Dealing with complexity through Planning, Monitoring & Evaluation

Mid-term results of a collective action research process.
Authors: Jan Van Ongevalle, Anneke Maarse, Cristien Temmink, Eugenia Boutylkova and Huib Huyse. Published January 2012
Praxis Paper 26, available as pdf

(Text from INTRAC website) “Written by staff from PSO and HIVA, this paper shares the first results of an ongoing collaborative action research in which ten development organisations explored different Planning, Monitoring and Evaluation (PME) approaches with the aim of dealing more effectively with complex processes of social change.

This paper may be of interest as:
1) It illustrates a practical example of action research whereby the organisations themselves are becoming the researchers.
2) Unpacking the main characteristics of complexity, the paper uses an analytic framework of four questions to assess the effectiveness of a PME approach in dealing with complex social change.
3) An overview is given of how various organisations implemented different PME approaches (e.g. outcome mapping, most significant change, client satisfaction instruments) in order to deal with complex change.
4) The paper outlines the meaning and the importance of a balanced PME approach, including its agenda, its underlying principles and values, its methods and tools and the way it is implemented in a particular context.”

Connecting communities? A review of World Vision’s use of MSC

A report for World Vision, by Rick Davies and Tracey Delaney, Cambridge and Melbourne, March 2011. Available as pdf

Background to this review

“This review was undertaken by two monitoring and evaluation consultants, both with prior experience in the use of the Most Significant Change (MSC) technique. The review was commissioned by World Vision UK, with funding support from World Vision Canada. The consultants have been asked to “focus on what has and has not worked relating to the implementation and piloting of MSC and why; establish if the MSC tools were helpful to communities that used them; will suggest ideas for consideration on how MSC could be implemented in an integrated way given WV’s structure, systems and sponsorship approach; and what the structural, systems and staffing implications of those suggestions might be”. The review was undertaken in February-March 2011 using a mix of field visits (WV India and Cambodia), online surveys, Skype interviews, and document reviews.

MSC is now being used, in one form or another, in many WV National Offices (NOs). Fifteen countries using MSC were identified through document searches, interviews and an online survey, and other users may exist that did not come to our attention. Three of these countries have participated in a planned and systematic introduction of MSC as part of WV’s Transformational Development Communications (TDC) project; namely Cambodia, India and the Philippines.  Almost all of this use has emerged in the last four years, which is a very brief period of time. The ways in which MSC has been used varies widely, some of which we would call MSC in name only. Most notably, where the MSC question is being used, but where there is no subsequent selection process of MSC stories. Across almost all the users of MSC that we made contact with there was a positive view of the value of the MSC process and the stories can produce. There is clearly a basis here for improving the way MSC is used within WV, and possibly widening the scale of its use. However, it is important to bear in mind that our views are based on a largely self-selected sample of respondents, from 18 of the 45 countries we sought to engage.”


Glossary. 4
1.      Executive Summary. 5

1.1 Background to this review.. 5

1.2 Overview of how MSC is being used in WV. 5

1.3 The findings: perceptions and outcomes of using MSC. 6

1.4 Recommendations emerging from this review.. 7

1.5 Concluding comment about the use of MSC within WV. 12

2.      Review purpose and methods. 13

2.1 World Vision expectations. 13

2.2 Review approach and methods. 13

2.3 The limitations of this review.. 14

3.      A quick summary of the use of MSC by World Vision.. 15

4.      How MSC has been used in World Vision.. 17

4.1 Objectives: Why MSC was being used. 17

4.2 Processes: How MSC was being used. 18

Management 18

Training. 19

Domains of change. 19

Story collection. 20

A review of some stories documented in WV reports. 22

Story selection. 24

Verification. 26

Feedback. 26

Quantification. 27

Secondary analysis. 27

Use of MSC stories. 28

Integration with other WV NO and SO functions. 29

4.3 Outcomes: Experiences and Impacts. 30

Evaluations of the use of MSC. 30

Experiences of MSC stories. 30

Who benefits. 31

Impacts on policies and practices. 31

Summary assessments of the strengths and weaknesses of using MSC. 32

5.      How MSC has been introduced and used in TDC countries. 36

5.1 Objectives: Why MSC was being used. 36

5.2 Process in TDC: a comparison across countries. 36

Management and coordination of MSC process. 36

Training and support 37

Use of domains. 39

Story collection. 39

Story Selection. 43

Feedback on MSC stories. 46

Use of MSC stories. 47

Role out of TDC pilot – extending the use of MSC to all ADPs. 49

Integration and/or adoption of MSC into other sections of the NO.. 50

5.3 The outcomes of using MSC in the TDC. 51

Experiences and reactions to MSC. 51

Who has benefited and how.. 52

5.4 Conclusions about the TDC pilot. 55



Using stories to increase sales at Pfizer

by Nigel Edwards, Strategic Communications Management Vol. 15, Issue 2, Feb-March 2011. pages 30-33. Available from Cognitive Edge website, and found via a tweet by David Snowden

