All posts by Jamie MacAlister

Jamie teaches risk and strategy at Hult International Business School and the International Health Sciences University in Kampala, Uganda. He is also an executive coach, facilitator, strategist and commercial manager, having previously been Commercial Director at Ashridge. He has had over twenty years experience as a management consultant with PwC and running his own business, Blonay. He learned about marketing with Procter & Gamble, has an MBA from Wharton Business School and an MA Engineering from Cambridge University.

Expect to gain when you take the right risk

We should expect there to be a reward for taking risk.  This is the principle on which the stock markets work, and financial investment in general.   This is different from thinking that flirting with danger of itself should be rewarded, and instead reflects the way that financial investors see risk – as variability rather then the prospect of danger or harm.   Statisticians and analysts measure variability in financial data – they call it things like variance or standard deviation in outcomes like profit.  And one way that they picture this is in  normal curves  (a.k.a “bell” curves) like the ones below.  Narrow tall bell curves represent limited variability of likely outcomes – and therefor represent low risk options.  Wide bell curves represent high levels of variability of outcomes, and therefore higher risk.

This diagram seeks to show that when comparing different financial investments with different risk profiles, we should expect to gain from the higher risk option.  This is sometimes referred to as the risk/return tradeoff.

riskreturncurve

[Extract from book: “Risky Strategy” to be published soon]

The risk in financial markets is measured as variability over time or between investments, as I touched on in Chapter 4 when talking about definition of risk. This may be variability of share price, or indeed profit, or some other important measure. So an investment where this key measure varies a lot over time is higher risk than one where the measure is more stable.  This risk and variability tends to follow patterns by certain groupings of investments, for example by industry sector.    So a new technology sector such as the bio-technical sector, with smaller companies and unproven technology would be a higher risk sector than for example consumer goods,   with established large organisations with mostly established brands and technologies.  So according to our risk-return thinking, we would expect to get a higher return from an investment in the bio-medical sector compared to the consumer goods sector.

As we explored in Chapter 4, one way we represent this variability is through the normal curve, sometimes called the bell curve. So for example, our likely financial returns in a given sector, are distributed around our expected return, the peak of the normal curve.  If there is a wide range of expected returns, this is a high risk situations which is represent by the wide normal curve.  A lower risk sector with a smaller range of possible returns is represented by the taller narrower normal curve.

If we build in our risk-return thinking into our normal curve model, and combine our broad, high risk curve with our narrow low risk curve,  we end up with something that looks like the diagram below.  First of all, in the low risk case, represented by our red curve, our expected outcome or return is more likely, than in our high risk case;  hence it is taller.  More to the point, the expected return or outcome from our high risk option is higher than the expected return from our lower risk option.  This is risk return thinking. And the difference in return between the two options is referred to as the risk premium

Lets look at this diagram more closely because it highlights a fascinating insight when we look at risk in this way. There are two shaded areas in the diagram. The shaded area on the left, what I have called the area of danger, is the main reason why we may not go for the higher risk option.   This represents all those possibly outcomes or returns that are worse than our expected outcome, that are more likely to occur if we choose the high risk option.

But now, lets look at the shaded area on the right side. This is the area of opportunity, and represents all the outcomes or returns that are better than our expected outcome, which are more likely to occur if we select the high risk option. What is interesting is that this is a much bigger area than our area of danger.  This is because, when we look at risk in this way, there are two important assumptions that lead us to this place.

  1. Our risk profile is symmetrical as represented by a normal curve. That means that better than expected outcomes are just as likely to occur as worse than expected outcomes. This is clearly not the way we always think about risk, and when we think of it in terms of possible crisis situations, it generally doesn’t have this symmetry. But in the case of financial investment, and more generally, business innovation, it probably often does.
  2. Risk-return thinking is valid. We should expect on average to earn more from a high risk investment than a low one.

When looked at like this, there is quite a compelling case for taking more risk. Our chances of doing better are disproportionately higher than our chances of doing worse.

It begs the question, if we saw business investment in this way more clearly, would we be inclined to take more risk.

The reality appears to be that we tend to be drawn to focus more on the smaller shaded danger zone on the left , almost like Greek sailors to the siren call. This leads to the phenomenon of “loss aversion”, which I shall pick up in more detail in Chapter 7, when I talk about illusions and traps.

Feeling safe with risk

In this Christmas season when some of us celebrate the idea of a saviour sent to our planet to rescue us from sin and death,  it seems appropriate to explore what it is that actually helps us to feel safe. It is part of the human condition to need to feel safe,   while at the same time recognising that we live with risk, and regularly take it.  I explore this paradox in the penultimate chapter in my book: “Feeling safe with risk”

feeling safe on a girder

[Extract from “Risky Strategy” to be published in 2016]

So in handling this paradox of safety with risk, our approach to risk will of course therefore be determined by where or how you experience safety. We tend to experience safety where we can truly place our faith.

