HAVE WE BEEN DEALING WITH OUR DATA SKILLS SHORTAGE ALL WRONG? - Polymatica: Big Data Analytics and Powerful Data Science


April 2018

A recent review of the list of top graduate employers in Australia reveals an interesting story – one that points to a fundamental change in what employers are now looking for in graduates.

Added to the stack of Science, Technology, Engineering and Mathematics is now Arts, even for the big accounting and consultancy firms.

And the catalyst for this is something you wouldn’t normally associate with the arts disciplines – technology.

On closer inspection, this isn’t as strange as first thought, as digital and technological disruption is requiring employees who can adapt to the changing needs of clients and can bring an ability to think critically and creatively.

The data skills shortage is one such area that could benefit from this change in approach.

Especially given that this shortage has been forecast since as early as 2013 by McKinsey and will potentially hit crisis-point by 2020, when the EU is set to be short of 346,000 data scientists.

So what are the top 3 things to consider when looking to address the data skills shortage?

  1. Reconsider recruitment processes and organisational structures.
    • As the review mentioned above shows, the traditional and somewhat easy route is to recruit individuals with data-related backgrounds. And whilst critical and creative thinking is harder to assess in an interview process, the long-term benefits really do outweigh the short-term approach.
    • In addition, many organisations fall into the trap of pooling analysts and data scientists into ‘shared services’ teams, perhaps because they lack the ability to manage this type of resource at scale. However, perhaps a more effective approach is to consider how this resource fits into a wider marketing or product team, thereby enabling them to learn the true business context of what they do and to ultimately share in any successes their work may bring.
  2. Focus educational courses on real-life business scenarios.
    • A number of universities and colleges are now offering data-related courses, some even for free such as this one from Berkeley. And whilst these are a great first step in tackling the skills gap, all too often they focus on the theory behind data analytics and forget the real-world scenarios we have to deal with – these being the tools and platforms we have to work with, and the last-minute modelling that so often has to be carried out to inform changes in business decisions.
    • Both educational establishments and companies themselves have a responsibility to ensure that data programmes are designed for real-life usage and practice.
  3. Take advantage of modern BI tools designed for the ‘Citizen Data Scientist’.
    • Realistically, both of the above considerations are strategic decisions that require careful planning. And fewer and fewer organisations have the luxury of the time and resource needed to do this justice. So another option is to take advantage of more modern BI tools that are built with the business user in mind – i.e. those with embedded intelligence that allow for more rapid analysis work to be done on the spot and by employees that might not have a data science background, but do understand the business context.


There are definitely ways to crack the data conundrum and address the skills shortage that so many organisations are suffering right now.

The key is to consider new and innovative methods that may not have been considered before but that ultimately match where the business driver originates.