If data is to succeed in improving insight, analysis, and, therefore, organisations, then data must reflect the true diversity of society. At the recent Women in Data Flagship Event 2023, data leaders have called for a more diverse data community that showcases the impact of women in data. 

"Women's health issues are under-served and yet are critical to women's career success," said Nina Anderson, Head of Digital at ClerksWell. With women making up 50 percent of the world population, the development of healthcare products and services isn’t accurate or representative if it’s using data that does not include data about women. Anderson was not alone in feeling this is one of the biggest topics for the data community to tackle; and this forum inspired me to write further on the importance of diversity in data. 

As artificial intelligence (AI) tools creep into our everyday lives and impact the work of employees, diversity and representation in data is all the more important. If these tools are trained on non-representative data, it will exacerbate lack of inclusion in decision-making, product design or services for years to come. 

Diversity as a team ethos 

Having a diverse data team is vital if organisations want to ensure that their data is representative of their customer base. Carol Parillon, Chief Data Architect at Shell spoke on the importance of how she builds her team,"Make space for diversity. I have male, female and people from all different backgrounds in my team, and that gives me a rich mix when it comes to developing products." 

Anderson at ClerksWell  agreed and added: "Intersectionality is important — the presence of organisations like Black in Data was crucial to reminding us all that gender is only one aspect of diversity and inclusion."  

Diversity will continue to improve the quality and output of every business. In the words of Parillon, "Our markets are changing, and you need to make sure that you reflect that.” 

The importance of women in data leadership

Reflecting on a 30-year career in data leadership, Parillon said women in  leadership must increase the recognition of women in data. "You have to recognise what your superpower is, and when building my teams, I always try to help people recognise what gifts and skills they have. Celebrating these gifts is about the impact and how you take those skills and gifts and use them." 

Parillon mentioned that as a data leader; she uses the Performance, Impact and Exposure (PIE) model to ensure that her team is acknowledged for the role they play in the success of the business. Looking back at her East London childhood, her mother, a Windrush Caribbean, said, "self-praise was no praise". But Parillon said women in data cannot adopt that passive approach; they must demonstrate the performance and impact they achieve for their businesses by exposing the outcomes they deliver. 

She added that mentorship and sponsorship play an important part in gaining exposure. "If you are a team leader, you will deliver some element of exposure, so give your team members space to demonstrate their expertise," she said, adding: "Sponsorship is not something that you request and is often delivered when you are not in the room." 

The Women in Data movement aims to help female data leaders with the development of their exposure. "There is such a huge community of inspiring women working in data," said Anderson. 

Data leadership is about more than publicising success stories, though. As demand for data is at an all-time high, it places increased pressure on the data workforce. "You need to make sure that you take care of your staff; it is not a sign of weakness, it is a sign that you are astute," said Parillon. Data leaders — of all genders — need to protect data teams from burnout. Parillon mentioned "We are under immense pressure at work and living with the cost of living crisis," she said. The very best data leaders will look to uplift their teams, while still providing a stable foundation in the process. 

As data-centric business practices continue to grow, women in data are essential in ensuring that the data used for services, product design, care, policy and decision-making is not shaped by a single view.

Data sets historically reflect this one group, but as Parillon said, “markets are changing,” and therefore data teams and data sets have to adapt.