The boss of RBS has scored a Gordon Brown-like “own goal”. The bank’s Chairman, Sir Philip Hampton, has admitted that city bankers are paid too much – “astonishingly high”, is what he said their salaries were. He went on to say, however, that if you don’t pay these big salaries, then people leave. Indeed, said Sir Philip, many of the “top people” have already left RBS. That was before he went on to explain that the bank had achieved much better results than expected. Sorry, run that past me again? The “top people” have left – and the bank has improved. Er…sounds to me like you should let more of them leave, Sir Philip…!

which is more or less what I have been saying for sometime!and Graham goes on to say:

But why is it that everyone in the banking industry – and the Government – falls for the line “we have to pay people high salaries in order to keep them”?

If you want to read more on this then go to Graham’s blog here

The boss of RBS has scored a Gordon Brown-like “own goal”. The bank’s Chairman, Sir Philip Hampton, has admitted that city bankers are paid too much – “astonishingly high”, is what he said their salaries were. He went on to say, however, that if you don’t pay these big salaries, then people leave. Indeed, said Sir Philip, many of the “top people” have already left RBS. That was before he went on to explain that the bank had achieved much better results than expected. Sorry, run that past me again? The “top people” have left – and the bank has improved. Er…sounds to me like you should let more of them leave, Sir Philip…!

which is more or less what I have been saying for sometime!and Graham goes on to say:

But why is it that everyone in the banking industry – and the Government – falls for the line “we have to pay people high salaries in order to keep them”?

If you want to read more on this then go to Graham’s blog here

Math 1.0 can be considered to be a special case of Math 2.0, where certain aspects of reality are ignored for the purpose of making things black and white and therefore easier to manipulate and compute.

Math 1.0 is helpful in specific circumstances like simple counting and manipulation of number, adding, subtracting, multiplying, dividing of pure number, and for making approximations, and is also useful in statistical manipulations where it is valid to manipulate data away from its context. Math 1.0 thinking successfully delivered a rocket to the moon but has failed to deliver insight into most chronic problems affecting humanity today. Math 1.0 thinking is part of the problem!

Math 1.0 is not valid in the domain of measurement nor when ‘counting’ is actually for the purpose of measuring ‘things’. And yet we use Math 1.0 with measurement all the time!

Using Math 1.0 as the ‘logic vehicle’ for interpreting changes in measurement data is a major reason why we have witnessed so many decisions by leaders and politicians in the last few decades that have turned out to be wasteful and that have exacerbated rather than solved ‘problems’. This happens when the Math we learn at school (Math 1.0) is applied into the world of measurements. And a science based around this maths re-inforces it as a science of reduction and ‘ism’ (“ism” happens when a discipline comes to believe its working model of the ‘world’ as true rather than ‘useful in defined situations’). So the belief (as true) in the mechanistic universe and the use of Math 1.0 as a sturdy, reliable and incontrovertible companion has led the traditional Newtonian scientist up the proverbial garden path and is still being led there daily. Multi-billion pound projects based on the assumptions of a reductionist science leading absolutely nowhere, whereas situations that could be drastically improved based on a science thinking in terms of systems and Math 2.0 are not being allocated the same research money.

To fully appreciate the meaning and consequences of data measurements, a good understanding of Math 2.0 and its application is required. If we care to look, we will find that the scientific, political and business literature is littered with examples where statisticians (who we would think would know better) have fallen into the trap of applying the thinking of Math 1.0  to the situations described best by Math 2.0, thereby giving us misleading ‘expert’ information and advice

This venn diagram shows the relationship between Math 1.0 and Math 2.0:

It was Walter Shewhart (the man who has been called the father of quality) who said “Data is meaningless outside of its context”. Using my language here, he could have rephrased this as “Data is meaningless unless processed using Math 2.0″ (Math 2.0 is a way of working with numbers that keeps the important context ‘in view’)

