The low down on Most Significant Change as a tool for qualitative data collection in complexity
Most Significant Change – beyond indicators
Bethany Davies from Clear Horizons gave an overview of the Most Significant Change tool for monitoring and evaluation. This blog captures Bethany’s slides and comments. Check out a user guide to Most Significant Change here.
What is Most Significant Change?
- A qualitative, participatory tool for monitoring and evaluation
- Used to complement traditional monitoring tools
- Originally developed to monitor less tangible outcomes
- Later adapted for use in evaluation
- Now used across sectors
- Collect stories from a diverse range of people
- Review and select stories
- Discuss and communicate results (feedback)
- Use results for program learning – this is key!
What is it and how does it work?
- Generated– used to generate learning in organisations across siloes and strata.
- Adapted – used to generate learning across users, deliverers and funders of empowerment programs in international development.
So Most Significant Change Stories provide:
- Information about instances of project impact } The dialog
- Information about how people value those impacts } is what matters
Purpose s for using Most Significant Change
MSC is commonly used for:
- Fill gap in exiting monitoring data
- Identify unexpected changes
- Understand complex changes that cannot easily be enumerated
- Respect and represent the voice of people participating in a program
- Encourage reflective practice
Very accessible and fun, when data and reflective practice is often not experienced that way.
- People tell stories naturally
- It has a cultural place
Where is MSC relevant?
MSC is appropriate if your project has:
- Complex and produces diverse and emergent outcomes
- Focused on social change
- Participatory in ethos
- A learning culture
May not be right if you mainly want to
- Develop good news stories for public relations
- Understand the ‘average’ experience participants
- Produce a report for accountability purposes
Monitoring changes that matter
MSC was a solution to a challenge facing program staff
- Draws on deductive reasoning, seeks to develop theory and test it
MSC can capture expected AND unexpected outcomes
- Draws on inductive reasoning
- Can tell us the things we don’t know and need to know
- Can help develop program theory as learning emerges.
MSC and traditional monitoring
- Setting metrics of success are participatory – democratising data analysis
A systemic approach
- Driven by a deliberate, planned methodologies
- Produces structured, deliberately sampled comparable narratives
- Has structured analysis processes that embraces subjectivity
- Transparency around conclusions and rational for communication
- Understanding what is important to who and why.
- It is deceptively simple and intuitive. However, the question may be simple but the design and planning needs to be careful and deliberate.
- It is like the ballet – looks beautiful but lots going on behind and in preparation.