National Assembly Futures Institute officially starts future research for 2050
- hold the 1st integrated meeting for a commissioned research on the「future scenario and policy variables discovery」 -
Summary -
The National Assembly Futures Institute (President, Park Jin) held the first integrated meeting for a commissioned research on “future scenarios and discovery of policy variables” in the meeting room of the National Assembly from 2 pm on October 31. In this meeting, major drivers and findings of discovering unexpected variables in 13 fields were shared and discussed according to the institute's future research methodology and process.
The methodology for conducting research was designed for efficient promotion of research in 13 areas by external joint research teams. First, the research team will find the factors that will shape the future of Korea in 2050 by field and draw the future through scenarios. The team then will analyze which futures to avoid using the derived scenarios. The method of conducting research is composed of finding policy tasks to avoid these futures.
The NAFI plans to draw the research results by the end of December through joint research and to draw a final conclusion by converging the results with the internal researchers at the center.
(Attachment) In addition, the results of this research will be used in conjunction with internal research projects and as the basis for research projects planned for next year.
Prepared by : Research Fellow of the National Assembly Futures Institute Kim Yoo-Bin (02-786-2198, ybkim@nafi.re.kr)
※ Please schedule it for morning report on November 1, 2018.
The National Assembly Futures Institute (President, Park Jin) held the first integrated meeting for a commissioned research on 'future scenarios and discovery of policy variables' in the meeting room of the National Assembly from 2 pm on October 31. The NAFI draws out various future scenarios based on the long-term predictions for 2050 and pursues this year's research with the aim of discovering policy tasks to move forward to a desirable future through the National Preference Survey for the scenarios. To this end, 13 areas of future environmental variables were determined through big data analysis and expert consultation, and 11 joint research teams were formed in each field with internal and external researchers.
■ How is the research pursued and utilized?
As this year's research is conducted based on the main drivers focused on 13 areas, it is very important for each external research team to produce research results with the same direction. Therefore, the institute has set a methodology for conducting future research through about 3 months of internal and external expert discussions and has finished explaining the guidelines for methodology to all external research teams in time for launching the research. The research implementation process is divided into 'process for deriving main drivers and core scenarios' and 'process for deriving policy variables', and consists of 9 and 5 sub-research activities, respectively. Each research team will conduct a research according to the research process defined in the methodology, and draw conclusions by converging the research results in each field finally with internal researchers.
In today's first integrated meeting, discussions were held focusing on the main drivers and unexpected variables discovered by each research team. Afterwards, the teams will share the results of research through a monthly integrated meeting and occasional progress reports.
■ Draw the future for 2050 in a scenario.
First, the main drivers and unexpected variables for each field are derived from the 'process for deriving the main drivers and core scenarios'. The main driver is defined as an exogenous variable that can give implications from various perspectives due to its high future uncertainty and influence. In addition, it is a quantitative and qualitative index that makes it easy to identify the bipolar in preparation for the scenarios in corresponding field, and leads to derive detailed indicators that can be quantified in connection with the long-term predictions for 2050. Each research team will discover five drivers for each field by using the discovery indicators such as the ripple effects, ripple scope, and speed of changes in trend etc. An unexpected variable is defined as a variable that has no precedent in the past and has a low probability of occurrence, but has a high ripple effect when realized. The research team will discover at least two unexpected variables that can be affected by the corresponding field or other fields by using indicators such as probability of occurrence, ripple effect, ripple scope, and need for quick response etc. The discovered major drivers will be used for long-term prediction to 2050 through meta search, trend analysis, simulation, etc., and the unexpected variables are used to analyze the impact of each major driver, focusing on the impact of the trend and the possibility of conversion due to the unexpected change.
Then, at the stage of combing scenarios by each driver, the research team derives 10 of 2x2 scenario for each field through the mechanical combination (5C2) of the five major drivers. In this process, it will conduct an implications analysis from the people's perspective by each quadrant (configuration scenario) of the 2x2 scenarios and driver combinations where there is a conflict such as cultural diversity and social integration, and the results will be used in the national preference survey in connection with internal researchers.