I am reminded of the exploits of the Niagara Falls tight rope walker in the mid nineteenth century known as “The Great Blondin”, whose real name was Jean Francois Gravelet. He repeated the stunt of crossing the falls on many occasions, sometimes using other props, like bicycles and wheelbarrows.  On one occasion he is reputed to have taunted the crowd with the question: “How much do you believe in me?” and getting loud affirmation.  He then asked who in the crowd who said they believed in him would get on his back as he crossed the falls.  No one was prepared to do that – no one had that much faith in him. He did apparently eventually do it with his own manager, which caused quite a stir not just for the crowd but also for the manager.

How can you feel safe with risk? To whom or what can you put enough faith to feel safe?

  • For some it’s more in numbers and logic – the evidence is enough.
  • For some it’s in relationships – and knowing that certain key people are in the same place as me.
  • For some it’s in intuition and gut – I know it down deep – it’s a whole body experience
  • For some it’s in a belief or worldview – perhaps a cultural or religious view which also informs values

 

My initial interest in exploring the subject of risk in leadership was shepherded by another related interest – the role of faith in business. I have for some time been fascinated by how some people make quite difficult decisions, on issues involving quite high levels of uncertainty, with an almost equally high degree of confidence.  I am particularly fascinated when this happens with leaders in business.  And I would tend to express this confidence as faith.  Normally there is some object of that faith, and actually the real sentiment attaching that leader to that “object of faith” is trust.

 

So what are those objects of faith, those factors on which a leader bases a decision and which is the source of confidence?   They can be a number of things.  First and foremost, they can and often are other people.  I will take this decision because I trust you;  either that you have done your homework adequately in recommending this decision in the first place;   or that in going with this plan of action, I can trust you will make sure that it happens the way it needs to.  So my faith in taking this decision is in another person or group of people.

 

I have some experience of working with private equity investors and venture capitalists.   They take decisions involving risk all the time – that is their business calling.  They will review business plans, take positions on certain technologies and market sectors, and meet the proposed teams that will be leading the ventures that are requesting funding.  The single biggest factor that will determine whether or not to invest in that venture is what they think of the management team.  Essentially it is: do they trust them to do what they say they are going to do in the business plan.  The investors are primarily basing their risky decisions on whether or not to invest, on whether or not they have faith in the management team.

 

Leaders can also base their faith on other factors. A strong well-reasoned argument with good supporting evidence can also be a basis for faith.  This can be especially true where this forms part of a proven process.  This was the culture of decision making at Procter & Gamble (P&G) whom I joined as a trainee Marketing Manager, straight out of business school.  P&G has a culture of encouraging new young business managers (Brand Managers, Market Managers) to take ownership for a small portion of the business and take initiatives that require decisions involving some degree of business risk. The primary process for doing this were that juniors like me wrote proposals – often famously no more than one page long – which were submitted, approved and forwarded to increasingly higher levels of management, until they were finally approved for implementation at the appropriately highest level, quite often either the regional General Manager, or the President of the Division, which in my case was P&G’s Export and Special Operations Division, headquartered in Geneva, Switzerland.

 

I remember meeting my regional General Manager for the first time after I joined. He gave me a few tips. One of them was that when I submit a proposal for some kind of investment, if the decision comes down to a difference between his opinion and mine, his would always win.  But if it came down to his opinion, and a well-reasoned and evidenced argument on my part, mine would win.  Leaders at P&G place a high level of faith in evidence and logic,  not to the exclusion of faith in individuals, but the evidence is a major contributor.  And of course, because this is part of the P&G culture, the two go very much hand-in-hand.

We know people place their faith in a name. Customers make daily decisions on product or service purchases based on brand names.  There is risk in any purchase – we often cannot be sure that the product or service that we pay money for, will deliver what it is supposed to.  This is the basis of branding.  P&G launched the first branded soap, Ivory, in the mid nineteenth century because they noticed that unscrupulous soap makers were supplying poor quality soap to customers – the kind that would just disintegrate after a couple of washes, for example.  So you bought your soap from a vendor you trusted – you placed your faith in the person.  But as markets got bigger and more impersonal, you couldn’t do this any more.  Every purchase was a risk that you were buying a soap that would disintegrate. So P&G created a soap with a quality controlled process, and marked it with a name, a brand name, Ivory.  As it happens the brand name was inspired by Psalm 45: “From palaces adorned with ivory, the music of the strings makes you glad”.  Here was a soap you could trust – a brand name you could put your faith in.  One that effectively mitigated the risk of the purchase.

