Ensuring Quality SDG Measurement for all 17 SDG Goals (Part 1)
December 11, 2018
Every single one of the 17 Sustainable Development Goals represents an urgent need on a global scale. With those needs are opportunities for innovative solutions and along with each solution, a need for proper SDG measurement and reporting.
In this blog, we’ll look at half of the 17 goals (the rest will be in part 2) from the perspective of our team of impact management experts in order to explore the SDG impact measurement and data context of each goal.
Let’s take a step back and understand what the SDGs are, as well as the reason why the United Nations created them. During a summit of world leaders in 2015, the world at large agreed to build upon the Millennium Development Goals and set forth a sustainable agenda to achieve by the year 2030.
The 17 goals (which we have listed further below) define the path to achieve this ambitious agenda and are a truly global call to action.
We’ve covered the importance of impact measurement in other blogs, and those reasons also pertain to the SDGs as well. If your organization uses SDG alignment to define strategy, proper tracking enables you to make better strategic decisions.
Furthermore, if countries, cities, and private sector players implement good impact data management techniques not only are we able to evaluate progress, but we are also able to allocate capital with more clarity about the impact “risk” of those investments.
As we dive into each SDG, the importance of measurement and management will become even more evident.
The purpose here is not to define the Goals (see the links in each Goal title for more info on the goal itself) but to explore the nuances of impact measurement and data management for each.
In an absolute sense, it sounds good to increase how much money a person lives on a day, raise the number of people with access to basic goods and services, and to design policies to help achieve those objectives.
Where there needs to be more oversight and deeper assessment is in the outcome of those achievements for the individuals involved.
If 80% of people worldwide have access to basic goods and services, that’s a start. But if we’re simply providing access to extremely low quality goods and services we’re not improving lives substantially. Assessing how those benchmarks are improving lives (or not doing so) is an essential step to truly ending poverty.
Some studies suggest that there is enough food production, just not the right logistics in place globally to get food to everyone on the planet. So while we do need to measure how many people don’t have food, malnutrition rates, etc., we also need better data management.
From local farmers and community leaders, to national policy makers and international aid organizations, being able to access real time data and collaborate for decision-making based on those data could be the difference between a world where hunger exists and a world where no one goes hungry.
Reducing disease and mortality rates has a clear positive impact on the lives of those most often affected.
From an impact measurement perspective, what will always remain difficult is being able to confidently assign a causative relationship between those reductions and the intervention(s) that took place.
For example, one of the SDG 3 targets seeks to improve prevention and treatment of substance abuse, and suggests measuring per capita abuse of the substances like alcohol. Because the causes of this issue are so widespread, the style of interventions and efficacy are also going to vary.
Quality impact evidence for this goal must go beyond tracking reduction in per capita instances to include data which helps us understand which interventions are working, and in what context, so they we can replicate on a larger scale if possible.
Arguably one of the most important goals, especially as it relates to breaking cycles of poverty, one of the key impact measurement issues here is the theme of metrics language.
When we talk about “quality” what exactly do we mean? Is it the same in every country? Is it changing as learning systems evolve?
Metrics must remain relevant to region and while we don’t need to have the exact same definitions, we do need to know if and how definitions of quality education differ across regions as well as the ability to still compare data on education from those different contexts.
Gender gaps in terms of access to resources, equality of opportunity, etc. exist even in the most developed countries. The difficulty in assessing how well we’re doing, beyond an equalizing in gender percentages across impact areas, is determining which interventions were primary causes of positive changes and how enduring those changes really are.
This is a systemic issue bound by history and culture so when we talk about measuring the impact of initiatives directed towards gender equality, we need to first understand what the leverage points are in our systems so that the data allows us to clearly see how much (or how little) we are shifting those forces that maintain this status quo.
There’s a logistics issue here, ensuring access to clean water, as well as a resource management issue, keeping water sources clean and not overused.
Impact measurement for Goal 6 is a balancing act between the assessment of access and how well we’re doing in keeping our water systems healthy.
The latter means measuring and mitigating the externalities of our other activities (e.g. energy production), which further points to the measurement complexity and the importance of holistic measurement systems.
The impact measurement picture is quite clear for this goal. Are we able to produce energy in a renewable way in more and more places? Do people have access to this energy? How much are we investing, and is that investing yielding a return?
A more interesting, and just as important assessment, is the continued investigation of how clean energy stacks up against other forms (i.e. fossil fuel based). Comparing how well we can deliver clean energy to the world and its benefits-to-risk ratio compared to traditional forms, will help policy makers and capital movers make better decisions.
The most essential piece of this Goal is that it makes it clear that growth for growth’s sake is not the objective.
Growth is important but so is how we grow. Fast growing countries like Ethiopia have the opportunity to capitalize on economic growth and to do so in a sustainable way. How do we incentivize that?
One way is through measuring and demonstrating that sustainable development means even more economic success in the long run, especially because it helps infuse resilience into urban and country infrastructure.
In part 2, we’ll explore the rest of the 17 Sustainable Development Goals from our perspective as impact data experts to help you better understand how we might achieve quality SDG measurement. For now, if you want to dive deeper into the data on targets and indicators provided by the United Nations, click here.
And if we’ve piqued your interest about our cloud-based solutions to impact data management, we’d be happy to talk with you about these tools, whether you are seeking to align with the SDGs or simply manage your impact data in a more efficient and effective way.
Topics: SDG Indicators
Alan is a social sector consultant and one of the founding directors of Quantica Education, a school of social entrepreneurship in Colombia.