Making Sense ofMaking Sense of SensemakerSensemaker®®
::
Evaluating development initiativesEvaluating development initiati...
Connecting Needs ChronologicallyConnecting Needs Chronologically
 Learning by DesignLearning by Design
• find a methodolo...
Options to Find and ExpressOptions to Find and Express
 StatisticsStatistics
• Decontextualised fragments (end results/in...
But when you’re off the beaten path…But when you’re off the beaten path…
 future doesn’t necessarily mirror the pastfutur...
GlobalGiving’s M&EGlobalGiving’s M&E
 self-generated reportsself-generated reports
 incidental evaluatorsincidental eval...
Design FeaturesDesign Features
 Numbers derive meaning from their contextNumbers derive meaning from their context
 Stor...
Methodological LogicMethodological Logic
1.1. Prompting question or imagePrompting question or image
• triggers a lived ex...
Designing Use of SenseMakerDesigning Use of SenseMaker®®
1.1. Develop signification frameworkDevelop signification framewo...
1a. Triggering1a. Triggering
storiesstories
Example of a Story (GlobalGiving data)Example of a Story (GlobalGiving data)
This library is located in Kibera Otiende opp...
 Insert short Rimisp storyInsert short Rimisp story
1b. Questions to1b. Questions to self-indexself-index
Storyteller gives meaning to own storyStoryteller gives meaning to o...
The questionsThe questions
 Probes for additional story context: 9 questionsProbes for additional story context: 9 questi...
2. Strategies for Data Collection2. Strategies for Data Collection
 paper-based, then typed uppaper-based, then typed up
...
3. Data Analysis3. Data Analysis
 Any combination of triad, polarity, MCQ,Any combination of triad, polarity, MCQ,
demogr...
Stories (n = 2530)Stories (n = 2530)
 #1 Food#1 Food
 #2 Shelter#2 Shelter
 #3 Safety#3 Safety
 #4 Water#4 Water
 #5 ...
4. Feedback loops4. Feedback loops
 Dissemination and institutional feedbackDissemination and institutional feedback
 Pa...
Next Steps for GGNext Steps for GG
1.1. Improving story collection: significationImproving story collection: signification...
ApplicationsApplications
 Organizational aggregation from diversityOrganizational aggregation from diversity
 Rolling ba...
More informationMore information
 http://www.cognitive-edge.com/blogs/news/2010/09/final_report_pubhttp://www.cognitive-e...
Sensemaker for Partos Plaza  - Irene Guyt
Sensemaker for Partos Plaza  - Irene Guyt
Sensemaker for Partos Plaza  - Irene Guyt
Sensemaker for Partos Plaza  - Irene Guyt
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Sensemaker for Partos Plaza - Irene Guyt

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  • Background to the logic
    Core elements
    An example of a ‘signification framework’
    Showing analysis in action
    Talking through some details
  • GG – web based ‘connector’ – donors with community projects that need support. Low threshold to get listed, no guarantees, people donate 10, 25, 50.
    Since 2002, 119,605 donors $31,769,585 to 3,126 projects.
  • Need ways to provide decision makers with the ability to ‘see the world’ through eyes of their customer, their staff, their citizens or even their enemies.
  • Closed learning cycle
  • Stress importance of self-indexing, it gives ADDITIONAL meaning to
  • The platform would provide continuous feedback and trends analysis to implementers (via the website) and stories/NGO announcements to community members (via SMS) that will support periodic community meetings.