On a larger scale, where risk is a more blatant issue, faith in a brand still plays a significant role. Consider IBM and the mantra that echoed around the corridors of power in many organisations: “at least you won’t get sacked for buying IBM”. Similar stories could be told of other major service business-to-business brands.  “We are confident in this difficult decision because McKinsey or PwC have recommended it”.

My interest in this approach was also kindled by a conversation with a colleague, on leadership in sustainability, and a particular example from Coca Cola. They became aware that one opportunity to generate significant energy savings and environmental benefits was to put doors on their coolers in retail outlets.  And yet they also knew from research that doing this would have a significant adverse impact on sales and profit.  So what was the underlying “leadership mindset” that led them to put doors on all their retail coolers?  I was interested in how  leaders saw “faith” as playing a role in leadership  and I saw the link between risk and faith.

Bayesian tale of two cities

This season of Christmas and New Year are particularly well celebrated in the major cities like London and New York.  I remember people celebrating the New Year in, in both cities, by taking Concorde from London to New York and taking advantage of the time difference.

Part of the theme of my book is in working with the juxtaposition of polarities of difference – and I kick off with reference to Charles’ Dickens “Tale of Two Cities”;  “it was the best of time, it was the worst of times, it was the age of wisdom, it was the age of foolishness, it was the epoch of belief, it was the epoch of incredulity, it was the season of Light, it was the season of Darkness, it was the spring of hope, it was the winter of despair, we had everything before us, we had nothing before us, we were all going to Heaven,  we were all going direct the other way”.  I suggest that as we stand in the gap between difference, it can be uncomfortable but rewarding.

And this talk of two cities reminds me of the types of illusions that can throw us off the scent of how we evaluate risk.  It’s about Bayesian logic, and the basis of one of my favourite jokes, which is how I start the next extract from my book.

[Extracts from “Risky Strategy” to be published in 2016]

Tworisks

One of my favourite “one line” jokes goes like this: “Did you know, I am more likely to be mugged in London than I am in New York..[Pause for effect] … That’s because I hardly ever go to New York”

This is an example of Bayesian probability. The Reverend Bayes in the nineteenth century came up with a formula for calculating the results of conditional probability.  Put more simply, that is what happens to overall likelihood when you combine two types of variability.   So in our joke example, we have the variability of getting mugged in either London or New York,  and the variability of the amount of time I spend in either London or New York.  So given I am in New York, my likelihood of getting mugged is say 5%;  whereas, given I am in London, my likelihood of getting mugged is say 1%.  However, I only spend 10% of my time in New York, and 90% in London.  So overall the chances on any given day that I am mugged in New York are  0.5% (5% x 10%), whereas the chance that I am mugged in London is 0.9% (1% x 90%), ie London is higher than New York.

 

This might sound like a trivial example which doesn’t matter that much, but I believe we see Bayesian confusion created by authoritative voices in society, particularly when it comes to medical issues. Taleb picks up on this particular example in “Fooled by Randomness” (Taleb N. N., Fooled by Randomness: The Hidden Role of Chance in Kife and in the Markets)

You have a disease which can affect 1 in 1000 people (ie  0.1%), and the test for the disease is 95% accurate, which means there is 5% false positive. That means that in a sample of 100 test results, 5 of those will  indicate a disease which isn’t there. If someone gets a positive test result what are the chances they actually have the disease?  Many would say 95%.  Actually it’s much lower: 2%.  That’s a surprise to many of us. This is how it can be explained.  In a random group of 1000 people all who happened to have been tested, only 1 probably has the disease. However, of the remaining 999, about 50 (5% of 999) will have tested positive for the disease. So out of that 50, that chances that you are the one that have the disease is 1 in 50 ie 2%.  This is quite a powerful illusion. I wonder how many people who have been tested for a fairly rare disease with what appears to be a fairly reliable test, and testing positive, have been told there is a high chance they have the disease.

Illusions about acceleration of change impact our view of risk

A recent Economist article:  “The Creed of Speed”  http://www.economist.com/news/briefing/21679448-pace-business-really-getting-quicker-creed-speed   challenges some of the generally held views that change is accelerating, which makes long term strategy setting potentially futile.   This ties is with my chapter on mind games, covering some of the factors that can influence our approach to risk in developing strategy.

[Extract from “Risky Strategy” to be published in 2016]

One of the most pervasive concepts we have when thinking about strategy under uncertainty, is that it is getting more difficult because change is just happening more quickly.  So we tend to be more likely to conclude with Error Type B (See Chapter 1),  there is no point in making decisions because the chances are very high that we will have to change them in a little while, when something else big happens to change everything.

