The Three-Phase Framework: A Dynamic Process for Catalysis

Our philosophy is put into action through a structured yet adaptable three-phase framework. This is the operational model that allows us to move from understanding a system to actively enabling its regenerative potential. This is not a linear sequence but a continuous, iterative cycle.

Phase 1: Identifying Value

Goal: From an abstract model to a co-created, contextual understanding of what value means here.

Before we can track value, we must first define it in collaboration with the community we are serving. This phase establishes the “playground” for evaluation.

• Global Model & Best Practices: We start with our robust multi-capital and systemic sphere frameworks as a foundation.

• Contextual Co-Creation: Through participatory workshops, we work with stakeholders to adapt the model, defining the specific capitals, spheres, and value-generating activities that are most relevant to their context and goals.

• Iterative Baselining: We establish a qualitative and quantitative baseline—not as a fixed starting point, but as the first snapshot in a living story of a system’s evolution.

Phase 2: Tracking Catalysts

Goal: To make emergent dynamics and value flows visible in near real-time.

During an active engagement (like an ALJ), we capture data that reveals not just what happened, but how it happened and who catalyzed it. This is the “reading” of the system.

• Diverse Data Capture: We use multiple instruments to gather rich data, including structured forms, peer ratings, facilitator observations, and qualitative voice notes—capturing both quantitative signals and nuanced narrative.

• Reliable Relational Indexing: Our technology doesn’t just store data; it creates a relational map. Every entry is indexed by who contributed it, when, in what context, and in relation to which other activities or people, allowing us to see the web of influence.

• Composite Map Creation: We synthesize this multi-source data into dynamic “maps” and dashboards that visualize value flows, identify emerging leaders, and highlight key leverage points.

• Multi-Source Verification: Insights are continuously cross-referenced and verified through a combination of facilitator feedback, peer attributions, expert review, and relevant literature to ensure reliability.

Phase 3: Enabling Stewardship

Goal: To turn insight into actionable resource flow, empowering adaptive learning and governance.

This is the most critical phase, where evaluation becomes a direct catalyst for change. The data we track is fed back into the system to inform decisions and guide resources.

• Transparent Contribution Recording: We make contributions and value flows visible to the community, fostering a culture of recognition and mutual accountability.

• Catalytic Weighting: In collaboration with stakeholders, we can assign weights to different forms of value, prioritizing contributions that have the greatest catalytic effect on the system’s health.

• Automated & Deliberate Allocation: The evaluation system can enable more effective stewardship, from automating the distribution of resources based on contribution to informing deliberate, group-based decisions on where to focus energy next.

• Iterative Feedback Loops: The outcomes of these allocation decisions are fed back into the tracking phase, creating a tight learning loop that allows the system to adapt and evolve with increasing intelligence and coherence.