The Practice & Art of Thinking

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Announcing SenseCatcher Problem-Solving Software

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You might have noticed that I have not being blogging for awhile. The reason is that I have been very busy with the final touches of our new visual problem solving software that will be launching soon. There is quite a bit involved in launching software and this includes the website. I am hoping that the launch will be within the next 2-3 months.

This blog will also change in look. It will be integrated with the website but you will still be able to access it via the old link.

I am also busy writing a white paper and possibly an e-book on problem solving /visual thinking and the software.

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If you are interested in being notified when the software will be launched and/or if you want to receive our free e-book/white paper, head over to and leave your email address. Your personal details will be kept confidential, don’t worry.

You might be interested to know what the software does. Briefly, SenseCatcher is a visual tool that will enable you to unlock and make sense of complex problems or situations and harness the power of visual thinking to target core issues with ease and confidence every time. Often we are overloaded with ideas, documents, spreadsheets, half-finished proposals and so on.

SENSE CATCHER ORGANISES THIS CLUTTER VISUALLY. Your screen becomes a high-tech feltboard, with high-impact imagery and smart tools so you can attach links, recordings, notes etc and also generate coloured heatmaps that make the big issues stand out. Doesn’t matter what industry or sector you are from, SenseCatcher will help to visualize the problem-situation more dynamically than using PostIt notes or mindmaps.

I’ll let you know more about the features of the software closer to launch. Meanwhile, head over to to register your interest.

sensecatcher contact us

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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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Root Cause Analysis – Tracing a Problem to its Origins

This is an important concept and should not be ignored. When solving a problem, you do not want to solve the problem by addressing only the symptoms. You really need to address the issues that cause the problem in the first place.

If you are in pain, you obviously need to take painkillers to alleviate the situation. However, if you have broken your leg, taking painkillers is not going to heal you. True healing is needed before the symptoms can disappear for good.

The above example is easy to understand where the problem is. When the problems are more complex, as social problems can be, jumping in to address the symptoms is not the way to go. If you do this, you may create more problems by complicating issues further. You need to listen to the data and ‘sniff out’ (sorry for the metaphor – but my dogs have been teaching me how good the senses can be) the root cause of the problem.

Make sure you solve the correct problem. Image source: LOR.

Make sure you solve the correct problem. Image source: LOR.

The normal steps to root cause analysis are:

Define the problem
Collect Data
Identify possible causal factors
Identify the Root Cause(s)
Implement Solution(s).

However, let me give you a hint – the process is not linear and sequential.

For instance, to be able to define the problem, you need to have data. To be able to collect the data, you need some indication of what the problem is – otherwise you might be collecting endless, meaningless data. Stalemate? No. I like to see it as a dynamic; a sense making process; a to and fro; a dance.

Image source unknown.

Image source unknown.

We need the assistance of reason.

Let me do a side step and remind us a little about reason.

Broadly speaking, the three thinkers that have changed the concept of reason over time are: Socrates, Descartes and Kant.

The term reason has evolved though time in four basic stages:

  1. Pre-Socratic – reason meant everything that distinguished man from animals – including intuition, mystical experience and dreams;
  2. Socratic – giving clear definitions and logical proofs (Socrates invented logic);
  3. Cartesian – something more like the scientific method – the act of calculating, reasoning and proving, rather than wisdom or understanding. Something we all have the ability to do – unlike wisdom – where some have more than others.
  4. Kantean – he psychologized reason. He said reason constructs or shapes the world, rather than discovering it. It can’t know things as they are in themselves. We cannot know objective reality by reason.


So, in our attempt to make sense and get to the root cause of the problem, we need to use reason as a blend between Socrates’, Kant’s and a touch of Descarte’s definition of reason.  In other words, we need to construct reality as a sense making process (discourse) and we use logic as structure, with the rigours of the scientific method.

Good luck – it is actually quite easy. All you need is the frame of mind to be honest, keep your ego in check and genuinely seek to understand.

Next post, I will explore the notion of complexity, chaos and sense making. I promise it will be super short!

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Tools for Problem Solving – Listening to the data

When we want to solve problems, we need to find out what we are about to do and, to achieve this, we need to ‘listen’ before we take action. This will take us to the data.

To ‘listen’ means to be on the ‘outside’ and by this I mean we need to suspend all forms of judgement. To be objective without any form of preconceived ideas is difficult.

