The Practice & Art of Thinking

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Chaos, Complexity and Sense Making in Problem Solving

It occurred to me recently that these concepts can be daunting and a serious turn-off for some. They are, however, very useful concepts, especially in the highly-changing and complex environment we live in. If we want to solve problems, it would be smart for us to understand them.

To attempt to explain them, let us consider the game of pick-up sticks also known as Mikado (originating in Hungary).

image source unknown.

image source unknown.

When we drop the sticks, they all fall in a heap and there is no rhyme nor reason about the way they land. They are just a bunch of beautifully shaped sticks, randomly scattered on a table. It appears chaotic.

Problems at first seem very much like this – they are confusing and jumbled up – a little like life can be. We touch on something and something else is affected. Just like the sticks, you attempt to move one stick and other sticks move.

What one really needs to do is approach the situation and look for the patterns, the leverage points, and the relationships between the sticks. We need to create meaning and make sense of the data (sticks) in front of us.

The sticks stop appearing to be chaotic because we have been through a process of sense making and essentially ‘tamed’ the chaos. We have attached meaning to the relationships between the sticks, the spaces and gaps. We start to observe and spot the emerging points where action can take place.

After ‘listening’ to the data – observation and learning – we start to tame the chaos. It becomes familiar and we feel comfortable with the patterns that once were so strange and unfamiliar. Nothing has changed; all we did was go through a process of reasoning and sense making.

Problems are very much like this. At first, we are faced with unfamiliar and a highly-interconnected jumble of issues but, as we slowly interact with the data, we learn and make sense. We start to be able to plot the landscape and it becomes familiar. At this point, we are able to develop a theory that explains the situation and we are able to identify solutions to the problem.

I have not explained what chaos, complexity or even sense making is here because I have done so in many previous posts. What I wanted to achieve in this post is to use a metaphor of the game ‘pick-up sticks’ to illustrate how simple these concepts can be and how they are interrelated.

Reality remains chaotic and complex – the sticks remain a heap – all that has changed is that we are able to articulate and understand it. We tame it not by having changed anything; the only thing that has changed is that we have internalized and understood the reality. Reality becomes familiar and we are able to navigate through the various situations.

Image source - LOR

Image source – LOR


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How do we deal with change?

The next few posts are loosely connected under the theme of ‘rationality’. They explore rationality from different perspectives.

Change is not an easy thing to manage. To be able to use a systematic approach, like a formula, to orchestrate change would be great. There are many methods and theories that have been written about the promise to facilitate change.

Some approaches are quite complicated and require the ‘conditions to be just right” for the method to work. In other words, they are fragile and might only work in very specific conditions.

Change management has evolved over the last fifty years. Up to the beginning of the 1990s, the focus was on establishing the foundations and exploring how humans experience change. The underlying theory was based on psychology and human behaviour.

The next decade up to 2000, the principles were applied to business and organizational change management. Up to 2012, we saw the formalization of the profession and the establishment of procedures and rigorous methods. We are now seeing the maturing of the discipline.

There is much to be done for the practice of change management tends to be reactive and ad hoc. The body of knowledge is contradictory and lacking in empirical evidence. There are many hypotheses that have not been challenged or tested. The discipline is now ready to learn – we hope.

We need firstly to remind ourselves what the main objective of the discipline is. It aims to facilitate the organization to continually renew its direction, structure and capabilities to ensure that the ever-changing needs of external and internal customers are met. The organization wants to survive into the future and change management is there to ensure that happens.

This is a great objective, however, we now know that, as reported by various writes (e.g. Balogun and Hope Hailey) that there is a 70% failure rate of all change programs that have been initiated. Clearly, something is not working.

Change management is based on the work of Kurt Lewin in 1947. The model is not only linear and static, but assumes that one can design and rationally plan for change to take place.


This is the fundamental problem. There are massive contradictions in the discipline. The main overarching principle is based on the assumption that one can plan and control the change process. It is like saying that you know exactly what is going to happen on your 5 year old’s birthday party with 50 sugar-hyped children. The parents that dance with the flow and channel the energy might possibly live to see the end of the day. Those that think they have everything under control are living with the fairies in the bottom of the garden. Anyone who believes that one can manage change through control and design is living with the fairies.

The paradigm for change management is stuck with systems thinking (first order systems – I will explain this one day soon). Systems thinking talks about emergence and interconnectivity, yet it fundamentally believes that one can design ‘the system’ – control it and plan so that it produces the designed outcomes – yes there is a blatant contradiction. It assumes that all people will always behave in a rational way – the change manager believes s/he knows what people think and therefore is able to have the organization change in the planned way. Sounds like beautiful music.

The problem is that people do not march to the manager’s sound of music. Actually, not even the manager marches to his/her own sound of music. Intuitively we know this yet we plan and believe that if we do ‘x’ and ‘y’ and then ‘z’ will happen and when it does not happen we are innocently surprised.

