TL;DR

Underrepresented groups are populations that appear in a workforce, industry, or role category at lower rates than in the broader available talent pool or general population. The term is descriptive, not prescriptive: it identifies a gap between representation and availability without specifying the cause. In recruitment, it shapes sourcing strategy, job design, candidate experience, and reporting.

Defining Underrepresentation Accurately

Underrepresentation is a relative measurement, not an absolute category. A group is underrepresented in a specific context when its share of a workforce is meaningfully lower than its share of qualified candidates, the broader labour market, or the general population. The benchmark matters enormously. Women are underrepresented in software engineering roles relative to the overall labour force; they are not underrepresented in the overall economy.

Which groups are considered underrepresented varies by country, industry, and role:

• UK context: Women in senior and technical roles, Black and Asian professionals in executive and boardroom positions, disabled workers across most sectors, and workers from lower socioeconomic backgrounds in professional services and finance.
• US context: Black, Hispanic, and Native American professionals in technology, finance, and senior leadership; women in engineering and executive roles; veterans and people with disabilities across corporate environments.
• Other dimensions: Age (older workers over 50 in technology), LGBT+ individuals in certain geographies or sectors, first-generation university graduates in elite professional roles.

The honest version of this conversation acknowledges that underrepresentation is documented through data, not assumed. Organisations that track representation carefully know where their gaps are. Those that do not track it tend to claim the problem does not apply to them.

Why It Matters for Recruitment

Recruiters who do not actively address sourcing bias will reproduce existing representation gaps at every hire. This is not a statement about intent. Default sourcing channels — employee referrals, the same universities, the same job boards, the same professional networks — tend to surface candidates similar to those already in the organisation. A workforce that is 90% one demographic will generate referrals that are mostly that same demographic. The gap perpetuates.

For employers, the business case for improving representation is established by research. Teams with greater cognitive diversity produce better decisions, identify more risks, and generate more varied solutions. Financial services regulators in the UK have begun treating diversity data as a governance metric. FTSE 350 boards face public reporting requirements on gender and ethnic diversity.

For recruitment agencies and in-house teams, underrepresentation shapes sourcing investment. If the goal is to change the composition of applications, the sourcing strategy must change first. That means:

• Identifying alternative talent pools where underrepresented groups are active
• Auditing job descriptions for language that deters specific groups
• Removing or contextualising educational requirements that screen out qualified candidates without improving role performance
• Structured interviewing to reduce the effect of affinity bias at selection stage
• Reviewing offer acceptance rates and decline reasons by demographic where data exists

None of this requires lowering hiring standards. It requires being honest about whether current standards are genuinely predictive of performance or are proxies for familiarity.

In Practice

A technology company analyses its engineering hiring funnel. Applications are 18% women. Phone screens pass 16% of female applicants versus 22% of male applicants. Final round offers go to 30% of women who reach that stage versus 28% of men. The gap is at the top of the funnel, not the bottom. The company reviews its job descriptions with a gendered language tool, removes the degree requirement for mid-level roles (where performance data shows no correlation), and adds two historically women-focused coding communities to its sourcing partnerships. Female application rate rises to 26% over six months. The offer rate remains the same because the selection process was not the problem.

Key Facts