The Practice & Art of Thinking

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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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The TED talk below is a great demonstration of when we are able to Visually ‘see’ data and, even better, ask questions and interact with the data set.

Suddenly, we are able to think differently, question old Theories and correct incorrect assumptions of reality. This allows us to start to see and gain a sense of the importance of data visualisation. It also helps us to recognise complex adaptive systems and understand how they behave. This essential skill is demonstrated in the video.

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The video is a presentation by Edward Segel, who is giving a talk at Truila for the data visualization meeting at an event around telling stories with data. He not only gives some great examples but also clearly articulates how to create these stories from data. The video is 19.34 minutes. If you have the time, he gives a good lecture (1.07 hours long) here.

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Data Tells Stories

Still keeping with the theme of the power of data, the video below by Dataveyes is a beauty. It is a promotional video but it is well done and illustrates the point very well.

“Dataveyes is a start-up focused on interactive data visualization.

Data visualization turns large volumes of raw data into a meaningful piece. It creates a visual, esthetic and kinetic interaction, which directly reaches out to the user’s intelligence.

At Dataveyes, we want to create a new visual grammar, a new way of telling stories with data. We think this appears as necessary, for complex information is better memorized by the human brain through a visual form than words could ever be.”

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Data Analysis The # One Top Trend for Business in 2014

I know that the Top (whatever) lists are due by the latest in February. I am not trying to wow anyone. I am simply referring to a list created by Tableau that I think is important and reinforces many of my arguments and certainly my next few posts.

The paper is called – “Top 10 Trends in Business Intelligence for 2014”.

I am not going to list the trends; you can read them for yourself. What is important for me is that data skill analysis is considered number one. They argue (and I agree) that we have come to a point where data analysis is no longer reserved for the specialists. It needs to be a skill that every individual in business must have (I will add – an essential skill for everyone for the future).

In previous posts, I have referred to data analysis. There is data everywhere and tons of it. How do we deal with it?

Data visualization is an essential skill. If we can translate dense data into a form that is easy to understand, we can then act on that information rather than rely on specialists to translate data for us. The information gets filtered by the specialist too depending on his/her focus or bias.

This aspect of bias or worldview is something that will always happen, irrespective of how objective we try to be. We need to keep this in mind when we deal with data and shape it into a form to communicate to others. Keep this at the back of your mind whether you are at the receiving or creating end of information.

Storytelling is also an important criterion in Tableau’s list and I agree.

Image adapted by Rui Martins

Image adapted by Rui Martins

By using the concept of stories, we can make data accessible to the reader in a form that is open-ended and helps us create meaning from the data. Visual storytelling, as a concept to communicate data, becomes a very powerful mechanism. It creates room and enables people to individualize the data and create personal meaning and adapt the story to their own needs.

I suggest that it can also get over the problem of bias, as it does not pose as a black and white absolute truth. Instead it is fluid and, with any organic shape shifting (metaphorically speaking), one ‘gets’ the subjectivity of the creator that is embedded within the story that is not hidden or disguised. I need to point out – there is a careful skill required – data and statistics can lie.

If we see stories as complex adaptive structures, conceptually we can harness their full potential.

Visual stories are extremely powerful if created with this in mind – where we consider data as the ‘agents’ within the story system; data becomes a dynamic; and the emergence of meaning is recognized for what it is, as temporary and subjective.

To summarize: visual stories are vignettes of complex adaptive systems.