What sort of skills does your company need in a world of democratised data?

Research and tips from the IT recruitment world

If there's one thing that's becoming prevalent in big data and analytics now that organisations are finally finding their feet with the so-called ‘big data revolution', it's the democratisation of analytics.

It's a trend Computing has witnessed more than ever recently, whether looking into the industrious data science around Tesco's grocery ecosystem, which is fast changing the workings of the business down to the most junior level, or seeing Lloyds Bank and Toys ‘R Us - coming from the opposite viewpoints of IT and the business - both agree that big data is now a concern of everybody in the company, with process, infrastructure and skills all starting to reflect this.

These experiences matched a lot of our discoveries from our white paper Computing Research: Big Data Review 2016, which we carried out in association with recruitment firm Michael Page, and its technology specialists at PageGroup.

We sat down with Doug Rode, senior managing director of PageGroup, to find out how the growing democratisation trend may be affecting the IT recruitment needs of companies.

Most of those we surveyed - well over 30 per cent of respondents in each case - put "problem solving", "statistics knowledge" and "data visualisation" as the highest ranked wants and needs in data analysts. But communication and commercial awareness are still ranking lower. Does this fit PageGroup's experiences, and what does this say about IT's current relationship with the wider business?

"While we are seeing problem solving, statistical knowledge and data visualisation rank highly, we expect communication and commercial awareness to spike with so many businesses now recognising the power of data and turning to data analysis to solve business issues," Rode told us.

"New adopters are recognising the need for not only visualisation but individuals who can accurately convey the impact of the data to the wider business. Data is no longer considered as merely a necessary cost. Businesses are recognising the value it can add across all functions of their operation."

Meanwhile, 61 per cent of our respondents said they wanted a company structure that allows data scientists or analysts to bridge IT and the business. However, only 34 per cent seem to want analysts in cross-functional interdisciplinary teams, whereas 46 per cent want to keep using specialist data science and analytics teams.

It can be a tricky balancing act to achieve. According to Rode, however, many successful solutions do actually involve crafting bespoke teams drawn from several business disciplines - unpopular as a possible option in our research, but something businesses should consider to see success.

"A number of recent solutions to this include placing a data science team separate from the traditional IT unit which bridges the gap to the rest of the business," confirmed Rode.

"The best way to ensure smooth communication is to build the data team from people with strong stakeholder management, particularly at team leader positions. If data science is to be brought toward the nerve centre of a business the entire operation requires free flowing lines of communication.

"Clients are also encouraging key heads of department to actively liaise with the data team and be clear as to what type of data has potential to benefit them. It is equally important for the data team leaders to be proactive in identifying business needs. Both these approaches require a hybrid data team."

Nearly half our respondents also said they are looking to build companies in which data analysts are listened to "at the right level". Unsurprisingly, Rode agrees there's still some inconsistency as to what this "right level" means, and says the process is still heavily dependent on stakeholder or board-level buy-in to decide who can lead or build teams.

"If [stakeholders] can clearly see the benefit of data then someone at junior manager level can adequately spearhead a data programme," he told us.

"Where key stakeholders are less convinced about the value data can add then someone more senior may be necessary in order run the programme and get buy-in."

But one thing is for certain - it's now easier to recruit cross-business skilled workers, i.e. "data scientists" - there may be a skills gap, but it's going somewhere towards closing. Diverse backgrounds are now becoming the norm for companies slowly learning to feed essential data analytics skills and knowledge down through the business.

"While the best talent is keenly fought over companies are open to hiring individuals with diverse backgrounds providing they have the cross-business comms skills. We are seeing people from business development, marketing and finance backgrounds hired into data teams and trained up," Rode concluded.

The research seems to suggest the major factor holding back companies placing big data skills in positions outside IT may be their own fear of change, as opposed to any provably negative results. Don't be left behind.