So, what is the problem with our thinking?

logicChange management deals at the core with people. It is not about managing self-contained neatly inert objects. One is dealing with dynamics and agents behave in a way that is not predictable. As soon as some small change happens (often not detectable), there is a dramatic amplifying effect on the behaviour of the agents (known as the butterfly effect). Individuals will make decisions based on the information they have just received and that same piece of information will be interpreted differently by different agents.

Sounds like chaos – remember the 5 year old’s party? That is exactly what one is dealing with – the attitude one should have is how do we manage highly complex and chaotic systems? This attitude is fundamentally different to that of managing something that we think we can control and predict rationally.

It is not that difficult. It simply requires a fundamental internalization of the way things behave and how to manage them. Once you realize that people are complex adaptive systems, the management approach must be different. You cannot use the same tools that you would use to manage highly predictable and fully-understood behavior (utopia).

Control and micromanagement is really a sign of ignorance. Management by algorithms is a joke to say the least. People who like closure and are not able to sway with constant uncertainty need to change jobs or, better still, need to go to ‘finishing school’ – try the liberal arts!

I would even go further and propose that the nature of thinking required to manage complex situations under conditions of uncertainty is the type of thinking similar to that of visual thinking.

Next week, I will look at the work of Daniel Kahneman.

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Is the Secret to Innovation Management – Creativity? Part 2

Originally, there wasn’t going to be a Part 2 and now there will also be a Part 3.

Current literature on strategic management suggests that for a business to survive current economic times, it needs to be innovative and to be innovative you must be creative.

Is this advice good – to mix innovation with creativity? I do not have a problem with the concept and as a matter of a fact I fully agree. I would even suggest that at the core of everything we do, there should be a good dose of creativity.

Some people hold that innovation is a repeatable process and such processes are at odds with creativity, the reason being that creativity is more about spontaneity and mixing the two is not a good recipe for achieving innovation.

The underlying assumption with this view is that anything that is turned into an algorithm is at odds with any activity that has uncertainty at the core of its function such as creativity, where innovation is an algorithm.

The objective of any business, as stated by Roger Martin, is to turn a ‘mystery’ (the market problem – whatever that might be) into a heuristic and refine it further into an algorithm (repeatable process). The business advantage then becomes how effective the algorithm is to maintain the business ahead of the competition.

The problem, however, is that business stops at the algorithm (which has been the destination) and shifts its focus on managing the production of product ‘X’ that gave it the market advantage. Forgetting that as soon as the product is out there, competitors start to work on how to improve on product ‘X’ in order to capture market share.

Image by Rui Martins

Image by Rui Martins

I created the visual below for a conference in Hong Kong a few years ago on Knowledge Management and Design Thinking. The visual tells the above story of the single iteration of innovation – as a one-off event.

Image by Rui Martins

Image by Rui Martins

The reality is that business must remain in a perpetual, innovative frame of mind. The old algorithm becomes part of one of many other criteria forming part of the new mystery of the emergent market conditions. The frame of mind for this is a high tolerance for uncertainty. Creativity is that capacity.

The innovation 'funnel'' process. Image by Rui Martins

The innovation ‘funnel” process. Image by Rui Martins

If you believe that creativity is the result of maverick geniuses, then creativity has no place in the innovation process because innovation is itself a repeatable process. It is a method that can be used repeatedly so that business has more control over its destiny and is not at the mercy of a bad run of no creative breakthrough.

Creativity is many things and, in a recent post, I suggest that it is the sweet spot of structured chaos. Other people see creativity as:

  • “ … seeing and acting on new relationships …” (Joseph Anderson).
  • “… generating new ideas and concepts, or making connections between ideas where none previously existed.” (Mitchell Rigie and Keith Harmeyer).
  • “… the ability to find new solutions to a problem or new modes of expression; … [bringing] into existence something new …” (Betty Edwards).

Creativity, as described above, is not really that mad moment that happens when ‘the gods’ think we should be allowed a flash of genius. It is really something that can be harnessed and repeated – a method, a process. In this light, creativity is a fitting ingredient for innovation. It just needs to be managed and understood.

If one looks at successful innovation leaders (I know a few people that are very good at this – Swee Eng Chen from Australia is one), they describe the process of innovation as having a structure or a process where people have quality conversations that are facilitated by the leader (not forced). The process might at times feel chaotic but is managed by establishing a scaffolding structure. This structure is essentially creating a basin of attraction where talented people with different perspectives are able to have critical conversations, thus maintaining that sweet spot of structured chaos. The emergent creativity leads to the innovative outcome.

This might appear to be not very algorithmic – complex adaptive systems have a different logic but, once the penny drops, the algorithm is repeatable. Whatever you do, do not attempt to approach this from inductive or deductive reasoning. Try abductive reasoning, where the prerequisite of ‘mental agility’ becomes an emergent property that can be channelled when the leader has the right mind-set.

