Author: Brian Hills, Head of Product Management, The Data Lab
In the first of a series of articles on education and the data skills challenge, Brian Hills discusses recommendations from new research by Nesta to create skills for the data revolution in the UK.
I fell into data by chance. Growing up in the Highlands, I moved to the bright lights of Aberdeen to study computing and came out the other side as a graduate software engineer at Hewlett Packard. I was part of a small team creating custom solutions crafted in C and Perl that processed messages from mobile telecoms systems. We knew we were sitting on a potential goldmine of high value data that could be used for other customer departments such as marketing. A few months later I found myself creating a new product on the fly: sitting in a customer’s data centre plugged into a terminal learning to customise an Oracle data warehouse (without any knowledge of Oracle)… And from a modest start, I began my journey into analytics.
That was in 2000. 15 years later, we are now well into the age of data and facing a global challenge for talent. Clearly, relying on that talent falling into analytics by chance doesn’t scale. Equally, focusing on one particular channel, such as increasing the volume of new graduates, doesn’t drive the required velocity either. So how should we approach this challenge? Last week NESTA launched their new research and policy briefing ‘Analytic Britain: Securing the skills for the new data revolution’. The event brought together industry, academia and the public sector to listen to and debate the key findings. I’ll summarise some key themes in this blog, and the document with the full list of recommendations is available for free from the NESTA website.
The research, compiled by Nesta and Universities UK, covered over 400 companies across the UK. The recommendations focused on the development of a talent pipeline: from schools to universities and into the labour market. These included, for example:
School and colleges
- More and better information about analytical careers and role models with exciting examples.
- Support extracurricular data activities such as Data Summer Schools.
Universities and vocational education
- Increase visibility of analytical courses and add quality kite mark branding from organisations such as The Royal Statistical Society.
- Boost business & soft skills.
Labour market & training
- Create a cross-cutting taskforce around analytics.
- Actively convene industry & community networks (The Data Lab was given as an example of this in action).
- Develop innovative solutions for data analytics training.
The approach to scaling was discussed during the panel session. It was clear this could only be achieved through change across the talent pipeline, and one of the strongest themes was the need for training and education for those already in employment. For example, Jenny Warrilow from Boots discussed how they have launched an insights professional academy within the company to grow the team from 10 to 80, whilst the Government discussed the challenge of up-skilling existing staff such as statisticians. Another great initiative discussed was Science to Data Science who runs five-week workshops to train PhDs and scientists in the commercial tools and techniques needed to be hired into data science roles (Marks and Spencer is a partner).
One area that was not covered was the role of technology as an aid to the challenge. Over the next few years could the use of cognitive platforms such as IBM Watson help plug the gap? Let’s cover that one in a later blog.