In search of a diverse data sector

Diversity, Equity and Inclusion has been both a focus and a topic of fierce debate amongst data practitioners and talent experts for a number of years now. 

With the rapid expansion of the sector, the exponential demand from organisations to recruit increasingly large and varied amounts of data expertise and the consequential strain placed upon educational establishments and training service providers to identify and nurture new sources of grass-roots talent, it stands to reason that ensuring as “even a playing field as possible” for everyone working in or showing an interest in working in the sector should be an absolute priority.

However, is this really the case? Are we seeing equal opportunity for all? Or, like so many other sectors within Technology, are we paying lip service on the odd day we’re required to change our Linkedin logo to a rainbow flag or show support to our different gendered, neurodiverse, or disabled colleagues without changing any of the underlying fundamentals that could result in a fairer, more meritorious, and equitable sector for all? 

Don’t worry, this short blog won’t attempt to answer such a profound (and potentially controversial) question within a thousand or so words.  A much larger volume of work has been created already that explores the topic in far more depth and, in many cases, provides substantial answers to the questions raised above. 

Instead, this piece will focus on exploring three potential practical steps that anyone, regardless of protected characteristic or otherwise, can implement immediately should they be interested in being part of the growing movement to “level the playing field”. 

There are no instant answers promised, no panaceas for a very acute condition. What there are, though, are pragmatic examples of what other data practitioners are doing, right now, to help Diversity, Equity, and Inclusion efforts within their organisations. 

Hire for Cognitive Diversity 

Cognitive Diversity, defined as the inclusion of people who have different ways of thinking, divergent viewpoints and contrasting skill sets in a team or group, has become a discussion point amongst many members of the business and academic community arguably due to its recent popularisation by Matthew Syed in his book “Rebel Ideas”. 

Syed proposes that we, as humans, are naturally inclined to surround ourselves with people who think just like us. It makes us feel good, he suggests, when others agree with what we think. 

However, when solving complex tasks (like the type of work undertaken daily by teams within the data sector!), it helps to have the exact opposite – differing opinions from different people with varied backgrounds and contrasting viewpoints – because in these scenarios the whole is greater than the sum of the parts.

Syed’s theory was explored recently in our Podcast Episode, Diversity in the Workplace, by Aggreko Director of Insight, Elizabeth Hollinger. Elizabeth said: “You are bringing together people that just think in different ways. And that might be because they are a boy or a girl or because they grew up in a more affluent or deprived area or it might be that they went to school and left at 16 and decided to go into the world of work or that they went on to have a PhD in a particularly technical subject. It doesn’t really matter. All that it means is that we are all unique and individual. All shaped by our life experiences”. 

Elizabeth goes on to talk about how she has tried to ensure cognitive diversity from the outset within her team, by deliberately looking to hire beyond the “traditional” educational background of post-Graduate qualified mathematicians or computer scientists. Recognising the importance of communication skills, she has often hired Arts graduates and, in some cases, has forgone the need for a degree qualification at all but focussed on equivalent work experience. 

Adopting a “cookie cutter” or “one size fits all” approach to team building can naturally promote “group think” or confirmation bias within the collective – exactly the opposite of what the team needs to be able to solve the complex problems that data teams can be engaged to solve. 

Force change from inside the tent

Another theme that recurs within debate around Diversity, Equity, and Inclusion is that of identifying the correct catalysts for change. If it is understood that increased Diversity within business leadership has a direct and measurable impact upon profitability (see McKinsey, Why Diversity Matters, 2015), then surely leadership within all areas of business should, on their shareholders behalf, be arguing constantly and consistently for increased Diversity? 

However, the phrase “turkeys voting for Christmas” springs to mind here. When we think “business leadership” we invariably think “white, male and pale”. That’s the fundamental issue here. For the data sector to embrace a truly diverse future, those within data leadership positions must begin to agitate for successors that don’t look, act, or speak anything like they do. And, based on the latest available information on gender diversity within the broader but still indicative Technology sector, there is a massive gap to be bridged before anything like parity can be achieved   

50% of workers in the labour market are women, in tech, it's half that, at 26%

Only 3% of Chief Technology Officers (CTO) or Technical Director roles are held by women. 

It is doubtful whether diversity figures for ethnicity, sexual orientation, disability or neurodiversity or any protected characteristic would preset as anything more promising. 

Herein lies the major challenge. We all recognise that Diversity is morally the correct path to go down. More and more hard scientific data asserts that it’s also the most profitable path to go down, but the people who hold the power to lead the industry down this path are, overwhelmingly, not diverse. It’s time for the “allies” of change to drive the agenda. Especially those who are “white, male and pale”. Change must come from inside the tent. 

Can you help? 

Although the broader Technology sector has been referenced, it would only be fair to point out that the data sector does, if we take gender as a microcosm, appear to have a more balanced and diverse make-up than many other areas within Tech.

The recently published Data IQ 100 for 2022, as representative a barometer for influence within the UK data sector as any other measure, lists 6 females within it’s top ten leaders and influencers. (For reference, 2019 had 7/10 of the top 10 female, 2020 had 3/10 and 2021 also 3/10). 

With consistently visible female representation at the highest level, sometimes in the majority within the top ten, the data industry (in the UK, anyway) compares very favourably with the previous 3% CTO figure from the broader Technology sector.  

Initiatives such as Women in Data (numbering 25,000+ members) and The Data Lab’s MSc Placement Programme (consistently funding post-graduate data courses in Scotland over many years with a 50|50 gender balance) are also highly visible and recognised initiatives, specific to the data sector, that are ensuring opportunities at grass-roots levels for those females aspiring to perhaps join the female data leaders that Data IQ frequently champion. 

Broadening the argument out to include other protected characteristics we have Auticon (promoting neurodiversity within Tech and data teams and encouraging/advising employers how to make the changes required to allow this to happen), Code Your Future (working to re-train refugees and asylum seekers in Tech skills and then securing placements for them within industry), Data Kirk (working to change the face of Scotland’s future talent pool by increasing the representation of disadvantaged groups in the data economy), Data Inspiration Group/ Dig Data (working to promote careers in data within diverse groups of school, college and university students) and the Data & Marketing Association (DMA) long-standing support of a variety of diversity initiatives including neurodiversity and gender representation. 

These are organisations that MBN are familiar with, and have supported and promoted in the past, and we encourage all “allies” to collaborate with them, and the many, many more similar organisations doing equally laudable work promoting diversity within the sector in any way they can. 

So, what’s next? 

To close, it’s probably wise to think back to the radical change that the data industry has undertaken in the last decade. From a little-known and often misunderstood discipline to “sexiest job of the 21^st century” for those of us who have been working in the sector for the last ten years or more it’s been a remarkable time. 

The sheer volume of people now employed in the industry, the reach and influence that the industry has within commerce, the myriad complexities of the skills found within the sector and the impact that data professionals have had, through their work, on ordinary peoples’ lives has been nothing short of breath-taking. 

Now is the time to act to ensure that the next ten years sees the industry reflect the diverse nature of the society that it is drawn from. Concerns over privacy, bias, governmental overwatch and manipulation and a plethora of other real ethical concerns characterise the debate over the future of the industry any time practitioners, leaders, and observers’ gather. However, the answer lies in our own hands. These concerns can be negated, largely, through a Diverse, Equitable, and Inclusive workforce. We know this intuitively. What we now must do is to make it happen. No matter what.

Ultimately, we will have the future data sector that we deserve.