Breaking the silos through participatory systems mapping: Youth employment and the future of work in Bhutan
This blog documents the collaboration between UNDP Bhutan and Dark Matter Labs in a three-month project investigating the systemic challenge of youth employment and the future of work in Bhutan. The intelligence report published by UNDP Bhutan can be found here.
Bhutan in transition
Designing a viable and sustainable employment market for its growing youth population remains a daunting challenge for Bhutan. More than half the country’s 700,000 population are under 27. The youth population is projected to bulge further in the next couple of decades. This could potentially exacerbate the already bleak labor market. Unemployment rates have remained consistently high over the past decades and peaked in 2018 at 15.7 percent. And then came the COVID-19 pandemic. The crisis brought tourism to standstill, forcing thousands of young people out of work. According to the Rapid Socio-Economic Impact Assessment on Bhutan’s Tourism Sector conducted in April 2020, the pandemic has impacted over 50,000 young people working in the tourism and hospitality sector. They made up 50 percent of the welfare applications received in 2020.
These demographic and economic shifts prompt questions about how Bhutan’s economy and society may develop in the 21st century, and within this, what the future of work would look like. The pandemic, while posing several challenges, also presented opportunities to redefine the country’s employment scenario with many educated, experienced Bhutanese diasporas returning home from abroad. Amid huge technological leaps taking place globally, there is a growing demand for new markets and business models, new jobs, the reshaping of old industries and the re-definition of work itself in Bhutan as well. Central to this is the need to unleash human potential — creating capabilities in the system for innovation, purpose, shared value creation, and the realization of new futures.
Systems approach to youth employment — a methodology for collective sensemaking
How can we think beyond job markets, and expand our understanding of the employment issue?
Too often, unemployment is viewed as a supply-demand problem, where solutions are designed to trigger job creation (increasing supply) or job training (increasing employability and fulfilling demand). But what if that is not enough? The persistence of the problem in Bhutan, and elsewhere, confirms that intervening in the job market alone does not provide a sustainable solution. The behaviour of the individual, and the social and economic environments that the labour market is embedded in — are shaped by numerous interconnected factors such as, the availability of social protection, parental influence, changing expectations, stigma of certain professions, access to digital infrastructure, and so on. The sum of their complex interdependencies we call — a system (or systems). This is how we — UNDP Bhutan and Dark Matter Labs — approached Bhutan’s youth employment issue in this 3-month project. The challenge for us was to find a methodology that would allow us to build an awareness of the systemic nature of the issue at stake, and to broaden our horizons to imagine new solutions.
How can we understand and embrace complexity?
Complexity begets complexity for wicked problems. An attempt at analyzing the intricacies of systems — the pain points, underlying drivers, risks, and numerous interconnected factors — can easily become overwhelming for one person. Moreover, if we have 10 people attempting to do the same, we will probably end up with 10 different versions of the analysis. So, how do we prevent ourselves from getting lost in this vast web of interdependencies? How do we do this collectively? How do we build a shared comprehension that can steer us towards the coveted solution space?
Through extensive engagement with multiple stakeholders, UNDP Bhutan and Dark Matter Labs experimented with the methodology of participatory systems mapping as a process of engagement — creating a shared language and comprehension. More importantly, the systems map that we collectively developed, functioned — and still functions — as a critical storytelling tool that represents the diverse interests and experiences of the people involved in the process. Below, we share some key learnings from this process.
Complexity vs. Simplicity
Using data collected from prior research (which involved desk research and interviews) and ideas generated through stakeholder workshops, we mapped the connections between factors — each representing a problem — that influence individuals’ options and behaviors regarding work: from family background to market conditions, and global and regional forces. To organise and process the vast number of nodes (factors) and their connections, we created a classification system using the following domains.
As we mapped the connections, we realised that the more connections there are, the more challenging it is to make sense of data. Multiple layers of lines not only made it difficult to track connections visually, but also to see patterns and hierarchies. However, privileging simplicity might risk simplification — leaving out details and erasing the nuances that make the map authentic. So, the challenge was twofold: we needed to create a visual solution that could communicate complexity without sacrificing legibility and devise a narrative solution that could preserve — and would allow us to exfoliate — the layers of complexity.
We did the latter by highlighting a series of micro-narratives that each represent a critical issue that contributes to the challenge of youth unemployment in Bhutan. Each narrative comprises a cluster of nodes (pain points) and takes into account the weight of the connections (which is determined by the number of connected nodes). Superimposed on the map itself, these micro-narratives provide an entry point into the critical issues and allow zooming in at the numerous branching connections.
