Do you always know exactly what you are doing?

July 27th, 2021

Know what you are doing, do what you don’t know.

You have all read lots about the Euro 20 final.  Let’s look at another game that has lessons for us at work.

Spain versus Italy in Euro 20 was a football lesson about the importance of a balance between clarity and chaos.

Both teams played very characteristic football.  Both teams scored once during the 90 minutes and Italy won on penalties (sounds familiar).

The Spanish football was beautiful to watch – a case study in their trademark tiki-taka play.

We wrote about the spirit of their game in our case study about Xavi in our book Belonging.  Describing his role in the game in one of the humblest utterances

from a world-class footballer, Xavi said it was simply: “Receive,

pass, offer”:

  • Receive the ball.
  • Pass the ball to a teammate.
  • Get yourself into a position where that teammate can pass the ball

back to you.

We used this as a great role model for leadership in the office to create a culture of Belonging where everyone can thrive.  Let’s put aside the brilliance of being able to describe everything that you do in three simple words. Focus instead on what that means for every other member of his team. Xavi’s role here was not focused on scoring goals or on tackling the competition, nor specifically on defence. It’s certainly not about him looking good. It was entirely to be at the service of his team members. “Truly if you played for Barcelona

at its peak, there was always someone to pass the ball back to, so you didn’t run the risk of being the idiot that let go of possession to the striker from the other team who might score the winning goal.”  And for most of the Italy Spain game on July 6th 2021, this kind of football was on show whenever Spain had the ball.  Now, you may or may not have a Xavi in your team at work.  But in the likely case that you do not, what if instead you create a culture of Belonging, where the whole success of the business is more important than individual stardom or each person crushing their own KPIs? If you can galvanize the culture in this way, the chances of success

over the competition are much greater.

But as we saw, this strategy alone is not always enough.  Fans of Barcelona, with long memories, may recall the game in when 2012 Chelsea played Barcelona in the semi-final of the Champions League.  It’s probably fair to say that most people who watched the game on the TV in the UK, excluding Chelsea fans, were rooting for Barcelona, home of some of the most beautiful football in the world at that point.

I watched my partner watch the game.  At the end of it he was yelling “Just stick it in the mixer!”

I had to ask him what that meant.  He said that Barcelona were renowned for their passing game and maintaining possession of the ball.  They knew what worked, and what didn’t work, and played to a system that made them extraordinarily successful, and conquered all before them.  A system that they refined all the time, but that they didn’t like to deviate from.  Unfortunately for Barcelona fans (or anyway non-supporters of Chelsea) the only people who understood Barcelona’s system better than Barcelona were Chelsea.

Their fans were desperate for Barcelona to deviate from their system of keeping the ball in possession and take some chances.  To stick it in the mixer (goal area) and not worry about the chance of giving the ball away.

How many glaring opportunities are passing by because the rigour of the media playbook means that they can’t be proved to work in advance of trying?

There needs to be a balance between following the rules and justifying actions on the basis of known data, and taking a leap into the unknown.  Sometimes, most of the time, sticking to the tried system is good and proper.  Yet this is based on what we know we know, and as economist John Kay and former Bank of England chief Mervyn King write in “Radical Uncertainty”: “Good strategies for a radically uncertain world avoid the pretence of (certain) knowledge.. they acknowledge that we do not know what the future will hold.”  Or as we might conclude from the beautiful game:  Sometimes you need to stick it in the mixer for any chance of a win. Know what you are doing, but also be clear about what you don’t know and when to try something where you cannot predict the outcome.




This one weird trick will transform your career

July 9th, 2021

There are 48 techniques that can transform the creativity of the work that you do.  Here’s one of them.  The power of diverse voices.

Its not a secret that I believe that diversity drives business growth.  It is also crucial to creativity, and truly creative people, whoever they are, synthesize different voices to create powerful new work and ideas.

In 1963 Mike Nichols (who subsequently went on to direct and win an Oscar for The Graduate, a movie that is more interesting by the way from the point of view of Mrs Robinson than the other characters) was just about embark on directing for the first time (he had been a comedy performer until then).

His first play, which he delivered in just 5 days, was Barefoot in the Park (later also a hit movie).  Written by Neil Simon and starring Robert Redford in one of his breakthrough roles.  Speaking on the Sky documentary “Becoming Mike Nichols”  Nichols talked about the process of creating the play, which included a lot of rewrites and improv – his preferred way of working.

New job, lots to prove, 5 day turnaround, script unfinished.  Quite a challenge.

He said that the play was funny, but didn’t have an ending, and though he and Simon wracked their brains they couldn’t find a good third act.  The breakthrough came from an older friend of Nichols who watched a rehearsal.  The writer Lillian Hellman commented on one scene saying that she had a much better idea for it.  She thought that the mother-in-law of the lead character played by Redford might sneak off with the rakish elderly gentleman who lived upstairs for a fling.  This in fact wasn’t the plot, but as Nichols considered it this actually was the twist that the play needed – the action that allowed the resolution of the stormy new marriage of the main plot.

