My flirtation with numbers started in the 1980s, long before I knew what a spreadsheet was, let alone how to use one; I would spend hours listening to the radio, watching live games, ploughing through newspapers and magazines such as Shoot and Match and writing as much information down as I could. All of this was done in the hope of finding out when Liverpool would win, information I could then sell on to the school masters who liked a bet believing this would be my passport to wealth. The fact I am still working and not dividing my time between Hawaii and Val d’Isere shows how successful I was.
At university, I became more immersed in numbers, using SPSS for my dissertation on middle class deviant voting patterns (and it was that long ago SPSS still stood for Statistical Package for Social Sciences) and whilst I would keep pushing out the Disrali quote of “There are three types of lies -- lies, damn lies, and statistics,” I never really believed it but was worried about being labelled a geek if I was too enthusiastic about the use of numbers.
As I left university and moved into sales, I would record every single sale I made, every call I made, every quote I gave to analyse my performance and used this information at the end of each month to learn what had gone well and what needed to be improved going forward, something I took forward into recruitment.
As time has moved on I have realised the importance of statistics, how the analysis and insight generated have become part of every facet of society. In sport their use is widely accepted both on and off the pitch, “moneyball” is a recognised analytical, evidence-based, sabermetric approach to improve the fortunes of various sporting teams (notwithstanding Liverpool’s failed attempt at using it under Damian Comoli as the owners had used the concept very successfully in their baseball franchise). One of my favourite books remains “Why England Lose” (updated to “Soccernomics”) by Simon Kuper and Stefan Szymanski, looking at many aspects of football, such as why some transfers fail, why Spain are currently so good and whether penalties are a lottery or not. It explores the science of sabermetrics and how this analytical approach can add value to any sporting team. If you are into football or sporting analysis, it is a must read.
My other passion of politics also relies heavily on the use statistics and analysis to help win over the floating voters, identifying where politicians and political parties should focus their efforts both geographically and issue based. It has however been left to Nate Silver, an amateur blogger, who used complex models covering every state in the US to most accurately predict the result of the recent presidential election, putting the large pollsters to shame.
The wider picture of course is how businesses are starting to use big data to analyse every part of life and use the models to predict what consumers and customers are going to want. Whilst some may see this as Orwellian, this use creates far more efficiency for businesses, reducing the waste of money on failed marketing campaigns or cold calling people who are never going to buy. Taking this to the extreme has been the recent reports about the algorithm patents filed by Amazon which will predict what each consumer is going to buy next and therefore ship the goods to a local depot before we have even ordered, (http://mashable.com/2014/01/21/amazon-anticipatory-shipping-patent/). How great to think that one day I might come home to a new pair of jeans waiting for me and because I did not order them, there can be no guilty feelings.
I find these advances hugely exciting, eventually I will have even less to think about in my day to day life leaving more time free for more important things like praying for Liverpool to once again win something (anything) or even giving me more time to exercise enough to get my body back in the same condition it was when I first encountered SPSS.
Working within analytics recruitment I now see this bigger picture and can indulge my passion for numbers without having to be intelligent enough to do it; everything we do is driven by numbers and the analysis that goes on behind it. What this means to you all is that whilst I may not have the statistical background and do not know my SQL code from my SAS code, I do have a passion for stats, so rest assured that your career or recruitment campaign is safe in the hands of somebody who is as passionate about numbers as you.
Jamie Allan is Analytics Director at Forward Role and has recruited for some of the largest UK and international companies over the last 15 years. He has advised them on their attraction, selection, engagement and remuneration strategies, to help them not only target the best talent for their business but also retain them. For a selection of the latest jobs in the region please visit www.forwardrolerecruitment.co.uk