Knowledge Management in an Organization of the Poor

In “Knowledge Management in an Organization of the Poor” (2009), Aldo Benini and Bhabatosh Nath visit a federation of poor people in Bangladesh that, by its own initiative and unassisted by outsiders, conducted a survey of all extremely poor households in the local government area. The federation then linked this information to a critical resource listing – an inventory of government-owned lands supposed to be allocated to the poor. The creative re-interpretation of the survey concept and a tactically variable involvement in project-related data collection drives earn the federation the title of knowledge manager. Its significance, in a highly stratified world of development expertise, is in the demonstrated ability of poor people to map their own complex environment, on their own terms, and for their own betterment.

*Outcome Mapping Training in Switzerland – June 28 to July 2, 2010

Date: June 28 to July 2, 2010
Venue: Switzerland

We from Agridea International are happy to announce another learning event and training on Outcome Mapping in Switzerland. From June 28 until July 2, 2010, we will spend 5 days getting to know the nuts and bolts of planning, monitoring and evaluating with Outcome Mapping.

We will discuss specific issues regarding the facilitation of OM planning events, key challenges and solutions for participative monitoring and sense-making, and we will organise peer-learning sessions for your own cases and realities.

The fusion of other existing approaches, methodologies and guiding principles with Outcome Mapping is another workshop topic.

Do not miss this unique opportunity for learning from the experts – in a practice oriented way.

For further information or registration contact Mr. Carsten Schulz

website :

PAQI How-to-do-it Annex

This is a technical annex to

Data processing steps

The network diagrams were produced using UCINET & NetDraw (a package). Very briefly, this involved producing the following files:

  • For relationships between sorted items:
    • Create a .txt file in a specific Dl file format, known as PARTITION, as shown in this example
      • This shows five sets of sort results, seperated by a # marker. With each set, each row shows a set of items put into one group, by the participant
    • Convert this to the first Ucinet file, using these commands: Data>Inputs text file>Input text file in DL format:
    • Aggregate the five sets of data into one items x items matrix, by using these commands: Transform>Matrix Operations>Within Dataset>Aggregations>Input dataset: [the new file you created], Sum, Break-out resultsby: rows and columns
    • Then view the saved file in Netdraw. View with link strength >1, because you want to see the connections created by multiple participants, not one.
  • For relationships between categories used
    • Take the original .txt file in PARTITION format and re-structure it as a .txt file in another Dl file format known as EDGELIST2, as shown in this example.
      • N=66 because there are 24 items and 42 categories. A1-4 are categories used by the first respondent, B1-6, by the second etc. Each row lists items put in that category
    • Convert this to the second Ucinet file, using these commands: Data>Inputs text file>Input text file in DL format:
    • This shows a categories x items matrix
    • This needs to be converted to a one mode matrix, of categories x categories. Use these commands: Data>Affiliations (2-mode to 1-mode)>Input data set:
    • Then view the saved file in Netdraw. View with link strength >1, because all categories will have at least one shared item with others.
      • PS: You can also use Netdraw to visualise the two-mode categories x items matrix (See Necheles reference below)
  • For relationships between the respondents
    • Use these commands: Tools>Similarities (e.g.correlations,)> Input Datset: name of first Ucinet file above, Measure of profile similarity: Correlation,  Compute similarities amongsts: Columns.
    • You then have a matrix of correlation values, ranging from 0 to 1. To make these easier to discriminate, when using NetDraw, it is best to multiple them by 100. Use these commands: Transform>Matrix Operations>Within Dataset>Cellwise Transformations>Multiply by constant
    • Then view the saved file in Netdraw. Focus on relationships with above average strength (because all participants will have some similarities in their classifications)

PS:  I have set up a seperate posting on the merits of different kinds of social network analysis software, including UCINET and NetDraw.

Adding qualitative “flesh” to the quantitative “bones”

The network diagrams are the structure. They are the results of all the sorting activities by all the participants. But in the process of sorting the items each participants also added qualitative information, in the form of descriptions of the categories they created. In the Indonesian example 33 category descriptions were provided by the 5 participants. This next section will describe how that qualitative information can be made accessable, as people explore the individual nodes and links in the network diagrams. This information will be in the form of node and link attributes.

