SenseMaker is a narrative-based method that starts from people's stories and experiences. It is used in action research, citizen participation, citizen science or monitoring, evaluation & learning processes. It is particularly useful to get insights into less tangible aspects such as behaviours, drivers, values, perception and dynamics. It enables a better understanding of reality through the respondents’ eyes and helps generate actionable insights and guide interventions in complex systems and processes.
Narrative Inquiry using
Sensemaker
Collecting micro-narratives
A narrative inquiry starts with the collection of a large number of stories (a few hundred to a few thousand) that are immediately interpreted by the storytellers themselves.
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The starting point is the personal experience around the topic of inquiry, and not the collection of opinions or scoring against pre-defined indicators. This story can be a description of an experience, anecdote, moment, situation, event ...
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It is not a collection of long and in-depth, perfectly constructed stories from a small group of people like it's the case with other storytelling methods. Instead, it is a listening exercise gathering day-to-day experiences, as if they were shared among relatives, friends or colleagues.
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Just as oriental carpets or frescoes generate finer patterns and more detail when more pixels are used, a better representation of reality will emerge when we are able to collect more stories or fragments of experience.
Self-signification
The method then invites respondents to self-interpret their experiences or stories through a set of follow-up questions that provide additional layers of meaning to the stories. This ‘self‑signification’ process reduces the external evaluator or researcher’s bias during analysis and shifts the power of interpretation to the respondent, instead of the external expert.
Emerging patterns
All stories and answers to the questions are digitalised using the SenseMaker software. The answers to the follow-up questions allow us to generate patterns across the multiple and diverse stories, allowing comparison between specific (sub)groups. Clusters, trends, and outliers give rapid insights into the drivers, behaviours, dynamics, contextual factors and actors in people’s lives. This is particularly useful for spotting less tangible aspects of change in complex situations, based on the nuance of people’s lived experiences.
Dominant voices are not favoured above others: every voice, every story holds the same weight in the visualisation and analysis emerging from patterns and trends. It is therefore an ideal method to give equal voice to those people who are often go unheard.
Sensemaking
After an emergent pattern analysis key stakeholders are involved in sensemaking workshops. Patterns and stories are read, discussed and further meaning is given in the group. Different people add relfections and expertise when reading and looking at the findings and raise different questions for further inquiry. The collective nature of sensemaking contributes to new findings and insights.
We work closely together with Cognitive Edge who developed SenseMaker, and use the supporting software in our projects.
“While numbers are useful and can be objective, they are rarely persuasive by themselves as they lack the rich context of anecdotal data. While anecdotes can be persuasive, they lack objectivity and can be easily dismissed. What is needed is an approach that combines the merits of both – the objectivity of numbers with the explanatory power of narrative” (Dave Snowden, Cognitive Edge).
Inspired and curious to know more?
We look forward to discussing with you how to use narrative inquiries with SenseMaker in your organisation or project.
Contact steff@voicesthatcount.net