Tell me about you and your role/firm?
I have been involved in setting up and leading HR functions in the tech sector for 25 years with Lotus Development/IBM, Cable & Wireless and Remedy Corporation among my past employers. I joined SAS in April 2013 following seven years with Vodafone where I led HR teams and several significant transformation programmes on a global basis.
My role is to lead the people agenda for the SAS businesses based out of the UK and to evolve the HR model and team to be a strong partnering function to the frontline business. Focus areas include talent acquisition and driving the right employment brand for SAS in the market, talent management, compensation philosophy and managing organisational change.
SAS is a leader in business analytics and is the largest independent vendor in the business intelligence market. Through innovative solutions, SAS helps customers at more than 75,000 sites globally to improve performance and deliver value by analysing data to make better decisions faster.
The company has specialised in analytics for almost 40 years and is unusual in being privately owned. Jim Goodnight, the CEO and founder, has prioritised making SAS a great place to work and is very committed to educating future data scientists that are now in such high demand.
What key HR initiatives are you working on?
A key area of activity for us is the talent acquisition programme. This aims to identify, engage and hire talented people.
We really value referrals as we know they are more likely to be successful in SAS than most other sources of candidates. We also provide career coaching to family members of SAS employees should they need support when considering a new role.
Both SAS and our customers are facing challenges due to the lack of available skills in data analysis. This is despite Harvard Business Review describing the data scientist role as “the sexiest job of the 21st century”.
We have carried out regular research into this area with the Tech Partnership, the Sector Skills Council for Business and Information Technology. Our latest report revealed that the demand for big data professionals in the UK has created a salary bubble enabling them to command more than double the average wage. The study anticipates that by 2020 the UK will have created cumulatively 346,000 big data positions since 2013 and there will be approximately 56,000 job opportunities a year in 2020 for big data professionals. This equates to 160 per cent growth in demand between 2013 and 2020, while overall UK employment is set to rise by just six per cent for the same period.
However, other research we carried out last year into ‘What Makes a Great Data Scientist?’ also revealed that over half of data scientists are reportedly suffering from some level of work-related stress, with one in four men and almost a third of women identified as being heavily stressed. It would appear this is driven by increased industry demand and a shortage of data scientists with relevant skills, meaning some individuals are being asked to do too much and take on responsibilities unsuited to their personality types and skills.
How have you overcome these challenges?
SAS is working with industry peers and government organisations to develop these skills at a grassroots level. Through SAS® Curriculum Pathways in schools, university partnerships and its own certification courses, it can lead big data professionals on a full data science career path. Last year we launched SAS® University Edition, which is free software providing training in all the analytical skills someone might need to secure their future.
The challenges remain significant and cannot be overcome without widespread support. The UK Government is supporting the drive for more big data professionals with the implementation of national standards and the creation of new projects, especially around open data.
We are also making sure we are open to all individuals that may have the skills we are looking for. People with Autistic Spectrum Disorder (ASD) typically display many of the skills needed to analyse and interpret data – e.g. statistical and mathematical capability. We have established links with a group of academics from Nottingham University who are exploring the possibility of working with us and potentially carrying out a workplace audit which would analyse how well our existing policies, processes, culture and environment currently support the inclusion of ASD.
Our pending graduate programme could provide an excellent pilot opportunity. This would start with the recruitment phase by working alongside the talent acquisition team who are in full support of the idea. We are also working closely with the National Autistic Society through their Network Autism online facility to discuss and develop initiatives.
Why is it vital that firms focus on your topic?
Big data is on the cusp of going mainstream as the Internet of Things takes hold, and government, businesses and individuals look to use information to make better and faster decisions. To put things into context, 90 per cent of the data available today was created within the last two years, and by 2020 it is estimated there will be 10 times more information in the digital universe than there is today.
We believe that big data is the ‘new oil’ that will power the information economy – but all this data in its ‘crude’ form is worthless. Big data analytics is what’s needed to refine this ‘new oil’ so valuable insights can be extracted quickly and inform business decision-making.
What have you learnt from your role?
Developing an ownership model where employees feel they can contribute to new work practices and be part of the decision-making process is very important and can drive different thinking. For example, we’re currently involved in a ‘Be the Best’ initiative where employees have teamed up in various groups to collect the thoughts of fellow employees, report to the executive and then create action plans to put their findings into effect. One involves attitudes to flexible working hours, and working from home. Another is looking at ways we can have more ‘fun’ in the workplace together. People are more likely to buy-in to these new ideas if they feel they’ve directly contributed to them, or at least been given the opportunity to contribute.
Another thing that’s become clear to me is the role analytics can play in HR. As with finding any sort of match, the more data that can be analysed around what the right role for person X is as opposed to person Y, the better. Otherwise, simply relying on ‘gut feel’ will always be a bit hit-and-miss and an often inefficient use of people’s time. Far better to be able to use analytics to make evidence-based hiring decisions. Not only that, but by tracking, analysing and sharing employee performance-related data, employers and HR not only gain more insight on employees, but boost individual motivation and overall engagement.
I’ve also seen how important it is for us to get our graduate recruitment right. Young minds can add considerable value to any business, mainly because they often bring a fresh, innovative mind to business situations. While older employees may have considerable wisdom and experience of a particular subject-area, it’s important that gets complemented with new, questioning approach. As our head of analytics says, the best data scientists are the ones that are the most creative and ask the most searching questions. That will often be the younger employees, who are sometimes less afraid to ask these questions.
We will continue to engage with employees. The ‘Be the Best’ initiative to make SAS a better place to work is still in its infancy and there is a lot more we plan to do. The feedback so far has been very positive from all sides, and we’re excited about putting the ideas that have emerged into action.
More use will be made of analytics and SAS’ own powerful analytical software to ensure we make the right hiring decisions, properly track and assess employee performance and also understand more about why certain employees leave the organisation and why others stay. The latter point will help us to predict (and therefore prevent) employee attrition.