  • Sensemaker for Partos Plaza - Irene Guyt

    1. 1. Making Sense ofMaking Sense of SensemakerSensemaker®® :: Evaluating development initiativesEvaluating development initiatives through micro-narrative capture and self-through micro-narrative capture and self- tagging in Kenyatagging in Kenya Partos PlazaPartos Plaza October 14, 2010October 14, 2010 Dr. Irene Guijt, Learning by DesignDr. Irene Guijt, Learning by Design with John Hecklinger and Marc Maxson (GlobalGiving)with John Hecklinger and Marc Maxson (GlobalGiving)
    2. 2. Connecting Needs ChronologicallyConnecting Needs Chronologically  Learning by DesignLearning by Design • find a methodological option for ‘seeing’ emergencefind a methodological option for ‘seeing’ emergence  Cognitive EdgeCognitive Edge • test application in international developmenttest application in international development  Rockefeller FoundationRockefeller Foundation • fund methodological innovationfund methodological innovation  GlobalGivingGlobalGiving • generate non-intermediated target group feedback flowsgenerate non-intermediated target group feedback flows
    3. 3. Options to Find and ExpressOptions to Find and Express  StatisticsStatistics • Decontextualised fragments (end results/inputs)Decontextualised fragments (end results/inputs) • Outliers ignoredOutliers ignored • Hard to get to explanatory levelHard to get to explanatory level • Work well within the known/knowableWork well within the known/knowable  StoriesStories • Few in-depth voices, sometimes purposively selectedFew in-depth voices, sometimes purposively selected (dilution)(dilution) • Biases of the intermediaryBiases of the intermediary • Representativeness assumed; validity questionedRepresentativeness assumed; validity questioned • Richness cannot be dealt with if many storiesRichness cannot be dealt with if many stories
    4. 4. But when you’re off the beaten path…But when you’re off the beaten path…  future doesn’t necessarily mirror the pastfuture doesn’t necessarily mirror the past  ongoing sensing of multiple perspectivesongoing sensing of multiple perspectives neededneeded  real time feedback loopsreal time feedback loops Stories, then Statistics in SenseMakerStories, then Statistics in SenseMaker®®
    5. 5. GlobalGiving’s M&EGlobalGiving’s M&E  self-generated reportsself-generated reports  incidental evaluatorsincidental evaluators  postcards from the fieldpostcards from the field ButBut  closer to userscloser to users  continuouscontinuous  not mediatednot mediated
    6. 6. Design FeaturesDesign Features  Numbers derive meaning from their contextNumbers derive meaning from their context  Stories told by people are filters through which theyStories told by people are filters through which they make decisionsmake decisions  Mass capture of fragmented material, self signified atMass capture of fragmented material, self signified at the point of origin gives quantitative datathe point of origin gives quantitative data  Semi-constrained signifiersSemi-constrained signifiers  Visualization most important human sense-makingVisualization most important human sense-making capability (patterns, then stories)capability (patterns, then stories)
    7. 7. Methodological LogicMethodological Logic 1.1. Prompting question or imagePrompting question or image • triggers a lived experiencetriggers a lived experience 1.1. StorytellerStoryteller self-indexesself-indexes storystory • gives meaning, but can be done by othersgives meaning, but can be done by others 1.1. Software detect patternsSoftware detect patterns • visual patterns among storiesvisual patterns among stories 1.1. Sense-making in dialogueSense-making in dialogue • people discuss patterns and story clusterspeople discuss patterns and story clusters 1.1. Act on patternsAct on patterns • Weak signals phase shiftsWeak signals phase shifts • Stimulate beneficial patterns; dampen undesirable onesStimulate beneficial patterns; dampen undesirable ones
    8. 8. Designing Use of SenseMakerDesigning Use of SenseMaker®® 1.1. Develop signification frameworkDevelop signification framework • Content and ‘translation’Content and ‘translation’ 1.1. Strategies for data collectionStrategies for data collection • Who, how, how often, how long, etc?Who, how, how often, how long, etc? 1.1. Data analysisData analysis • Where to nest learning?Where to nest learning? • How will analysis take place, who will be involved, what isHow will analysis take place, who will be involved, what is the rhythm of analysis (how often at which level?)the rhythm of analysis (how often at which level?) 1.1. Feedback loops with the systemFeedback loops with the system • Who needs to look at what aspects of the initial analysis andWho needs to look at what aspects of the initial analysis and how, in order to enable change?how, in order to enable change?
