Is Hiring a Big Data Scientist a Game Changing Strategy?

“Data Scientist, The Sexiest Job of the 21 Century“- Harvard Business Review 

“Two thirds of firms have appointed a chief data officer to lead analytics in the last 18 months”-Accenture 

“71% of firms plan to hire a Chief Data Scientist in the near future”-Accenture

“We reckon demand for data scientists will be up 100% on last year”-Cititec via The Financial Times 

Now, I am not sure about the sex appeal of any data crunching role, not by any stretch of the corporate imagination, but as you can see there is certainly plenty of intrigue around the role of data scientist, which needs further examination.

The unquestionable rise and rebirth of the data scientist has corresponded naturally with the rise of big data processing. Every industry from marketing, sales and now to talent management are getting aboard the big data analytics train and it is now very much on the “C – Suite Agenda” according to Accenture’s white paper, Analytics in Action: Breakthroughs and Barriers on the Journey to ROI . While in 2009, just 12 percent of the organizations surveyed by Accenture were using Predictive Analytics – the most powerful and seductive area of big data that predicts future trends to aid critical decision making – today it seems that 33 percent of companies are now “aggressively using analytics across the entire enterprise.”

So, if you want to be ahead of the curve, now is the time to be making the case for and investing in hiring a data scientist in your company or department. If the trend continues as it is currently going, in a year or two you could find yourselves behind the curve and simply following the crowd into the big data science game. That may not be the ideal place for your department or business to be, particularly as there is reportedly a shortage of data scientists available in the job market that is expected to get worse, not better, in the near future.

The Accenture study also reported that internal customers within 60 percent of businesses are now asking for their internal suppliers to “predict trends rather than simply report on the current status of the business“, which suggests that in most businesses there is a growing and overwhelming demand for big data scientists. CEOs want greater decision support; they don’t just want to know today’s employee turnover, they want to know what it will be in two years if they adopt this strategy or if this external event happens.  These questions will be contextualized and replicated throughout all the functions from finance, to customer service, sales, IT, and procurement.

We know there is demand for data scientists, and now is a great moment to get ahead of the curve, but is this curve actually going anywhere? Accenture found that 25 percent of firms now rely habitually on big data as a source of inspiration or as a basis for decision making, which is up from 12 percent in 2009, so firms are definitely making more effective use of big data.

But, hiring a big data scientist at the moment probably constitutes a gamble until there is more convincing data showing that companies that based decisions on big data are actually performing better than companies that use more traditional, more intuitive, gut-based decision making processes.

So for the moment, gambling on the big data-big hire might be the preserve of the elite; and the more economically challenged might still want to keep a watching vigil and hold fire on the data scientist game changing hire, considering extreme talent shortages and exorbitant daily rates.

Or alternately, those with more modest budgets might try dipping their toe in the water with the more economical alternate of getting a project focused big data intern to start opening the doors to big data decision making in their own business or function.