Data collection and analysis tools for food security and nutrition

partnerships, and ensure coordination on 
these under-covered areas at the national and 
international levels.
PARTNERSHIP AGREEMENTS TO 
MANAGE AND SHARE DIGITAL DATA
The development and adoption of data-driven 
technologies have the potential to increase data 
availability and reduce data gaps, but governance 
mechanisms must be in place to protect the rights 
of data contributors and data users.
The spread of new data sources (satellite data, 
data from sensors, citizen-generated data, 
social media data) contributes to impressive 
improvements in data availability and timeliness 
and will likely have important implications for 
FSN (Weersink 
et al., 2018). For example, the 
higher amount of nutrition-related data available 
to consumers can help them to make better 
decisions. However, more FSN data does not 
translate automatically in improved data systems 
and there are risks involved in the operation of 
new data sources and technologies. For instance, 
the transfer of consumer data to the private 
corporations that provide digital technologies 
raises concerns about data ownership, data 
protection and consumers agency. Thus, data 
governance frameworks must account for the new 
challenges posed by data-driven technologies to 
balance their positive and negative impacts on 
FSN and on all stakeholders (Deichmann, Goyal 
and Mishra, 2016).
Digital data and data technologies entail complex 
governance challenges. Digital data can be in 
multiple places at the same time, making control 
over data very complex. Governance mechanisms 
implemented in some countries have shown 
limited effectiveness because data providers can 
easily relocate to countries with more flexible 
regulation (World Bank, 2021). Therefore, global 
agreements are necessary to effectively govern 
digital data.

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101 
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Italy, 15 October 2018, FAO Headquarters – CFS annual Plenary.
©IFAD/Daniele Bianchi

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102 
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DATA COLLECTION AND ANALYSIS TOOLS FOR FOOD SECURITY AND NUTRITION
O
ne overarching conclusion from all the 
discussion in the report is that
we live in 
a world where data and information are 
generated and flow with unprecedented volume 
and speed
. Much more data and information 
potentially relevant for FSN is being generated 
today 
outside the traditional, official domains 
of data and statistics.
As such,
the number 
of actors who play an important role in this 
has increased substantially
.
Use of data and 
information to reach effective, evidence-informed 
decisions, involves a distributed process, 
including
both public actors
(such as national 
governments and international multilateral 
organizations in the UN System) and 
private 
actors 
(from large multinational corporations 
to small farmers and other actors in food 
value chains, to NGOs and representatives of 
consumers and citizens throughout the world). 
The recommendations set forth in this report 
constitute a call to action on the part of all these 
actors, which, if followed, may prove useful 
in moving towards more effective, evidence-
informed decisions that will make food systems 
more sustainable and ensure food security 
and better nutrition for all, particularly for the 
billions of people throughout the world who 
still experience hunger and various forms of 
malnutrition.
Many of the messages in this report will not be 
new. The importance of data and evidence-based 
decision-making to transform food systems 
has been widely published and reviewed (World 
Bank, 2021). The 2014 Global Nutrition Report 
(GNR) called for a Nutrition Data Revolution 
(International Food Policy Research Institute 
[IFPRI], 2014), and many subsequent efforts 
have drawn attention to both the challenges 
and the emerging efforts to address them (see, 
for example, Piwoz 
et al., 2019). Indeed, several 
of the challenges across the data cycle were 
effectively highlighted, and solutions proposed, 
in the 2021 United Nations World Data Forum.
34
Ample literature has also stressed the essential 
role of sustained investment in the financial and 
human capacity needed to accompany the data 
revolution.
35
Despite this recognition and prior efforts, the 
generation and use of data for advancing FSN 
remains woefully inadequate. For example, 
while the effects of the COVID-19 pandemic 
34 For more information, see
 https://unstats.un.org/unsd/
undataforum/blog/promoting-data-use-a-key-challenge-for-
statisticians/
.
35 See for example this initiative from the Strategy for Agricultural 
Transformation in Africa 2016-2025: Invest in country level systems 
and data to support Climate-Smart Agriculture practices and 
agriculture sector resilience; develop the acquisition, application and 
management of big data for resilience decision tools and services; 
invest in country-level infrastructure and training for meeting CSA 
targets, monitoring GHG emissions and supporting innovation; 
support the design and development of agriculture climate risk tools 
and products. (African Development Bank, 2016, p. 20).

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have been modelled (FAO