The Practice & Art of Thinking

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Heat Maps

Heat Maps is a simple yet powerful technique that leverages the human’s superior visual cognitive capacity to gain deeper and faster insights into data and information.

Cormac Kinney coined the term in 1991 to describe a 2D-display depicting real-time financial market information.

A heat map is any data visualization that uses color to represent data values in a two-dimensional image. A simple heat map provides an immediate visual summary of information. More elaborate heat maps allow the viewer to understand complex data sets.

There are many different types of heat maps used in different disciplines, each referred to by the term “heat map”, even though they use different visualization techniques.

The reason heat maps work so well is because of our ‘Pre-attentive Processing’ ability. The term refers to the ability of the low-level human visual system to rapidly identify properties, such as color and size, in less than 250 milliseconds.

According to Van der Heijden, we unconsciously accumulate information from the environment ,which is pre-attentively processed. The brain filters and processes what is important based on what stands out the most. Once the individual’s attention is captured (based on what is of relevance to what the individual is thinking), at that point the information is selected for further and more complete analysis by conscious (attentive) processing.

It is a two-stage process, which happens in seconds, and this is why heat maps are so powerful.

Heat maps are being used in many sectors and that is great. The best way to demonstrate these is to show you examples. I use some examples as shown by John Brandon in a slide presentation.


Marketing people created the map above. By using eye-tracking devices, a heat map is created showing where attention of the user is focused on display pages. The map above is a sample heat map of a Google search result.

A dominant pattern for search engine results is the “F” pattern showing the eye being drawn to the upper left (hot colors) and then moving down and across from there (shown as the blue colors). There are, however, factors (such as the inclusion of images, graphics, and additional columns) that can significantly alter this pattern.

This heat map displays risk by location. It was created by RMS (risk management company) to show risks related to catastrophic events: Earthquakes, hurricanes, severe storms (including tornados and hail), wind storms, wildfires and volcanoes. An insurance company might use it to determine the “probability of loss” related to such an event.

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This heat map shows the reality of fraud attempts in real-time using live data. A red dot pops up to show a fraud attempt. ThreatMatrix culls the data from 1,950 customers, which includes about 9,000 websites, and tracks about 360,000 cyberattacks per day.

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This heat map from MarketProphit shows buzz and sentiment around specific stocks. The larger blocks indicate the most buzz (or discussion) around a stock as culled from Twitter. The colors show sentiment; the red blocks denote negative comments and the green denotes positive comments. In an instant, financial planners can see general trends with stocks based on social media posts.

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This heat map shows the movements of customers in a retail store aisle. Red areas represent the spots where most customers shop. Retailers can use the heat map for product placements and to see whether a sales campaign was successful.

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This heat map shows the age of buildings in the Portland, Ore. area. About 544,000 structures are represented, including about 4,500 erected in the 1800s and 10,265 buildings constructed in 1978 alone.

Justin Palmer created this heat maps based on public data released by the City of Portland. It shows the age of buildings. This can help municipalities see which neighborhoods hold the greatest concentration of structures that may need repairs.

Click on the link ( to see the map in large scale, iit s beautiful. It shows the nearly 10 million buildings in the Netherlands; some in central Amsterdam are more than 1,000 years old.

Some would argue that heat maps are very specific – “the heat map is a treemap-like graphical technique used to represent a two-dimensional array of data” as shown in the example below.


Many techniques illustrated in this post, as argued by the purists, are not heat maps. I agree and I disagree. The principle of using color to very quickly highlight the issues of concern, attention or importance is extremely valuable and it is a perfect example of how we work better with visuals than with coded jargon. The fact that it is called a heat map – well, does it matter? Notionally, it is a perfect description even though it might not be as it was originally labeled – I think this is a good and natural evolution of the principles. I will call these techniques ‘heat maps’ – it works and it is powerful.

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Visualisation is a powerful skill for solving problems – Yes it is

I have often said that our human brains were primarily designed for cognitive visuality but that we’ve developed mistrust for this skill. For this reason, I suggest research into exploring our cognitive visuality has been scant and we only have a relatively primitive understanding of how our cognition operates.

