1. Tool to capture or collect information in the form of stories
or fragments in order to facilitate:
Information to emerge:
- what people need?
- what dynamics are at play?
- what services are not yet delivered properly?
- what would people like to see happening?
-…
Decision on:
- Enforcing beneficial patterns
- Dampening non-desirable patterns

2. Methodological Logic
1. Prompting question or image
triggers a lived experience
2. Storyteller self-indexes story
gives meaning, but can be done by
others
3. Software detect patterns
visual patterns among stories
Prompting question
• A single question that triggers people to tell a
story
Story capture
• From whom? Incentives?
• Technology?
• Lots of stories (min.>100-200)
• Visualize patterns (Triads, Dyads, Multi-choice
questions)
4. Sense-making in dialogue
What does it mean for us? For the actors
people discuss patterns and story clusters involved?
5. Act on patterns
Stimulate
beneficial
undesirable ones
patterns;
dampen
How does it inform us to act?

3. Process:
Create set of questions
Create an online form – make available software for users to enter the stories and
make necessary analysis
Collect the stories – paper form and online collection (People tell stories about the
topic and tag them against some questions)
Analyze collected data (increased number of stories bring up the patterns, patterns
and stories help identify issues, solutions and actions and create feedback loops,
involving people in solutions and monitoring)
Based on data analysis propose the next steps and agree on actions to be taken

4. Benefits:
-Easy to use
-better understand the system being looked at and gain insights that allow the development
of appropriate interventions
-can point to areas for further investigation and gaining deeper insight
-ability to have patterns visualized, that every "dot" present is a real experience from a real
person
-when an interesting pattern appears you can explore down into the source data and derive
context and meaning from the experiences displayed
-enables discovery and enhances ability to see patterns
We learned:
-People like telling stores and want acknowledgement
-SenseMaker® Visualizations is important for data presentation
-Stories Help Organizations Learn
-Communities and decision makers see things differently
-Possibility to have unfiltered voices heard is beneficial for the organizations

7. New technologies and rapid feedback loops
in environmental monitoring
1. Air Quality Egg- Experimental technology for measuring levels of NOx, CO in
ambient air quality
- Pilot is running from December 2012 – Data from sensors are online
- Lessons learnt :
 - data collected are not reliable , not in compliance with official reading
- Calibration and re-registration of sensors, further piloting
- - engagement of citizens and institutions (CETI, HMI, University Pg)
-International cooperation : Wicked Device, Citizen Sense, Smart
Citizen Kit
-Air quality campaign for children in kindergarten – 350 children, 8
kindergarten in 6 municipalities

8. New technologies and rapid feedback loops
in environmental monitoring
2. Waste dumps – one of two more often complaints of tourist coming to Montenegro
based on NTO reports in 2011 and 2012
•Piloting mobile application for locating of waste dumps and using online platform for
reporting to utility companies – waste dump campaign March – April 2013
•App and platform, final version in July 2013
•Reports received so far – 260 reports, 170 waste dump locations identified
•Encouraging citizens to participate more active in environmental monitoring, opening
data to public and in decision making processes
•Idea in development – establishing a national system for more efficient waste dump
management based on

9. United Nations Development Programme
Montenegro
http://www.undp.org.me/
Thank you.