Part 3 will look at management as the issue that could be blocking the use of creativity in innovation.

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Creativity is for Everyone

David Kelley (philosopher and founder of IDEO) proposes that everyone has the ability to be creative. We simply need to ‘touch the snake’. We need to lose our fear of the chaos of creativity. The TED video is about 12 minutes long.

Notice the story of Doug Dietz and how he used the impact of visuality to redesign the experience children have who require MRIs at the pediatric department of the Children’s Hospital of Pittsburgh. Before his redesign, 80% of the children needed to be sedated. After the redesign, only 10% needed to be sedated and some actually wanted to return to play at the MRI Pirate Island.

Pirate Island - screen shot of TED Talsk Video by

Pirate Island – screen shot of TED Talsk Video by

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Creativity – The Madness of Creativity

This post is a TED talk by Elizabeth Gilbert (author). She does a beautiful job in describing the madness of the creative process. I have chosen the video because the presentation describes creativity, not only as a complex adaptive system, but the notion of basin of attraction is also described – pay careful attention. The video is 19 minutes long – I watched it a few times and got something different every time.


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Creativity as a Complex Adaptive System

In the previous post on creativity, I considered Poincaré’s explanation of creativity. If one takes a closer look at his detailed explanation of how creativity happens in the brain, he used the notion of atoms being unhooked, dancing freely and emerging with the solutions that are critically analyzed by us in the conscious phases.

The explanation he gives could easily be reframed from a complexity perspective. I use the term loosely for the simple reason that there is no unified framework for complexity theory. The term does, however, refer to concepts and behaviours such as:

Eureka - By Rui Martins

What is this – exclamation mark, a hat? – By Rui Martins

  • Systemic interdependence;
  • Leading to things like non-linearity;
  • Emergent order creation;
  • Unexpected dynamics;
  • Multiple basins of attractions;
  • Limited predictability;
  • Self-organising;
  • Agents change behaviour and learn (not necessarily people);
  • Feedback;
  • Stochastic (non-deterministic);
  • Heterogeneous (diversity) agents
  • Changing network between agents;
  • Hierarchical organisation
  • Complex adaptive systems have an open-ended evolution;
  • Building blocks.

To attempt to explain creativity using all the concepts above would be beyond the scope of the objective of any post. However, I list them here as I will be referring to different ones in future posts.

Using the concept of attractors (from chaos theory) – where the dynamic system finally settles over a period of time into basin space – one could also interpret the creative process as a strange attractor. The ‘noise’ in the unconscious phase feels like one is in a state of chaos, which emerges (over time) or settles as order (this being when the solution is arrived at). Stability remains until the next turbulent phase of creativity is triggered by the need to  answer a new question or solve a new problem.

Example of a strange attractor (Lorenz attractor) Created by XaosBits using Mathematica and POV-Ray.

Example of a strange attractor (Lorenz attractor) Created by XaosBits using Mathematica and POV-Ray.

The mind could be considered as a state phase (an imaginary map of all the possibilities open to the system), where we have a massive amount of resident attractors (mental categories – one per concept we have knowledge of and have learned). When we are confronted by a question/problem/challenge that we wish to innovate or solve, creativity could be considered as the trajectory followed towards the strongest attractor – this explains why we tend to think of one thing rather than of something else – the starting point was in the basin space of attraction of a particular idea. The initial condition is strongly determent by our worldview (this is unique to each individual – even though it is culturally influenced to some degree).

The mind’s state space is highly complex. The starting point for each individual is different and constantly changing, depending on the basin of attraction tendency that the individual is in at the time (this varies over time and depending on what forces [ideas] one is exposed to). The path or trajectory that the creativity/thinking will take is impossible to predict. If this were not the case, then the act of creativity would be repeatable, controlled, turned on and off and not so painful (see the next post – a TED presentation where Elizabeth Gilbert talks about the elusive nature of creativity).

Minor perturbations cause thinking to switch to a different attractor. Different external stimuli (sounds, ideas, drugs, alcohol), memory, even thought trajectories, can cause perturbations. This causes the landscape or terrain to change (see previous post), which in turn will surface new categories/patterns in the form of attractors that form the landscape. The mental attractors are in constant evolution as we mature, learn and shape tacit and explicit knowledge.

Creativity from a complex adaptive perspective could be seen as a dynamic where information, knowledge and different perturbations cause the network of the brain to reconnect. The reconnection refers to the changing of the flow of signals between agents and over the network and not the actual physical restructuring of the brain’s network.

The creative eureka moment is when the random interactions between the multiple agents settle around a basin of attraction long enough. I say long enough because after some testing, if the idea remains feasible, it validates the idea as creative. If it is not, the attractor is temporary and moves on until a strong attractor emerges, where the actual confirmation of creativity happens.

The YouTube video below (7 minutes long) explains some of the concepts of complexity. It appears not to make sense at some points but bare with it.