Recently, we have a revived interest in the brain and there is very exciting evidence that is emerging to support our amazing abilities to think visually.

This post is not about that new research, rather it is about showing how much better we are at solving problems visually.

Simply put, the best way to solve problems is to convert the problem situation as much as possible into visual elements i.e. pictures. This is why many people naturally use pen and paper or any medium that helps them make sense of the problem situation and, in the process, visually come to a solution.

Image source: MsBuchman

Image source: MsBuchman

To try and do things in your head is clumsy, especially if there are quite a few relationships and variables involved. It improves if you talk about it – the verbal discourse allows for emergence and is a good trigger for complex adaptivity but still not as powerful as visuality.

I think the reason we try to do things in our heads is mostly vanity and relates back to being praised for doing mental maths at school.

There is no reason or even suggestion that people who use visualization techniques are not smart. On the contrary, those who have developed and perfected their visualization skills ‘see’ things that those who do not use such techniques do not ‘see’. The great minds, and those who have made substantial contributions to our civilization, describe their methods and approaches to problem solving as being highly visual.

Einstein, for example, said that he never thought in terms of symbols or equations. Instead, he thought in terms of images, feelings and music. The pictures came first and the descriptions came later. I have a previous post that explores how a few others used visuality.

“Discovery [as stated by Einstein] is not a work of logical thought, even if the final product is bound in logical form”.

It is relevant to note that Einstein did not receive a conventional education. His mastery of visualization started at the Aarau School in Switzerland. The school’s teaching was based on the philosophy of the educational reformer, JohannPestalozzi, who believed that “Visual understanding is the essential and only true means of teaching how to judge things correctly,” and “the learning of numbers and language must be definitely subordinated.”

Einstein’s school helped students move through a series of steps from hands-on observation to intuition, conceptualization, imagination and visual imagery.

We all have the ability for visualization but what we need to develop is respect for that skill and put it to work.

We are very good at pattern recognition. Herbert Simon proposed that humans are wired to recognize patterns and think visually. According to him, we are naturals at this and, in fact, we are able to process visuals in a way that a computer is not able to. Computers are good at processing symbols but not patterns and are far less able to make sense of visual information and extrapolate unique novel meanings from such visuals.

In a paper entitled “Why a Diagram is (Sometimes) Worth Ten Thousand words”, Simon compares two approaches to solving a problem; a symbolic one and an approach that uses a diagram. The symbolic approach is sequential and can run to several pages; whereas a diagrammatic approach is highly efficient, information is organized visually, it is explicit and organized by physical location.

image source:

image source:

Additionally, cues to other issues or steps are often present at an adjacent location. Diagrams are better because they are efficient and convincing. This is not rocket science – it is simply because we can see it and we are using our innate natural abilities of pattern recognition when approaching a problem visually; whereas if we use the ‘proof’ or long approach, we can easily get entangled in contrived logic.

My bugbear is that we are taught not to trust our visual skills and are forced into believing that the only possible or correct way to argue logically is to use symbols and sequential linear logic. I am not suggesting that we need to throw the baby out with the bathwater. Rather, I am saying that we need to learn to use both and explore other personal options – creativity needs to be encouraged not annihilated, especially at school and yes even in the mathematics class.

Thinking visually is a powerful and highly efficient way that requires very little effort compared to the computational approach like that of a symbolic exploration of a problem, which is typical in mathematical calculations and computers.

The unquestioned assumptions to problem solving methods is that one needs to go about solving problems the ‘right way’ with the ‘right method’, implying that there is one and only one way of doing things. It has reached a point, even common practice in many business MBA’s ethos, that you simply need to match a method to a problem. Honestly, how have we allowed things to become so simplistic?

We seem to have lost the ability to be creative and recognize that when we are taught ‘methods’ we are not being given the key to unlock access to all ‘knowledge’ or, as Condorcet believed, that methods are a universal instrument to solve all problems, giving one access to all: ”combination of ideas”. That statement was made in 1793 and unfortunately it still dominates today in varying degrees.

