Visual SenseMaking Framework

visual sensemaking framework

What is Visual SenseMaking?

Visual SenseMaking engages with complexity to reveal patterns which explain and map the thinking process. Visual SenseMaking framework is a dynamic architecture of discovery.

 
 
 
 

The framework is a

dynamic architecture

of discovery

The foundation of Visual SenseMaking consists of the following concepts:

  • Visual thinking
  • Sense-makingent
  • Complexity
  • Narrative
  • Pattern making

To better understand Visual SenseMaking, we recommended you read the pages that consider the concepts independently - the exception being for sense-making. Because Visual SenseMaking is an evolution of sense-making, we'll start with sense-making. 

The Origins of SenseMaking

The term sense-making can be traced back to the 1970s, with three related streams of activity:

  1. 1
    Sense-making was introduced to human-computer interaction by PARC (a research and development company in Palo Alto, California). The main actors were Russell, Stefik, Pirolli, and Card in 1993.
  2. 2
    Information science by Brenda Dervin (often written as sense-making)
  3. 3
    Organizational studies by Karl Weick

Sense-making is interdisciplinary and has come together using ideas from:

  • philosophy
  • sociology
  • cognitive science (especially social psychology). 

Why SenseMaking - What is the Fuss?

The moment we're dealing with situations where cause-and-effect (linear causality) does not explain the outcomes - we have a problem.

The reason we have difficulty solving social problems is that the behaviour of such systems is challenging to model - they are complex. Complex issues are tough to describe dependencies, competitions, relationships and other types of interactions between the system and its environment. The behaviour of the thing (system) we are interested in is adaptive and context dependent. It is unpredictable and not easily understood from its characteristics.

 For this reason, we need complexity science to explain this type of behaviour. 

What is SenseMaking?

It is the process of making sense, and we do this by creating a structure of meaning around the things we do not know or understand.

When faced with ambiguity and uncertainty, we automatically search for meaning. We try to:

 
  • comprehend
  • explain
  • attribute 
  • extrapolate
  • predict.

Sense-making is action-driven and cyclical:

  • What is happening?
  • What do I do next?
  • Does it make sense?
sensemaking framework is a cyclical process

Adding Complexity

The process is iterative, circular, non-linear. It leads to emergence (new understandings) until a plausible narrative makes sense and can stand up to scrutiny and critique. The process is a complex adaptive system. 

It tests existing knowledge and creates new knowledge that enables us to describe the complex world in ways that allow us to take action. 

The driver for inquiry is plausibility. We are not particularly concerned about looking for truth or getting things right. Some people might use these terms to explain their motives – irrespective, it drives motivation.

The process is one of constant rewriting of the narrative by incorporating as much of the collected information and data as possible. The story under construction is a collection of dynamic adjustments and fragmented narratives that are always under scrutiny, adjusted or discarded. The process is iterative - the refining of our understanding goes on until the new reality can be explained satisfactorily - given the known data and information available at the time.

Weick describes sense-making as a micro-mechanism that leads to macro-change over time.

Adding Patterns

Humans are complex pattern-based agents. We see and understand through abstractions and metaphors.

We use patterns to find order and predictability to make sense of things in unknown situations. Patterns are something we actively and instinctively create, as Mary Douglas suggests, ambiguity is the trigger for seeking patterns to construct understanding.

Pattern making and recognition play central roles in our cognition and sense-making and decision-making processes, according to Patterson and Eggleston (2017).

Adding Visual Cognition - Visuality

 
 

Visuality is one of five semiotic modes - the relationship between a sign, an object, and meaning. There is growing interest in the visual mode of thinking, communication, and creation of meaning. We focus on the unification of visuality with the other modes of making meaning. We see visuality as complementary and serving a mutually reinforcing role. 

Complex ideas are articulated and made sense of not only through language but through visual artefacts such as images, icons, symbols, and colour. When we refer to visual thinking, we are not referring to visual facilitation - we are referring to visual cognition.

sensemaking allowed for emergence

Visuality focuses on how meaning is constructed, communicated, and stored through visual means. 

The coding and decoding of visual meaning are an enactment of sense-making. Visual SenseMaking operates simultaneously at an individual and socially shaped level of the meaning making. It is a multimodal discursive dialogue (dynamic) of dense meaning. We're referring here to discourse in the Foucauldian sense of the production of meaning. 

Visuality also acts as pathways that speak to the deep-seated components of human consciousness. 

SenseMaking

The act of visually mapping the fragmented narratives is the codification of Visual SenseMaking. The resulting visual SenseMaps can be those of a structured problem situation, knowledge domain etc. 

The act of mapping is the visual enactment of the system as perceived by the author(s); bracketed by time and focus.

