UNDP Tunisia has been on a journey of exploring and making sense of trust dynamics in Tunisia within the framework of the UNDP’s Deep Demo initiative and with the support of the Chôra Foundation. This blog is a continuation of the team’s first piece and aims at zooming into what has been our experience during the two first phases, namely the design of the portfolio and sensemaking.

The blog aims at sharing and illustrating our experience and excitement in these first few months that focused on exploring in depth and understanding better the notion of trust in Tunisia. This was done mostly through series of individual and group interviews conducted by core team. The interviews allowed to, and even forced us, to review our understanding of the trust dynamics due to the, often, eye-opening findings of what undoubtedly is a complex but solvable problem, that can better be grasped through data selection and making sense of concrete experiences.

Hope you enjoy it!

Complicated vs Complex

It is right that complicated problems can be hard to solve, but they are solvable if specific tools and processes are applied. Organizing the workflow in public administrations is a complicated problem: apps, protocols and software can be used to solve this problem. Complex problems, on the other hand, are difficult to solve because they engage different people with different experiences. Trust is one of them. It’s a complex and a wicked problem (Rittel & Webber, 1973) that can be continuously redefined. It is better understood through examining the interrelations between constituent parts and by ‘probing’ to generate dynamics that reveal underlying relationships.

Therefore, addressing trust demands a holistic, systemic, qualitative, and experience-based approach. UNDP Tunisia has risen to the challenge.

Data collection vs Data Selection

We started by articulating a north star, a direction, a strategic intent that signifies where we want to go. Our aim was to develop a portfolio of interventions that are coherent with that intent. We dug in deep, speaking with hundreds of citizens, who after all are the experts on trust, in order to collect plural experiences around the thematic of trust.

The goal was not to interview countless people, but to have a representative sample: It was not about data collection; it was data selection. The effort was meant to distil patterns across a broad range of people and not go for representation because in complexity, we are meant to ‘see’ emergent new signals and be able to rapidly adapt. We have interviewed a wide range of people and profiles: former ministers, sociologists, marginalized youth, artists, bloggers, activists, and even soccer fans.

The interviews were formal and informal, virtual and over coffee, semi-structured and open. In fact, the relationship we had with the interviewees and the place in which the interviews were conducted, were variables that played a crucial role in the flow of the conversations.

Expertise vs Experience

Experts bring valuable knowledge and insights advice to UNDP’s work. Deep Demo tries to enrich this intelligence space with cultural knowledge that celebrates and values human experiences.

The interviewees are considered users with experiences and experts of their environment. A combination hardly found in the development world.

Everyone, in the course of their daily activities, has acquired knowledge that seems specialized to others. A street merchant, for instance, is an expert of branding and marketing techniques worthy of Ivy league universities.

When we engaged with a group of marginalized young people about how they have managed to survive with available means, they answered confidently like experts: they shared with us how they created their own communal security system and how they managed to survive on gigs. They have successfully mastered the complex Street culture.

From this perspective, the distinction between expertise and experience disappeared. A paradigm shift has occurred. The question for us then is what a system for continually sensing the coping strategies of citizens look like that allows us to ‘see’ emerging dynamics and continually churn out interventions that augment those that tend to be positive.

Sense-making vs Decision-making

In addition to looking at ways of continually sensing and learning externally, we turned to exploring the existing UNDP portfolio through the newly designed, distinct lens of trust. The intention was to build coherence between the intent and existing work through extracting intelligence from our ongoing projects — from climate change adaption to employment and women empowerment- that speak to specific dynamics of trust.

UNDP’s sense-making protocol is designed as a process by which we can extract how people give meaning to their collective experiences. Sensemaking has led the team to two very interesting outcomes:

1) Cognitive dimension: sensemaking is a facilitated, socialized, designed to extract insights, induce learnings and create meaning from experiences. By engaging with the full office in a structured process of reflection and layering of insights that emerge from their work, we surfaced deep qualitative intelligence about the Trust; for example, the intersection of climate adaptation and trust, or commoning as a democratic practice to establish trust dynamics through collaboration and sharing.

2) The praxeological dimension: sensemaking as a practice, a constructivist process aimed at elucidating information by UNDP staff: data, information, insights, knowledge and wisdom. Ultimately, it is a practice that allows to a dynamic management of a portfolio based on sensing emerging insights, layering learnings over time, tapping into the collective intelligence of a full office, identifying areas for connections within the portfolio that accelerate learning.

Probing vs Planning

For those of us present from the beginning of the process, we witnessed the evolution of the problem space and its different visual representations.