You will have gathered by now that I don’t support this view. I believe we do need to be prepared to make tough choices as leaders, even though they can entail significant risk.  Now comes perhaps one of the more radical ideas in this book:

“I’m not totally convinced that change is actually happening faster now than it was in the past”.

Oops there, I have said it.  Partly, I wonder if it’s the basis for not making decisions which as leaders, I believe we are often paid to make.  I wonder if it’s a bit of a cop out.

I also am aware that there is a growing body of business people who have a vested interest in the idea that change is happening fast. It is the fundamental calling card for management consultants, of which I am one and have been for much of my professional career.  So with this kind of vested interest, I naturally feel a tad suspicious that the very same people are the ones promoting the idea that “you’d better watch out, because change keeps accelerating!”

There is one example of where I am aware of an illusion that helps to promote this idea.  It is the illusion that our population has been growing faster in recent decades than it has been throughout the history of mankind. And it is captured in a graph that looks something like the one below.

Population growth

The headline is “here is another example of how much change is accelerating in the last hundred years or so”.  The reality is that this curve is the output from a mathematical model of population growth.   The rate of   growth actually remains the same throughout the time period represented by the x axis – ie as shown here, since the beginning of time.   The main driver of population growth is the average number of offspring per couple who then go on to reproduce themselves. If this growth factor is above 2, population grows; if it is below 2, population declines.   In this model, this growth factor is actually the same throughout the time period represented.  Population growth is not actually accelerating; the rate of sustainable reproduction has remained the same throughout the time period.

 

 

Do you embrace variability?

[Extract from “Risky Strategy” to be published in 2016]

As we have seen, variability is at the heart of risk.  We also know that the world would be a dull place without variability.  And we are somehow conditioned to want to do something about that variability – to work with it and at the same time against it.

Imagine a game of tennis where the ball bounced in exactly the same place and to the same height before you hit it.  So you would master the game very quickly by playing pretty much the same shot every time. You might become very good at it, but how interesting would it be.  Why don’t they make golf courses with all the holes the same length, in a straight line with same size greens, and the hole in the same spot on each of them.  You can see the point. We enjoy the variety, and at the same time, we are honing our skills to try and counteract that variability;  that we hit the same quality of tennis shot regardless of where it bounces and how high;  that the golf ball heads towards the green regardless of the distance we are away and what type of ground surface we are hitting it off.

Its as though life is designed to create risk, and then deal with it, either by going with it, or working to counteract it  … and that is part of how we enjoy life.

I am reminded of one of John Cleese’s Video Arts humorous training videos which were popular in the 1980s – the one on time management. Most of the film was about being ruthless with time-wasting activities.  Then there is a shot of John Cleese sitting at his desk when the phone rings several times, without him answering it. The voiceover asks him something like: “Why aren’t you answering it?”, to which Cleese responds that it would be just another distraction that would waste his time. The voiceover then says: “No, wrong. You need to answer it. That’s your job calling!”

While the elephant mindset is, to some extent, that variability is an annoying distraction,  for tigers it’s their job calling.  In fact, tigers are naturally anti-fragile, according to Taleb’s view of risk. (Taleb N. N., Antifragile – How to Live in a World We Don’t Understand, 2012). His proposition is that we as individuals and organisations are naturally fragile within the uncertain world in which we live.  The market can change due to new technology; our lives can change due to an unexpected illness or accident.  And we tend to respond by doing things to compensate for this fragility by trying to create robustness.  We diversify by investing in other products with other technologies in other markets.  We cut costs to save money for that unforeseen event, and we take out expensive insurance to cover eventualities of various kinds. And somehow it doesn’t seem to bring the peace we seek.

Taleb proposes an alternative model – anti-fragility. It’s a kind of working with the variability and risk, rather than against it.  He takes part of his cue from nature.  Plants work through a process of death being the source of new life. Part of the fruit or flower of the plant, a seed, is  deliberately disconnected from the plant and is buried – and this is what creates new life. Or the cutting of a branch through pruning creates an environment for even more vigorous growth than was there before.

“The best way to verify that you are alive is by checking if you like variations …. Food would not taste if not for hunger; results are meaningless without effort, joy without sadness, convictions without uncertainty;  and an ethical life isn’t so when stripped of personal risks”  [Taleb N. N]

Our human bodies are built to be anti-fragile – clearly designed to deal at least as much with the consequences of risk as to be able to avoid it.  Wounds heal themselves with relatively minimal outside help, and white blood corpuscles fight off unwelcome bugs which are part of the risky external environment that our bodies inhabit.   Our health systems seek to create robustness which is a pale comparison to the anti-fragility that is part of our human make-up.

