This Is Why We Need More Data Scientists

Business IntelligenceData Storage
Machine learning
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In an increasingly competitive business landscape, Elizabeth Bramwell, director at Iron Mountain, believes data scientists are more important than ever

The majority of UK businesses have a cupboard or server in the corner of the office somewhere that has become a dumping ground for all that information that no one knows what to do with, whether it’s on paper or electronic data.

However, many believe that the information in the cupboard could be of potential value to them some day, hence nothing is thrown away. Many are living a keep-it-all-in-case culture.

Cause for concern

In fact, according to recent research, UK organisations have the second highest volume of data with unidentified value in EMEA. This results in a growing pool of ‘dark data’ – data whose value has not been identified. This comes as a cause for concern, as the untapped potential of the hidden gems in the dark data, which could, potentially, be utilised for competitive advantage, are left sitting there gathering dust.

In order to realise the true potential from this valuable asset, there are a number of resources, skills and tools that are lacking. First of all, organisations need to understand what information they hold; how it is being used and how it flows through the business. This would go a long way towards giving an organisation the ability to recognise where insight and intelligence would be most valuable and most vulnerable.

hiring jobs wantedThis is reflected by recent news which reported a growing need for data scientist’s to cut through the dust and extract value from the data. It has resulted in the number of advertised data scientist jobs in the UK increasing by 22 percent over the past year. This comes as no surprise given that the technology industry, in particular, continues lobbying for data scientist to be added to the UK’s skills shortages list, as businesses continue to lack employees with the specific skills to interpret data.

Data science is rapidly becoming a critical tool for business growth. However, our recent research conducted with PwC revealed that over a quarter (26 percent in the UK) of those surveyed don’t employ data analysts to extract value from information, or lack the data interpretation skills (19 percent in the UK) or insight application capabilities (27 percent in the UK) required to turn information into the decision-ready facts, targeted marketing campaigns and improved processes, innovation that deliver a return on information.

This is a particular cause for concern when we found that as little as four per cent of businesses are able to extract the full value from the information they hold and, as a result, 23 percent of European and North American companies surveyed obtained no benefit from their information whatsoever. So why aren’t businesses doing more to enhance and gain a competitive edge from their information? Given that 64 per cent of UK business leaders believe that they are already making the most of their information, there is a notable disconnect.

While information risk and security remains important, it’s no longer just about locking information away to keep it secure from data breaches. It’s about striking a balance between managing information for risk and for value to ensure the right information reaches employees with the skills to use it for insight that results in informed business decision making. By exploiting the potential of data scientists who understand the business strategy, utilising tools that are readily available and fostering a culture of using information to support decision-making, businesses have the potential to grow exponentially.

In a 24/7 digital world, information is insight and insight is power, which means it has never been more important to harness, use it and protect information like any other asset in the business. Any business not thinking about how to harness the value of its information today may find itself losing out to its competitors and may ultimately become obsolete.

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