Survey shows gaps in predictive analytics skills as businesses seek to gain greater forward-looking insight from their data
Feltham, UK — The race to harness the growing volumes of data for competitive advantage has put increasing strain on skills and resources within businesses, according to a new survey by SAP AG (NYSE: SAP).
The research – of over 300 businesses in the UK and US across retail, FMCG, and financial services – shows that as expected, 92 per cent have seen the amount of data grow in their organisations over the last 12 months.
However, when it comes to barriers to using this information to greater effect, 42 per cent see lack of time and resources as their biggest challenge. Furthermore, 75 per cent of those surveyed believe that new data science skills are needed within their organisation, and 84 per cent would like specific training to integrate analytics into their day-to-day work.
“Getting access to – and making sense of – data has until recently been seen as a complex and highly-skilled task, delivered by people with advanced degrees in statistics and prior analytical experience,” said James Fisher, VP of Marketing for Analytics Solutions, SAP. “This dynamic simply can’t scale at the pace of the business but now, with the availability of new predictive analytics technologies, for the first time people at all levels of the business can self-service their need for insight.
“It is now possible to embed predictive analytics into all areas of an organisation, from point of sale to the call centre, but to make this possible, it is critical that companies empower their staff with both the skills and systems to self-service their analytics needs.”
This is reassuring news as respondents estimate that 28 per cent of the workforce currently uses predictive tools regularly, and that they expect this to rise to 42 per cent over the next five years. By providing education and training on advanced analytics, and marrying this with intuitive predictive technology, businesses will be able drive real value and insight across the organisation.
“Skills gaps are common as new technologies emerge, but sophisticated predictive analysis is moving from a small population of specialists to a broad spectrum of users,” added Fisher. “We could be in a situation in a few years where up to half of employees are using predictive analytics in some capacity as part of their daily routines. We need to think about how we provide easy to use interfaces that address the needs of the data scientist, the business analyst and the end user.
“We’ve seen a real shift in the skills employers are looking for,” said Aidan Anglin, Chairman of the Recruitment & Employment Confederation’s Technology Sector Group. “The most important qualifications for these types of data analysis roles might not be academic degrees, certifications or job experience but so called ‘softer skills’ – curiosity, creative flair, the ability to visualise and to communicate clearly with non-technical people throughout the business.”
In addition to the skills challenges, other findings from the research show businesses are prioritising and investing in predictive analytics:
Positive effects on competitiveness – 85 per cent of those asked agree that predictive analytics has had a positive impact on their businesses, and 77 per cent believe that they have gained specific competitive advantage.
Growth outweighs risk – Predictive analytics seems to be about exploiting new opportunities (69 per cent) rather than minimising risk (31 per cent). When asked about their overall strategies, it seems that data analytics is being used to drive new growth opportunities, such as predicting customer needs (85 per cent) and forecasting market trends (84 per cent).
Line of business – Finance (44 per cent), sales (46 per cent), marketing (42 per cent) and manufacturing (23 per cent) are the functions benefitting most from predictive analytics.
A growing investment – Around a quarter of businesses (27 per cent) report using predictive analytics solutions to a great extent and 61 per cent agree it is a current investment priority for them.
There are also some subtle regional differences when comparing UK companies with their US counterparts. The survey suggest that US companies are more advanced in their current use of predictive analytics in predicting customer needs (UK: 80%, US: 90%) and new market trends (UK: 78%, US: 90%) while also reporting fewer barriers around skills and resource challenges. They also look set to focus more in the future, with an 11 per cent difference in predictive analytics as an investment priority moving forward (UK: 77%, US: 88%).
“Despite some of the skills and resource challenges, there is a real sense from the research that the emphasis on predictive analytics has moved from minimising risk to maximising future growth potential in areas such as customer relationship management,” concluded Fisher. “If businesses can put the right investment into developing a data-driven workforce, alongside data-driven processes and applications, they can accelerate their performance, increase speed of decision making and uncover new revenue opportunities.”
For further information and to see the report, ‘Predicting the Future of Predictive Analytics’, in full, please click here.
Note to editors:
The findings of this research were based on responses from 309 UK and US business decision-makers with some responsibility for / input into overall company strategy. All had some knowledge of predictive analytics, and worked in organisations with 50 or more employees.
153 online surveys were completed by UK organisations in June and July 2013. Interviews were conducted in each of the following three verticals: retail (51), FMCG (51) and financial services (51).
156 online surveys were completed by US organisations in August 2013. Interviews were conducted in each of the following three verticals: retail (51), FMCG (53) and financial services (52).
Statistics from each of these verticals are available on request. The research was conducted by Loudhouse, an independent research agency based in London.
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