Image by LOR

Image by LOR

We need to have empathy and imagine, as vividly as possible, the data we are collecting in whichever form it might be (text, video, speech, audio, visual etc.). We must try to enter into the teller’s (so to speak) experience as much as possible – imaginatively, respectfully and non-judgementally – before we make an assessment, evaluate and argue. We must collect the data – hard to do but possible.

Without this stage of truly getting to understand what the issues are, not what we think they are, we are not able to solve the root cause of the problem.

The scientific method is the foundation of good problem solving and, for it to work, we need to ‘listen’ to the data. We need to make sure the data is not distorted or contaminated in any way. Our personal worldviews tend to play tricks on the data and we need to be very mindful and aware of this. After all, ‘listening’ is the basic rule of fairness in any conversation.

To be a good listener is very important but, unfortunately, a rare trait. Listening is an act of mental unselfishness, if done correctly. We just need to be aware of how we listen and catch ourselves when we start to make assumptions and draw conclusions while we listen.

Listening does not contradict asking questions and being critical. These are parts of the same thing – honesty.

This brings us to the second stage of collecting of data – to ask critical questions. This does not mean being aggressive, nasty or unpleasant – it simply means making sure the data is not distorted and making sure you have understood the data for what it is, rather than what meaning you might have superimposed onto it and assumptions you might have inadvertently created.

Image source unknown.

Image source unknown.

This active inquiry process is known as logic. This happens after you have collected the data (with an open mind).

Basic logic requires us to demand three things of any argument:
• Clear definitions of terms;
• True data (premises); and
• Logic consistent proofs.

These rules of logic can be applied in any circumstances and to any topic.
No discipline has a special type of logic – logic is logic.

In the process of solving a problem, what we are doing is developing a theory that might explain the problem situation – this then becomes the ‘problem narrative’. We then test the theory by seeing how much it can explain and how robust it is. The theory has to explain the weak and strong points.

Remember – when collecting data about the situation in which you are wanting to make an intervention (like solving a problem) you need to ‘listen’ to the data and make sure you do not contaminate it with personal worldviews

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I normally would present the complete ‘picture’ – in this case, the ‘method’ for problem solving – and then explain what I mean by the individual components of the method. This assumes that the method consists of a combined set of components, which is the case here.

I am using this approach for the simple reason that I think the ‘journey’ (to use an over-used term) is important, allowing us to develop and visualise a personal version of the whole, which would be negated if presented with the conclusion upfront. I will add, many principles of the method have already been touched on throughout this blog.

The method consists of a mix of concepts and specific principles. In this post I will be looking briefly at aspects of the concept of ‘Reason’.

The notion ‘reason’ is important but we tend to park it in the ‘hard basket’ for the simple reason that it has connotations of ‘philosophy’ and such discussion can have the feeling of talking to someone who has forgotten to take their medication – it all seems a bit ‘random’ – as some New Zealanders would say.

Let us quickly look at why reason is important. A great example is that captured in one of Popper’s books (title at end of post), where he suggests that a healthy society is one that is open to ideas and reason. In contrast, non-open societies are (as Popper states) ‘barbaric’, with no capacity for sympathy or understanding for others and diversity of opinion (I could not agree more. We can currently see this happening in our world).

urlWithout the ability to reason, we cannot progress and understand the world around us. We reason to consciously make sense of things and to establish and verify facts. This is exactly what one needs to do to get to grips with any problem situation.

We tend to confuse the term ‘reason’ with logic and use them interchangeably but they are different. To explain, we can use the example of the difference between movement and locomotion. All locomotion is movement but not all movement is locomotion. A tree moves but it does not locomote because it is rooted in the ground. Likewise, all logic is reason but not all reason conforms to the standards of logic.

If logic is the map of what’s really “out there”, reason is the process of trying to read and follow the map. Using another example – reason is the application of logic to one’s perception of the real world, like engineering is the application of physics.

Simply put, reasoning is the actual process of evaluating information and applying logic to arrive at an appropriate (correct) conclusion.

It might now be clear to see why refining our skill of reasoning is essential to good problem solving. It should be considered as the overall concept of the method of problem solving – the balancing force.

I have used the metaphor of the spinning top before (see here in relation to design thinking). We could consider reason as the overall resultant force that keeps the spinning top performing at its optimum – in this case, good problem solving could be seen as a spinning top humming away, where reason is the element that feeds all the other forces and ensures they are performing at peak condition.

