‘From geek to chic’: Supply chain opportunities for data analysts

Physics and maths may not be everyone’s cup of tea but if you are looking to be at the forefront of data analytics, they are a great spring board.

I am not sure if it is the advent of the cyber-physical age, an increase in cautiousness post Global Economic Crisis (GEC) but the last 8 – 10 years have seen the rise of the ‘geek’. Historically the term was a slang term used in a slightly derogatory way to describe eccentric or non-mainstream people. Now it is used much more affectionately to refer to someone who is an expert or enthusiast, usually in an intellectually complex topic. Maths and Physics are intellectually demanding subjects, and as the TV series ‘The Big Bang Theory’ illustrates, they are commonly associated with the more traditional view of the ‘geek’.

Not anymore. The data driven economy, and need for data analytic solutions is creating the need for a new breed of data analysts. These influential, well remunerated, and often coveted roles are primarily filled by those with a maths or physics background. The first advances in analytics solutions have been in the financial services and marketing domains. It is algorithms that support financial traders to such an extent, that it is arguable if they will be required in the future. Such data driven approaches are starting to permeate the supply chain, and the last 5 years have seen an increased need for supply chain analytic experts.

In her role profile video, Christine McNeill (Head of Client Engagement, Concentra) provides some insight on her pathway to becoming a supply chain data analyst. With a background in physics, she moved onto a career in general management with BOC. Having moved around the company a lot both in terms of function and location, Chris was able to identify that she had a real love for logistics, building on her mathematical expertise. She used these skills to conduct different types of logistics network modelling, network optimisation, a transferable skill set that enabled her to move to Petrofina.

Wishing to continue to absorb as much knowledge as possible, Chris decided to move to Accenture to get some consultancy experience. This gave her experience in Fast Moving Consumer Goods (FMCG) and retail which provided a segue way into a role at BAT. This was a pivotal moment in her career as Chris moved into the supply chain planning domain. This really opened Chris’s eyes to the art of the possible in terms of more data driven approaches to planning. Given her considerable expertise Chris was headhunted to join Concentra where her combined supply chain and analytics skills are high valued and put to good use.

Talking point

• What type of skills make a good data analyst?
• What are the similarities and differences between a SC data analyst and financial data analysts?
• What other types of degree / training other than maths and physics could be a useful foundation for a career in supply chain analytics?