Learning Partnerships: Collaborative learning in practice

By: Suzane Muhereza

Contributors: Morag Mwenya Neill-Johnson, Raquel Rubio Rodriguez, Robbie Gregorowski

UNDP has set up an M&E Sandbox to nurture and learn from new ways of doing monitoring and evaluation (M&E) that are coherent with the complex nature of the challenges facing the world today. Read more about the Sandbox here.

We convene a series of participatory sessions as part of the M&E Sandbox. In each session we collectively explore a theme in depth, inviting practitioners to speak about their experience testing new ways of doing M&E that helps them navigate complexity. You can read digests and watch recordings of our previous Sandbox sessions here: using M&E as a vehicle for learning, measurement and complexity, progress tracking and reporting and how to measure systems change. Do also consult our overview piece on innovative M&E initiatives and resources. You can also join our M&E Sandbox LinkedIn group to connect, learn and share insights with like minded Sandboxers.

In our most recent Sandbox session, we began an exploration of learning partnerships in the systems and complexity space. Learning partnerships are evolving, with a growing recognition of the need for neutral parties to facilitate collaboration and learning in complex systems. These partnerships can help to create safe spaces for learning, and to ensure that all voices are heard. We were curious to hear how learning partnerships are set up and how they support teams to make the leap from learning together to enacting change. If this post has sparked your interest, we recommend that you watch the full recording right here.

The Collective: A Collaborative Learning Experiment

Morag Mwenya Neill-Johnson from the Centre for Public Impact (CPI) shared about their evolving role as a learning partner hosting CPI’sthe Collective and supporting actors through action-learning and sensemaking. Through the Collective, CPI is exploring how to facilitate intentional collaboration across systems — systemic collaboration — to tackle the root causes of complex, interconnected challenges, and the role of experimentation in collaborative learning within a systems Community of Practice (CoP). According to Morag, “CPIs approach acknowledges the growing demand for learning partnerships that can address problems systemically, fostering long-term sustainability and community ownership.” CPI views learning partnerships as a way to tackle problems from a systemic and interconnected approach for longer sustainability and community ownership.

• Moving at the Speed of Trust: Trust is fundamental for effective collaboration and experimentation. Building trust from the outset is crucial and requires time. Morag shared further, “Without a focus on the relational component of this work, reaching the level of collaboration and experimentation required to develop new pathways and approaches is challenging to accomplish.” CPI used the Community Weaving Framework to deepen the relational component of the work and strengthen their growing tapestry, and integrated multiple theoretical frameworks, including the Systems Innovation Initiative’s Four Keys to Systems Innovation, the Berkana Two Loops model, Social Imagination, and the Public Narrative framework integrated into training by the Caravanserai Collective while remaining flexible and not beholden to any single approach.
• The Complexity of the Who in Learning: Effective learning partnerships require careful consideration of who participates. It’s crucial to balance diverse perspectives with the need for participants to have a shared understanding and institutional capacity to act on the learning. Open call recruitment during the pilot resulted in diverse Communities of Practice (CoPs) for CPI’s Collective. However, some topics required participants to have a common starting point in order to develop a coherent collaborative learning and experimentation journey. In designing the systems CoPs, key questions arose around participant prerequisites, roles (e.g., M&E Officers), institutional vs. individual representation, and how to effectively engage decision-makers in emergent initiatives.
• The Discomfort of Emergent Learning: Facilitating emergence is challenging, as there’s a tendency to revert to the status quo. Morag acknowledged that, “Even without external pressures, it is easy to fall back into old habits of control, certainty, and risk-aversion.” While embracing emergent learning in community, there are varying scales of learning from the individual mindsets and mental models, learning new pathways for collaboration and exchange within the CoP, learning about the practicalities of influencing systems, and learning about the topic at hand. Morag acknowledges that learning occurs at different and varying comfort levels.

Javiera Godoy leads a Systems CoP for CPI’s Collective on Innovation for Democracy in Latin America. She shared that this cohort builds on insights from the pilot cohorts, particularly the value of focusing on a single geographic region to support more cohesive coordination. Geographic proximity has enabled deeper trust-building and experimentation, while cultural and linguistic specificity have helped lower participation barriers. Conducted in Spanish, the CoP navigates the complexities of real-time translation in emergence and ambiguity — underscoring that language inclusion is not a logistical detail but a foundation for equitable collaboration. Speaking in native languages supports collective belonging and accessibility, though challenges remain around accommodating Portuguese and other regional languages. Despite the added effort, this commitment to multilingual engagement has proved worthwhile. Recruitment for this cohort also differed: institutional representation, rather than solely individual participation, helps embed learning and create pathways for systemic, regional collaboration. To support facilitation and strengthen sensemaking, the team also brought in a regional advisor with democratic innovation expertise to anchor the work in both practice and research. These design choices are not just practical — they’re enabling conditions to build learning communities that are contextually grounded and poised to work in complexity.

ESLA Loops: New Approaches to M&E in Complex Systems

Robbie Gregorowski’s presentation highlighted that learning partnerships should embrace flexible, iterative approaches that allow for emergence and adaptation, by better integrating evidence with stakeholder experience and insight. This means moving beyond rigid, pre-defined plans and embracing experimentation and collaborative sense-making. Organizations need to be adaptive in the face of complex challenges, and this requires moving beyond traditional reporting to focus on generating evidence to support and enable collaborative sense-making. This shift necessitates new skills and expertise to co-design and facilitate collaborative sense-making that links evidence and learning to strategy.

Robbie’s presentation also outlined several practical lessons and recommendations for fostering effective learning:

• People need to feel united by a shared context, vision, or objective to facilitate collective learning.
• First experiences are critical in shaping future learning; it’s important to start small, keep it simple, and find an excellent facilitator.
• Explore the modest but productive use of AI to shift the emphasis from reporting to generating evidence for collaborative sense-making.
• Demonstrate practical application by moving from efficiency and effectiveness questions and criteria to a more adaptive learning orientation — “What and how? So what? Now what?”
• Frame the journey as a transition from a traditional M&E ‘function’ to a collective organizational ‘capacity’, embedding evidence-based collaborative sense-making and learning throughout the organization.

Robbie also highlighted the power of storytelling in learning, storytelling is a powerful tool for systems change — helping to define and explore ‘meaningful change’ (often defined as intermediate outcomes), make sense of complex issues, and foster shared learning. In a learning context, storytelling can help actors connect with the material on a deeper level, and to share their own experiences and insights.

Raquel Rubio, who was part of the Q&A session, built on Robbie’s presentation, sharing that collaborative sense-making for learning is as much an art as it is a science. Like any intentional practice, it requires proper resourcing — this includes technical skills, time for staff to engage meaningfully, and funding to support both. The sector should adopt a mindset shift: viewing actionable data not as a nice-to-have, but as a must-have that never ends but changes. She also reminded us that “right-fit” data depends on the purpose, and that the experiential data within a team holds a lot of value and can be a powerful starting point for learning.

Both presentations emphasized that systemic collaboration is not just about stakeholders working together, but about how they work together. The quality of interaction and connection within the system is crucial for effective learning and knowledge sharing. Power dynamics can create barriers to learning, preventing some stakeholders from fully participating or sharing their knowledge.Most importantly, learning partnerships work best when there is trust among stakeholders. This requires creating safe spaces for sharing, vulnerability, and open dialogue. To hear more about what was discussed in the lively Q&A session, please watch the session recording here.

Additional resources:

• Blog post on Systemic Collaboration
• ESLA Loops approach

If you would like to join the M&E Sandbox and receive invites for upcoming events, please reach out to contact.sandbox@undp.org