An attendant enters vaccination data on a computer at a clinic in Nairobi, Kenya.
An attendant enters vaccination data on a computer at a clinic in Nairobi, Kenya. Photo by Elphas Ngugi.

Data are the lifeblood of decision-making and the raw material for accountability. Without high-quality data providing the right information on the right things at the right time; designing, monitoring and evaluating effective policies becomes almost impossible.” 

  - A World That Counts, 2014

These words still resonate almost seven years after the UN’s landmark report, A World That Counts. Harnessing the data revolution for sustainable development has always put using data at the center. Yet, in practice, the development community has placed much greater emphasis on the early steps in the data value chain, focusing more on collection and publication of data than its usage. This is understandable. After all, patchy, unreliable, and inaccessible data can’t be used effectively. But the last few years have demonstrated that access to high-quality data does not guarantee its use. 

Why access to good data doesn’t guarantee better development outcomes

Despite increasing amounts of available data, data-driven decision making is still not the norm for many organizations. More often, use of data by organizations remains scattered and doesn’t translate into evidence-based policies or decisions. 

Studies on barriers to effective data use generally distinguish a few broad categories: 

  • Barriers linked to the data themselves - data accessibility, quality and appropriateness.
  • Barriers related to stakeholders’ skills, capacity and incentives to use data, as who is using the data also matters. 
  • Barriers concerning institutional and organizational resistance or lack of data culture.

Other barriers include: political economy considerations; a lack of funding; infrastructural barriers; or situations of conflicts within countries. 

Among low and middle income countries in particular, significant barriers exist due to limited access to data and a lack of organisational incentives and political will to use data. For instance, in countries where political and academic freedom is limited there is less space for using data for policy making purposes as policy outcomes are generally not challenged. Furthermore, many low income countries face major problems with accountability, participation, corruption and lack of political incentives to draw in evidence in policy implementation.

Likewise, there are factors that enable the effective use of data. Research shows that good data governance and infrastructure, organizational strategies that foster data use and the presence of feedback loops, lowering cost of data acquisition and high quality interactions among data users and producers--with clear incentives for both--all enable sustained data use. Partnerships and coalitions of stakeholders along the data value chain can also enhance the resilience of data practices and embed data use in everyday activities and strategies. 

The questions we’re asking on how to harness data for development

These themes of data use, barriers and enablers are our starting point for exploring pathways leading to sustained data use for development. Here at the Data Values Project our third track of action is focusing on data that delivers sustainable and equitable development.

Building on the diverse knowledge and experiences of the Global Partnership for Sustainable Development Data’s Technical Advisory Group, we are exploring pathways to sustained usage of data for development and identifying ways in which our collective advocacy can drive change. Particularly, we are looking to leverage collective knowledge and experience on the incentives and demand structures that drive sustained data use. We will explore models for scaling and institutionalizing these practices in public and private sectors and in civil society.

The initial phases of this track of action are focusing on four key questions:

  1. What incentives contribute to sustained data use by different stakeholders, and how should such incentives be structured?
  2. How can we foster increased and sustained demand for data from prospective users?
  3. How do choices related to infrastructure, tools and methods affect potential for sustained data use?
  4. How can we  harness local solutions that address local data users’ needs, specifically by examining measures to mitigate digital and data colonialism?

The Data Values Project will gather input from the data for development community on these questions to build a knowledge base of examples, evidence and best practices concerning sustained data use for development. We invite you to join the discussion,  participate in the track’s events and share examples, research or analysis that responds to the four questions we plan to tackle via our email datavalues@data4sdgs.org

Deepa Karthykeyan is the Founder and Managing Director of Athena Infonomics. Grant Cameron is Director of the Sustainable Development Solutions Network - TReNDS. Deepa and Grant co-lead the Data Values Project track on 'Data that powers sustainable and equitable development.

GPSDD’s Jenna Slotin and Martina Barbero provided input into this blog.