Taleb’s arguments apply the lessons of organisms such as plants and the human body, to human organisations.  Those that try to create systems to constrain risk, by having checks and balances at every corner, will never be as effective as anti-fragile organisations that work with risk, where every part of that organisation is designed and motivated to take a risk situation and do something better as a result of it.

Organisational leaders could benefit so much from learning how to get more from their people in their natural capability to deal with risk and variability.

Linking risky strategy to character

 

[Extract from my book, “Risky Strategy” to be published in 2016]

I recount my experience as a strategy consultant working with the value disciplines set out by Treacy & Wiersema in their book: “The disciplines of market leaders”

I found that when I worked with clients on the organisational factors which would help inform which strategic discipline they would be most likely to prosper in, there was one important question which was hard to answer.  I could see fairly readily what types of processes they had in place, how much they spent in each, what performance metrics were most important, what they told the market they were about.  All of these would give me some idea of whether or not this business would lean more readily to product leading, or being intimate with customers,  or being operationally excellent.

The big question I couldn’t easily answer, nor could the client’s senior management, was:  what personal attributes of the people in the business supported one discipline or the other.  So I developed a management tool to help me do that,  a Character Profiler which was named after my business, Blonay.

Blonay Character Profiler

An important influence in developing this tool was a sentence I came across in the Apostle Paul’s letter to a colleague called Timothy, for whom he was very much a mentor.  Paul initially reminds him to “fan into flame the gift that God has given him”.  He is talking about personal strengths in his character.  I was moved by the picture that made me think of fanning the glowing embers of a campfire to the point where it bursts into flames – the idea that a little persistent encouragement to an apparently lifeless situation with signs of potential, can suddenly create so much energy and vitality.  What a picture of leadership that is.

He then goes on to say, “For God did not give us a spirit of fear, but a spirit of power, of love and of self-discipline”.  I remember thinking that this sounded like a complete set of virtues to which many probably aspire and are able to exhibit to varying degrees.  “Power” spoke to me of the ability to create or inspire positive change; in other translations, it is “boldness”.  There is the virtue most closely connected with courage.  This spirit is the spirit of the pioneer,  bold and creative at the same time.

Then we have the spirit of love. The word “love” I believe is much abused in modern life to mean a plethora of things.  For me the essence is about relationship with our fellow human beings, to be committed to positive relationship. The underlying ability is to be able to see or feel things from another person’s perspective: to be able to empathise.

And finally there is the spirit of self-discipline.  In essence, for me, this is about a personal attention to getting and doing things right, to be ordered and organised, and to be passionately interested in truth.

These for me appear to be demanding personal attributes.  Some of us I suspect are stronger in one of these virtues than we are in the other two. In fact it is probably very difficult to be consistently strong in all three dimensions.  Be strong in one doesn’t help you to be strong in either of the other two. From a mathematical perspective, I would describe them as orthogonal – completely mutually independent of one another in terms of human character.

And it occurred to me that this was a similar story to that which Treacy tells. There are three organisational disciplines which can lead to a prosperous position in the marketplace.   And it is very hard to be strong in all three – because to some extent they conspire against one another.  They create trade-offs.  As do Paul’s three virtues.

So I borrowed this idea to develop the Blonay Character Profiler, which is about assessing personal character on three character dimensions.  I have called these:  Bold Creative,  Empathic and Self-Disciplined.

The main similarities between these and the Treacy disciplines is the idea that these three dimensions create tensions, either within us as people as in the case of the Character Profiler, or within organisations, as in the case of the disciplines.   This means there are trade-offs to be made – dilemmas to be addressed.  I have already discussed this in the organisational context, and will explain more about how this works in a personal context a bit later.

There is also some similarity in terms of what these three dimensions represent.  So in this sense, I chose to map one model onto the other.  Bold Creative maps to the Product Leadership discipline.  Empathic maps to the Customer Intimacy discipline. And Self-disciplined maps to the Organisational Excellence dimension.

At the time of writing, I have as yet unsubstantiated hypothesis that Product Leadership organisations need more Bold Creative leaders, Customer Intimate organisations need more Empathic leaders, and Operational Excellent leaders need more Self-disciplined leaders.  What I have discovered is that the Blonay model has a high level of resonance with managers considering these kinds of issues, more generally in connection with strategy.   The model also works well in helping to understand the attitude and appetite individuals have to risk. Bold Creatives tend to have a greater appetite for risk than the other two character attributes.