Navigating complex systems
A map is not merely a representation of a place (in this case, a system), it serves a function of navigation. Just as geographic coordinates give you a sense of location, and terrain data informs your direction — a systems map helps to orient ourselves; to find direction and make better decisions. The micro-narratives are one layer of information, the domain classifications are another. These layers were designed not to simplify information, but to provide entry points from where the full complexity of the system can be explored. And, because this is an open-ended map that has been validated and iterated constantly through the stakeholder workshops, the narratives also provoke and invite further engagement and augmentation.
Perspectives from within the system
While drawing inspiration from the system dynamics model which sees the world as a complex system of feedback loops, our approach to systems mapping diverged in its method and purpose. The participatory — as opposed to the technical — approach to systems mapping invites multiple stakeholders, experts and non-experts alike, to map their knowledge, experience, and perspectives onto a collective map. Rather than the map itself, it is the process of co-creation, of collective reflection and discussion, that leads to a shared comprehension of the problem at hand. Often, it is easy to interpret the systems map as something factual, providing a holistic overview of the system from a distance. Systems maps crafted through the participatory process may not serve such an objective function. Instead, they can demonstrate the collective insights gathered from those within the system.
New possibilities of sensemaking in the digital age
During the process of mapping and synthesizing, we used digital tools such as Graph Commons and Kumu that played a vital role in supporting human synthesis and discovering insights. By interacting with machine-generated clusters and correlations, we became more aware of the human biases involved in creating connections and causal relationships. For example, due to the nuances of language, the way in which a node was described had an effect on how we drew connections, and thus required continuous crafting and validation. The digital tools and algorithms helped us in this process and contributed to the visualisation and compounding of our very human sensemaking efforts by highlighting and weighting the connections we had made.
We are aware of the growing number of tools and technologies that support our human sensemaking capacity, such as sentiment analysis, factor analysis, network analysis and many more. Perhaps through these new methods of combining human and machine analysis, while acknowledging the limitations and possibilities of both, we could arrive at a more nuanced and plural understanding of the system.
The opportunity space — creating horizontal capacities for innovation
Building a portfolio of experiments across the system
Complex systems require a variety of different actors: civil society organisations, research organisations, entrepreneurs/local corporations and governments working in coalition to build transformative, long-term visions, and diverse solutions. The portfolio approach enables us to create a network of experiments — for collective learning, hypothesising, testing and validating across different sites. It can reduce information asymmetries and allow different actors to share and manage risks in the real world. The catalyst for change may not come from one organisation or one single intervention. Instead, it can emerge in the form of portfolios, and networks of portfolios, owned and developed by multiple organisations invested in and committed to the same mission.
Every actor in the system can create their solutions
The portfolio approach brings into perspective the possibilities of a dynamic innovation mechanism, where the number of experiments multiplies by the number of actors involved, and interventions can generate positive change across different parts of the system, simultaneously. It leads to a number of critical questions as well. How can we ensure that these experiments are not carried out in silos? How can we facilitate actors to organise around shared missions? How can ownership be distributed, equitably, regardless of the power dynamics within the system? How can we create the conditions for deep system awareness, and facilitate learning between actors? These questions prompt us to think about the capacities and capabilities that could be built into the system to enable the matters of the “how”.
The framework for the portfolio of experiments that we designed, partly reflects these concerns:
In the Y axis, we categorized types of experiments, ranging from governance and regulatory, to financing and cultural experiments. On the X axis, capacities are defined according to scale — ranging from individual, collective, to system capacities. Instead of seeing the experiments as direct solutions to tackle the problem (a form of product innovation), this new framework prompts us to ask what the experiments can catalyse in terms of building the capacities to innovate from within the system. Does it contribute to building individual capacities — a sense of agency, awareness, ability to imagine, and collaborate? And does it contribute to our collective capacities of shared sensemaking, decision making, generating political will and legitimacy? And/or is it about building the infrastructure and mechanisms at the system level for shared accountability, shared data, knowledge, financial structures, and metrics that could help us prioritise and measure the success of our interventions?
These perspectives and questions provide a glimpse into the potentials of shifting the focus from a service/product centred innovation (emphasis on the what) to a capacity/capability centred approach (touching upon the how) where every actor in the system can innovate and build their solutions/portfolios towards long-term transitions. It also brings to attention the role of backbone organisations such as UNDP and its partners in facilitating and provoking systems change. Perhaps a first step towards this shift is cultivating and refining the methods to build deep system awareness, allowing us to explore freely, digest, validate, and socialise the complexity of the system.
