Strengthening Agro-climatic Monitoring and Information System (SAMIS)

MAF learns about use of big data for better policies

10/04/2021

Recently, the SAMIS project has received support by the global FAO project Sustainable Productivity in agriculture in the context of climate smart agriculture and agro-ecology, also known as FMM project. In this framework, on 6th of April a Discussion on “Big Data and Foresight for better policies; Process, Success stories and Lesson Learnt” was organized by the University of Utrecht.

The discussion was moderated by Dr. Rathana P. Norbert- Munns, CCAFS SEA Regional Scenarios and Policy researcher. From the side of the Government of Lao PDR, the meeting included representatives of the Ministry of Agriculture, namely the Department of Planning and Financing, the Department of Policy and Legal Affairs, Department of Agricultural Land Management (DALAM) and the National Agriculture and Forestry Research Institute. Main speacker included Dr. Ariella Helfgott, Director at Collaborative Futures, Network Member at Collaboration for Impact, Senior Researcher at University of Adelaide, Mr. Bart Edes, Author and distinguished Fellow, Asia Pacific Foundation Canada, and Ms. Imelda Bacudo, Convenor for the ASEAN Climate Resilience Network and International coordinator for Climate and Clean Air Coalition Vietnam.

Surrounded by competing priorities, limited resources, complex and multi dynamic changing environment, governments are searching for new planning tools to meet multiple economic, political, social, and environmental and climate change challenges. Whether it involves government setting parameters for the way our society manages, protects, restores complex systems such as food systems, today policy makers are in a unique position to design the raw framework of transformative changes and innovation but fundamentally to rethink how policies are made and how future oriented they can be with today legislation.

Foresight demonstrated its success and the increasing uses in the public sector set this approach as an accepted and credible practice to better policies formulation. Datafication or the so called “Big data” phenomenon is also changing the relationship between governments and stakeholders. The progress made in data production, management and analytic are phenomenal opening the opportunities to strengthen decision making process that are more robust and informed.

FAO with the SAMIS project is producing the climate scenario at 20, 50 and 100 years for Lao PDR. SAMIS is producing the Agro-Ecological Zoning (AEZ) Suitability and Yield maps for the six major crops of Lao PDR at present time, and at 30 and 60 years in the future for three IPCC RCP scenarios. The AEZ method use soil, climate and cropping system data to simulate suitability, harvested areas and yield in present time, and in future scenarios.

This work is done by the Department of Agricultural Land Management (DALAM) with the guidance of the Asian Institute of Technology AIT. It is under this project that FAO, CCAFS and Utrecht University collaborated in 2020 to design and implement the first advanced training on foresight and anticipatory governance in Lao PDR.

In 2021, application of the foresight methods at both sub-national and national levels are in preparation. This discussion is the first event organised under this project. This discussion aims to present success stories and lesson learnt from people in the front line of the uses of “big data” and foresight across the globe. The speakers will share their experiences and insights building knowledge on:

  •  the different expectations and consensual agreement on the key qualities of “advanced data”
  • the key challenges faced by multiple stakeholders into generating, managing, analyzing advanced data for transformative agriculture.
  • the strategies/actions that has been implemented that directly or indirectly enhance decision making capability sharing the individual or institutional lesson learnt.
  • the foresight methods used to support better policies in agriculture.