    9. 9. 1a. Triggering1a. Triggering storiesstories
    10. 10. Example of a Story (GlobalGiving data)Example of a Story (GlobalGiving data) This library is located in Kibera Otiende opposite the upgrading project.This library is located in Kibera Otiende opposite the upgrading project. It started some years back not more than three years. Their library cameIt started some years back not more than three years. Their library came because most of children in the community lacked textbooks. Theybecause most of children in the community lacked textbooks. They demanded that in school everybody is entitled to to homework and indemanded that in school everybody is entitled to to homework and in order the homework to be done and saw the way forward is to contributeorder the homework to be done and saw the way forward is to contribute together and share the problem equally and raise some money for thetogether and share the problem equally and raise some money for the library construction then for the books. They struggled to raise thelibrary construction then for the books. They struggled to raise the money and at long last they raised and built a well equipped nurserymoney and at long last they raised and built a well equipped nursery textbooks because the of the victims were primarians. Now the childrentextbooks because the of the victims were primarians. Now the children are happy and also the load that parents had is reduced. The communityare happy and also the load that parents had is reduced. The community is very proud because their children are passing and doing well duringis very proud because their children are passing and doing well during their national exams. That is a sign of excel to parents and also childrentheir national exams. That is a sign of excel to parents and also children since they are making good use of the library and materials available.since they are making good use of the library and materials available. The library is there upto date and still going strong.The library is there upto date and still going strong.
    11. 11.  Insert short Rimisp storyInsert short Rimisp story
    12. 12. 1b. Questions to1b. Questions to self-indexself-index Storyteller gives meaning to own storyStoryteller gives meaning to own story a.a. TriadsTriads b.b. PolaritiesPolarities a.a. Multiple optionsMultiple options b.b. ‘‘About you’About you’
    13. 13. The questionsThe questions  Probes for additional story context: 9 questionsProbes for additional story context: 9 questions about each story; 5 questions about storytellerabout each story; 5 questions about storyteller This community effort improved … Social relations Physical conditions Economic opportunities
    14. 14. 2. Strategies for Data Collection2. Strategies for Data Collection  paper-based, then typed uppaper-based, then typed up  3000+ stories (2700 usable) in 10 weeks3000+ stories (2700 usable) in 10 weeks  via 50 volunteers (snowball) for 1500$via 50 volunteers (snowball) for 1500$ Incentives matter, so does chasingIncentives matter, so does chasing Target a focused time to trigger flood of storiesTarget a focused time to trigger flood of stories
    15. 15. 3. Data Analysis3. Data Analysis  Any combination of triad, polarity, MCQ,Any combination of triad, polarity, MCQ, demographicsdemographics  Explorer: glance, browse, compare, range,Explorer: glance, browse, compare, range, distribute, cluster, graph, landscapedistribute, cluster, graph, landscape
    16. 16. Stories (n = 2530)Stories (n = 2530)  #1 Food#1 Food  #2 Shelter#2 Shelter  #3 Safety#3 Safety  #4 Water#4 Water  #5 HIV/AIDS#5 HIV/AIDS  #6 Education#6 Education Experts/implementers (n=65) Why self-signify?Why self-signify?
    17. 17. 4. Feedback loops4. Feedback loops  Dissemination and institutional feedbackDissemination and institutional feedback  PartnershipsPartnerships  Community feedbackCommunity feedback  Geo-taggingGeo-tagging  Global GivingGlobal Giving
    18. 18. Next Steps for GGNext Steps for GG 1.1. Improving story collection: significationImproving story collection: signification framework & data uploadingframework & data uploading 2.2. Experiment with different incentivesExperiment with different incentives 3.3. Expand geographic scopeExpand geographic scope 4.4. Integrated technology - combined web-SMSIntegrated technology - combined web-SMS platformplatform 5.5. Cross-organization learningCross-organization learning 6.6. Use ‘needs’ stories for advocacyUse ‘needs’ stories for advocacy 7.7. Partner rewards programPartner rewards program
    19. 19. ApplicationsApplications  Organizational aggregation from diversityOrganizational aggregation from diversity  Rolling baselinesRolling baselines  Cross-organizational comparisonsCross-organizational comparisons  Focused moments – MTRs, final evaluationsFocused moments – MTRs, final evaluations
    20. 20. More informationMore information  http://www.cognitive-edge.com/blogs/news/2010/09/final_report_pubhttp://www.cognitive-edge.com/blogs/news/2010/09/final_report_pub  http://www.youtube.com/watch?v=ZV-lcTuUawc&NR=1http://www.youtube.com/watch?v=ZV-lcTuUawc&NR=1  http://www.sensemaker-suite.com/sensemaker-videos.htmlhttp://www.sensemaker-suite.com/sensemaker-videos.html

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