I have a serious problem with this attitude. I agree that it is invaluable to learn about the various methods because they give us a perspective, a rigor and deep grasp of how to create knowledge whilst being critically aware of the ‘worldviews’ associated with the method.

However, creativity cannot be lost in the process. You must not become indoctrinated into ‘the right way’ or so paralyzed that you cannot freely explore without fear of the consequences of falling off the ‘edge of the earth’ or dare to experiment with the unknown.

Visualization is the conceptual skill of insight that enables you to ‘see’ the fuzzy ‘stuff’ that does not necessarily have a label and has not been articulated and categorized; the acknowledgement and audacity to act on our visual insights; even fleeting at times as they might be.

To illustrate the point: Pythagoras originally visualized the solution to the Pythagorean theorem visually by manipulating shapes. He did not use any Maths.

As described in Wikipedia, “… the Pythagorean theorem is a relation in Euclidean geometry among the three sides of a right triangle. It states that the square of the hypotenuse (the side opposite the right angle) is equal to the sum of the squares of the other two sides. The theorem can be written as an equation relating the lengths of the sides a, b and c, often called the Pythagorean equation:


where c represents the length of the hypotenuse, and a and b represent the lengths of the other two sides.

Simply put, the theorem claims that the sum of the areas of the two small squares equals the area of the large square always.

One can find many ways to prove this theorem. Below is one way taken from

Unless you use mathematics on a regular basis, I suspect that it could be difficult to follow the proof below and to be convinced by the solution. You might glaze over it and possibly zone out.

A visual way to solve this theorem is shown below. Not only is it extremely clear but also there is no ambiguity in its communication. By simply manipulating shapes (no mathematics) you can demonstrate that the area of the two smaller squares are equal in area to the large square, which is precisely what the theorem claims.



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Visualisation and Problem Solving – use your brain for what it was designed for.

The next few posts will deal with visuality and problem solving.

When you try to solve a problem in your head, it can be difficult, especially if the problem is relatively complex.

Try doing the following calculation in your head:


This is not easy and the rate of error is quite high. The solution – solve it with pen and paper; using a calculator is not the point here.

Why is it difficult? It is difficult because of our cognitive capacity – there is only so much that we can hold with conscious attention at any one time. This is known as cognitive overload and was highlighted in George A. Miller’s 1956 paper The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information.


Further research verifies that the number of items we retain in our short-term memory varies depending on whether it is digits, letters, words or even familiar chunks of information. Of interest is the limited capacity of our cognition – it is still somewhere between 4 and 7 items, so Miller was correct in general terms.

This is why we should maximize what we were designed for and use our superb visual abilities, rather than posture about how smart we are by ‘doing things in our heads’!

Going back to the calculation, the obvious solution is to use pen and paper as it frees up cognitive load. You simply assign the memory capacity to the piece of paper, leaving your visual cognition to maximize your thinking for problem solving, which is a skill that needs perfecting, especially since we have been neglecting it as a society.

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A Retrospective of Visual Thinking

I thought I would do a retrospective of some ideas on visualization that I have explored during 2013.

Because I thought that people will be more interested in having a good time and catching up with family and friends over the Christmas holiday period, I am posting this in January. I am still in Bhutan by the time this post appears and, when I get back to New Zealand, I am looking forward to sharing some of the different insights gained during my trip.

Here are some of my thoughts:

  • Vision is one of those things that humans do very well and naturally.
  • The human brain has a very large portion dedicated to vision and visualization – this must say something!
  • We are awake more than asleep. This means that we are ‘doing ‘vision’ the majority of the time in our lives.
  • Through evolution, we are designed to ‘do vision’.  Again, this must say something very obvious about the importance of visualization.
  • Visualization is more than passive seeing.

My question is: does this mean that visualization is a massively important component in the way we make decisions and make sense of the world? Yet, we have not really defined this capacity and fully understood it. Is it too difficult or have we considered it to be one of those nice but not serious topics? I think this is about to change, especially as we are making a social shift towards recognizing the importance of design, innovation and creativity as a powerful component to the future survival of our civilization. The dominant ‘left brain’ (I have used this mostly as a metaphor) is not able to suppress and dominate the centre stage of our thinking anymore. Balanced critical thinking includes creativity.