From this, it is not too difficult to see why it is vital that we are eloquent at reasoning and understand the importance of reason in relation to good problem solving practice. The cartoon below by Luiz Oswaldo Carneiro Rodrigues stresses the point that data should not be forced and distorted to do what you want it to do. One needs to use reason at all times.

Treat Your Data with Reason - Not With Force. Cartoon by LOR

Treat Your Data with Reason – Not With Force. Cartoon by LOR

I look briefly at reason and ‘listening to data’ shortly in the future.

Book: By Karl Popper – The Poverty of Historicism; The Open Society and Its Enemies. First published in London in 1945, Russia in 1992 and US 2013. This book was on the Modern Library Board’s 100 best nonfiction books of the 20th century. It criticizes Marx, amongst others, for relying on historicism to underpin their political philosophies.

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Problem Solving – Learning and Sense Making

Explaining how something works is important, not only for the sake of knowledge itself, but because explanations can lead to solutions and improvements of our understanding of how something works or behaves.  You cannot fix something if you do not understand what has gone wrong.  You can’t prevent cancer cells from growing if you do not know how and why they started to multiply in the first place.  To interfere in the process, you must understand the process in all its enormous complexity. You need to start somewhere and a theory is the beginning.

This post is a hybrid; it uses observations and years of teaching and solving problems as the source to attempt to explain problem solving.

A large component of problem solving is learning. When we solve problems of relative complexity, we have to go through a stage of learning. I will explore this within the context of problem solving in a future post. For now, let us accept that a good chunk of what we do, when we solve problems, involves learning. The link between learning and sense making is also made.

Learning is a natural process that originates from us and enables us to interact with the environment. Learning is something we ‘do’ – we do not acquire ‘learning’. Like breathing, learning is a normal function of living. The activity of learning originates from our desire or need to make sense of our experiences; to manage the unknown and uncertain aspects of life; and to take action in the best possible way to ensure our survival and security.

Humans are constantly making meaning. As William Perry said: we are wired to organise meaning. We make sense of our experiences and give them meaning.

We learn to make sense of the chaos and confusion of the raw uninterpreted ‘data’ surrounding us and we learn to develop ways (methods, heuristics etc.) to best respond to and interact with the environment (external and internal). We also learn to define who we are and our personal view of the world. This filters and conditions how we interact with the ‘world’ and how we choose to ‘see’ and make sense of it.

We do this thing called learning instinctively. Current research proposes that our brain is intensely aggressive and is designed to learn throughout life – learning is an inbuilt survival strategy of our species. We create meaningful patterns from the environment that we then use as constructs that make sense to enable our survival.

unknown image source

unknown image source

Sense making (as explained by Karl Weick) refers to how we structure the unknown so as to be able to act in it. Sense making involves coming up with a plausible understanding of our perceived reality of the ever-changing world around us. It is a mapping process that attempts to give structure to the unknown.

This process enables us to “to comprehend, understand, explain, attribute, extrapolate, and predict”. It is a cyclical process that we go through, as we obtain more information. We refine our understanding through the patterns and associated meaning we have created and which we constantly test, verify and refine. Eventually, the complex unknown situation becomes ‘tamed’ and we reach a higher level of understanding at this point. We have learned and created new knowledge that we can call on to solve our problems. Learning from a constructivist point of view is essentially a sense making process.

From what we have seen, there are three conditions required for learning:

  • Enough raw data or experiences must be available with enough repetition and variations on themes to allow for the differences in patterns to emerge;
  • Enough time for the patterns to emerge naturally; and
  • Sufficient, prior meaningful perspectives to be able to handle new experiences productively. If these do not exist, then a longer learning process is required or this can be acquired from other people we trust (we do this with caution).

Learning is dialectical. It is a process that involves interaction through discussion and reasoning by dialogue, whether carried out internally with oneself or eternally with others. This dialectical process explores alternative viewpoints in order to develop an integrated point of view, resulting from the best aspects of all the alternatives we have been exposed to up to that point. The process goes on as new alternatives emerge and it is interactive because we generate meaning by exchanging information with the environment and integrate the meaning into a constructed whole. We construct our knowledge.

unknown image source

unknown image source

There are many aspects that affect our learning, such as past experiences (these can act as a barrier or can enhance our learning). We also have preferred learning styles (a fascinating topic on its own, which I will try and explore in a future post); cognitive styles (a term referred to more by psychologists); preferred learning strategies (visual, auditory and Kinesthetic) and our mental models, to name a few.