[RD comment| This article is about the collation, analysis and use of a large volume of qualitative data, and as such has relevance to aid organisations as well as companies. It talks about the integrated use of two sets of methods:  anecdote circles as used by a  consultancy Narrate, and SenseMaker software as used by CognitiveEdge. While there is no mention of other story based methods, such as Most Significant Change(MSC), there are some connections. There are also connections with issues I have raised in the PAQI page on this website, which is all about the visualisation of qualitative data. I will explain.

The core of the Pfizer process was the collection of stories from a salesforce in 11 cities in six countries, within a two week period. With a further two weeks to analyse and report back the results.  Before then, the organisers identified a number of “signifiers” which could be applied to the stories. I would describe these as tags or categories that could be applied to the stories, between one and four words long, to signal what they were all about. These signifiers were developed as sets of choices offered in the form of polarities and triads. For example, one triad was “achieving the best vs respecting vs people, making a difference”. A polarity was “worried vs excited”. In previous work by Cognitive Edge and LearningbyDesign in Kenya the choice of which signifiers to apply to a story was in the hands of the story-teller, hence Cognitive Edge’s use of the phrase self-signifiers. What appeared to be new in the Pfizer application was that as each story was told by a member of an anecdote circle it was not only self-signified by the story teller, but also by the other members of the same group. So, for the 200 stories collected from 94 sales representatives they had 1,700 perspectives on those stories (so presumably about 8.5 people per group gave their choice of signifiers to each of the stories from that group).

I should back track at this stage. Self-signifiers are useful for two reasons. Firstly, because they are a way by which the respondent can provide extra information, in effect, meta-data, about what they have said in the story. Secondly, when stories can be given signifiers by multiple respondents from a commonly available set this allows clusters of stories to be self-created (i.e. being those which share the same sets of signifiers) and potentially identified. This is in contrast to external researchers reading the stories themselves, and doing their own tagging and sorting, using NVIVO or other means. The risk with this second approach is that the researcher prematurely imposes their own views on the data, before the data can “speak for themselves”. The self-signifying approach  is a more participatory and bottom up process, notwithstanding the fact that the set of signifiers being used may have been identified by the researchers in the first instance. PS: The more self signifiers there are to choose from, the more possible it will be that the participants can find a specific combination of signifiers which best fits their view of their story. From my reading there were at least 18 signifiers available to be used, possibly more.

The connection to MSC: MSC is about the participatory collection, discussion and selection of stories of significant change. Not only are people asked to describe what they think has been the most significant change, but they are also asked to explain why they think so. And when groups of MSC stories are pooled and discussed, with a view to participants selecting the most significant change from amongst all these, the participants are asked to explain and separately document why they selected the selected story. This is a process of self-signification. In some applications of MSC participants are also asked to place the stories they have discussed into one or another categories (called domains), which have in most cases been pre-identified by the organisers. This is another form of self-signifying. These two methods have advantages and disadvantages compared to the Pfizer approach.  One limitation I have noticed with the explanations of story choices is that while such discussions around reasons for choosing one story versus another can be very animated and in-depth, the subsequent documentation of the reasons is often very skimpy. Using a signifier tag or category description would be easier and might deliver more usable meta-data – even if participants themselves did not generate those signifiers. My concern, not substantiated, is that the task of assigning the signifiers might derail or diminish the discussion around story selection, which is so central to the MSC process.

Back to Pfizer. After the stories are collected along with their signifiers, the next step described in the Edwards paper is “looking at the overall patterns that emerged”. The text then goes on to describe the various findings and conclusions that were drawn, and how they were acted upon. This sequence reminds me of the cartoon, which has a long complex mathematical formula on a blackboard, with a bit of text in the middle of it all which says “then a miracle happens”. Remember, there were 200  stories with multiple signifiers applied to each story, by about 8 participants. That is 1700 different perspectives. That is a lot of data to look through and make sense of. Within this set I would expect to find many and varied clusters of stories that shared common sets of two or more signifiers. There are two ways of searching for these clusters. One is by intentional search, .i.e. by searching for stories that were given both signifier x and signifier y, because they were of specific interest to Pfizer. This requires some prior theory, hypotheses or hunch to guide it, otherwise it would be random search. A random search could take a very long time to find major clusters of stories, because the possibility space is absolutely huge. It doubles with every additional signifier (2,4,8,16…) and there multiple combinations of these signifiers because 8 participants are applying the signifiers (256 combinations of any combination of signifiers) to any one story. Intentional search is fine, but we will only find what we are looking for.