Creativity is not about rearranging the furniture or choosing the wall colour to match the curtains. It is hard, yet everyone has this capacity in varying degrees and it must be cultivated seriously.

We live in a visual jungle. How do we articulate this skill so that we can use it mindfully rather than simply doing it? A sprinter runs, so do the majority of humans, but not all humans run like a trained athlete – can we, in a similar way, harness and understand our visual skills so that we become fantastic at thinking and, as a consequence, leap into another realm of awareness and understanding?

Visualization is a new language of cognition. With this skill we are able to zero in on the emergent factors, variables and otherwise hidden patterns in front of us and, in so doing, unlock new knowledge.

We need a high Visual IQ (V.I.Q) to deal with nuances and subtleties in the noise of life. As a society, we have progressively been increasing our I.Q in general – this means we are getting smarter as a species. But we need to define our Visual I.Q so that we can survive in the dense, visual jungle, make sense of it and not be afraid of it.

Visualization is a form of knowledge compression, as expressed by David McClandless. This allows us to identify not only the gestalt but make and design new knowledge. Knowledge has become a construct that gets reconstructed within new contexts by individual observers. Individuals are now the curators of knowledge and visualization has become the means to creatively explore and innovate our new futures.

I think we should celebrate this ability and use it to its full potential to enable us to unlock the creative spirit dormant in all humans. Everyone needs to be able to see that the emperor has no clothes. We need to change out thinking from a mindset that can only tolerate the logic of  2 + 2 = 4 to one where we can see the message captured in 2 + 2 = 5.

Tom Fletcher by mywonde - modified by Rui

Tom Fletcher by mywonde – modified by Rui

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Theory of the Brain – Part 1 – why do we need theory?

I hope this post will be useful to clarify some terms. I have found that the term ‘theory’ is sometimes considered as mere speculation, guesswork or hunch.

The reason we need theories in general and of the brain in particular, is to know who we are and understand ourselves better. We also want to be able to make better decisions, gain greater insights into perception, understand our actions and, hopefully, consciousness.

What does it mean? By Caraman –

A good brain theory would also enable us to develop the ability to find new therapies for a variety of mental illnesses and diseases like Alzheimer’s and Parkinson’s. Other areas that would benefit from a good brain theory would be artificial intelligence – by being able to build intelligent machines.

Before looking at our current theories of the brain, it will be useful to look at some basics and clarify what theory, model and frameworks are.

The purpose of a theory is that it guides the investigation (research). It is based on a hypothesis/proposition and backed by evidence. A theory presents an idea or concept that can be tested. It is a data-based framework that describes phenomenon. For example, in psychology, theories are used to produce models that enable us to understand human thoughts, emotions and behaviours. It not only describes the behaviour but it makes predictions about what future behaviours might be.

A hypothesis is a tentative statement about the relationship between two or more variables. It is a specific, testable prediction (there is a possibility to prove it false) about what you expect to happen. Converting the question into a predictive form can develop the hypothesis.

The conceptual framework links concepts to establish evidence in support of the need for research that will lead to producing a theory. If the concepts have already being linked through research then a theoretical framework exists, which can then be used as a guiding map for others to use their own research questions to test the theory from different perspectives.

A theoretical framework is a collection of interrelated concepts and is the foundation for the parameters, or boundaries, of a study.

A model is used to make predictions, stimulate thinking, and suggest ideas, to discover lever points for intervention and to validate theories. They need to be evaluated for their accuracy and prediction.

In most cases, models and theories tend to be indistinguishable. Technically, however, a model need not elaborate the reasoning of the topic it is modelling. It tends to be presented in simplified terms. In contrast, a theory will explain the why of a model. For example, the Bohr model (1915: also known as the planetary model of the atom) simply states that electrons have discrete energy levels. No explanation is given as to why. The model is now considered not to be completely correct – it approximates quantum mechanics (regarded as the correct theory of the atom) but has the virtue of being much simpler.