In the race to eradicate polio, achieving 99 percent reduction isn’t enough. Reaching the last, often remote, kilometer can determine national success or failure. Likewise, for the 193 countries striving for the Sustainable Development Goals, leaving no one behind requires new attention to subnational actors, local data ecosystems, and digital tools that transform data into meaningful insights. So how can technology support data use by government actors — and not just feed reporting systems?
The evolution of country-led aid information management systems offers important lessons for putting technology to work in the SDG era. “Ten years ago, we used to track aid data using Excel workbooks, and this proved daunting,” noted Tiyamika Kanthambi of Malawi’s ministry of finance. The need to track development inputs, such as financial and technical assistance, led Malawi and other partner governments to adopt AIMS. As countries strengthened their management of this information, decision-makers began exploring the next frontier: Relationships between financial investments and outcomes — such as student learning, food security, and disease prevalence — and impacts, or noticeable improvements in people’s lives
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“Going forward, we plan to use [AIMS] to aid evidence-based policy decisions,” shared Kanthambi. “Communities want to know more about projects being implemented in their areas and the impact of investments. Next we are working to link financial data to results.”
As governments seek to localize the SDGs, the use of digital tools to track development inputs, at the local and national levels, provides a solid foundation on which to tackle this next frontier.
So what lessons from the past decade of digital development can we use to support the next phase of using technology and data to achieve sustainable impact?
1. Kill the law of averages
Tracking progress at the national level matters for global commitments: More granular, subnational data shines a light on disparities lost in data aggregates. Enabling government actors to visualize, understand and dialogue around funding and outcome inequality is a vital input to smart resource allocation. Finance ministry officials in Nepal credit subnational data and mapping with their ability to reveal stark gaps in aid flows to high poverty regions, such as the Far Western Region. This information allowed government and development partners to discuss the issues and subsequently implement course corrections. Auspiciously, some development partners are also calling for greater disaggregation of geographic, gender, disability, and age-related information in order to ensure SDG inclusivity.
2. Don’t do something new
Tools to localize SDG information should build on what has come before. Flexible approaches, and interoperability with established data and systems, are key to making all stakeholders more effective. Beyond the technology, new approaches should align with existing medium term and long term national strategies. Tanzania’s Sectoral Dashboards, for instance, are part of the Tanzania Open Data Initiative, and draw on existing government open data sources. Being aware of the total cost of ownership for systems — not just set-up costs — and designing for low budget and low bandwidth environments reduces the chance of system graveyards. Côte d’Ivoire embedded its aid management system in established bureaucratic processes, leveraging existing quarterly circulars to ensure broad system awareness from the outset.
3. Bust up old silos
On paper, each goal is distinct from the next; in practice, the goals and indicators are related elements in complex systems. Digital tools that visualize linkages and interdependencies help users understand tradeoffs and synergies. They can also help bust up old, siloed ways of solving problems and mobilize people to tackle interrelated issues. For example, childhood immunization campaigns (health) can impact school attendance (education); tools that enable both education and health experts to visualize these relationships can strengthen ministry collaboration and facilitate multi-sector problem-solving. Critically, rendering complex relationships need not compromise user-friendliness. New York City’s data dashboard, for example, renders these relationships cleanly by applying good practices in human-centered design, user experience and complex data visualization.
4. Go low tech (or no tech)
Local government actors want granular, disaggregated data to measure results — and they need tools, skills, resources and incentives to use data. But we should not assume that tech is the starting point. The latest in digital for data collection and dissemination may be less practical than paper-based systems, low-tech tools, or hybrid approaches. In Lanet Umoja, Kenya, the Open Institute worked with community members to manually collect — and later digitize — information about five priority SDGs; they also instituted a process for regular data updates. The Open Schools Kenya initiative in Kibera, while centered around a digital platform, uses physical kiosks to share paper maps with parents. Simplicity of design, phased approaches and sustainability plans are key when designing any solution.
5. The best tool is the one people use
To achieve the 2030 Agenda for Sustainable Development, we must create simple tools for adaptive management and planning, instead of retrospective reporting. Ghana’s district health information management system, DHIMS II, for example, is largely used for aggregating and reporting data vertically. Simple tools for visualizing trends across geographies, maps overlaying indicator data with financial flows, or dashboards with local trends over time would better support local-level analysis and management. Beyond the tech, democratizing technology use requires designing for the management decisions and realities at hand. But even with the ideal tools in place, staff must be incentivized and expected to use them for decision-making.
The road ahead is messy and complex, but if we iterate on what we already know, we stand to gain immense returns to scale. Country-led progress in using tools and data offers new avenues for innovation, and will push technologists to develop more agile tools grounded in local needs. As with eradicating polio, “leaving no one behind” will require high-tech and low-tech efforts, national and local ownership of solutions — and, of course, people-centered innovation.
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