1. What is the one characteristic every leader should have?
One of the main things a leader needs to do is make something happen, and the world rarely goes in straight lines, so you have to be persistent.
The characteristic that I think demonstrates persistence (the most) is resilience.
Things never go according to plan. There’s always something that drives you off course.
When I look at leaders that I admire they are people who have gone through the tough times. learned from the tough times and come out the other side having just kept at it!
If you believe in something enough you’ll be able to put up with the tough things and turn them to your advantage.
So resilience would be my number one characteristic for a leader.
2. What inspires you?
I’ve got the best job in the world (for me) because what inspires me is mobilising the power of data to help people make decisions.
This is one of my favourite stories that demonstrates this.
I was working on statistics of social exclusion, quite a long time ago now, and this young researcher in a local authority had produced a map of where the worst housing estates were in the area, and had been invited by one of the leaders of this housing estate to give a presentation.
The presentation showed that the housing estate was the worst for jobs, health, housing conditions, and he was slightly anxious about going to this meeting, but he went there anyway.
All the local residents duly turned up and said nothing at all.
At the end of his presentation nothing happened and he thought was about to be lynched. But then suddenly the residents broke into applause and he turned to the community leader and said: ‘what was going on there?’
The community leader said: ‘look we know this is the place with the worst jobs, worst health, the worst housing, but now it’s captured in statistics we can make our case to make it better. People did not believe us before but now it’s official. The data enables us to have a voice!’
It’s those kinds of stories that are really, really powerful. It’s a micro-level story.
My favourite macro-level story is what the Americans did with Japan after the Second World War.
They sent out statistician W. Edwards Deming, after whom the prestigious Deming prize for business excellence is eponymously named.
He used the power of statistics to help Japanese manufacturing industries get back on their feet and to think how they could successfully iterate to make things better.
This is now known as lean six sigma movement, but it comes from the export of a statistician to Japan to help them with their reconstruction.
You can maybe overplay that a bit but in terms of me telling a story to my folks and me being inspired by it, seeing what happened in Japan in a very short period of time by using the data to help them improve and learn. And that played a big part in the transformation of a whole country.
That’s inspiring to me.
3. What do you do to ensure you continue to grow as a leader?
I think the thing for my own learning that works best is seeing other leaders and seeing how they get through problems and draw strength from their experiences.
There’s an internal drive there, of course, but my learning comes from examples that make me think: ‘that was very clever , I’ll try that’. In other words, when I see something that someone I admire does.
We have a shadowing programme between public sector and private sector leaders - chief executives on either side. It’s run by The Whitehall and Industry Group, and I was shadowing a chief executive in a private sector company. I spent a day with him and I came back thinking he is so decisive, he knows enough about his situation and he just gets on with it.
I don’t see enough of that in myself or some other public sector leaders and I thought we can do that as well. That’s a good way to learn.
Peer learning – a very strong thing.
4. Do you have a pivotal moment when you decided to pursue this career path?
It was a first year undergraduate statistics course.
There were a lot of theoretical courses that we were doing, but the one that captured my imagination was described as ‘social trends’, and there used to be a book that came out every year which was called ‘social trends for the country’.
The inspiration for this book was Claus Moser, who became Lord Moser, who used to do the job I’m doing now!
The book made me realise that data, which is well presented and well communicated, could open your eyes to what’s really going on in the world - whether it be the economy, population or the environment - anything you’re interested in.
Understanding the facts and the context was just so powerful. I could see this theoretical thing I was learning in other courses could be put to some social use through statistics.
I think it was probably at that moment my future was mapped out.
Now, of course, it hasn’t gone entirely in a straight line since; for some of the reasons I’ve already mentioned, but I look back on that moment as significant.
Claus later became a mentor of mine and he died last year.
I was invited by his family to give a speech in his memory and that was a very emotional moment for me - thinking back to being an 18 year old undergraduate reading some of his work and then being with his family so many years later.
5. What characteristics would you look for in a graduate employee?
Clearly I would want someone who is technically competent but that’s the kind of ‘pass go, collect £200’ sort of thing.
Everybody has to be that, but the people that I need as an employer are people who can communicate their own brilliance.
Quite often that’s a tricky combination. There is a truth to the idea that there’s a rational brain and an emotional brain.
You can be the most brilliant person in the world but unless you can put that to use - and putting it to use generally means explaining things in straightforward terms to someone much less brilliant than you are - you’re wasting your time.
So someone who doesn’t see that as somehow dumbing down: if you’ve got to explain in plain English what you do.
That’s something I would advise students to get. To think about how you can explain in your elevator pitch to someone who really needs to know this amazing thing you’ve found out: why it matters to them.