■ Which future should be avoided ? (deriving core scenarios)
Using each configuration scenario of the 10 derived scenarios, the research team classifies them into the most likely areas (possible future), the most desired areas (preferred future), and the most avoided areas (future to be avoided) through an expert discussion process. If the possible future conforms to the preferred future, the scenario is classified into 'optimistic scenario'. If the possible future conforms to the future to be avoided, the scenarios is classified into 'risk scenario', and otherwise, it classified into 'intermediate scenario'.
The reason for classifying the types of scenarios is to derive a 'core scenario' based on a pessimistic future. In other words, among the risk scenarios and intermediate scenarios, scenarios with high potential for future impact and policy improvement become candidates for core scenarios. In addition, if there is a possibility that the 'optimistic' or 'intermediate' scenario can be converted to a 'risk' scenario through the effect analysis between the driver combination scenario and the unexpected variables, respectively, using the derivation of the unexpected variable and analysis result of its impact performed previously, this is also identified as a candidate for core scenario. The core scenario candidates derived in this way are determined as the final core scenario by considering the link with the derivation process of the policy variables and policy task.
■ Finding a policy task to avoid a bad future.
When the process of deriving the main drivers and core scenarios is completed, the result is linked to the subsequent research phase, 'policy variable derivation process'. First, policy variables are identified for the “risk” and “intermediate” scenarios. At this time, the policy variable should be able to lower the possibility of a going into the future to be avoided and to increase the possibility of going into the preferred future. In particular, the identified policy variables may have conflicting values, such as energy safety and electricity price, ease and universal access to education. Therefore, the research team will analyze the expected side effects and policy alternatives for side effects by each identified policy variable, and will conduct a survey in connection with the national preference survey for policy variables having important conflicting values that need to be directly asked by the public.
The identified policy variables are determined by deriving around 10 to 15 high-priority items through expert discussions by area. And then unit policy analysis and policy network (causal map) analysis are performed according to corresponding policy variables. Using the results, the relationship between policies, such as policy direction and weight etc., is analyzed by system thinking, and core policy variables are derived through expert Delphi survey. In final, the research team will derive 5 to 10 reform tasks composed of these core policy variables by area, and analyze the importance, urgency, feasibility, implementation period, and subject of each policy task to present specific reform tasks that can enhance the effectiveness of policy implementation.
The NAFI will draw the final research results by the end of December and use them for future research on preferences for the people, policy research for future preparation and future research on North Korea and the Korean Peninsula, which are being pursuing by internal researchers. The NAFI also plans to improve the linkage between researches by using it as a base research for the “Deriving Combined Scenarios and Comprehensive Scenarios by Area” research, which is scheduled to be carried out next year. The president of the National Assembly Futures Institute Park Jin said, "We will conduct a survey on the national preferences for a comprehensive scenario, and ultimately present a reform strategy for the future that the people desire with the '(tentative name) Vision 2050 Strategy Report.
Prepared by : Research Fellow of the National Assembly Futures Institute Kim Yoo-Bin (02-786-2198, ybkim@nafi.re.kr)
[Attachment] Research Implementation Process and System for the 'Future Scenario and Policy Variable Discovery' Research
Research Process and Implementation System for the Future Research of the NAFI
converging the research results
13 areas for future research
climate change
science and technology innovation
energy·resource
food·water resources
international politics
North Korea
economy
settlement conditions
human
population·society
politics·administration
research process by research team
① process of deriving main drivers and core scenario
Draw the future for 2050 in a scenario.
1.1 deriving main drivers and unexpected variables (emerging issue) for each field
1.2 main driver's long-term predictions for 2050
1.3 analyzing unexpected variable
1.4 combining scenario by driver
② process of deriving risk scenarios
Which future should be avoided ?
2.1 possible future, preferred future, future to be avoided
2.2 identifying optimistic and risk scenarios
2.3 analyzing the most dangerous scenarios with main drivers
2.4 analyzing the risk scenario which could be caused by unexpected variables
2.5 confirming core scenario (core risk scenario)
③ policy variable derivation process
identified for bad future and policy task to be avoided
3.1 identifying policy variables based on risk scenarios
3.2 analyzing policy causal map to avoid dangerous future
3.3 analyzing mutual influence among policies
3.4 deriving core policy variables
3.5 presenting detailed reformation tasks
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