Math 1.0 is the Math of the Counters. Math 1.0 works for the abstract Math-World. Math 2.0 however is needed for Real-World Problems. Many of our “number experts” (mathematicians and statisticians for example) base their life-long working knowledge on this Math 1.0, so they are then part of the problem. Math 1.0 is entrenched in academia and science. It is now one of those implicit unquestioned assumptions (like water is to fish and air to birds) that Math 1.0 is numeracy and that Math 1.0 describes the sole reality of numbers. There will certainly be a few people in very high powerful places who know about Math 2.0 but are happy for the rest of us to just learn Math 1.0. When it comes to comparing things, Math 1.0 does not clarify issues, instead it clouds them. All this means so few people know or understand the limitations of numbers, and therefore that numbers can be used to keep us all in the dark (ages?) about most things. We will never really know whether our Health Service or Schools are getting better or worse using Math 1.0. What is certain is that using Math 1.0 we get into endless debate about the trivia from the data (we can call this “noise”) and we will nearly always be missing the important understandings (we can call this the “signal”). Without Math 2.0 the useless information (noise) is drowning out the important information (signal).So although it seems ludicrous that some, if not most, of our main ‘experts’ in Maths and Statistics use a Math that was devised for the special case of pure numbers and counting and that is strictly NOT applicable to numbers as MEASUREMENT. But it is such experts that write a numeracy curriculum for our schools, universities and accountants that is based on a special case with numbers (the Math of simple counting – Math 1.0). In the real world most of the important numbers we deal with on a day to day basis are to do with measurement, or involve counts that are being used as measures, and so we need to apply “Math 2.0″ in order to interpret these situations. When we use simple Math 1.0 for interpreting data measurements we create problems and misunderstanding. Because we have come to rely on numbers in every facet of life and business (we found we could no longer trust the word of leaders, doctors, scientists etc so we needed their numbers) numbers now heavily impinge on our emotions. We can get very angry when we see numbers we don’t like. The problem is often there is no valid reason to get angry with the numbers, it is Math 1.0 we should be getting angry with. We should be getting angry that we are not taught the ‘numeracy of measures’ at all. Everyday we are all making decisions with sometimes life-threatening or very severe unintended consequences because of a lack of real-world numeracy because we don’t have the skills of Math 2.0No-one is excluded. Politicians, scientists  and business leaders all continually make poor decisions when they apply Math 1.0 thinking to real-world Math 2.0 situations, making us depend on numbers in a way that is totally irrelevant, abstract, misleading, artificial, and distorting. Our lack of real-world numeracy Math 2.0 skills is I believe a big part of the problem why so much today seems to be going wrong. We follow the numbers but we don’t understand the numbers and as a consequence we jump to the wrong conclusions and we take actions misguidedly on the numbers and actually then make matters worse rather than better. (Deming called action based on misguided interpretation of data – tampering and he devised the funnel experiment to help us understand how tampering makes matters worse)So at this point you may be asking what is this Math 2.0, why isn’t it taught in school and what difference would it make? I will some outline the key differences between Math 1.0 and Math 2.0 next time but here is a taster.Math 1.0 is an artificial world where lines have no thickness, parallel lines can’t meet and numbers are absolute. When we use Math 1.0 there is only one correct answer and it is not possible to have variation in the answer. (in the real world however variation is always present)Math 2.0 on the other hand is a real-world Math where lines have thickness, parallel lines can meet and most importantly measured numbers are never absolute. As variation exists in all things Math 2.0 does not ignore its effects (whereas Math 1.0 assumes random variation does not exist)So here is a little teaser to see if you are working from Math 1.0 or Math 2.0MATH 1.0Math 1.0   2 + 2 = 4   YES this is absolute, there is only one answer and that is 4Math 1.0 implies that this answer is the same whether we are using simple counts or measures. So 2 inches plus 2 inches will always equal 4 inchesMATH 2.0Math 2.0 – when simply counting, the results are the same as for Math 1.0So 2 + 2 = 4   this is absolute, there is only one answer and that is 4However when adding together measures or comparing measures: 2 + 2  =  4  but only on the average (so each time we take measurements and add them together the answer can vary either side of the number 4 by an amount which Math 2.0 can reliably approximate )this scenario would be more precisely written as:2 (v1) + 2 (v2) = 4 (v3) where v1,v2,v3 is the variation (plus minus 3-standard deviations) that is inherent in each measurementThis brings me on to a further significant difference between Math 1.0 and Math 2.0. In Math 1.0 there is ALWAYS significance in any change of number and therefore there is value in comparing just two data points. So if something measured 20 last month and 23 this month Math 1.0 says there is a change (an improvement if good stuff, a worsening if the measure is bad stuff. So as Math 1.0 is the math of pure counting if we have 20 apples in one basket and 23 apples in another it is clear that the second basket has (three) more apples in it. Math 2.0 would come to the same conclusion. However if the tree in your garden produced 23 apples this year and 20 last year we actually need Math 2.0 when seeking to make a decision about whether this difference means the tree yield is improving? For we are now not looking at the pure count of the apples we are seeking to use the numbers to give us knowledge about the tree. Now instead of apples and tree performance think of pupil exam success and school performance. And then by way of extrapolation think school success and league tables.In Math 2.0 we CANNOT KNOW IF THERE IS A DIFFERENCE between 20 and 23 unless we have more data (and then a lot of the time Math 2.0 will show there will be no likely significant change). Math 2.0 tells us that comparing just two data points is ALWAYS meaningless (and of course it can provide the evidence for this). Each time we just compare two data points we are viewing the data outside of its context.If only journalists were schooled in Math 2.0 we would not have so many meaningless, stupid headlines in our papers. But there again, they probably wouldn’t sell so many newspapers, so you could see that their bosses would be quite happy that their journalists are only numerate to Math 1.0 level. Using Math 2.0 many headlines in the newspapers would read “Probably no change in the trade figures this month” rather than something that appears very dramatic like “4% fall in trade figures throws UK back into recession”. Which of these two headlines would make you buy the newspaper – the first one (‘probably no change” so nothing much is happening  -  a quite likely scenario using Math 2.0) or the second headline derived using the inappropriate use of Math 1.0 ?Have I grabbed your attention? If you already know what I mean by Math 2.0 great, please post your own examples here about how Math 1.0 misleads, If you think I am a raving lunatic and it simply can’t be possible that we are being taught the wrong numeracy at school for making sense of the real-world, then please follow, watch and learn. And if you still think I’m being stupid tell me so.In the next two articles in this series I will be comparing in much more detail some of the differences between Math 1.0 and Math 2.0 and seeking to impress upon the sceptics out there that this is really important stuff.Next Time: Maths and Science leading us up the (wrong) garden path

