Most Significant Change
Collect stories, discuss significance, and select for learning
Torch brings the Most Significant Change methodology into your MEL platform. Gather change stories from staff and external contributors, organise them by domain, and run transparent selection rounds with documented decisions.
How It Works
Three steps to meaningful insight
MSC in Torch follows the established methodology: collect stories of change, organise them by domain, then use structured selection rounds to surface the most significant.
Story Collection
Structured stories, flexible participation
Rich, structured change stories
Every MSC story in Torch captures the essential elements: a clear title, a narrative describing what changed, a rationale for why this story matters, and a domain of change to categorise the story within your programme's framework.
Stories move through a clear lifecycle — from draft through shortlisted and selected to archived — reflecting the outcomes of your selection process.
Women's savings group transforms village market
After joining the savings group, women in Karatu village pooled resources to establish a weekly market that now serves three neighbouring communities...
This story shows how financial literacy training can catalyse broader economic change beyond the individual participant...
Selection Rounds
Transparent decisions, documented reasoning
Kanban-style review board
Each selection round presents stories on a visual board. Reviewers move stories between columns — unreviewed, shortlisted, selected, and not selected — using drag-and-drop or decision modals.
Every move records the reviewer's decision and notes. A round cannot be closed until every assigned story has a documented decision, ensuring no story is silently overlooked.
Rounds can also be prepared with a full-screen canvas view for spatial layout and group discussion.
External Participation
Collect stories from anyone, without accounts
Contributor invites
Create labelled invite links that let external contributors submit change stories without needing a Torch account. Set optional expiry dates and usage limits for each invite.
Contributors open a secure, signed URL to view existing stories and submit their own. The system records the submitter's email and tracks which invite was used, maintaining full provenance of externally submitted stories.
3 of 10 uses · Expires 30 Apr
7 of 20 uses · Expires 15 May
12 of 12 uses · Expired
Optional AI Assistance
Drafts for facilitators, not automated storytelling
When enabled, Torch can draft MSC story fields — title, narrative, domain, and significance rationale — from your project context and qualitative evidence. The AI is instructed never to invent facts or quotes.
Every draft is presented for human review. Facilitators edit, accept, or reject AI suggestions before they become part of the MSC process. Your administrator controls whether AI features are available.
Community health volunteers reduce malaria incidence in three districts
Based on field reports and indicator data, community health volunteers trained in the second quarter...
Solutions
Where MSC fits
The same Torch platform described on each solutions page brings MSC together with your MEL framework and reporting.
International development programmes
Run MSC alongside your MEL framework: collect change stories from the field, organise by domain, and document selection decisions for participatory learning and accountability.
Impact investors & portfolio teams
Surface significant change narratives across investments, align story-based learning with strategy and results, and strengthen how you communicate impact beyond financial returns.
Social enterprises
Capture beneficiary and staff stories of change, involve external contributors without accounts, and feed learning into stakeholder reporting without a separate storytelling tool.
Be the first to try Most Significant Change in Torch
Join the waitlist and we'll let you know when MSC is available for your team.