Learning is central to problem solving. Our ability to solve problems is affected by some of the aspects listed below:

  • Independent learners – the degree to which we are able to communicate and learn from the meaning created by others – we create meaning for ourselves without reference to others. Some people need to learn things for themselves, whilst others are quite happy to develop a shared meaning through interaction with others;
  • Ability to communicate – learning is dialectical –our ability and how rich our vocabulary is and other non-verbal expressions such as drawing gestures etc. Our ability to understand what needs to be stated and how best to communicate that.
  • Mental flexibility – how prepared we are to adjust our own learning and theories of the world around us. Some people can be quite stubborn (or mentally lazy) and are not flexible or open to adjust their opinion about their worldview. Good problem solvers are highly flexible but critical and keen to reassess their mental models. They are agile and curious. They know that the world is in constant change and, the best strategy to survive, is to make sure they adjust their knowledge to meet the new changes. Their mental models are constantly being renewed and tested against new data and information;
  • Ability to actively re-examine personal constructed theories – we place our ‘self’ at the centre of our reality. The meanings we assign to reality, together with our constructed theories about life and reality, enables us to operate in the environment – without these we are lost and paralyzed. However, at the same time, a good learner and problem solver is very mindful of the fact that these maps of reality are only temporary and approximate reality. The good problem solver will not objectify these maps but, instead, will re-evaluate them eagerly when presented with new information and patterns that emerge and will adjust reality to match the new meanings.
  • Critical thinking – the rigour in critical thinking allows us to evaluate the data, make sense of it and assess its usefulness within the context of the problem to be solved.

The above aspects are important for us to be aware of when we solve problems, especially if we want to be good at solving problems. The objective of this post was to provide background and I will be referring to some aspects covered in future posts. It was also important to make the link to sense making, as I often use the term and will be using it frequently, especially as I start to elaborate on a problem solving method we have been developing.

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Problems – What is this?

When we say we have a problem or we need to solve a problem, we tend to think of a situation that is negative or unpleasant and, at the back of our minds, we would simply like the problem to ‘go away’. The reason for this tends to be that we were not expecting the circumstances to arise in the first place. It will also require some energy to deal with and we are often taken ‘off course’ – this can be frustrating and cause us to have negative feelings towards this thing we refer to as problems.

This negative feeling is probably due to the fact that we are not equipped to deal with unknowns and uncertainty.

If we could have a method or the knowledge that, if we approach ‘problems’ in a systematic way, then we might not go through the uncomfortable stage of wrestling with the confusion and uncertainty. A method would immediately give us the confidence that we will be able to sort the problem out and become productive very quickly and not spend time in a state of confused negative energy.

Original from CartoonStock - adopted by Rui Martins

Original from CartoonStock – adopted by Rui Martins

Essentially, we need to realise that problems are not all bad – it is simply the attitude we have towards them. Professionals who routinely solve problems for a living, especially problems within their field of expertise, will generally look forward to solving ‘the problem’. They intuitively know how to go about solving the problem and probably have developed an explicit, or at least tacit way, to solve problems of the nature they are frequently faced with.

This is all good so far. However, when things change – and change is becoming the norm – professionals can quickly fall into a routine or frame of mind and they will not notice that some initial conditions have changed. This is where the problem becomes serious. It is serious because professionals will be solving the wrong problem.

They have not understood what the problem is that they are solving. Most problems will have many variables that act on the problem and all variables need to be addressed for the problem to be solved. Making sense of these variables is not easy and, depending on the complexity of the problem, it can be quite difficult to get a good understanding of the variables and dynamics between them.

Shifting target - image recreated by Rui Martins. Original unknown.

Shifting target – image recreated by Rui Martins. Original unknown.

The level of complexity increases exponentially and very often one is not able to quantify the variables as an exact science. Many problems need to be solved sooner rather than later and one cannot research the problem to death to make sure we know what it is that we are dealing with. We need a fairly good method that enables us to quickly gain a deep understanding of the issues we are dealing with and what the root causes are – so that we can solve ‘the problem.

I do not like processes that require long upfront research periods. My objection is simple, things change too fast and often the terms of reference do not get adjusted. By the time we understand the problem, it has morphed into something else and we end up solving half of the problem or the wrong problem.

In the next few months, I will be proposing an approach to problem solving that will enable us to have a good degree of confidence that we can make sense of any simple or complex problem. Before this though, I will be exploring a variety of issues and revisiting some topics I have blogged about previously within a problem solving perspective.