Powered by Twitter Tools.

“We cannot solve the problems of today with the same level of thinking that created the problems in the first place”

Albert Einstein (He said words to this effect many times over his lifetime)

What did Einstein mean by this? Well I guess using my terminology from the previous few blogs on this topic he did not mean crowing cockerel thinking, nor flat world thinking, not even earth around the sun thinking. Neither of these three ways of thinking would  cut the mustard for Einstein.So lets look at three further levels of thinking that would ‘cut the mustard’Here are the three levels of thinking that our human brain was wired to do, ways of thinking that clearly differentiate us from the abilities of  reptiles and other mammals.(1) “Out from my Existing World” ThinkingThis is thinking where the thinker takes a (one dimensional) step out from their current set of beliefs (or paradigm) about how the world (and everything in it) works. So rather than staying ‘imprisoned’ within the assumptions, beliefs, and theories of the existing system (my current world) to take a step outside/above and look from a different viewpoint or perspective. This level of thinking is sometimes described as ‘out of the box’ or ‘lateral’ thinking(2) Multiple Perspectives Thinking (MPT)MPT occurs when you can suspend you existing assumptions and start to scan ‘reality’ from multiple perspectives or ‘viewing points’. For example when you are in dispute with someone you can look to hold three different perspectives in your head and view the situation from each. What is your thinking on this issue, what are the likely thoughts the other person has, and  what would a third person who no axe to grind think about this situation. By viewing this issue from three perspectives gives insights not possible from just one. Anyone acquainted with W. Edward Deming’s ‘System of Profound Knowledge’ will appreciate that Deming created a tool that let’s us view any issue through the lens of four different perspectives. When we do this we get a good sense of the unintended consequences that we might ‘cause’ by simply taking a ‘one perspective’ viewpoint.This type of thinking is greatly enhanced when we are in multilogue. Here we listen and share information in a particular way and sitting with people who hold widely differing perspectives. Everyone in the room  suspends their existing assumptions and then as the multilogue progresses they seek to hold the totality of thoughts and ideas in their heads. And then (and only then) from a state of nothingness (shown by absolute silence) there begins to emerge through the vehicle of the group, new thoughts and ideas. In a society that is not used to sitting in the silence, multilogue is tricky to achieve (Many of us seem to be threatened by it)However there are however tools and techniques that will allow us to achieve this type of thinking whilst working on our own and Deming’s System of Profound Knowledge is one such tool.(3) Meta-ThinkingThis is our ability to think about thinking. To be able to think and to challenge our own thinking and the thinking of others. It appears that we are the only life-form on this planet to be able to ‘meta-think’ and it is this one ability that has made us so successful. All the great major breakthroughs in human advancement have come about through this ability. We cannot achieve any of the other five levels of thinking without having this ability. Yet what are we most likely to do when we have a problem? Think-about-our-thinking or sit and watch a reality TV programme?It is sad to know that the three levels of thinking described here (each of which lift our abilities above that of reptiles and mammals) are so rarely used to focus and seek solutions to the challenges we have today. Einstein would not be happy. If you live in the midlands and you want to jump-start your thinking and creative ability I have some upcoming workshops on these topics in Birmingham and WorcestershireComing Next:  Black and White thinking – the curse of our society