Before developing the dynamics of this profiler further, I was further encouraged in my quest to focus on these three character attributes by the work of Jim Collins at Stanford, covered in his book, “Good to Great”. (Collins J. , 2001)   Jim Collins in his research identified that the leadership characteristics which differentiated his high flying 11 organisations from the rest seem to fall into three buckets: discipline, humility and resolve. The Blonay Profiler mirrors these in a similar set of three character attributes.

Assessing risk is impacted by how easily you can change your mind

[Extract from “Risky Strategy” to be published in 2016]

Cognitive inertia (a.k.a in long form Cognitive Dissonance Reduction) is our inability to evaluate a situation objectively, or to come up with new creative solutions,  when we face conflicts with decisions we have already taken.  We experience  Cognitive Dissonance  when we encounter evidence that conflicts with a decision that we have already made and it feels uncomfortable, so we try to minimise that dissonance.  So, we tend to find it hard to evaluate the new evidence objectively or rationally.  This can affect both risk averse and risk taking behaviour.

Let me illustrate with the Game Show Host conundrum. Try and do this without looking at the answer below, because your response to the answer is important.   Then once you have completed the exercise,  read on.

In a game show, contestants are asked to pick between three doors. Behind one of the doors is a prize. As a contestant you pick one door. The Game Show Host then opens a second door, one of the doors you didn’t pick, to reveal the prize is not behind that door. The rules of the game is that the Host will always open another door which doesn’t have the prize.  You are then asked if you would like to switch your choice to the last remaining door. What do you do?

a)  Stick with your original choice, or

b)  Switch your choice to the remaining door

THE ANSWER: Having selected your choice , I will now tell you that the majority of respondents answer ‘a’  But I also need to tell you that you double your chances of winning if you change your choice… you have a 2 in 3 chance of winning if you switch doors, compared to a 1 in 3 chance of winning if you stick with your original choice.

While this may not make intuitive sense, and indeed a number of professional mathematicians don’t accept this outcome, you can prove it to yourself by doing a simulation with a friend a number of times with three cards (an Ace as the prize).  Ask a friend to pick a card, then show them a second card which is not the Ace and ask if they would like to switch their choice to the remaining card. If you do this 10 or 20 times, you will begin to see that by switching to the remaining card, your friend would win the prize 2 times out of 3, whereas by sticking, they only win 1 time out of 3.

This is a metaphor for cognitive inertia, and illustrates something interesting about our intuitive approach to risk.  And it’s a double whammy – it does this in two ways.

Firstly, the idea that we have already picked a door (ie, made a decision) makes it more difficult for us to consider changing that decision.  This is the first level of inertia.  But to switch doors increases our chances of winning, ie, it reduces our risk of losing.  So the change option is actually the low-risk option.

Secondly, there is a much more pervasive form of inertia where we justify our decision based on our own assessment of probability.  Most people think that they have a 50:50 chance whether they stick or switch, so why switch.  But what happens when I explain that actually the odds are twice as good if you switch.  Normally, the initial reaction to that piece of news is “You’re wrong!”, rather than “So how can you show me that that is the case”

It is fascinating that there is, or at least was, an internet site with this problem and solution set out, and a blog of commentary from supposedly leading mathematicians arguing quite vociferously that this is not true, that the odds do not improve or that this is bad mathematics.   And yet, as I suggest, you only need to run it as a simulation enough times to convince you of the pattern, to see that you do indeed double your odds.  So it’s an illustration of how hard it is to stand back from decisions and hard-fought beliefs, and to look at something from a different perspective.

When it comes to risk, are you more tiger or more elephant?

 

[Extract from “Risky Strategy” to be published 2016]

One of our respondents told us that the reason for the success of a major global product launch was the presence of a combination of ‘elephants’ and ‘tigers’ in the launch team.  This technical product needed to be developed quickly but also reliably, to seize an important opportunity in a fast growing consumer electronics market.  This respondent described these two types of individuals involved in the launch process as follows:

tiger & elephant

Elephants are methodical and analytical, have good memories, build momentum, but tend to be slow and grey. These are the formal risk workers who assessed risk using objective, quantifiable and evidence-based outputs. Often working in response to regulation (compliance, governance, legal, industry standardisation), their focus was on high visual sharpness, accuracy and timeliness in an attempt to reduce subjectivity.

Tigers are colourful, fast, intuitive and brave, but if you have too many, you have chaos. They are the informal risk workers.  The emphasis was on breadth, was multi-dimensional, making use of wide channels of information, employing intangible and subjective processes. Informal risk workers used peripheral vision to scan the environment and to provide space for generating hypotheses.  Sometimes referred to as instinct, gut feel or common sense, this requires an inherent ability to consider what is at stake by looking for threat or identifying opportunity. There is no single focus of informal risk; three dimensional, entrepreneurial, holistic and peripheral vision are the words we heard managers use when describing how informal risk perceivers scan their environment.

