Modelling to discover Cause and Effect
Cause and effect lies at the heart of problem solving and decision-
1. Identify the main ideas and issues on magic white board paper.
2. Identify relationships by drawing lines between items that are related.
3. The model is then built with software. The group then assign values to the model,
which allows the group to test assumptions and define holistic solutions.
Applications:
- Sustainable Procurement.
- Partnership mapping /shared services.
- Local Area Agreement indicators and target setting.
// -
_root["nSustainableCommunities"+LA] = (_root["nEnvironmentalQuality"+LA]*0.3) + (_root["nHousingQuality"+LA]*0.1) + (_root["nCommunityWellbeing"+LA]*0.3) + (_root["nEconomicBoosters"+LA]*0.3);
_root["nSustainableCommunities"+LA] = _root.MinMaxDec(_root["nSustainableCommunities"+LA], 2);
Strategy through Modelling
Using a tailored or bespoke learning simulation delegates are able to do multiple runs with the assistance of a facilitator. We suggest that these workshops can help guide strategy development by testing scenarios. While this won’t give perfect answers, as the learning simulation is only an approximation, it will provide a more holistic understanding upon which strategy can be built. Feedback can be used to continuously refine the simulation model.
