- The polymath versus the specialist: The role of talent in our post-digital research world
The polymath versus the specialist: The role of talent in our post-digital research world
By Adele Gritten
Speaking on a UK panel about the future of media research this week, one of the questions I was asked to ponder was about the role of talent in research. Where is the innovative talent coming from these days? Is research polarising between advanced statistical skills for Big Data and advanced qualitative skills? Is there still a role for the polymath, the all-round media researcher, or does the future lie with the specialist? Is talent disposable?
Pondering such questions in advance of the debate made me realise just how complicated the research world has become. Despite technology making things cheaper, faster, and better (such as much marketing hype in the self-serving research world leads us to believe), the actual skillsets required of us in the 21st century research world are actually pretty exacting and require some very talented people. Whilst it's clearly not possible to be expert at everything, being a good generalist – someone who knows quite a bit about a lot of things – is an underplayed skill in our world. Some sort of talent at least is needed.
Research agency structures are still by and large based on sector verticals (certainly in the top global agencies), and Qual and Quant departments are still very much structured along the same lines as they were pre-digital disruption. Operations still tend to sit on the periphery with a more inward facing role, whilst the Data Scientists and Advanced Analytics gurus who used to be relegated to darkened server rooms in the basement have found much better ways of making the unexplainable explainable and have adopted a more client facing, arguably glamorous role. Certain kinds of talent are beginning to surface.
More and more, however, all of these people have to work together, whether it's jointly bidding for or writing proposals, attending client pitches in a multi-disciplinary fashion, or simply dipping in or out of a specific point in time of a project. Each brings a specific expertise that individuals alone cannot be expected to bring given the vast amounts of data these days, structured and structured, text based and numerical, all of which is available at our disposal. Talented researchers, if they are to be useful, have to be collaborative.
I've previously written about the new breed of Data Artist so vital to this industry. These are individuals and teams who are able to detect patterns in passive and active data streams, and, ultimately, find connections to a business model. These people, crassly speaking are equally talented at left and right brain thinking, are arguably still in sparse supply, and do not fit neatly into the agency models of Qual, Quant, Analytics or Business Development, Sales and Marketing silos of traditional agency models. Basically, the talents of the future will require better collaboration across departments to aid more multi-dimensional use of data sets.
For sure, people with social science skills – social sciences, economics, psychology degrees etc. – are the people our industry tends to look for, particularly at the graduate entry level. But more and more, there's a push for those with advanced maths, behavioural economics and of course physics and computer science based background, as the growth of predictive modelling and machine-based learning continues to push the boundaries of what we think we know, as does the use of Apps and Gaming in research and Virtual Reality – the latter of which is still very much in its infancy in terms of hitting the mainstream research toolkit (but it will).
The term “Thick Data” that has entered our vernacular in the last year or so is also important. An early adopter of the term, Tricia Wang claims that Thick Data reveals the social contexts of and multiple connections between data points. Big Data delivers numbers; Thick Data delivers stories. Big Data relies on machine learning; Thick Data relies on human learning. In that context, it's hardly surprising that the talents required to make sense of thick, thin, tall, smart, big data etc. are diverse, but must also be complimentary up and across the research value chain – whether we are talking agency and/or client side.
A number of insight driven client side organizations have started to resource their teams with multi-disciplinary talent in order to make big and thick data accessible and digestible throughout their businesses. These companies have centralised business intelligence into an inclusive and readily accessible repository, where Qualitative and Quantitative data can be streamed, recorded and stored, and – most importantly – available at the touch of staff fingertips. They are the companies making real time global collaboration possible, as all staff has simultaneous access to customer data, tweets, videos and much more, thus enabling their companies to better drive commercial impact via evidence-based decision making. These teams are staffed by traditional Insight Professionals, Strategists, Project Managers, CRM experts, Statisticians, Ethnographers, Story-tellers and many more! Multi-language skills are also increasingly important in a research world where the new commissioning budgets are to be found in MENA and BRIC regions.
So, the future is a specialist one from a talent perspective for sure, but one that is also pulled together by a project team of very good generalists and all-rounders; people who can absorb lots of data, whether Qual or Quant, structured or unstructured, thick or thin. If these talented people currently sit in your organisation, keep hold of them! They are indeed precious, and they hold the key to the future success of your company.