Communication is the ultimate skill.
6. If you could go back what advice would you give yourself as a new graduate?
I could’ve given myself an easier time I suppose.
I think and hope that most students see themselves as aiming for the stars and really wanting to push themselves and challenge themselves because I think that’s part of being at ease with yourself – wanting to make the best contribution you can.
I would never want anyone to settle for less, but I think I’d advise myself not to be in so much of a hurry!
Not plotting the next steps, and thinking right I now need to get past this step in order to get to the next step.
I would’ve let myself breathe a little bit and I think that’s would’ve been hard advice for a young John Pullinger to have taken. But I could’ve been less tough on myself. And though things don’t always turn out as planned, that’s not always your fault.
Keep aiming for the stars and the opportunities will come.
7. What role do universities play in meeting the workforce requirements of the future?
Data is going to be the seminal resource of the next twenty or thirty years.
Every student, whatever discipline they’re studying, needs to be confident with data.
There are very few disciplines now where interpretation and the understanding of evidence isn’t critical , but also just to be a good citizen and a good employee, you’ve got to be able to understand quantitative information.
Even if you’re a nurse in a hospital or a policeman on the beat there is quantitative information that is thrown at you.
Too many people are scared of statistical information and if they’re scared of it they shy away from it. So I think there is an imperative for universities to come up with some quantitative skills training.
The best example of this that I’ve been involved with is the ESRC's Q-step programme.
This is a programme that teaches people who have done non-quantitative subjects that bit of quantitative understanding that enables them to be effective in the use of evidence.
When I talk to students, particularly in humanities subjects, at schools they have rarely come across numbers or they’ve rarely come across teachers who have been confident with numbers. So they’ve come to university and they’re told to think about evidence and they don’t know where to start.
In English if you’re asked to do some kind of textual analysis of something, a numerical facility really helps you to get into those kind of areas , but if you don’t know where to start you’re really struggling.
So my number one thing for universities is to think of some basic numerical and quantitative training to enable students to be good at their discipline and much more confident in navigating our very data rich world.
8. What advice would you give to a budding statistician?
Choose a career that you’re really going to enjoy because you’re going to be much more successful at something that is going to inspire you.
Often that is something that is quite close to your degree.
Don’t look too far ahead, think about how you can do something really good with what you’ve got now.
That gives you a bridge to do the next thing that’s good.
In order to get that something that’s good, put yourself into the mind of your employer. What does that employer want?
It’s a very competitive marketplace at the moment.
Maybe it’s easier for people who are very strongly quantitative to pick and choose, but employers are still very discerning and they’re going to want to see in you something that’s going to give value to them.
Put yourself in their shoes – would you employ you?
9. Is this the statistician’s moment? What’s the power of big data?
It is our moment but with one big caveat. The reason it’s our moment is that data is everywhere, it can be mobilised and when we do mobilise it we make better decisions.
A very simple example of this: suddenly in the last 3 or 4 years every bus stop has got the data on it that tells you pretty precisely how long it’s going to be before the bus comes.
That helps me.
I know whether it’s worth me waiting for the bus or just walking on to the next stop.
That is the power of data.
When I’m going to the doctor to get a diagnosis I can find an awful lot more about whether I want to follow this diagnosis or not by using the data.
Everything can be done better if we use the data well, so this is the moment for the people who are translating the raw material into something useful. But the caveat is this: we shouldn’t get carried away.
The data never tells you what to do, it gives you the evidence to make a choice.
More important than being clever with the data is remembering that we are human beings and that we live through our emotions.
The data community needs to have a little bit of humility and try not to tell people that if they feel something is right, then that it is wrong because the data says so.
We are feeling beings.
Some of the concerns around experts or post-truth, stems from data people having forgotten that we are actually quite humble contributors to decisions.
We’re not the people who tell you what to think. We know what to think by how we feel.
Unless data connects with us as humans, we’re not going to be helping people, we’re just going to be trying to take them down a path that they don’t necessarily want.
10. Do people interpret Mark Twain’s “lies, dammed lies and statistics” quote differently nowadays?
I think we’re stuck with that as a profession.
It is annoying because it’s used as an all purpose put down.
You can use something well or you can use something badly , but if you use that phrase as an excuse for not using it at all you’re missing out because you’re missing out on something that would help you make a much better choice.This series of free public lectures brings top level business leaders to Bristol. The full schedule for spring 2017 is now available. If you have any queries please contact firstname.lastname@example.org. Discuss these events on Twitter using the hashtag #BristolLectures. View content from John Pullinger's lecture here.