Nichols as a younger man, more of an age of the young married couple who star in the show, couldn’t imagine the mother-in-law (in her 50s) having illicit sex with the man upstairs.  As he reminisced about it he sounded somewhat shocked even in retrospect.  What was clear was that without Hellman, a women in her late 50s, the 30 something men who were writing and directing would neither have considered, nor felt permission, to add this charming twist to the plot.

Nichols and Simon, two men in their thirties, stumped creatively and saved by listening to the voice of a woman who because of her age, is fairly invisible in traditional creative departments.

As MediaCom’s global ceo of creative systems Stef Calcraft writes: “Here’s to the creative ones, and that can be all of us”.  If it isn’t all of us, really all of us, in our full differences in every respect (including age), there just won’t be as much creativity.

That was the first of the 48 ways to transform creativity.  The others I will come back to in future blogs.



Do you believe in data magic?

June 25th, 2021

Are we mixing up magic and science (again)?

It’s always been true that people can manipulate data to fool others. (A index chart with a scale that starts at 50 not zero for instance is a classic and somewhat disappointing feature of some awards entries to exaggerate impact).

Now data may be manipulating us as AI takes control.

The consequences of this are far reaching and profoundly dark.  We should not believe in what we see without interrogation.  For some this has echoes of the pre-enlightenment mass belief in magic.

Until the late seventeenth century in the west the magic and science were pretty much the same thing.  Isaac Newton “discovered” gravity but he also worked hard to turn metal into gold with alchemy.  Queen Elizabeth 1 sponsored the magician/mathematician Dr Dee who cast spells and also taught Drake and Raleigh how to navigate the globe.  Dee conversed with angels, and wrote algorithms (they aren’t anything new) to explain the solar system.

Magic fell from grace as an endeavor for scholars and scientists in the enlightenment replaced by cold hard data.  Today, one leading commentator on data science believes that we are in danger of thinking about it in terms that are magical.

  1. David Edelman is director at the Massachusetts Institute of Technology. A one time advisor to Barack Obama he joined me at a keynote for NextM Austria – at a fascinating conference session chaired by Omid Novidi, ceo of MediaCom Austria.

Edelman pointed to one example of “magic” in tech:  DeepFake (where machine learning and artificial intelligence is supercharging the ability to fake content)  – the fun aspect of which is compelling, the dark side of which is yet to be fully understood, or accounted for.

Artificial Intelligence (AI) is climbing up to the “Peak of Inflated Expectations” according to the Gartner Hype Cycle (though nowhere near the “Plateau of Productivity”), but it is cropping up widely, and often usefully.  Outside of our industry Edelman cited an education experiment where 2 years of progress was made in just 6 weeks as a result of personalized AI driven online learning programmes for schoolkids.  AI is saving lives in screenings for breast cancer.

For our industry Edelman warns that AI is in its infancy.  And there are dangers if we don’t guide AI ethically, responsibly and monitor its progress.

Edelman advises 5 key questions to ask when using AI.  Crucially this means asking specifically who designed it and whose reputation is damaged if it goes wrong.  Many systems are designed for the current status quo by the current leaders of that status quo.  Yet simultaneously we’re trying to change the status quo, to make our businesses stronger and better for the disruptions to come.

As industry changemakers we need to interrogate AI carefully.  Can we on the one hand make pledges about being more inclusive in the work and in our management and at the same time allow AI to make decisions based on the biases of the past?

One glance at the current situation shows that the status quo is not ok.  The Economist has taken a look at how AI is working in Google Open Images and ImageNet.  They found just 30-40% photos are of women,  (50% of the population of course), that men are more likely to appear as skilled workers and women in swimsuits or underwear.  Frequency of labels for men are high for “business, vehicle, management”. The equivalent for women include “smile, toddlers, clothing”.

Edelman reminded the conference audience of a key episode from America’s history  The Salem Witch Trials took place in the seventeenth century in Edelman’s county of residence Massachusetts.  He warned that if we allow the narrative about AI to become magical then we are in danger of behaving like the residents of Salem, of becoming like uninformed credulous children and allowing unfair and even harmful practices to become the norm.  We will fail to challenge the systems in a way which will create a better world.  In Salem being an outsider was harmful at the minimum to your prospects of flourishing (most of the victims were misfits to a strict Puritan society).  We need to actively design AI to encourage more diversity and bring in outsiders in our systems now.  We must actively ensure that we design AI to drive change and difference.

Edelman says: “Don’t just build AI for performance, but also for opportunity, for justice and for inclusion”.

As WPP UK Country manager and Group M ceo Karen Blackett wrote in the foreword for our book Belonging: “Diversity is not a problem to fix.  Diversity is the solution.”

When it comes to the development of revolutionary new systems and ways of working we all need to pay attention to ethics, to inclusion and belonging.




Is your career suffering because of all the noise?

June 14th, 2021

The Media Week Awards are back

The awards, which Campaign calls “the most highly prized awards in UK commercial media” are now open for entries with deadlines looming in June and July.

I’m honoured and delighted to have been asked to judge again.  I have seen the growth of professionalism and rigour in the judging over the years.  But a new book, by Nobel prize winner Daniel Kahneman, makes for grim reading as far as judgement in terms of the effects of what they categorise as “Noise” on human judgement.

