“The real voyage of discovery consists not in seeking new landscapes, but in having new eyes” – Marcel Proust
In this vast existence, from the movement of a blade of grass to the explosion of galaxies, it is difficult and complex to find a reason or cause for a particular event. When looking at it superficially without digging deeper, we can point out obvious reasons for an event to occur, but that may not necessarily be the only cause. Which brings me to the point I intend to explore; Sense-making. I will go on a meandering and hopefully insightful ramble about what exactly is Sense-making, sensemaking, active sensemaking and naturalising sensemaking; and their role in decision making, businesses and people’s participation.
Big disclaimer here: I will be using the words Sense-making, Active SenseMaking, Sense making, naturalising sense-making and sensemaker software a lot, each of them very intentionally! I hope this can be useful to you (as it was for me to write this) as a glossary of terms or a way of distinguishing the differences without having to go too far down the rabbit hole.
The word sensemaking is a name for the ability to take multiple sources and varieties of data and synthesise it into one picture and make a judgement call based on that. Karl Weick who is considered the father of sensemaking suggests that the term means simply the “making of sense ” (Weick, 1995, p. 4). It is the process of “structuring the unknown” (Waterman, 1990, p. 41) by “placing stimuli into some kind of framework” that enables us “to comprehend, understand, explain, attribute, extrapolate, and predict” (Starbuck & Milliken, 1988, p. 51). Sensemaking is the activity that enables us to turn the ongoing complexity of the world into a “situation that is comprehended explicitly (Weick et al, 2005, p. 409).
Little conventional details (like that hyphen) can act as distinctive markers that introduce novelty in soft ways, distinguishing one meaning from another; it’s a verb rather than a noun, something people do. Our use with a hyphen points specifically to our approach as one of the five recognised schools of sense-making/sensemaking. When you see that hyphen, think of the phrase “making sense of the world in order to act in it”. The primary concern of sense-making is with supporting contextually-appropriate decision making.
Whilst Sense-making can be enabled and scaled using digital ethnography (such as SenseMaker® software), the process itself requires a human element of sense-making, that is augmented or super charged by the use of SenseMaker® software. So whilst SenseMaker® will give you data at a scale and in a format that you may not have been able to achieve otherwise, the combination of a) SenseMaker data and b) methods designed to social sense-making (such as through workshops/ co-analysis) is where this stuff begins to really add value.
The major characteristics of sense-making are:
Subjective nature: The sense/experience/meaning of the same event will be different for each individual. Here it is important to note the role of epistemic injustice, whereby some people’s knowledge or contribution is unjustly given greater or lower value than others. Sense-making offers the potential to make decision making and organisational understanding more ‘epistemically just’ through providing a platform whereby grounded and experiential knowledge is valued, shared and considered.
An epistemic injustice is when someone is “wronged specifically in their capacity as a knower” that is to say, they are unduly discredited or their knowledge is seen as less valuable, based upon a certain characteristic such as gender, role or seniority for example (Fricker, 2007).
Social activity: Sensemaking is a social activity; sense can be made with a feedback and feedforward mechanism between two or more people.
The proverb of the 6 Blind men and the elephant explains these first two points pretty well:
Where each of the blind men reaches out and touches a different part of the elephant (the system), upon making conclusions for themselves as individuals one man explains to the others “It’s a fan!” as he feels the thin large expanse of the elephant’s ear that swishes by and creates a gentle breeze. “No, it’s a rope,” says another, feeling the long, thin, rough length of the elephant’s tail. “You’re mistaken,” the third man says from near the tusk, “This is a spear…” However, if they were to come together and each describe their part of the elephant or system and start to figure out how it all fitted together, they would stand a far better chance of having an accurate understanding of the whole.
Retrospective: Individuals make sense of things by thinking about past experiences. The golden hour rule applies- the sooner after the event or experience it is recorded, the more reliable and valid the observation is likely to be. There is a distinct difference between memory recall and present moment noticing. So whilst there may be a retrospective element to looking at the collection of stories and data, creating a real-time as possible feedback loop and processes makes for better, more valid data and protects us from the danger of projecting our neat story of the past into an unformed future.
Ongoing: Sense-making is an ongoing process and people will react to situations based on the frequent fashion of sensemaking. Especially the case when operating in Complex Adaptive Systems where the system itself is in a constant state of flux or change.
Cues: It means we should look for the signal, not the innumerous noise when making sense of something. But what is the indicator? This is almost always context dependent on the environment you are operating with, so again highlights the need for a healthy scepticism of one size fits all approaches.
In this approach, organisations actively engage staff or networks to collect narratives and data, analyse it to create feedback loops, whereby sensemaking is participatory and evidence informed as opposed to sensemaking being a purely intuitive process. People’s experiences are important ways to begin to understand what makes situations so challenging. These give important information, identify relationships and changes over time. The more personal and emotionally driven they are, the more memorable they are as well. Multiple stories with these traits help us broaden our perspectives of a situation.
Participants in collective sense-making are encouraged to give more than one kind of story or experience through a set of questions or prompts. In the analysis of the qualitative and quantitative data, the stories remain open to different interpretations. This allows active participation in the sensory system whilst recognising both the individual and the collective implications and perspectives.
A Case Study: Live Learning Partnership (Wales)
During the pandemic, a collaboration of 10 organisations from across different sectors and industries in Wales chose to run an active sensemaking approach to capturing what was happening as the pandemic unfolded, learning in real time about how the rapidly shifting environment people were working with was offering new opportunities and challenges and seismic systemic shifts. The Live Learning Partnership used SenseMaker software to capture these insights through their distributed network. You can see the project story books here, which we hope in years to come will be a valuable reminder of the pivots, challenges and affordances of what the COVID-19 pandemic enabled, from diverse perspectives.
Fricker, M. (2007). Epistemic injustice : power and the ethics of knowing. Oxford: Oxford University Press.
Starbuck, W. H., & Milliken, F. J. (1988). Executives’ perceptual filters: What they notice and how they make sense. In D.C.
Hambrick (Ed.), The executive effect: Concepts and methods for studying top managers (35–65). Greenwich, CT: JAI.
Waterman, R. H., Jr. (1990). Adhocracy: The power to change. Memphis, TN: Whittle Direct Books.
Weick, K. E. (1995). Sensemaking in organizations. Thousand Oaks, CA: Sage.
Weick, K. E., Sutcliffe, K. M., & Obstfeld, D. (2005). Organizing and the Process of Sensemaking. Organization Science, 16(4), 409–421
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