In the last Blog I looked at how our models, theories, beliefs and assumptions can be either helpful or harmful. Also I looked at how our assumptions influence our thinking and vice-versa.

In this blog, I am going to focus on thinking.

There are many different ways to look at thinking (because there are many different ways we can model thinking). The first model I am going to share in the next three blogs is one I put together just a few days ago (so one of my own creations – thought I accept there is little new under the sun). I am going to call this model the “Logical Levels” of thinking (not to be confused with NLP Logical Levels) and I use this term because I see the ways of thinking I am about to describe as being on a continuum from quite illogical (though sometimes understandable) through to very sensible, and very logical.

I have given these logical levels of thinking my own names but if anyone can come up with any ones please let me know. My logical levels of thinking are: (1) Crowing Cockerel (2) Flat World (3) Earth around the Sun (4) Out from my Existing World (5) Multiple Perspectives and (6) Meta-Thinking and I will briefly describe the first two here.

Crowing Cockerel Thinking

This is the level of thinking that is followed when people believe that the sun rises every morning because the cock crows. The proponents of this way of thinking will defend it as absolutely correct. There can be no argument with this way of thinking because the sun rises after the cock crows. In the 21^st Century, you would think that we are far too clever to believe or to use this way of thinking, but you will regularly discover in this column (and the sister column – the Non-Political Party) that “Crowing Cockerel Theories” are all around us and they have the effect of protecting the status quo. This thinking stops us from looking at things in new ways, is superstitious, and it stops us from improving. Even intellectuals and academics are not immune from this type of thinking. Scientists also have their fair share of this thinking.

Why does such an illogical form of thinking persist?

One reason may be that we rarely give time to think about our thinking. So we do Crowing Cockerel Thinking thoughtlessly and without any constructive engagement with it.  Another reason is that we believe for every effect we see there is a cause. So we seek causes but often have no way of knowing (insufficient data?) what is a cause and what is a co-incident. Indeed in this specific example it is the sun that ’causes’ the cockerel to crow not the other way around (even this of course is far too simplistic).

And before you say that you never think in this way, I intends to have great fun showing otherwise. Maybe you do think-about-your-thinking and so you are partially immunised from this false idol. But I will bet that you probably (without realising it) take advice occasionally from an expert who (unknowingly) practises this form of thinking.

So let’s try to identify this perverse thinking mode whenever and wherever it appears in the media. And do please send me any examples you find.

Flat World Thinking

This form of thinking has some definite logic to it. It is represented by a theory that is true (useful) but only under very limited conditions. Imagine living thousands of years ago in the middle of a vast plain. This thinking was adequate. The theory says “my world is a flat place”. The model will always be true (useful) within certain confined limits. However to extrapolate from this (specific place) model into a general model of thinking would be dangerous (particularly if you were gambling with your life or your worldly possessions, or gambling with the lives of future generations on the assumption that the model was true). As I intend to show time and time again, Flat-World thinking is (unfortunately) alive and well. If you have your personal examples of this Flat-World Thinking please send them to me so I can add them to my collection.

Coming Next:

Earth around the Sun Thinking