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The low down on Most Significant Change as a tool for qualitative data collection in complexity

March 16, 2016By Kerry Graham

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.

Why stories?

  • 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.

Key messages

  • 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.
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