Why data literacy is important in the aid sector

16 July 2021

The humanitarian and development sectors amass more data than ever. This has naturally led over the past few years to an increasing focus on the role that data plays within aid organisations, at HQ and in the field. In the sector, like in other sectors of activity, information managers (IM) have up to now always been the sole people whose main responsibilities revolve around data management.

The data revolution of the 2010s has profoundly changed the way emergency response and development activities are handled, making it crucial to foster a “data ready” working environment where leaders and decision makers, colleagues and staff are all familiar with data. Whether it is acknowledged or not, making sense of data is no longer the prerogative of IM/data officers, as almost all humanitarian and development practitioners have become “data people” (Centre for HumData, 2019).

As a result, many humanitarian and development organisations are focusing on how to improve data literacy without always knowing both how it will help them improve their practices and the type of investment in the topic they should be considering. In a series of blog posts, this new Resource Portal, initiated by CartONG, will put a spotlight on the concept, sharing resources and expertise, and serving as guiding principles for organisations embarking on this journey.

So, what’s data literacy?

There are various definitions of data literacy and ongoing debates about these definitions. In this blogpost, I will focus on Bhargava and D’Ignazio’s definition which describes data literacy as “the ability to read, work with and analyze, argue with data”.

  • Reading data involves understanding what data is, and what aspects of the world it represents.
  • Working with data involves creating, acquiring, cleaning, and managing it.
  • Analysing data involves filtering, sorting, aggregating, comparing, and performing other such analytic operations on it.
  • Arguing/communicating with data involves using data to support a larger narrative intended to communicate some message to a particular audience.

 

Illustration by CartONG, adapted from VENNGAGE, Lydia Hooper

The first thing that comes to mind when thinking about data is usually numbers and spreadsheets, or to be more precise, quantitative data. However, data driven does not equal numbers driven! It is important to note that qualitative information is also data, and requires the same rigorous attention as numbers do. In the sector, we use text and collect various types of documents that do not have a quantitative focus, such as surveys with free form text, reports from observations, interviews or focus groups, which should be used in their own right to gain insights and meaning. It then becomes clear that when referring to data literacy, we are including the whole scope of data we consume and produce on an everyday basis.

The 2020 CartONG study on practices and needs of francophone Civil Society Organisations (CSOs) identified the lack of data literacy as one of the six main issues of humanitarian and development organisations in terms of information management practices. In such a “data driven world”, it is critical for everyone in an organisation to have the ability to read, work, analyse and use data to a certain extent.

Illustration from, “Program Data: The Silver Bullet Of The Humanitarian And Development Sectors? Study”, CartONG

Within the sector, data-oriented professionals engage in all data activities including data collection, analysis, development of data products, quality assessments, and communicating with data through visualisations and narratives. Obviously, the level of data literacy necessary for such a profile differs from the one required for non-technical roles such as programme managers. The extent of the skills will thus vary from role to role but they remain vital nonetheless (to explore this in more detail, feel free to refer to the “HR Pack – Program data management for Humanitarian Aid and International Development CSOs”). In order to minimise information barriers, ineffective communication and uneven knowledge between technical/data oriented and non-technical roles, it is crucial for everyone in the humanitarian sector to become data literate to a certain degree (“Information as a Second Language: Enabling Data Literacy for Digital Society”, 2018). As a result, organisations should focus on cultivating a data culture by building capacity for the diverse roles in contact with data. The Centre for Humanitarian Data 2019 survey analysis suggests that broadening the understanding of “data activities” may strengthen data cultures and investment in data workflows within teams. As such, NGOs, International Organisations, consortia and networks of actors should use data as a vector for the different teams to understand each other and speak a common data language.

What makes it essential?

In a way, data literacy can be seen as one of the most important new skills of this century, just as  “literacy” was key in the previous one (Venture Beat, 2014). As shown in the UN data strategy, the use of data is an essential competency for all organisational roles and contributes to promoting a data-driven culture. Having seised the challenge, major organisations such as the Centre for Humanitarian Data, UN OCHA, the ICRC, and the IFRC, to name a few, are all developing strategies to train collaborators to harness the power of the increasingly abundant flow of information rather than being overwhelmed by it. Indeed, data literacy calls for an organisational culture change: creating an environment where data is analysed, criticised, deconstructed,  understood, and ultimately used to design relevant responses that advance our mission. Because making operational decisions from poor quality data, or, worse, from inaccurate interpretations of otherwise reliable data, can truly have a negative impact on our activities. Let’s have a further look at why data literacy should play such an integral role in an organisation.

#1 Data literacy as key to a “do no harm” approach

Data can be a very positive force, but it is so powerful it can also reinforce discrimation, widen inequality and even be weaponised (Weapons of Math Destruction). Let's be honest, line graphs, bar charts, maps and our “famous program dashboards” have become key to communicating vital information about humanitarian activities. In other words, working with data about crisis-affected people, can promote our ideological work, prioritise certain points of views and conceal others, or perpetuate existing power relations. We usually put so much trust in data, without acknowledging that “numbers aren’t neutral, facts come from somewhere, loaded with history, with freight” (Data responsibility starts with you, Ben Parker). 

As humans are intrinsically biased, sometimes against their better judgments, it makes it difficult to avoid the pitfalls of “selection bias” of information. Ethical issues can therefore arise when people decide to ignore or misinterpret the results of collected data in order to support a specific perception. Data literacy training can help teams understand data, learn how to challenge what it says, identify personal interpretability biases, and how to address ethical issues related to data. This is then how data can really be transformed into information upon  which the organisation can build its programmatic orientations.