The book (with co-authors with Olivier Sibony and Cass Sunstein) is packed full of evidence casting significant doubt on nearly every aspect of judgement, many of which underpin business and society.  For example, a study of 208 federal judges in 1981 who were all exposed to the same 16 hypothetical cases found that in only 3 was there agreement on the verdict.  There was also huge variation in sentencing – in one case where the average sentence was a year, one judge recommended 15 years in prison.

In real life (as opposed to a hypothetical case) judgements judges have been found more likely to grant parole at the beginning of the day or after a food break.  Hungry judges are tougher.  One study which examined 1.5m judgements over 3 decades showed that when the local football team loses a game on the weekend judges make harsher decisions on Monday.  A study of 6 million decisions made by French judges found that defendants are given more leniency on their birthdays.  And when it is hot outside, people are less likely to be granted asylum according to evidence on the effect of temperature on 207,000 immigrant court decisions.

This is shocking of course and as you read through the book the evidence piles up for the unreliability of human judges and juries.

More evidence then that evidence based decisions, using rigorous modelling are so important in media and advertising thinking, and why the IPA data bank is so useful.

Are robotic judgements better?  Not by much according to this book.  Partly of course because the rules are based on history (past judgements delivered by humans and therefore subject to bias) or a set of rules (created by humans and subject to bias).  Machine learning is not as unnoisy as it seems.

Winning an award is important and can help your career path, but your career also depends in other ways on the judgements of others.  Studies based on 360 degree performance reviews find that the variance in scores based on empirical performance accounts for no more than 20-30% of the review.  The rest is system noise.  And the noise may have absolutely nothing to do with you – it could be down to a row that the rater had at home, bad weather spoiling their plans for the evening or the fact on the other hand that they have had a generous review from someone else.

We can’t delegate career decisions to machines anyway as the authors write: “Creative people need space.  People aren’t robots… people need face to face interactions and values are constantly evolving.  If we lock everything down we won’t make space for this.”

What should we do to account for noise in decision making, (aside from hoping for good weather and a winning football team)?

Kahneman, Sibony and Sunstein advocate appointing a “decision observer”.  Someone who has no skin in the game to identify and point out bias.  This is common on major boards in respect of non-executive directors and chairs, but non-existent in many reviews or on awards judging panels and should be welcomed (at least as a trial).

In addition, high performing teams need, as a matter of course, to understand how to reach agreement when they disagree in a way that steps aside from who is most forceful or charming.  We all need to develop a way of working through disagreements that is transparent in approach.    In Belonging, the key to transforming and maintaining diversity, inclusion and equality at work we say this: “Understand that there are 3 kinds of disagreement: a) we are using different facts and evidence to reach our conclusions; b) we are interpreting the facts and evidence differently; c) we actually fundamentally disagree.”  We detail how to do this in chapter 6.

Start with this, and at least some of the noise in collective decision making will quieten to ensure better outcomes for everyone.



What if we did less?

June 1st, 2021

The power of minus.

The power of “and” has been well documented.  Best selling author Martin Sharp has spoken about the power of a “life of combinations”.  He exhorts people to replace “but” with “and” for a richer existence.

Recent business book, “The Power of And: responsible business without trade-offs” by Edward Freeman, Parmar and Martin argues that the business of business is “responsible action, not simply profit seeking”.

“Yes AND” is a creative technique born in improv comedy and translated into idea generation where you build on each idea rather than dismissing anything.

But what if instead we did less?  If instead of “Yes, And” we said “No, subtract”?

Top designer, Thomas Heatherwick, (creator of the epic 2012 Olympic Cauldron, and the lovable new Routemaster bus), thinks subtraction can be as powerful, if not more so, than addition.  He recently said that in his design studio they always ask “Do we need this element?” and that subtraction and simplification have huge effect.  Less, for Heatherwick, is frequently much more.

When you are working on a project, critiquing and quality controlling, how often do you remove elements?  I would observe that most people’s tendency is to use their experience and smartness to ask for more, dig further and add work, rather than have an instinct to strip things away and do less.

It turns out that this is a quirk of human nature and is statistically substantiated.  The Economist points to a study in Nature which suggests that humans struggle with “subtractive” thinking.  When asked to improve something, anything, from a lego model to a golf course, their tendency is to add more things rather than strip things out.  In one test of a lego model, most people added to it and only between 2% and 12% of respondents removed bricks.  When asked to improve a piece of writing 80% added more words and only 16% cut the article back.

The research shows that when there is an increased cognitive load (which could be the stress of a new business pitch or big approval meeting), people are even less likely to remove features to improve the work.

In the spirit of keeping this article short, simple and without extra features, I will end by saying that it is very useful to be conscious of this newly identified cognitive bias.  If your tendency is to add more complications and features then don’t.  Ask instead what the minimum viable plan is (this is a key feature of Agile ways of working), and remember that when Dr Frasier Crane said: “but if less is more, then think how much more more is”, he was almost certainly wrong.