Demographic data provides the context, not the answer

Prioritising Diversity, Equity and Inclusion (DEI) commitments

Organisations have been capturing demographic data on their candidates and workforce for some time now and whilst this has provided useful information, it has not brought about significant change. This has led to some companies such as Google and Meta reducing their diversity, equity and inclusion (DEI) budgets, perhaps seeing it as a 'nice-to-have' business initiative rather than being fundamental to creating a productive work environment that leads to innovation. During times of greater economic instability, it seems DEI programmes are commonly deprioritised with Indeed reporting a 42% decline in DEI jobs being advertised between March 2022 and March 2023.

Many of these companies made grand public statements about the positive impact they hoped to make, however the challenge of making a difference is tough given that inequity is interwoven throughout our society. They have been quick to implement initiatives such as unconscious bias training, employee resource groups and mentoring schemes, but have not spent enough time diagnosing the problems. Certain common workplace initiatives like employee referral schemes may even be counter-productive, whilst they save on recruitment costs, they promote homogenous workforces perpetuating the DEI problem. Data forms an important part of being able to understand the problem better, however organisations often struggle to increase employee disclosure rates of demographic background.

As this is improving over time with organisations making it mandatory with a 'prefer not to say' option, employers are becoming more able to assess key decision-making moments. By analysing the employee experience, segmented by different protected characteristics, they can gain a better understanding of the impact of bias in the workplace. This provides greater context on the outcomes of bias, but it doesn't diagnose the causes. As these biases have been engrained in our society for many years, the causes are multi-faceted and complex.

Positive action is about equity, not discrimination

Rather than investing resources into more deeply understanding the complexity, organisations have used approaches such as positive or affirmative action. Positive action, a UK term, aims to level the playing field by providing proportionate support to help those who are disadvantaged, with the aim of creating equal opportunity. However, affirmative action which was previously allowed in the US, went a step further and enabled organisations to set quotas for underrepresented groups when it came to educational institution admissions or employment. In 2023, US case law repealed affirmative action making it no longer legal for the same reasons positive discrimination is illegal in the UK. Offering an individual a college place or a job based solely on a protected characteristic is considered disproportionate and unfair and it doesn't create sustainable change.

The complexity of intersectionality

To bring about more equitable workplaces, we need to go beyond focusing on demographic labels alone. By assessing demographic labels in isolation of each other, it doesn't provide the richer context of intersectionality where greater disparities are visible. For example, a woman's experience at work and in society will differ depending on her representation in other demographic fields e.g. ethnicity, disability, socio-economic status. A white male from a working class background may experience greater societal barriers than a white woman who went to a private school and comes from a more affluent background, but viewing it through a gender lens, the latter would be given additional support based on being a woman.

The obstacle with understanding intersectionality is often the lack of data. Once you start applying several demographic data points to a workforce, the sample size for each group becomes much smaller and identifying attributes of their lived experience becomes a challenge. In addition, as we gain a better understanding, there is a realisation that other factors that we might not be gathering information on may also have an impact. Factors such as whether you are a carer for a dependant have started to be introduced to demographic data gathering and the list will keep growing as we educate ourselves further.

At GotDis, we believe it is important to use demographic data as a way of understanding the context better, but not seeing it as the answer because the problem is far more complex. We aim to support organisations to create fair opportunity for emerging talent by not only removing bias data points such as educational attainment, but through also having a focus on the behaviours and motivations that reflect the barriers they may have experienced. Various studies have shown how human, social, cultural and psychological capital influence an individual's career success.

By assessing the networking capability and employability strengths of emerging talent, we can provide actionable insight to employers that enables them to understand how they can better support candidates and employees for more equitable outcomes. In turn, individuals can receive personalised career advice to support them to develop behaviours that will help them succeed in securing jobs and progressing in their career. By analysing behaviours linked to career success, using demographic data as a contextual indicator rather than a goal, the focus targets long-term behavioural change for a more equitable future.

By Lara Plaxton, CEO & Co-founder @ GotDis