We started with the experts’ assumptions and personal experiences of the problem space. We were a bit territorial in fact, everyone wanted to find themselves within the visualization. Collective intelligence and deep listening turned the whole problem space upside down, starting with the intent where each word was discussed at length. We could not help but mention the shift from “trust between citizens and public institutions” to “trust around public institutions”. The word “around” says a lot about how the paradigms of the intent have changed. We started with the premise that the state must ensure trust and we have arrived at a level of complexity where the relationships are more dynamic and entangled between all the stakeholders. This significantly expands the portfolio of policy options that we can deploy to learn about and engage with trust dynamics.

Objectivity vs Subjectivity

We must acknowledge that our process is biased as it is a subjective interpretation of other people’s experiences.

Like any individual, we are not completely isolated from our environment: we are the product of society, values and beliefs. This implies that the problem space is a subjective version created by consensus, negotiation and deliberation among the Deep Demo team members.

We always wondered what our problem space would be if we interviewed other people, or if another team did the sensemaking. At some point, we have to accept that it’s just a version and to celebrate the fact that many minds have merged to produce this knowledge.

So, we don’t pretend to say that it’s the perfect problem space on Trust, it’s just one version among others, a kind of photograph of Trust dynamics at a specific time and by a specific team. However, it remains a photograph that comes close to reality without ever reproducing it.

Reflection vs Action

We designed two comparative semantic maps based on the methodology of Belkhamsa & Lafargue (2011) that explain how empirical and cultural knowledge is richer and more vivid than the dictionary’s because it is based on experiences of how people think, decide and behave.

For example, it was enlightening for us to see how people associate trust with vulnerability. People tend to trust people who show sensitivity and emotions in public, they are perceived as human, honest and trustworthy. When we trust people, we want to give them the power. When we trust, we show vulnerability, we place our confidence in the hands of other people, even people we don’t know (like bus drivers and public servants). Trust is a social contract; it is essential to maintain social peace and civil society. Modern societies are built on it: banks, governments, services. Innovations like blockchain and AI need trust.

Designing Trust vs Designing Interactions

Sensemaking made it possible to peel off the layers and to consider the relationships between dominant and dominated systems. We realized that the relationships are more complex than the state/citizen, up/down, decision maker/user, horizontal/vertical dualities. Each system of actors is multimodal and multi-layered. At the community level, for example, there are parallel dominant systems that coexist together. This is also the case in the political decision-making sphere. This implies that designing Trust is about designing interactions and designing environments and conditions that enable the manifestation of desirable interactions. Let’s imagine a government that considers every interaction with citizens as a chance to add meaning to the relationship and to communicate how it cares about them. Or Imagine citizens that build significant interactions with migrants to establish social ties to the benefit of both parties.

Problem Solving vs Exploring

The idea of considering trust from the spectrum of a problem space makes us acknowledge the importance of exploration. Our intervention is based on inquiry more than initial problem definition. This is about the ability to solve a puzzle and not come up with a single solution. For example, instead of beginning with finding a solution to trust, we instead explore why trust is problematic for all parties involved, what are the situations and the environments that make the relationships untrustful. Marco Steinberg (2014) points out that the complexity is caught between human behavior, cultural traits, ideals, values, physical principles and perceived facts. What we did is a dive into tacit beliefs, profound and unformulated insights. We analyzed the metaphors used by our interviewees in their native language and we were attentive to their body language. This implies that the problem space is never finished, which represents an opportunity to engage and involve other stakeholders to enrich and transform it. We need, as project planners, to enhance the posture of the Explorer.

As UNDP, we have to acknowledge the importance of power dynamics and be aware of where we sit and our influence. We have to understand our position, how we are perceived, when we have to step back, our role in every relationship and interaction, and how to create a space for new and grassroots ideas to flourish.

This first phase of the initiative allowed us to deep dive into the sea of trust and acknowledge the specificities and richness that exist in its seabed. These remain hidden to the normal eye when we use the traditional observation techniques that we normally use in project formulation that often limit themselves to what can be seen on the surface.

This technique does have its limitations, however. When deep diving, the number of people conducting the interviews were limited in number. Since the deep demo in Tunisia concerns an aspect that is at the heart of the new UNDP Tunisia Country Programme Document, namely strengthening trust, it is important that the exercise is understood and owned by the whole country office.

And this is where the next phase of the initiative comes into play through sensemaking while we dig deeper into the areas of interest, such as neighborhoods, the commons and the intergenerational gap, that are starting to surface. More on this soon. Stay tuned…