Category: Strategy

We all know about the horrors that took place during the Second World War, in Cambodia, in Rwanda.

The history of humanity, in virtually every culture, is littered with stories where one group of people abused their power over another.

What do we infer from these stories?

One inference is that is was all down to a small group of individuals who were fundamentally evil and were able to dictate what was done from their position of power.

From Vlad the Impaler to Pol Pot, from the Nazis to Saddam’s Iraq, we can point the finger and find one person to blame, or a group of people that should be tried and punished.

Would you act differently if you were in their position?

The evidence suggests that you would not.

In a famous experiment conducted in 1971 at Stanford, researchers found that it took only six days to turn nice, normal college boys into sadistic monsters.

They did this by creating a prison, making some of the boys guards and others prisoners and setting up a simulation where the guards had absolute power over the prisoners.

They set up conditions that:

• Dehumanized the prisoners
• Deprived them of sensory stimulation – no clocks, no views of the outside world
• Took away their identify – they were referred to as a number
• The guards could punish infractions of the roles or improper attitudes

The end result was that the situation these people were put into brought out and magnified some of the worst aspects of their humanity and the experiment had to be abandoned after only six days.

Why is this relevant to us now?

Surely all this is just something that happened a long time ago somewhere else to people not at all like us?

The problem is that we tend to think that bad things happen because the people involved are bad rather than because the situation they are in allows them to do bad things.

This is called the fundamental attribution error and has been described as the “conceptual bedrock” of social psychology.

In every day life, we explain away our lapses by finding reasons in our environment for how we behaved as we did.

With other people, however, we tend to conclude that others are lazy, incompetent or thoughtless, explaning their behaviour as due to their internal characteristics.

Understanding that the environment has a huge impact on how people behave is crucial in some situations.

For example, I recently heard a someone talk about visiting a care home where the staff referred to the residents by their door numbers.

“Room 32 needs a change, Room 42 is hungry”.

This is the first step to removing that person’s identity – reducing them to a number rather than a person.

Such practices should have no place in an organisation – especially one where people have power over others.

Finally, on an individual basis, we place great emphasis on personal fulfillment.

For example, do work that makes you happy.

It turns out that what makes you happy is less to do with the work you do, and more to do with the conditions of your work – do you have autonomy, feedback and control over what you do?

People in charge of designing organisations need to realize just how important the environment is in influencing how the people in that organisation behave.

If you want your people to perform, first create the right environment for them to be good.

General Stanley McChrystal, a retired 4-star US General who commanded US and coalition forces in Afghanistan, creates a “red team” when planning an operation.

The idea is that when any group of people start to work on a plan, they think about certain ideas and strategies that they think will work.

As they do this, they start to focus on information that confirms what they believe and begin to discount what does not. It just seems to be the way the brain works – a confirmation bias.

In a military situation, this can result in the wrong decision – which can be fatal.

The job of the red team, which is made up of different people from those that did the planning, is to figure out how they would disrupt the plan.

Their job is to think creatively about the ways in which the plan could go wrong and what they would do to frustrate it.

This is also called ‘devil’s advocacy’, where one expert presents a plan and a second critiques it.

Importantly, the job of the job of the devil’s advocate is only to present flaws with the original plan, not to provide an alternative solution.

If they start to think about solving the problems they find, they start to introduce new biases.

In research by Richard Cozier and others from the 1970s onwards, they found that the use of a devil’s advocate significantly improved the prediction accuracy of strategic decisions.

Using a red team helps create a plan that is solid, rather than because the people who executed the plan were lucky.

We can still see how not doing this creates disastrous results now.

Theresa May’s result in the UK general election, where she managed to lose the conservative majority, is being blamed on how her chiefs of staff created an atmosphere where dissent was not tolerated.

This led to focusing on policies that lost them support and led to electing a UK parliment with a weakened government entering crucial negotiations with the European Union.

Some people may think that is actually a better result. A stronger government with an absolute mandate may have had the power to do what it wanted – resulting in a worse outcome.

The current parliment, with a stronger opposition critiquing the government’s plans, may result in a better outcome for the country in the coming years.

How can you become more successful?

One answer was inside a TED talk by Damian Kulash, the lead singer and director of OK Go, an American rock band known for its elaborate and quirky videos.

Damian explained that in one of their videos, a giant Rube Goldberg machine, there were 130 sequences that had to take place one after the other where each sequence triggered the next.

In each sequence, something fairly simple takes place. For example, a ball rolls down an incline, a counterweight lowers an object or an object something swivels on its axis and hits something else.

If each sequence works 9 out of 10 times then its probability of working correctly is 90% or 0.9.

How likely is it the band will be successful at filming the entire set of sequences in one take?

The maths of probability is used to work this out. In the equation P^n, P stands for probability and n is the number of events.

Plugging this into the equation, the probability of each sequence working is P = 0.9 and the number of sequences is n = 130.

0.9 raised to the power of 130 is 0.000001125.

That means there is literally one chance in a million that the series of sequences will work.

In life and work, we often have to do things that follow a process, where one thing needs to be done after another.

If we aim to be quite good at each thing – and get it right 9 out of 10 times, then the more things we have to do, the less often we will be successful.

For example, if an operation in a business takes 10 steps and you are 90% sucessful at each step, the probability of success is 0.9^10= 35%.

That means two-thirds of your customers are likely to be unhappy with what they get from you.

You can improve your chances of success by doing two things.

First, increase P. Get better at doing each thing.

If you get things right 99% of the time, 0.99^10 = 0.9, which means your customers are happy 90% of the time.

Only 1 out of 10 walks away unhappy. Still not great.

Second, reduce n, the number of things you have to do.

If n was 4 rather than 10, then you would get 0.99^10 = 96%.

Now 96% of your customers are happy.

In summary, the maths of success says work on optimising the formula P^n so that the answer tends to 1.

In other words: Do less, and do it better.

McKinsey talked what they called one of the ugliest and most common charts in strategy at the start of the year – the hairy back.

At the start of any process – a startup pitch, a sales plan, a production forecast, you need to show a chart where, from a standing start, forecasts go confidently upwards – the “Hockey stick” graph.

In reality, the forecasts are not achieved. Year after year, as actual performance stays flat or even drops, the forecasts create a series of lines that go up – and the hockey stick turns into a “hairy back” – like the ones cows have…

Why does this happen? Why do smart people get it wrong year after year?

There are a number of reasons, and they all come down to the psychology of business.