Moving forward, UNDP Bhutan and Gross National Happiness Commission (GNHC) will continue the process of co-creating a portfolio of experiments with relevant stakeholders in Bhutan and beyond. Experiments will be led by different actors, but with a common portfolio logic and a common framework to support collective intelligence; as well as the capacity to support continuous learning, testing and experimentation. The portfolio space will aim to institute a framework where experiments, initiatives and interventions can over time coalesce, generating more intelligence, leveraging more connections, and accelerating learning and impact.
The portfolio logic design is a new adventure for the UNDP Bhutan team and look forward to more learnings from the ground. If you are interested in learning more about our work and being a part of this journey with us, do reach out to us at email@example.com.
The team at Dark Matter Labs have started working with UNDP Bangkok Regional Innovation Centre and UNDP Philippines on another wicked problem of our time — food systems. We hope to continue our efforts in developing new methodologies and platforms that facilitate co-discovery and collaborative problem solving.
Note: If you want to find out more about how to engage with this mission and join the wider movement, please contact UNDP Bhutan Innovation team, Youth Co:Lab and Dark Matter Labs: firstname.lastname@example.org, email@example.com, firstname.lastname@example.org
For more detailed information about the project, please read:
● Intelligence Report by UNDP Bhutan: ‘Systems Approach to Youth Unemployment in Bhutan’, highlighting the overall context, process and methodology of the project.
● Youth employment: why business as usual won’t cut it: Earlier blog on portfolio approach and stakeholder engagement.
● Looking Beyond Statistics, For Stories: Blog on ethnographic research process and findings.
Special thanks to Eleanor Horrocks, UNDP Bangkok Regional Hub, and Hyojeong Lee (Dark Matter Labs) for support on visual communication.
Glossary (external document — not included in blog)
System(s): “A system is an interconnected set of elements that is coherently organized in a way that achieves something.” (Meadows, 2008, p.327) A system often consists of elements, interconnections, and a function or purpose. To take a systems/systemic approach to a problem means to understand the various elements, their interdependence, logic and function — how these different parts make up the whole — rather than isolating or singling out the problem.
Complexity: It expresses a condition where different elements/factors in a system are entangled in numerous forms of relationships, complicating the act of distinguishing or making sense of the whole.
Sensemaking: Sensemaking is a collaborative process/activity to extract and generate meaning from different individuals’ perspectives, varied interests and experience — creating shared awareness and accelerating learning.
Systems mapping: A collaborative process of identifying and mapping elements/factors in the system, their interconnections, and functions, which allows us to discover knowledge gaps, intervention points, and insights.
Micro-narratives: A cluster/group of factors connected together, which help us tell a story about a particular problem identified in the system. The micro-narratives combined can give us an insight into why a system is dysfunctional. For example, one of the micro-narratives we identified is called ‘Narrow social safety net’(see figure 3), and is composed of factors such as ‘weak social protection in private sector’, ‘lack of a comprehensive social protection system’, which is connected to ‘preference for public sector jobs’, which is also connected to ‘higher compensation in public relative to private sector’ and ‘high competition for government jobs’ — these connections show a level of causality, as well as demonstrate a larger issue of an employment imbalance which is due in part to a “narrow social safety net”.
Experiments: In our project, experiments refer to ideas generated through stakeholder workshops, each representing a possible solution to a specific issue identified in the system. For example, a ‘social safety net for youth so that they can dream, experiment and fail without major personal consequences’ was one of the ideas suggested for further experimentation.
Portfolio approach/portfolio logic: As opposed to a single point, silver bullet solution, where we rely on one great idea to solve difficult problems, a portfolio approach aims to curate multiple solutions that target different parts of the system — i.e. a portfolio of solutions/experiments working in tandem, creating a multiplier effect. In the case of youth unemployment, we mean taking a set of interventions related to the issue and constructing it as an interconnected portfolio. From here, the intention is to manage the portfolio in order to actively test hypotheses, leverage interconnections, generate learnings fast, adapt interventions based on learnings, and thereby accelerate impact (More on this here).
Horizontal capacities: Capacities, tools, knowledge that are distributed horizontally (as opposed to vertical/hierarchically) across individuals and organisations e.g. knowledge/data that flows throughout the organisation that everyone can access — instead of just a select few at the management level.