SenseMaker is a pioneering tool that allows for the collection and interpretation of micro-narratives. It enables individuals to express their own interpretations of their personal stories, which are then analysed collectively to reveal patterns and trends. This approach eliminates the bias that can come from traditional survey methods and allows for a more nuanced understanding of complex systems.

The tool utilises a three-step process: capture, signification, and exploration. In the capture phase, participants share their stories. They then signify, or interpret, their own narratives using a series of predefined questions. The exploration phase involves visualising and analysing the data to identify patterns or trends.

SenseMaker is versatile, being applicable in various fields such as monitoring and evaluation, organisational culture, and customer research. It allows for real-time feedback and can be used in any language or culture. It’s particularly effective in uncertain or complex environments, offering insights that can inform decision-making and strategy.

It is also a participatory process, empowering people to share their experiences and perspectives. This not only provides rich data but also fosters engagement and ownership among participants. The anonymised data can be shared back with the community, promoting transparency and learning.

The tool’s design is underpinned by the principles of complexity science and narrative research, combining rigorous academic theory with practical application to deliver a unique and powerful approach to understanding complex systems.

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