With the Indonesian data  I listed the members of each grouping of items in a row, and then in an adjacent column I entered the text description of that group given by the participant. When all the groupings of one respondent were entered I started with the next respondent’s groupings on the rows below

The challenge is to then collate all text descriptions that apply to a given item and to do that for all items, in a way that is not manually time consuming. To do this I set up a list of items (in rows), and in adjacent columns I set up a logic function that in effect searched for relevant text. A copy of the Excel sheet will be attached here.

This data then needs to be  put into an attribute.txt format (example here) and then imported into Netdraw as an attribute file, when already viewing the item x  item network (File>Open>VNA text file>Attributes). Then any node can be double right clicked to view its attributes, including all the descriptions given to it by the participants (See example). Bear in mind these are descriptions of the categories it belongs to, not that specific item.

New INTRAC publications on M&E

Tracking Progress in Advocacy – Why and How to Monitor and Evaluate Advocacy Projects and Programmes looks at the scope of, and rational for, engaging in advocacy work as part of development interventions, then focuses on the monitoring and evaluating of these efforts – offering reasons why and when these processes should be planned and implemented, what’s involved, and who should be engaged in the process. By Janice Griffen, Dec, 2009

The Challenges of Monitoring and Evaluating Programmes offers some clarity in understanding the different uses of the term ‘programme’, and uses the different types of programme to demonstrate the issues that arise for M&E. By Janice Griffen, Dec, 2009

Against Transparency: The perils of openness in government.

Being a keen advocate of greater transparency by aid agencies and programmes this article interested me.

See it on the New Replublic website, published on October 9, 2009

The author, Lawrence Lessig, “is professor of law and director of the Edmond J. Safra Center for Ethics at Harvard Law School, and the author most recently of Remix: Making Art and Commerce Thrive in the Hybrid Economy (Penguin). He is on the advisory board of the Sunlight Foundation and on the board of

The Use of Social Network Analysis Tools in the Evaluation of Social Change Communications

by Rick Davies (April 2009).

This paper was produced for the Communication for Social Change Consortium, as a contribution to their paper for UNAIDS on reviewing approaches to monitoring and evaluation and advocating an expanded monitoring and evaluation framework for social change communication. All rights to this paper are with the Communication for Social Change Consortium (]


2. What is Social Network Analysis? A brief introduction..
3. The use of SNA in the study of HIV/AIDS..
4. The use of SNA in the evaluation of HIV/AIDS interventions..
5. How could SNA be useful in the evaluation of HIV/AIDS programs?.
5.1. Within organisations: Moving from Logical to Social Frameworks.
5.2. Within organisations: Moving beyond linear models.
5.2.1 Mapping and modeling.
5.2.2 Looking inside and outside the network.
5.2.3 Matrix versus network models.
5.3. Amongst multiple organisations: Where there is no central planner.
6. The uses of theory..
7. Scalability..
8. Limitations..
9 Opportunities..
10. An Afterword..

Metaevaluation revisited, by Michael Scriven

An Editorial in Journal of MultiDisciplinary Evaluation, Volume 5, Number 11, January 2009

In this short and readable paper Michael Scriven addresses “three categories of issues that arise about meta-evaluation: (i) exactly what is it; (ii) how is it justified; (iii) when and how should it be used? In the following, I say something about all three—definition, justification, and application.” He then makes seven main points, each of which he elaborates on in some detail:

  1. Meta-evaluation is the consultant’s version of peer review.
  2. Meta-evaluation is the proof that evaluators believe what they say.
  3. In meta-evaluation, as in  all evaluation, check the pulse before trimming the nails.
  4. A partial meta-evaluation is better than none.
  5. Make the most of meta-evaluation.
  6. Any systematic approach to evaluation—in other words, almost any kind of professional evaluation—automatically provides a systematic basis for meta-evaluation.
  7. Fundamentally, meta-evaluation, like evaluation, is simply an extension of common sense—and that’s the first defense to use against the suggestion that it’s some kind of fancy academic embellishment.

