In my role as the Head of Exploration, my job is to continuously search for emerging, under-the-radar, and unique solutions. Explorers working for the Labs — like myself — are expected to use methodologies such as horizon scanning, scenario planning or systems thinking, as well as look into alternative sources to gather data and market intelligence tools. Such tasks help us provide UNDP with an understanding of how global trends and cutting edge issues might potentially affect current policy and practices in the near future.
Let me walk you through how this is done in practice through a real-life example from our work at UNDP Colombia’s Accelerator Lab. In Colombia, we have chosen to focus our work on vulnerable populations, because in our country there are many developmental gaps — what we call “hotspots” — in terms of poverty, migration, gender inequality, violence.
With our challenge defined, I set out on exploring how best to address migration. But how does one go about that? For me, exploring means taking a complex challenge like migration and approaching it in an open-ended way. It includes researching all related data and understanding how other countries have addressed this issue, so that we at the Accelerator Labs can apply what works to Colombia. Our theory of change is that, if we thoroughly understand a hotspot such as migration, we might be able to manage its effects and transform it into a development opportunity.
How does “exploration” work?
We start with desk research, identifying relevant case studies, stakeholders and potential new data sources. The desk research helps us to identify patterns, unforeseen opportunities and collect under-the-radar insights around how to address a broad topic like migration. Some of these insights might not be obvious at first glance, or may run counterintuitive to our common understanding.
For example, in my exploration, I found that the most recurrent strategies are humanitarian and economic inclusion responses (providing access to basic services, shelter, employment, skills training, entrepreneurship programmes), perhaps because these issues are the easiest to observe and address for most programme specialists. But a counterintuitive insight may be that migration challenges also relate to migrants’ motivations and behaviors — for example, the desire of a migrant to feel free, to be recognized and to be culturally understood in a new country.
Additionally, mapping out case studies helps us to broaden our solutions spectrum by giving us new ideas on how to tackle migration using new technologies, changing narratives, and gathering unconventional data like emotional analysis from social media scraping.
On the one hand, the systemic thinking approach aims to provide learnings about the patterns, relations and mental models that exist within migration as a system. Migration is usually seen as a process of adaptation, but what happens if we start seeing it as a person’s right to freely choose to stay home or migrate to a new place of residence?
In this way, we analyze migration not just from diverse angles — political, social, economic and so on — but also from the viewpoints of diverse observers — urbanists, ethnographers, public officers, lawyers, migrants, host communities and development actors. This brings inclusivity to our insights but also adds value by bringing in new learnings and untraditional ways of thinking that we have not necessarily seen before.
At the same time, foresight exercises create possible futures starting with the identification of current trends or disruptive events that are related to migration and the exploration of direct and indirect implications of these events. For example, a global trend is that migration caused by climate change might be one of the biggest reasons why humans migrate in the near future. So, having a forward-thinking mindset can allow decision makers to take accurate actions in the present to positively affect future outcomes.
As you can see, we employ these various methods to be able to explore an emerging issue from multiple angles, which lead us to new — and often unexpected — findings.
Beyond exploration: Completing our learning cycle
So what happens once the exploration phase is over? We combine the insights obtained from the research and systemic/foresight methods with the insights we get from the grassroot innovations mapped out by solutions mappers. For example, one of the recent insights we had is that it’s easier for migrants to establish themselves in a new country when they have an existing social network in Colombia rather than when they come by themselves, as that first contact allows them to navigate the territory and public services. Another insight is that migrants are being absorbed by the informal economy in Colombia. However, we identified that this insertion is more difficult for those migrants coming from the formal or public sector in Venezuela than for those with an entrepreneurial or informal background.
Once we have our insights from the sensing and exploring phases, we transform our findings into a hypothesis, which then become the basis of a portfolio of experiments to be tested hand in hand with UNDP’s country office and partners. For example, we recently conducted an experiment called “Augmented Development”. With this experiment we set out to identify and measure biases towards “otherness.” More specifically, our first measure was looking at the biases of urban populations towards left-behind hotspots and their inhabitants served by UNDP projects. In this augmented reality experience, each participant had access to 10 pictures, each one part of relevant UNDP initiatives. When a mobile device with the app was pointed at the photograph, a video popped up, telling the human story behind the project. Our aim is to run the experiment in other regions of Colombia and other targeted groups, to collect results and create new knowledge about behavioral science, the use of technology and reducing mental gaps as a path to reduce development gaps. Running experiments such as “Augmented Development” allows us and our partners to succeed or fail fast and learn to scale multiple and integrated solutions in parallel from a systemic point-of-view.
Our learning journey has just started, so stay tuned to see the results that will follow.