  • SenseMaps are not models.
  • They do not represent reality at any scale or predictions.
  • SenseMaps are visual artefacts of exploration and interpretation.
visual sensemapping framework

SenseMaps are visual records of what the author(s) has considered and articulated. By definition, a complex system can never be modelled or fully defined. We can only hope to have glimpses of the patterns of the system — each time we consider and articulate the system via the narrative, we gain a different awareness of the system. 

SenseMaps are not static - they are organic and conceptually perceived as dynamic space (boundaries are not constraints within the framework). Any notion of the boundary will be part of the understanding of the system and explicitly attributed meaning.

SenseMaps provide: 

  • A shared understanding and vocabulary of the explored topic.
  • Reveal the micro and meta relationships in the fragmented narratives depicted as visual elements (icons, images etc.).
  • The story has an emerging organic structure of nodes and networks.
  • The nodes and network carry encoded meaning, including becoming containers or links to data or information.
  • The shape and structure of the story can be reshaped and changed at any point.
  • Infinite historical records of narrative structures and meaning, including associated data.
  • Shared communication of understanding and self-awareness.
  • The means to make the invisible visible (e.g. silenced individuals, taboos, power relations, struggles - unmasks social reality).
  • A vehicle for more voice to be heard and taken into consideration.
  • Powerful tool of influence, shaping and perception. 
  • Powerful tool for learning and change
  • Interpretations of reality - not a mirror. 
  • A multisensory impact by combining rationality and emotions.
  • Ability to understand systems as wholes and the relationship between the micro and macro.

Mapping as a Process - Visual SenseMaking

As individuals or collectively, we do not have a single agency. We behave differently in different circumstances and with different people.

When mapping, the configurations of behaviour create patterns structured around micro-narratives (fragments). They emerge and are self-organizing. Each reconfiguration and composition of patterns move the narrative to a new point of stability until a plausible story emerges and can be scrutinized and tested.

I understand what visual sensemaking framework is

Meaning evolves and settles around an attractor of plausibility. The trajectory of the story can change at any time with the introduction of further data. Depending on the vector component of the new data, the narrative (system) can remain in relative stability or change direction radically, responding to the magnitude and direction the input provides (vector).

Data can be rejected or incorporated, creating little or substantial structural changes to the story. SenseMaps are never final nor finished - they are live artefacts that provide both a history and remain open to potential changes in the future.

Mental Models and Biases

These are important. We deal with both mental models and biases separately in different articles.

SenseMaps - a Tool for Managing Complexity

In our complex working environment, we need tools that can assist us in understanding and intervene in problems with high levels of uncertainty.

When we are dealing with complex systems, we have no means to explain or predict the future because its behaviour changes, evolves, and adapts.

Managing these systems can be tricky.

Complex systems have the following characteristics:.

  • Dynamic networks of interactions that follow comparatively simple rules.
  • The interactions are non-linear (small inputs or stimuli can result in unpredictable outcomes).
  • There are reinforcing feedback loops that can vary in quality.
  • The behaviour of individual parts does not necessarily convey the behaviour of the whole system.
  • Establishing a boundary can be difficult because these systems are generally open.
  • These systems have a history, they evolve, and their past is co-responsible for their present behaviour.
  • Interactions are primarily (not exclusively) with immediate neighbours and the nature of the influence is modulated.

Considering the behavioural characteristics of complex systems, we can see that using a tool like the Fishbone Diagram on such a system will be dangerous. The tool is for simple or complicated problems. It only works with cause and effect (linear) behaviour - aiming to identify the root cause of a problem.

The idea is that you solve a problem by breaking it up into smaller problems and then the solution is nothing more than putting it together. It works because we identify the order and use the defined logic to solve the problem.

Causality explains events in terms of a unidirectional unfolding chain of events from the past to the future. It cannot address a problem with any of the characteristics of complex systems. These problems are about order and logic.

Getting back to - how do you deal with complex problems?

 
 

First: A CHANGE OF MINDSET IS REQUIRED.

With casualty, you can safely operate outside of the problem, and you can treat the problem as a static entity. It does not mean it will be easy, but the problem is knowable from the outset and has order.

With complex problems, on the other hand, you are dealing with ambiguity. The thing you are looking at does not have a definable static entity - it is continuously fluctuating and responding to the forces (stimuli) from both inside and outside (environment) of the system. It does not follow a discernible order.

Agents interact with each other using simple rules of coordination and cooperation in response to stimuli.

The problem solver after having created a SenseMap has an awareness of the system, its challenges, hot spots, weaknesses, and strengths - a more in-depth understanding and state of the system. Although the system is not fully known, it is also not random or fickle. It has a degree of agency and order ascribed to it.

