Reports year after year tell us that we are far behind schedule on achieving the 17 Sustainable Development Goals set forth by the UN some years ago.
Reaching our objectives by the year 2030 was always an ambitious endeavor but the fact that we’re not on pace doesn’t mean we should stop.
What we need as we move forward is SDG measurement that doesn’t simply tell us we’re getting closer or farther from achieving the Goals.
Moving Beyond SDG Targets And Indicators
We need deeper assessments, focusing on outcomes, which can help policy makers, business leaders, and other impact sector actors understand which interventions are working and why, so that together we can begin to explore how to scale them.
In part 1 of this blog, we took an impact measurement and management approach in exploring the first 8 SDGs, breaking down each particular goal from that lens.
In Part 2, we’ll do the same for the other half of the SDGs, many of which are a bit more broad and more complicated to tackle from an impact metrics perspective.
The UN Sustainable Development Goals 9 to 17
Countries both rich and poor, new and old, are called upon to develop policies, collaborate, and integrate the overall strategic vision of the SDGs into their national agendas.
Data management from the ground up and top down needs to be seamless, efficient, and accessible to players at all levels. Reporting should be frequent and relevant. Data should empower decision-making not slow it down.
These are just a few of the important data themes which pertain to all the SDGs. Let’s dive a bit deeper into how they materialize in SDGs 9 through 17.
There is a clear place-based component to Goal 9. Smaller countries in particular have defined “industry” to a few specific areas. So when we measure progress towards Goal 9 we need to cognizant of these regional tendencies and assess to what extent and how fast diversification of industry can benefit these smaller economies.
When examining proportion of population with access to information (and mobile coverage), it’s also necessary to assess how such technology is being optimized so that the positive outcomes can be derived from greater per capita access to information.
Two issues stand out when we look at the targets for this goal. First, improving the income of the bottom 40% of national populations is in theory a positive thing.
Measurement programs should take into account, however, where that income comes from. For example, if it is being generated in the informal economy, that kind of progress might not sustainable.
Secondly, if we zero in on the push for better migration policies we see a clear opportunity to improve how we use data and data technology to make these often invisible populations more visible. For example, internally displaced refugees are frequently overlooked (the UN calls them some of the “most vulnerable people in the world”) and without accurate, real-time numbers about location, conditions, needs, etc., it remains extremely difficult to develop programs and policies to support them.
You can see our blog on this goal for a deeper look at its importance, but what is worth mentioning here is exploring the ways we might link data on green spaces, more efficient (and sustainable) transport, etc., to improved outcomes in quality of life across the spectrum of urban dwellers.
Discovering such correlations requires buy-in from local organizations working to implement such initiatives, and doing so (assuming the results are positive) could potentially help these leaders acquire funding for further initiatives and also spur innovation in other parts of the world which have been slower to adopt such strategies.
How might we incentivize markets to adopt practices towards a more circular economy? This is one of the essential design questions we see as an opportunity to tackle Goal 12.
From a data management and measurement perspective, we could begin by working with private sector leaders to better understand the relationship between dollars invested and social value returned. An SROI approach is a good place to start.
Bringing seasoned impact investors into the equation could also support an easier (and more profitable) transition, as they are well acquainted with the balancing of impact and financial returns.
Whether we hear reports of CO2 emissions still rising, or calls from scientists getting more and more urgent, the pressing nature of this issue still seems detached from our day-to-day response as a global community.
Impact evidence must be more strongly delivered to the general public in ways that are relatable to the context of that public. In other words, how we conduct social impact reporting can and should be delivered more strategically, making data more accessible, more easily understood, and with clearer calls to action to specific audiences.
Of course, the climate issue is much bigger and more complex than any impact report could ever address, but this is one area where we see room for improvement from a data perspective.
Again, we’re more interested in tracking the outcomes produced from targets such as “reduce marine pollution of all kinds.” Achieving this target would imply positive implications for the marine ecosystem, but to what extent?
The difference between indicators and outcomes is important here.
Because if there are other forms of environmental destruction in marine areas we need to take those into account, as well what is happening to those substances which were previously polluting this environment. Where are they now?
Impact evidence holds the potential to drive economic decisions if it is properly leveraged (and is credible evidence). Clearly linking how improving biodiversity, increasing reforestation practices, or the betterment of degraded soil with the socioeconomic benefits of each practice is one of the ways we can spur more action in these areas.
Being able to communicate the benefits to local communities will enable greater buy-in (the trade-off must make sense to them). Giving policy makers and investors access to those data can also help capital flow more confidently into these areas.
Peace is often the outcome of better outcomes across other SDG areas. Reduce poverty and you reduce conflict. Improve education and job rates, you reduce conflict. Increase resilience in the face of disasters, you reduce conflict.
So measuring progress towards peace can be measured along those impact areas, as long as we have clear correlations in our data which suggest one does indeed lead to the other.
When conflict disrupts economic systems, data on the economic impacts of that conflict can perhaps be more clearly and quickly delineated.
We’ve also covered this immensely important, and overlooked, Goal in one of our blogs. What we’ll highlight again here is not only the need for free information flow within and across national borders, but also the tools to enable that flow.
With internet connectivity reaching new highs every year, cloud-based solutions like the ones we’ve developed give community members and national leaders alike the platforms needed to help us all as a global community collaborate successfully for a brighter future.
To see how we can help you tackle SDG-alignment on any Goal, or to simply reach your impact objectives using tools designed to do just that, click the button below to schedule a chat with our team of impact data experts.
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