As we reviewed the responses from our leaders as to how they tended to work with risk, it became clear to us that there were broadly two ways.  There was a formal way, which was all about analysis,  risk assessment, and processes and models. These were designed to work out what kinds of risks were likely to happen, when based on some kind of evidence, and what we can do to reduce the likelihood of a harmful outcome.

The second way was the informal , intuitive way.  These leaders are aware of risk being around them daily, and that many of the decisions that they make daily have a distinct risk element to them. And the decisions they made would be based on some kind of judgements about that risk, with very little overt evidence.

It struck us that the elephant and tiger picture language that our respondent used to illustrate this particular case was a great way of describing these two modes for working with risk. The elephants are the ones who work with risk in a formal analytical way, and the tigers are the ones who work with risk in an informal, intuitive way.

We had the sense that while circumstances may well dictate in which of these two modes risk thinking is most comfortable,  it seemed clear that some people prefer the formal, elephant approach, and believe that is the only way to think about risk.  In fact, going back to our debate around Knightian definition,  they would probably say if you can’t deal with risk in this way, then it’s not risk, it’s uncertainty – and that’s something different altogether.

Others people prefer a more informal, intuitive way of thinking about risk. They may also call it uncertainty.  But they say things like; “I feel comfortable taking the risk” … or “for me, the risk is acceptable”.  It’s a personal assessment, with no overt data. In fact, I would say that it’s this personal fingerprint on the assessment of risk that is a defining characteristic of leadership.

Teaching how to feel safe with risk

This week an Ashridge team won a Training Journal award for our leadership development work with one of our clients, Heineken. https://www.ashridge.org.uk/executive-organisation-development/custom-programmes/case-studies/Heineken/  The essence of the programme is helping participants to experiment with different leadership styles and interventions in high stress situations, which they can do in the relatively “safe” environment away from the workplace.   This is done through a classroom simulation of an organisation in crisis, where actors play roles which create the stress. Participants wear heart-rate monitors, and are regularly evaluating their own approaches and physiological responses, as well as those of each other.  The idea is they develop a kind of muscle memory for the impact of different kinds of interventions and responses in situations involving significant personal risk.

In the introduction to my book, I state that the book is about the journey towards feeling safe with risk, which is the key to effective strategy.

[Extract from “Risky Strategy” to be published in 2016]

One of my stated aims from this book is to help leaders feel safe with risk. This is of course a paradox, yet I believe the reality is that leaders will not take the risks they need to take if they don’t feel safe in doing so.  This is looking under the bonnet of the leader, to understand what might be going on behind the scenes to support right risk taking.  Up to now we have been looking at the outward evidence of risk-taking decisions in organisations, with some exploration of what psychological factors might influence those decisions.  But the deeper issue is how risk makes you feel when you take it, particularly personal risk.

I believe at some level, right risk takers do have a mechanism for helping them to feel safe.  Part of this may indeed be the hormonal effect which not only prepares us with the capabilities to engage more effectively with risk, as in the case of testosterone, but also provides an anaesthetic to numb the fear.  This makes me think of adrenaline, and reminds me of the day my Achilles tendon snapped while playing indoor soccer. I can still remember the excruciating pain in my ankle the moment it happened, as if I had been struck there by the sharp edge of a brick that had been thrown at my foot.  Within only five or so seconds, the pain was already starting to reduce.  The adrenalin was kicking in.  Then I thought I had just been taken out with a tackle from behind. The first aider who took care of me accurately diagnosed it as an Achilles tendon going after a bit of research – no one had been anywhere near me.   But the numbing effect of the adrenalin meant I drove myself to the hospital, even though I was only able to use my heel and not the front of my foot to depress the clutch.

The idea of feeling safe with risk is one of the bases on which we have tried to offer Executive Education at Ashridge.

There is a conundrum. In traditional teaching environments, away from the buzz of everyday working life, how do we replicate the real risks that leaders face, in the relatively “safe” environment of the classroom?   Conceptualising risk for learning purposes appears to have an anaesthetising impact on our actual experience of it.  We may think our way through a case study involving risk in an abstract way, using suitable models to help us; but the emotion of risk is generally missing in a “safe” environment.  Virtually nothing we do or say in a classroom setting will put the company finances at risk, nor the health of our stakeholders, nor our own careers.  To some extent this is exactly why the “classroom” is designed to be a “safe” environment – it’s confidential, it’s safe. “What’s in the room stays in the room?”