The way a manager intervenes ('solves the problem') - the focus of attention should be on the interactions (dynamics) between the components (agents) while paying attention to the effects the stimulus has on the system (information, resources, ideas, new agents etc.).

The properties of the system emerge from the interactions - not from individual components. Stimulating a system with inputs will change the system to a new, better or worse state. The degree of change will be relative to:

  • Location of intervention within the system.
  • The intensity of the stimulus.
  • Nature of the stimulus.
  • Frequency etc.

The art of intervention is about nudging and guiding the system in the direction of the intended solution. Predicting the trajectory is not possible; the interactions and feedback loops driving the system towards the intended state is an emergent property in itself. The emergent properties become the source of new data feeding back into the system - capable of acting as a stimulus on its own during such trajectory.

complex systems unpredictable behaviour

Any stimulus can have an amplifying or dampening effect on the system. We always need to remain mindful - there is a multitude of interactions taking place, and all are context-dependent. For example, John and Harry up to until one hour ago were the best of friends. Together they had a significant influence on the system. But they have had a massive bust-up. All this happened just before a carefully managed stimulus is introduced to shift the system in the desired direction. The manager is unaware of the new events. The results will most certainly not have the desired effects. What will happen? No one knows. 

The manager's attitude and disposition needs to be one of careful observation. In reality, the manager is conducting an in vivo experiment - watching the dynamics, changes and any emergent behaviour. The manager must be ready to make any required adjustments. You can see that automation, complacency, one-size-fits-all attitudes will be catastrophic 99% of times. 

Effects of any inputs need to be observed in real-time along the way. The attitude should be about the journey and responding to changes – steering the system in the direction of the desired objective, not forgetting that at any time the system might evolve into the desired state before the calculated endpoint. Such observations require intervening in the system to 'slow' it down as it were.

It is not about deciding on the endpoint (solution) nor forcing/imposing changes onto the system. The approach works from the bottom-up.

Problem solvers can also be active participating members of a complex system. Initiatives are not about hierarchy, power or formal rules. It is about willingness to participate and take mindful and educated action. 

Visual SenseMaking Framework (VSMF) is an emergent property itself. Finding direction, building commitment and overcoming challenges are accomplished and triggered by the VSMF process. It is a social action-based process ideal for managing uncertainty.

The art of intervention is about nudging and guiding the system in the direction of the intended solution. Predicting the trajectory is not possible; the interactions and feedback loops driving the system towards the intended state is an emergent property in itself. The emergent properties become the source of new data feeding back into the system - capable of acting as a stimulus on its own during such trajectory.

Any stimulus can have an amplifying or dampening effect on the system. We always need to remain mindful - there is a multitude of interactions taking place, and all are context-dependent. For example, John and Harry up to until one hour ago were the best of friends. Together they had a significant influence on the system. But they have had a massive bust-up. All this happened just before a carefully managed stimulus is introduced to shift the system in the desired direction. The manager is unaware of the new events. The results will most certainly not have the desired effects. What will happen? No one knows. 

The manager's attitude and disposition needs to be one of careful observation. In reality, the manager is conducting an in vivo experiment - watching the dynamics, changes and any emergent behaviour. The manager must be ready to make any required adjustments. You can see that automation, complacency, one-size-fits-all attitudes will be catastrophic 99% of times. 

Effects of any inputs need to be observed in real-time along the way. The attitude should be about the journey and responding to changes – steering the system in the direction of the desired objective, not forgetting that at any time the system might evolve into the desired state before the calculated endpoint. Such observations require intervening in the system to 'slow' it down as it were.

It is not about deciding on the endpoint (solution) nor forcing/imposing changes onto the system. The approach works from the bottom-up.

Problem solvers can also be active participating members of a complex system. Initiatives are not about hierarchy, power or formal rules. It is about willingness to participate and take mindful and educated action. 

Visual SenseMaking Framework (VSMF) is an emergent property itself. Finding direction, building commitment and overcoming challenges are accomplished and triggered by the VSMF process. It is a social action-based process ideal for managing uncertainty.

 
 
 
 

"A social action-based process ideal

 for managing uncertainty"

 
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References:

Patterson, R. E., & Eggleston, R. G. (2017). Intuitive Cognition. Journal of Cognitive Engineering and Decision Making, 11(1), 5–22.

Frost, R., Siegelman, N., Narkiss, A., & Afek, L. (2013). What Predicts Successful Literacy Acquisition in a Second Language? Psychological Science, 24(7), 1243–1252.

Weick, K. E. (2001). Making sense of the organization. Oxford: Blackwell.