The other approach is to use tools which automatically visualise the clusters of stories that exist. One of the tools CognitiveEdge use for this purpose (and it is also used during data collection) are triangles that feature three different signifiers in each corner (the triads above). Each story will appear as a point within the triangle, representing the particular combinations of three attributes the story teller felt applied to the story. When multiple stories are plotted within the triangle multiple clusters of stories commonly appear, and they can then be investigated. The limitation of this tool is that it only visualises clusters of three signifiers at a time, when in practice 18 or more were used in the Pfizer case. It is still going to be slow way to search the space of all possible clusters of stories.

There is another approach, which I have discussed with David Snowden. This involves viewing stories as being connected to each other in a network, by virtue of sharing two or more signifiers. Data consisting of a list of stories with associated signifiers can be relatively easily imported from Excel into Social Network Analysis software, such as Ucinet/NetDraw, and then visualised as a network. Links can be size coded to show the relative number of signifiers any two connected stories share. More importantly, a filter can then be applied to automatically show only those stories connected by  x or more shared signifiers. This is a much less labor intensive way of searching huge possibility spaces.  My assumption is that clusters of stories sharing many signifiers are likely to be more meaningful than those sharing less, because they are less likely to occur simply by random chance.  And perhaps… that smaller clusters sharing many signifiers may be more meaningful than larger clusters sharing many signifiers (where the signifier might be fuzzier and less specific in meaning). These assumptions could be tested.

To recapitulate: Being able to efficiently explore large possibility spaces is important because they arise from giving participants more rather than less choice of signifiers. Giving more choice means we are more likely to hear the participants’ particular views, even though they are voiced through our constructs (the signifiers). And larger number of signifiers means that any clusters of highly connected stories is more likely to be meaningful rather than random.

Social Network Analysis software has an additional relevance for the analysis of Pfizer data set. Within the 1700 different perspectives on the stories there will not only be a network of stories connected by shared signifiers. There will also be a network of participants, connected by their shared similar uses of those signifiers. There will be clusters of participants as well as clusters of stories. This social dimension opened up by the participatory process used to apply the signifiers was not touched upon by the Dawson paper, probably because of limitations of time and space. But it could be great significance for Pfizer when working out how to best respond to the issues raised by the stories. Stories have owners, and different groups of owners will have different interests.

Updated MSC bibliography

PLEASE NOTE. The bibliography below has now been superseded by a more comprehensive bibliography here. This now includes pdf copies of many of the papers plus a search facility. It will continue to be updated

This (now older) page is intended to provide  an update of the bibliography in the 2005 Most Significant Change technique (MSC) Users Guide

Please feel free to suggest additions to this list, through the Comment facility below, or by emailing the editor (Rick Davies)




  • Seven sets of slides, used for 2 day MSC training in Delhi, 2008 by Rick Davies . Available on request , on condition of willingness to share any adaptations made

YouTube video



Research Integration Using Dialogue Methods

David McDonald, Gabriele Bammer, Peter Deane, 2009 Download pdf

Ed: Although about “research integration”  the book is also very relevant to the planning and evaluation of development projects

“Research on real-world problems—like restoration of wetlands, the needs of the elderly, effective disaster response and the future of the airline industry—requires expert knowledge from a range of disciplines, as well as from stakeholders affected by the problem and those in a position to do something about it. This book charts new territory in taking a systematic approach to research integration using dialogue methods to bring together multiple perspectives. It links specific dialogue methods to particular research integration tasks.

Fourteen dialogue methods for research integration are classified into two groups:

1. Dialogue methods for understanding a problem broadly: integrating judgements

2. Dialogue methods for understanding particular aspects of a problem: integrating visions, world views, interests and values.

The methods are illustrated by case studies from four research areas: the environment, public health, security and technological innovation.”

Stories vs. Statistics: The Impact of Anecdotal Data on Accounting Decision Making

James Wainberg , Thomas Kida, James F. Smith
March 12, 2010  Download pdf copy

Prior research in psychology and communications suggests that decision makers are biased by anecdotal data, even in the presence of more informative statistical data. A bias for anecdotal data can have significant implications for accounting decision making since judgments are often made when both statistical and anecdotal data are present. We conduct experiments in two different accounting contexts (i.e., managerial accounting and auditing) to investigate whether accounting decision makers are unduly influenced by anecdotal data in the presence of superior, and contradictory, statistical data. Our results suggest that accounting decision makers ignored or underweighted statistical data in favor of anecdotal data, leading to suboptimal decisions. In addition, we investigate whether two decision aids, judgment orientation and counterargument, help to mitigate the effects of this anecdotal bias. The results indicate that both decision aids can reduce the influence of anecdotal data in accounting decision contexts. The implications of these results for decision making in accounting and auditing are discussed.


