The Mythic Or Scientific? source method is a way to make sense of the complex challenges and paradoxes that cannot be simply addressed by working with apparently objective data. It is a way to understand the why of a situation rather than just working with the how.
The Mythic Or Scientific? concept is based on the conventional business approach of only attributing value to objective and analytical processes that are apparently proven and evidence-based. In reality, however, objective and analytical processes can often seem meaningless, especially when used out of context. In the same way that the map is not territory, the myth is not the data, but in the same way that the map gives meaning to territory, the myth gives meaning to the data. Although a myth is commonly regarded as something that is false or of no consequence, a myth is actually a sophisticated description of complex patterns of human behaviour. By working with a mythological structure, human behaviour can be understood and guided at scale. The process works both ways, with myth giving meaning to the facts and the facts providing edge detail and validity for the myth.
The purpose of Mythic Or Scientific? Is to understand the perceptions being generated and perspectives being formed around any data being collected and analysed in a specific set of circumstances. By understanding the bigger story, people can have a wider appreciation of context and also the systemic behaviours driving a particular situation. The Mythic Or Scientific? Method can also be used to work with complex human behaviours at scale within teams, organisations and enterprises. By working with factors that are usually unseen or ignored, the Mythic Or Scientific? Method opens up possibilities and connects people to a sense of meaning, purpose and potential.
- • To make sense of the stories beyond the data
- • To make sense of the context of reported data
- • To understand the stories that give meaning to the data
- • To make sense of the systemic behaviours that are apparently causing data anomalies
- • To make sense of human behaviours at scale
- • To influence human behaviours at scale
- • To validate subjective beliefs about a situation
- • To analyse ambiguities and paradoxes but the situation
- • To appreciate the wider context about a situation
- • To understand the deeper meaning of a situation
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