It used to be easy in the old days when companies were obsessed with what that mythical creature “The housewife” thought about everything from the cleanliness of her kitchen floor to the whiteness of her laundry.

One seminal research project involved canvassing Mrs Average to find out if she preferred drinking a nice cup of tea, or sipping a cheeky glass of toilet cleaner. Such research was easy because the large companies selling household products were respected, and because many women defined themselves, not always happily, as “housewives”. Both sides of the equation understood the rules; both sides agreed that “the truth” – or something like the truth – would result from the research; in this case that drinking loo cleaner would kill you. For the record, this research was never carried out (that would be silly). It’s simply the first “alternative fact” which has been cunningly threaded into this article.

The reputation of the research profession has taken a bit of a hit recently. For example, when it came to pre-election public opinion surveys, it wasn’t too long ago that voters were predictably flat-capped labour, sherrydrinking conservative, or sandal-wearing liberals – and were only too happy to say so. Contrast this with Scottish Referendum when many canny voters hid their intention to vote NO to independence from researchers (the so called “shy unionists”) leaving the Scots Nats to make all the noise – and mislead the pollsters.

Weeping into Chardonnay

Similarly, in the EU Referendum the cosmopolitan elite are still weeping into their Chardonnay after the Brexiteers confounded the pollsters and shattered their Guardianista globalist consensus. In the USA, the truth about Trump’s probable victory was hidden in plain sight when traditionally rock-solid democratic states were plastered with Trump posters – yet the polls continued to show erroneously that the next President of the United States would be female, rather than orange.

I blame society. It keeps changing, by which I mean we are changing as individuals. What would a 1950s housewife make of someone who, today, defines themselves as “gender- fluid”? These days, you can’t assume someone’s sexual orientation from their biological gender, you can’t tell their voting intention from their income, and you can’t tell their income from their clothes – well, perhaps you can with the Queen, especially when she is wearing a crown. Some things are, however, are certain; if someone lives in Chelsea you can safely assume that they are a Russian “industrialist” and if you drive past people working in a field, they will be Eastern European. Yes, we have all moved far away from the monochromatic world of the 1950s. Take me for example, I’m a genderdistressed, fox hunting vegan – make of that what you will.

“...the polls continued to show erroneously that the next President of the United States would be female, rather than orange.”

Then there’s technology. Proactively, it offers the unrivalled ability to reach people and engage with them. Passively, and perhaps sinisterly, it enables companies and governments to track, record, and analyse our every move as we click our way across the web. Crucially, it provides the sort of breadth and depth of data which would have been beyond the wildest dreams of a researcher only a decade ago.

50 Shades of ‘Truth’

Nevertheless, how does a researcher – especially someone just entering, or in their early years in the profession – make sense of this ultra-diverse world where 50 Shades of Grey isn’t just a naughty book, but can be applied to any “truth”. Interestingly, most research into the background of researchers shows that they “fell into” the sector. This is encouraging, I can’t think of anything creepier than a 10-year old telling their parents that they want to be a researcher when they grow up. Among researchers psychology degrees are common, and at the other end of the personality scale so too are maths-orientated degrees. At first, these are two diametrically opposed personality types, however they are unified by one shared characteristic – they are nosey – I mean inquisitive. Someone once said that research is formalised curiosity, and that sounds about right. People coming into the sector want to know stuff. The best of them want to see beyond the obvious, or see the obvious in a new light.

Younger researchers do, however, have one advantage in all of this – they are Millennials. A lot of research has been done into Millennials, mainly concerning their willingness to pay a huge amount for a cup of coffee, and unwillingness to enter into a romantic relationship with anyone who doesn’t offer free Wi-Fi. The serious point, however, is that they are “digital natives” and their attitudes and behaviours have been fashioned in response to the technological, economic and social implications of the worldwide web. They have grown up with the Internet and understand its grammar, its possibilities and its pitfalls. In theory, they should be able to understand how to apply suitable filters in designing and interpreting research better than the generation of researchers currently in their mid or late career.

“A lot of research has been done into Millennials, mainly concerning their willingness to pay a huge amount for a cup of coffee, and unwillingness to enter into a romantic relationship with anyone who doesn’t offer free Wi-Fi. ”

Big Data beliefs

Millennial researchers will, of course, have to deal with Big Data; companies are spending zillions collecting it, but are just in the foothills of learning how to deal with it. When it first appeared it looked like it was THE ANSWER, it was relatively easy and cheap to collect, and it promised untold insights. There have, of course, been lots of early successes, but there is a long way to go. For example, they tried to use Big Data to predict the results of the 2016 U.S. Presidential Election with varying degrees of success. Forbes magazine predicted… “If you believe in Big Data analytics, it’s time to begin planning for a Hillary Clinton presidency.” Err, yes.

Good old-fashioned tried and tested statistical methodologies struggle to handle big data, but clever people are working on that. While we will eventually solve the hard maths side of Big Data, the greater challenge comes with the belief that Big Data could mean the end of analysis – in some real sense the deskilling of research. Nothing could be further from the truth. Just because it’s BIG doesn’t mean that it won’t need to be contextualised in its social, economic and political contexts. There is a real danger that the awesome power of big data will lead to an “insight deficit” and, of course, no matter how comprehensive or well analysed, big data must be complemented by what some people have called “Big Judgment”. Professor David Hand, Emeritus Professor of Mathematics at Imperial College, London (where he formerly held the Chair in Statistics), nailed it when he said, “We have a new resource here, but nobody wants ‘data’. What they want are the answers.”

Geeks, gurus and poets

Compared to the Baby Boomers, or Generation X, who currently occupy most of senior positions in the sector, Millennials are arguably the most technologically connected, educated, diverse, tolerant and engaged generation ever. Big Data will undoubtedly have the biggest impact on your working life, and I predict that the research teams of the future will look very different; not only will they comprise stats geeks and IT gurus – they will also include culturally savvy poets. Together, they will wrangle sense from the monster. I think Millennials are up for that.

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