It’s hard to put a precise figure on the number of women working in data and analytics in the UK. If one assumes that the data sector is broadly reflective of the wider IT and telecommunications industry, it would a safe bet to estimate that there are roughly 11 men in the industry for every two women. This is a problem. Data and analytics is all about examining data, drawing conclusions and making decisions based on those conclusions. If large swathes of the population are excluded from that process, the resulting decisions could have a negative effect on specific groups of people which in turn would negatively impact people’s perception of the organisation making those decisions.
"The programs that make decisions need to reflect a really wide range of opinions, skills and backgrounds."
Charlotte Richards, audience, insight and analytics director at News UK, explained why diversity is especially important when looking at the rise of AI and automation. She said: “In both automation and A,I we’re taking the human element out of decisions. Therefore, the people who program the programs that make those decisions need to reflect a really wide range of opinions and skills and backgrounds so that we don’t make a really obvious mistake.”
Richards gave the example of a car designer who only thinks of themselves in terms of the ergonomics of the vehicle and not taking into consideration the needs of pregnant women or older people. She then explained that she has a non-standard background for a data professional. She is an arts graduate with a degree in history and works with colleagues who have backgrounds in maths and statistics.
She also works with some people who have worked their way up in the organisation, and others who have entered from academia with PhDs. Richards said: “They are all bringing really different perspectives and skills and that is what is most important. What data in particular really needs for us to be able to solve big problems in the best way.”
"Balanced teams are more successful, making commercial businesses more profitable.”
Roisin McCarthy drove home this same point when she said: “The research concludes balanced teams are more successful, making commercial businesses more profitable.” McCarthy has an enviable vantage point on the data and analytics industry as the manager of a recruitment firm Datatech Analytics.
She said that her research revealed that between 2000 and 2014, there was a significant decline in women maintaining and progressing careers in data. However, more light is being shone on the issue. “I am thrilled to say that diversity in data is a major agenda for many organisations in the UK,” she said.
Government has also taken notice. McCarthy is also the co-founder of Women in Data UK, a women’s network which hosts annual conferences. Last year’s event attracted over 400 delegates. McCarthy, co-founder Rachel Keane and chair Payal Jain, have been invited to 10 Downing Street to celebrate International Women’s Day. “This really recognises the importance of women in STEM – science, technology, engineering and mathematics,” said McCarthy.
Ideally, McCarthy would like to see gender parity at all levels in the data industry so as to reflect the population. She concedes there is still a long way to go, however: “the direction is positive with encouraging results.”
Caroline Bellamy, chief data officer at Ordnance Survey, detailed the ways in which she has championed and driven diversity and inclusion. She explained that when she was working in Germany there was a notable challenge with gender parity and so gender parity recruitment targets were implemented. Whilst acknowledging they are not always popular, they do stimulate interest among female applicants.
“They know they are going into an organisation that is acting proactively to redress the gender imbalance,” she said. “To address this, we reached out into the female community by using female head hunters and recruitment agencies.”
According to McCarthy, research carried out by Datatech Analytics suggests that women in data value flexibility throughout their career, career satisfaction, and acknowledgement, along with continued career development. These factors go a long way in retaining women once they have been recruited.
"The leadership shadow is important, as it is about consciously demonstrating behaviours that you accept and expect.”
Bellamy manifested her commitment to flexible working by setting an example to her staff. “Demonstrate that you are not always the first person in the office or the last to leave, and that flexible working is perfectly acceptable and normal. We should know there are challenges to accommodate if you are a working mother, partner or carer. The leadership shadow is important, as it is about consciously demonstrating behaviours that you accept and expect.”
"Women need to play an active role and volunteer, mentoring their junior counterparts."
The CDO is also part of Your Life, an initiative that fosters and encourages female growth in STEM areas. This is precisely the type of action that McCarthy said can improve inclusion. She said: “Encouragement, role models, development programmes and collaboration should be set on the agenda for organisations building data functions. Women need to play an active role and volunteer, mentoring their junior counterparts. Equally mentees need to reach up and ask for support and guidance.”
For Richards is it also imperative that the spotlight be placed on girls at school to get them excited at the prospect of a career in data. “We need to think about how we encourage people before 18 to consider our jobs as good jobs. When you’re 16, data probably isn’t on the list versus lawyer or doctor. We also need to think about more of an apprenticeship model, not assuming people need to have gone to university. Maybe there are things we could be doing to get people to learn on the job,” she said.
“Data, for all that it is about the numbers, it is actually about people."
Progress is being made. The number of women in the DataIQ 100 now stands at 38 but clearly, we need to press on to get the balance right because behind each figure is a person. Richards put it more succinctly by saying: “Data, for all that it is about the numbers, it is actually about people – what people are doing and how people are behaving.” When we get the numbers right, we'll be able to make better decisions about our own behaviour.