Mapping systems with Kumu

A shiftN Academy course

Why?
System maps are a powerful tool to visualize complexity. This hands-on course helps participants to build skills in developing and using a specific format of system maps: causal-loop diagrams, also referred to as influence diagrams. This is a rigorous mapping approach that requires clearheaded thinking. It can be used to pursue multiple objectives:

  • Showing the ‘big picture’;
  • Illuminating the architecture of a complex system in terms of feedback loops and leverage points;
  • Stimulating multi-actor engagement and collaboration;
  • Integrating expert knowledge;
  • Communicating complex messages and stories;
  • Providing access to an evidence base;
  • Developing future scenarios;
  • Identifying options for intervention in the real world.

In this course we will rely on Kumu as a powerful, web-based environment to develop causal-loop diagrams. Participants will learn how to use this rich mapping environment to craft complex, beautiful and richly documented system maps.

Topics

  • System maps as a tool to visualize complexity.
  • Overview of system mapping approaches.
  • Building blocks: variables and connections.
  • Building simple system maps.
  • Structural features: feedback loops, leverage points.
  • Building more complex maps.
  • Group model-building.
  • Deploying and using system maps.
  • System maps and scenario development.
Course language English
Course level Introductory, no prerequisite knowledge of systems thinking or mapping required
For whom Anyone who has a professional or personal interest in tackling complexity by visualization
By whom Philippe Vandenbroeck, co-founder at shiftN, and Liesbeth Jenné, consultant at shiftN
Format 1 full day
Dates 7 June 2018, 09:30 – 16:30h
Location De Hoorn, Leuven, Belgium
Price 400 euro, excl. of 21% VAT (includes meals, refreshments and course material)
Launch offer - 20%
Example of a system map Stress in the workplace

Visualization

Systems Thinking + Cutting Edge Visualization = A better handle on Complexity

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