Indeed, the  unique selling proposition for “away-from-the-workplace” learning is that it is  a safe environment in which to experiment, in which to take some ‘risks’ that participants wouldn’t normally take in the workplace.  These risks can be about exploring and articulating new ideas to colleagues, about having conversations that they wouldn’t normally have, about interacting with others in a way that may not feel comfortable.  So for some aspects of working with risk, the “classroom” offers an advantage, even if it may feel a little artificial or clinical.

But, paradoxically, if we are creating safety to work with risk, how can this be authentic?

We have successfully worked around this dilemma in our management development practice by using simulations that generate the emotion of risk.  These take the form either of team-based competitive decision making in a computerised market-place simulation over a series of rounds, or of working through specific artificial challenges working with professional actors, whose role it is to re-create some of the emotion of difficult, risky, situations.  Participants have also been asked to wear heart rate monitors over one or two days, as they work together to resolve simulated problems which may be creating tensions between individuals.    Participants are encouraged to experiment with roles which are different from those they would normally have, and with types of interventions which they would typically not employ. Their emotional responses are monitored and measured.

These programmes demonstrate that they can have a significant residual learning impact – i.e. this learning manifests itself after, not during, the experience of the programme.  Participants start to apply certain aspects of what they have experimented with on the programme back at work and they are encouraged, post programme, to reflect and to continue learning from these reflections.  They effectively build on the risk that they have already taken during the programme by applying the experiment in a real work environment.  There is effectively a physiological stress memory, reflected in the heart rate print-out, which gets replayed in the workplace.  This has been called the development of emotional muscle memory, in the same way that a tennis player only really learns how to hit an effective tennis shot when he does it automatically without having to think about it – i.e. when he has developed muscle memory.

Could Federer have won by taking more risk?

 

Yesterday, Djokovic won the ATP World Tour Finals tennis at the O2, beating Federer by two sets to zero.   I was disappointed because Federer had indicated he would pursue a more aggressive style of tennis, in particular by coming to the net to volley more often.  Overall, in 116 rallies in all, Federer lost because he only won 46% of them.  When he came to the net in rallies, he won 65% of the time.   But he only came to the net for 17 of those rallies!   The statistics suggest that if he had come to the net more often, he might have won.   Why didn’t he?  Part of the reason could be summarised in this extract from my book: “Risky Strategy”

[Extract from “Risky Strategy” to be published in 2016]   

My game is tennis, and I notice that an approach to risk is being played out on a point-by-point basis.  An approach can be planned in advance, in the form of an overall match or set strategy, but in reality you have a point strategy, or even an in-the-moment shot strategy.  So how does risk manifest itself in tennis?   Well, one way is in the approaches to the net as shown in the following diagram.  This is based on some fairly rough and ready research of rally length and outcomes in professional games.  The average rally length in a game is around a surprisingly low five to six shots total, so less than three per player.  In terms of winning or losing shots, at the top professional level of the game, this is split very close to 50:50 – it’s surprising how close a lot of professional games are in terms of points won or lost.

Tennis risk chart

So what is this chart showing us?  This is an equivalent to a normal distribution curve for two types of tennis shot: the blue bars represent the distribution for shots played from the back of the court, and the red from the net area.  There are just three points in the distribution for each shot type, as we are only interested in three possible outcomes from the shot; either it’s a winning shot, it’s a losing shot, or the rally continues so that the player gets another shot.

So first to note that our flatter ’curve’ is our more risky shot, remembering the way I demonstrated risk and variability in the earlier chapter. In other words, there is more variability in possible outcome with our flatter (brown) net shot – which is what we would expect. The net shot is more risky; there is more chance of the extreme outcomes, either a win or a loss.

A back of the court shot is less risky; it has a more peaked profile – the most likely outcome from the shot by a good margin is a continuation of the rally.

So what we see from this is that the shot which has a higher chance of winning the point is the shot at the net – ie the more risky shot.

What is interesting is that tennis players know this, and yet the shot at the net is a relatively rare part of the game at the professional level today.  It used to be more regularly played; up until the late 1970s and early 1980s, the serve and volley at the net was a regular way for players to win points, particularly on grass courts.   Of course, there are a number of reasons why that has changed. Tennis balls are slower and make it harder to hit winners.  The perfected top spin ground shot, pioneered by Bjorn Borg, changed everything, making it easier to hit dipping passing shots.  And longer rallies and games means energy is a bigger factor – coming to the net expends more energy.

However, the most interesting feature of this analysis is one other reason why us tennis players are more reluctant to come to the net. Yes there may be a higher chance that the shot will be a winner.  But there is also a higher chance it will be a loser.   And, in the tiger moment, away from rational elephant analysis, our loss aversion kicks in!