In the current business landscape, data skills are vital for all members of the workforce, writes Robin Sutara, Field CTO, Databricks.

Once, data skills were widely considered as only relevant to those in technical roles. Now, as businesses increasingly deploy advanced cloud-based technologies such as machine learning (ML) and artificial intelligence (AI) across all departments, all employees can benefit from a foundational understanding of how data is used to meet business objectives. I have spent a majority of my career helping organisations through their transformation of people, process, and technology to enable data-led insights and decision-making.

Data-driven operations can procure excellent outcomes for a business, including increased revenue and improved employee engagement. Organisations can only expect to enjoy these benefits if data competence is widespread within their workforce – a condition that all too often goes unfulfilled. To unlock the full potential of data, leaders must look to building diverse teams with functional data capabilities to tackle the ongoing skills gap. This means tapping into the skills of people of all genders, skill levels, and backgrounds to provide the most value to the business.

Democratise data competence by widening access to upskilling

Indeed, the lack of data skills within the British workforce is a well-known issue, with government statistics suggesting that around half of the UK’s working population have the numeracy skills of primary age children. In response to this, Prime Minister Rishi Sunak even went as far as to announce his intentions to have students study maths up to the age of 18. This approach has positive implications for the future, but there is certainly more to be done – and more we can do today.

Currently, only 15% of data scientists are women. Not only is the gender gap present in the workforce as a whole, but it is particularly noticeable in data. While education has an important role to play in narrowing the data gender gap for future generations, businesses can also have a huge impact on their current workforce’s data competencies. There is a clear need to encourage every employee to take part in relevant and regular upskilling, regardless of whether they have a technical background or not. Female employees may not naturally get involved with such programmes, meaning businesses need to create a culture of diversity and inclusion around data upskilling. Only when diverse teams have the opportunity to nurture their data skills can businesses hope to close the data skills gap.

Look beyond tradition to a diversity of talent

In line with encouraging greater upskilling across a range of organisational functions, leaders need to think outside the box when it comes to recruitment. During recruitment processes for roles involving data competencies, organisations tend to look for ideal candidates with extensive experience with multiple platforms and tools. Sometimes these individuals may come along, but in reality, very few people have this level of experience and skills. Business should look more broadly, considering a range of candidates with varying experiences.

Roles that require some data skills do not always need candidates from a traditional STEM background. In fact, in today’s world of cross-functional data skills, businesses can benefit from the diversity of experience that non-traditional candidates may have. For example, take someone who comes from a user experience background. They may have more to learn about the organisation’s data stack or analysis processes, but already have an invaluable understanding of what makes customers in the sector tick. This is likely to be far more valuable to the business than hard data skills, which can be learned through on-the-job training.

Publishing job descriptions that include a long list of technical requirements can result in businesses losing out on the full range of top candidates. This is especially relevant when considering gender, as women are more likely to self-disqualify themselves from a job if they do not meet all the requirements. As such, in their endeavour to encourage a cross-departmental data culture, businesses should carefully consider their hiring practices, to ensure that no strong candidates are discouraged from applying. My guidance is always to opt candidates in rather than out to have a varied pool.

Tackle the skills gap head on

Tackling the data skills gap is about so much more than recruiting greater numbers of data scientists, analysts, and engineers. This approach often limits diversity of thought around data, which is crucial in the modern, data-forward enterprise. Businesses today have masses of data at their employees’ fingertips, but they ultimately need a diverse range of talent who can interpret data, tell stories with data, and apply it to business needs.

Simultaneously, to broaden hiring, organisations should provide access to the right kinds of upskilling opportunities for existing staff. This is particularly important for female employees,  whose data skills often fall behind their male counterparts. The data skills gap is inherently gendered, meaning that businesses have a duty to ensure that any training programmes are open to everyone, and widely encouraged across the organisation. And when considering programs, think about equity, not just equality. For example, creating an after hours training program to help skilling inherently introduces bias for those team members with other commitments that prevent taking advantage of these types of opportunities. Through a combination of diverse recruitment and upskilling, businesses can leverage their data efficiently to create a data-driven future.