Prevent conflict through data

Peacekeeper of the UN Mission in Mali (MINUSMA) handling policy and guidance materials Peacekeeper of the UN Mission in Mali (MINUSMA) handling policy and guidance materials © UN Photo/MINUSMA/Harandane Dicko

This article is a brief presentation of ZIF's report on the importance of an early warning system based on quantitative data

In September 2020, the Center for International Peace Operations (ZIF) published the report “Predict and prevent: overcoming early warning implementation challenges in UN peace operations". Early warning systems, also known as preventive peacekeeping, consist of a set of practices and analytical tools able to estimate where and when new violent conflicts will emerge, to ensure the Protection of Civilians (PoC). Although substantial progress in the field of early warning has been made by the United Nations, these systems are still strongly linked to qualitative analysis and, since the average reaction time to violence conflicts is 2.8 days, there is considerable room for improvement thanks to quantitative data analysis. The strategic importance of this new type of analysis in a mission, preventing threats and formulating new strategies, is unquestionable. However, in the face of the new possibilities offered by recent technological developments, several challenges and peculiarities must be accounted for.

The main example of a preventive quantitative analysis system is the Situational Awareness Geospatial Enterprise (SAGE), which is currently available to all - military and non-military - personnel, with Internet access, from the United Nations Missions in South Sudan (UNMISS) and the Democratic Republic of Congo (MONUSCO). This system, besides eliminating redundancy in the information collected, allows field operatives to report incidents, protests, attacks, military actions and other relevant activities. Besides, the collection of data in a digital format allows for faster aggregation and processing, leading to the creation of more effective early warning tools.

Although SAGE is to be considered as a virtuous example, the use of these technologies presents several challenges. The first one is the data collection. On the one hand, a more horizontal sharing of data with a whole-of-a-mission-approach must be encouraged. On the other hand, the nature of many conflicts means that they take place in remote scenarios, which makes  it difficult to collect information, leading to a greater use of these systems near operational bases and, thus, partially undermining their effectiveness. The second challenge concerns the processing, storage and protection against cyber-attacks of this data and how these modalities must be adapted to the peculiarities of each mission. Finally, the report stresses that these data cannot and must not be considered as substitutes for contextual understanding in the field, which makes them important but complementary to a broader preventive strategy.  This factor must be taken into account,  considering the high risk of bias in the data analysis. For example, data collection through phone services involves certain technological knowledge and income (connectivity bias).

The report concludes by pointing out that, with the vast amount of data collected by the UN, the implementation of techniques and tools capable of aggregating them and understanding their recurrences has considerable potential in the recognition of risk scenarios. The introduction of these systems could, therefore, transform what is currently a reaction to violence into preventive action. This process is already underway, but very often what is driving this technology is the possibility of reducing costs on the ground in response to the decreasing funds available. The centre, therefore, warns against the unprofessional and unwise use of these data and the distorting or even malicious risks that may result from it.


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Author: Matteo Consiglio; Editor: Margherita Curti

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