In September 2022, under the auspices of the four-year Programme of Work (MYPoW 2020-2023) of the Committee on World Food Security (CFS), the High-Level Panel of Experts on Food Security and Nutrition (HLPE-FSN) released, at the 50th Plenary session, its 17th report called Data collection and analysis tools for food security and nutrition.
In the context of well-known widespread malnutrition, the current data and information systems, although sufficient to depict a failure of food systems, are not adequately shaped to influence the actions of all agents accounting for the management and functioning of food systems. The report investigates the weaknesses of existing data and analysis tools to address them to better contribute to more sustainable, healthy and nutritious food systems. It also touches upon new and emerging technologies to enhance food security and nutrition (FSN) data and analysis as well as considerations about data governance and data ownership.
“Data must be at the centre to diagnose and inform the food system transformations so urgently needed for FSN and for the planet.” – The High-Level Panel of Experts on Food Security and Nutrition.
An era of rapid data production and dissemination exhibiting flaws
Nowadays, data and information are profusely produced and rapidly circulated. It is largely acknowledged that sound decisions require appropriate information and data. However, tools, data collection and analysis skills are unequally allocated, especially in low- and lower-middle-income countries that lack sustainable data systems and related capacities. Therefore, there is a critical need to generalise the access to disaggregated, granular data at subnational and local levels.
Numerous opportunities can arise from new technologies to inform and transform food systems by guiding FSN policy and action. For example, online surveys can provide data on food consumption patterns and dietary intake, emphasised Carlo Cafiero, HLPE-FSN drafting team leader. On the other hand, new risks may emerge, and inequalities may worsen within or across nations and societies, stressed Bernard Lehman HLPE-FSN Steering Committee Chairperson. Digital technologies may be costly to implement, and inappropriate where internet connection is poor. Thus, advocating for necessary, accessible, affordable strategies is paramount.
Despite many FSN-relevant data, such as FAOSTAT food and agriculture data, FISHSTAT, or AQUASTAT, in some cases, gaps, inaccuracies, and outdated data prevent in-depth analysis. For instance, technical measures issued from ground-based stations, such as humidity and solar radiation, are not considered concerning meteorological data. Again, in the last decade, 92 countries have not performed an agricultural census which generates issues in updating and refining food and agriculture policies.
Additionally, in a context in which data are produced in high quantity and frequency, confusion and misunderstandings may emanate. As such, the resulting data may inadvertently trigger the proliferation of disparate indicators, data-collection initiatives and data quality assurance and, as a consequence, be counterproductive if coordination and harmonisation are lacking.
Calling for increasing multi-level coordination
A lack of coordination between various agencies that produce and analyse FSN-relevant data may lead to costly duplication of efforts, redundancy and inconsistency.
One of the prominent actions to foster coordination is the share of data. The HLPE-FSN acknowledged that data must be categorised as public goods and the restriction of data must only apply when protecting fundamental human rights.
International organisations must endeavour to harmonise and coordinate the release of datasets, stated Carlo Cafiero.
Drawing up a common language will ensure transparency, reproducibility, accessibility, and comparability. Notwithstanding, the use of the data may necessitate the need for data literacy.
Fostering the appropriate use of data
Throughout the data cycle, many stakeholders deal with the data. They should adequately parse the data. If not, they will ineluctably thwart the outcomes and may even mislead actions, particularly in low-resource countries. As policymakers make decisions that depend on the results of data analysis, they also need to be informed about the existence and relevance of the data because they are redundantly unaware of it. Policymakers also urgently need this knowledge, Bernard Lehman noted. The HLPE-FSN also recommends the dissemination of a sufficient minimum understanding of modern statistics and data science at all levels, such as by incorporating these subjects in school and academic curricula. In this light, the FAO proposes training in this sector.
Takeaways
- High-quality data, combined with its accurate, and timely parsing are substantial to shaping, monitoring, and assessing effective policies.
- Ascertaining the purpose of the data before collecting is essential. Harmonisation of data models is crucial to provide relevant knowledge for everyone.
- Existing data must be better tapped through a share at a larger scale and deeper analysis, by both public and private institutions at all levels, bearing in mind new risks.
- UN System organisations and donors reflect on the implementation of a fund for governments and other stakeholders to receive the financial resources to frame FSN data plans. Hence data could be used to spur effective, inclusive, evidence-informed decision-making.
Written by David Mingasson, SIANI reporter.