Bricolage is the perfect method to understand social systems

This term will be familiar to many. But for those who do not know, I use the term bricolage as intended by Lévi-Strauss.

The simple explanation is:
creating something by using whatever is readily available (even more simply - mixed media).
A more convoluted explanation is:
strategically and pragmatically using different methods from different disciplines to reach the desired outcome (solution).

The first explanation is more associated with crafts but does capture the essence of the approach. The second definition is a more accurate description of how I approach and explain why SenseCatcher works.

When dealing with social issues, we are dealing with 'complicated heavy stuff' to put it in everyday 'lingo.' 

In reality, we are, by definition, dealing with complexity, and complex adaptive systems in particular. 

Now, I could leave this sentence out, but then, we would be aiming politely in the dark. Language, unfortunately, is essential, and vocabulary is necessary to help us refine our thinking. There - apology made.

To solve problems in such systems, we need a useful and appropriate method.

By using the bricolage method, I am referring to a mixed-method that allows us to explore and understand these types of complex problems—the 'messy social stuff.'

My argument is that if I combine abductive reasoning and the freedom that bricolage provides me to understand this 'social stuff', we can then focus our attention to better understand what we are looking at. Traditional methods have not worked. They, unfortunately, are the wrong methods applied to poorly conceived models.

Without getting bogged down on semantics, I will simply say that reductive linear thinking is terrible to understand anything social in nature.

The new model's principle is based on the notion that we need to 'explore actively' rather than 'passively.'

We need to be amongst the data, moving with the data (data here refers to humans). Suppose we place ourselves outside of the system. In that case, we are looking at (the data) or attempting to manage the system - we immediately fall into the reductionist frame of mind. That skews the observations and distorts and pollutes the outcomes. Problems are created rather than solved.

Why Bricolague?

Let us look at bricolague a little more to see why it is useful. We are crossing borders between the different knowledge domains of disciplines (silos) – combining/weaving, mixing/picking different methods (informed by the context and circumstance) that challenge, enhance and surface alternative interpretations.

This reality mirrors how our cognitive networks process information - much like the way a designer solves problems.

The underlying approach is one of unfolding discovery. Like a sailor from the 15thC – 17thC navigating their way into the unknown, using multiple data sources (visual, audio, textural – the senses) – the cacophony of reality.

The creation of meaning emerges (comes out) from the interrelationships and the dynamics within the problem. In our case, the messy social stuff resulting when humans are connected and influence each other by just being human.

No single human knows in advance how a conversation ends between two people, let alone when more are involved. The data that emerges from any discussion is best captured and fully understood if the 'manager'* mingles amongst the data. True, the manager will impact on the data.

However, It can also be argued that the manager can become the trigger (vector) that guides the system (the collection of people) strategically in the direction that is best for the business.

In social research, quantitative methods are not helpful. It is really like using beautiful calculations to understand the geocentric universe: great tools but the wrong model.

Data collected and disconnected from the context is the same as sterilizing the data and forcing a narrative onto meaningless fragments.

The scientific method has been successfully used to study and explain existing phenomena to precisely predict the solution. This approach is very good in the natural world. But in complex systems, this is not possible. We can only suggest possible futures and work with possibilities and probabilities. 

The unknown solution cannot be solved using deterministic methods. We need 'flexibility' to deal with uncertainty, the undefinable, irregularities, and ambiguity.

We need to ask: 'does the method we use allow us to see and address the social reality?'

Bricolage allows us heterogeneity and variation. From a designer perspective, we need to draw on existing knowledge (any discipline) to navigate the way best forward – agency of change. The mindset is one of the negotiators, facilitator, visualizer, navigator, mediator, and coordinator. Complex problems need method flexibility to explore complex, indeterminate problems.
Word of caution – the approach is not one of DIY. Using bricolage requires sensitivity and clarity (ontological and epistemological) both to where the method(s) has been used and where it is to be used – sensitivity is required - that simple.

*I placed this asterisk next to the manager because the manager plays multiple roles. Collector of data, action research, impacting on the data, manipulating the data - all true. But, the manager knows all this. In contrast, with a deterministic mindset, the manager pretends to be looking at the perti dish experiment from a distance and commits many errors without even realizing it.

Essentially the manager's point of departure is that the data will behave in a certain way (deterministic). The manager then designs the paths to get to the solution - all in advance, even before anything happens.

To explain this approach's danger and drive the point home, consider a conversation between two people given an 'x' topic. After one hour, they end the conversation, and they conclude 'y'.
Now - consider the same topic with the same two people, but you add a third person. The concluding results of the conversation will never be 'y'; it might be 'y1' or most probably 'z'.
The point is simple - the solution is not about 'FINDING' the mysterious hidden perfect truth - it does not exist.

Instead, it is about allowing people to arrive at an agreed solution that they can live with and are prepared to move along to the desired destination at that point. Any future changes result in a process where everyone agrees to and is part of the new conversation - most probably triggered by new data (shifts in the market). The manager(s) as part of the collection of people (system), can influence and influence the path to the destination. Still, the manager is part of the system; it is a learning process of discovery - for everyone. However - if the manager is not an honorable member of the system and is not listening and faking it - the agents will pick this up. You get what happens in many companies - hostility, lack of co-operation, etc.

Do you see how real this is, but also how difficult and messy it is?
It is so much nicer to sort things out on paper - dish out instructions and then expect the EXACT predicted results. Design the solution like a predictable machine - lovely!

But then do not come crying, saying these people do not listen. These people refuse to cooperate; why are they so uncooperative. You are most certainly killing the potential of high performance with this style of management. It is easy to plan with efficiency in mind, but do not expect it to work other than with robots.