Date: 25-26th November 2009
Venue: Bogor, Indonesia

The Most Significant Change technique is a dynamic qualitative and participatory monitoring and evaluation method.  Through collecting stories of the impact of our program with the program stakeholders we analyse our work.  Through this process of selecting the stories, change management and organizational learning is facilitated. MSC has a particular ability to capture impact in complex cross cultural social change contexts.

With the shift in monitoring and evaluation to a mixed methods approach MSC is a method that fills the gap in data collection. MSC gathers rich qualitative data that captures intangible impact and unexpected outcomes of the program.

This two day training presents MSC through practical examples and exercises.  The training is designed for active learning.
At the end of the training the participants will:
•  Understand how MSC works
•  Understand how MSC fits into a Monitoring and Evaluation Framework,
•  Know the best situation to use MSC and when not to use MSC
•  Understand how MSC facilitates development of stakeholder relationships and organizational learning & development
•  Have learnt through practical exercises, skills to undertake MSC (story collection, story selection & feedback)
•  Know the specific adaptation of MSC for an Indonesian context
•  Have designed an MSC system for your program.

Who Should Attend These Trainings?
Organisations, teams and individuals seeking to:
•  Develop a program’s direction or clarify a shared vision
•  Try something new in an organisational learning context
•  Capture intangible and unexpected outcomes

Download flyers in English and Indonesian Details of the trainers, the location, the costs and contact names and email addresses are all in the flyer

Most Significant Change Training in Melbourne 1-2 December

Date: 1-2 December
Venue: Melbourne

MSC is a powerful tool for monitoring, evaluation and organisational learning. MSC goes beyond merely capturing and documenting participants’ stories of impact, to offering a means of engaging in effective dialogue. Each story represents the storyteller’s interpretation of impact, which is then reviewed and discussed. The process offers an opportunity for a diverse range of stakeholders to enter into a dialogue about program intention, impact and ultimately future direction. This two day workshop provides an introduction to MSC which includes designing your own MSC process. Participants will be provided with experiential learning opportunities and examples of real applications of the technique throughout the workshop.

This two day course includes the Evaluation Summit training. Evaluation Summit will take place on the second half of day two.

You can register online here

As well as our regular courses we are also seeking expressions of interest for two brand new courses in management: Management Core Concepts and Change Management Toolkit facilitated by Carolynne Wilson our newly appointed senior consultant!

Training in the Most Significant Change Evaluation Technique (Cardiff, UK)

Date: 15th to 17th December 2009
Venue: Cardiff, UK

There are many different ways to collect and analyse data as part of an evaluation. Each has their merits, and each has their weaknesses. Recently there has been an increased recognition that quantitative analysis (using numbers) may not always be appropriate, or give us the full picture. As Einstein said “Not everything that can be counted counts, and not everything that counts can be counted”. The importance of stakeholder participation in evaluation has also gained prominence. A new suite of qualitative evaluation tools have emerged in response to this, the Most Significant Change (MSC) story approach possibly having the greatest prominence.
Continue reading “Training in the Most Significant Change Evaluation Technique (Cardiff, UK)”

Training in Most Significant Change Technique (MSC) in Oxford, UK

Date: 28-29th July 2009
Venue: Oxford, UK

MSC is a powerful tool for monitoring, evaluation and organisational learning. MSC goes beyond merely capturing and documenting participants’ stories of impact, to offering a means of engaging in effective dialogue about what you are achieving. Each story represents the storyteller’s interpretation of impact, which is then reviewed and discussed. The process offers an opportunity for a diverse range of stakeholders to enter into a dialogue about program intention, impact and ultimately future direction. MSC has much to offer your existing M&E framework being especially good at capturing that traditionally hard to capture information about what difference did you make in the hearts and minds of those your were targeting for benefit – but it has much to offer beyond merely reporting on outcomes! This two day training workshop provides an introduction to MSC which includes designing your own MSC process. Participants will be provided with experiential learning opportunities and examples of real applications of the technique. We will also share our experiences of adapting MSC for use in evaluation studies.

Where: Oxford, England (venue to be determined)

When: Tuesday 28th & Wednesday 29th of July Cost: £550

* To secure your enrolment download and return your registration form today: [url] [/url]

* Concession rates and multiple participant discounts available contact for more information

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