Social Network Analysis And the Evaluation of Leadership Networks

Bruce Hoppe, Ph.D. Connective Associates LLC
Claire Reinelt, Ph.D. Leadership Learning Community
January 19, 2009

Leadership development practitioners have become increasingly interested in networks as a way to strengthen relationships among leaders in fields, communities, and organizations. This paper offers a framework for conceptualizing different types of leadership networks and uses case examples to identify outcomes typically associated with each type of network. One challenge for the field of leadership development has been how to evaluate leadership networks. Social Network Analysis (SNA) is a promising evaluation approach that uses mathematics and visualization to represent the structure of relationships between people, organizations, goals, interests, and other entities within a larger system. Core social network concepts are introduced and explained to illuminate the value of SNA as an evaluation and capacity-building tool.

Full text here

Stakeholder analysis and social network analysis in natural resource management

Christina Prell, Klaus Hubacekb, Mark Reed, Department of Sociological Studies, University of Sheffield and  Sustainability Research Institute, School of Earth and Environment, University of Leeds, 2009

Full text here


Many conservation initiatives fail because they pay inadequate attention to the interests and characteristics of stakeholders. (Grimble and Wellard, 1997). As a consequence, stakeholder analysis has gained increasing attention and is now integral to many participatory natural resource management initiatives (Mushove and Vogel, 2005). However, there are a number of important limitations to current methods for stakeholder analysis. For example, stakeholders are usually identified and categorized through a subjective assessment of their relative power, influence and legitimacy (Mitchell et al., 1997; Frooman, 1999). Although a wide variety of categorization schemes have emerged from the literature (such as primary and secondary (Clarkson, 1995), actors and those acted upon (Mitchell et al., 1997); strategic and moral (Goodpaster, 1991); and generic and specific (Carroll, 1989) methods have often overlooked the role communication networks can play in categorizing and understanding stakeholder relationships. Social network analysis (SNA) offers one solution to these limitations.

Environmental applications of SNA are just beginning to emerge, and so far have focused on understanding characteristics of social networks that increase the likelihood of collective action and successful natural resource management (Schneider et al., 2003; Tomkins and Adger, 2004; Newman and Dale, 2004; Bodin et al., 2006; Crona and Bodin, 2006). In this paper, we harness and expand upon this knowledge to inform stakeholder analysis for participatory natural resource management. By participatory natural resource management we mean a process that engages stakeholders on multiple levels of decision making and facilitates the formation and strengthening of relationships among stakeholders for mutual learning (Grimble and Wellard, 1997; Dougill et al., 2006; Stringer et al., 2006). To enhance stakeholder analysis, we use SNA to identify the role and influence of different stakeholders and categories of stakeholder according to their positions within the network. We do this using case study material from the Peak District National Park, UK.

What should be found within an M&E framework / plan?

I was asked this question by a client some time ago. After some thinking about something that I felt I should have already known, I drafted up a one page guidance note for my client. The contents of the note also benefited from a discussion about appropriate expectations about M&E frameworks with other M&E people on the MandE NEWS email list

I have attached the one page guidance note here: What should be found in an M&E Framework / Plan?

Please feel free to post your comments on this document below. And to suggest any other documents or websites where this topic is covered.

PS: 28 October 2011: This one-pager contains a summary of the proposed contents of an M&E Framework for a DFID project, prepared this year

PS: 12 February 2014: Benedictus Dwiagus Stepantoro has sent me this link to the DFAT (was AusAID) Monitoring and Evaluation standards that were updated in 2013. He points especially  to standard no.2 on Initiative M&E System there, and comments:

” I use it all the time as reference in checking the quality of M&E system in program/project/initiative, as I often receive 3-5 M&E System/Plan documents every year to be assessed.

 The main key feature for an M&E system there are:

 – Should have an ‘evaluability assessment’, as basis for developing the M&E system.

– Have clarity on program outcome, key output, approach/modality and the logic around them

– Have Evaluation Questions, or Performance Key Questions/Indicators

– Methodology/Tools – including baseline

– Should have sufficient resource (people with right expertise, fund for M&E activities.etc)

– Scheduling of M&E activities

– Costing/Budget allocation for M&E

– Clear responsibility

….People often shows me a logframe or a matrix of indicator and proudly state that their program have an “M&E System”,… But,…. For me, .. A logframe alone, is not an M&E System. A matrix of Indicators alone, is not an M&E system”