Another way of putting it is to question whether organisations can really respect their values and principles (such as the “do no harm” approach) if they don’t speak the data language (data literate)? They need to confront themselves with the topic at all levels of their organisation -and also in relation to external stakeholders - to ensure that no digital harm occurs. It is not the unique ingredient in the recipe and not everyone needs to be a data expert, however, people should just have enough data skills to help them do their work well.

#2 Data literacy helps increase collaboration between teams

Secondly, “Data is a team sport” (School of Data). Data literacy helps increase collaboration and understanding across different teams. Data and IM staff should not be the only data literate people within the organisation, nor should they be solely responsible for the collection and analysis of all their organisation’s data. Rather, aid actors should strive to cultivate a data culture. This should be done by creating environments in which people are more valued than data, working together to use data as a vector for operational efficiency and to better communicate on the impact of their work. This is a great way to help people in their different roles contribute to the access and use of data.

In terms of data literacy, each person in an organisation has a responsibility to contribute and play their role. Each position will have a view of the organisation that can provide context that enriches organisational data’s meaning and value. For instance, senior managers must understand and engage with data in order to draw conclusions, and communicate ideas for strategic decisions. Data and information managers make data accessible, and provide advice to colleagues and senior management on targeted products for data sharing and communication. Programme teams are key to pinpoint the important elements to consider or explore or to understand the thematic implications behind the figures.

 

Illustration and summary from CartONG and derived from, “Results and analysis for the UNOCHA Centre for Humanitarian Data’s broad-based data literacy survey”,
The Centre for Humanitarian Data 

Building data literacy helps connect the dots between all these different teams on a day-to-day basis.

#3 Data literacy increases accountability and transparency within an organisation

Thirdly, taking the time to invest in data literacy increases accountability and transparency. When the data is only accessible, understood or used by a handful of people, it remains in silos - non data oriented people sometimes just become afraid to ask questions - leading to possible misrepresentations and biases. Data is more powerful when accessible to all!

Data literacy empowers staff to ask the right questions, speak a common data language, and hold everyone accountable (starting with themselves). In data literate cultures, curiosity is fostered and staff have a desire to understand something from all angles. For example, when data is presented as evidence for a particular decision, staff will have the ability to question:  Why was it collected in the first place? Are the sources reliable? Is the analysis correct? What are the potential biases? What further evidence will we need in order to act? It also encourages openness, eliminates bottlenecks, and sheds a light on everyone’s contribution to the goals of the organisation. This kind of visibility paves the way for a more reflection-driven culture within an organisation.

#4 Data literacy improves organisational performance and efficiency  

Staff that lack data literacy skills don’t perform at the same level as those who use data confidently in their roles. Not only can people within the organisation make decisions based on facts, but teams will also be able to uncover new insights and opportunities. By increasing data literacy in all levels within an organisation, everyone, from the HQ to country level teams, can better understand why challenges arise, manage them more efficiently and hopefully spot them before they turn into problems. 

Furthermore, both technical and non-technical staff will be more confident to engage in conversations involving data. Teams or individuals in the sector will be better able to advocate data activities, explain why the data is important and how it contributes to creating value for people served or activities implemented.

The more data literate an organisation, the more value the organisation is able to derive from its data. Implementing a data literacy initiative helps build trust in data tools and their results, and increases the comfort staff have using those tools and data in general. Becoming data literate will provide staff the necessary capabilities and change of mindset, for example, before a team decides to initiate another household survey and develop a new platform for the collected data, they will have the ability to assess data needs, leverage existing datasets and solutions, and only collect what is relevant for a particular activity or operational context. 

Data literacy is a prerequisite for a data driven culture. Organisations can start taking steps toward creating a data literate organisation by focusing more on the people and skills rather than tools and systems. Helping teams collectively change their behaviors and beliefs, encouraging the use of data not just for data’s sake but to make better decisions, improve activities.

#5 Data literacy helps your staff grow, a win for both individuals and organisations

Humanitarian and development organisations should consider data upskilling as it could help staff improve the use of data and could add a new bow to their arc in their activities. To improve an organisation's data literacy, every member needs to develop some level of data skills. Thus, to make the best out of different tools and large amounts of data collected within the sector, non-technical staff are expected to acquire new skills (Datapack UNOCHA Centre for Humanitarian Data).

Data literacy training can help both the senior management, data and information managers acquire soft skills that can help invest in capacity building initiatives which, in turn, help other teams realise the full value of data through collaboration, critical thinking, curiosity and data storytelling. Organisations need a broader view of data competences. Those who understand the nature of data systems/tools and how they work, how to create sound data governance, protection policies, security, and trust. Consequently, new skill sets are also emerging, such as  “data translators”, due to the need for intermediary roles (Open Data Institute, 2020). As data becomes a critical component of humanitarian and development work, professionals in the sector will have the capacity not only to understand how to challenge and engage with the “data translators”, not just assume system decisions are always right.

Through data literacy programmes, organisations such as IFRC (with its Data Playbook) or UN OCHA’s Centre for Humanitarian data can make data competency, experience, training and stewardship part of all organisational roles and promote a data-driven culture within the sector.

Conclusion

The humanitarian and development sector collects and generates large amounts of data. However, some of this data still has untapped potential, while a lot of the data actually collected is more than what is really needed. To avoid these situations, it is critical that aid practitioners have the capacity to read, work and interpret data, to derive relevant insights and make informed decisions.

Organisations should also invest in building a data-driven culture by implementing training strategies for their staff from the junior to senior levels. Improving data literacy will create a more empowered team that can serve communities through effective activities. Our next blog post will highlight the various existing resources focused on building data literacy skills.

 

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 This publication is supported by the French Development Agency (AFD). Nevertheless, the ideas and opinions presented on this post do not necessarily represent those of the AFD.