Financial services firms tap into diversity data to improve workforce
Progressive financial services firms are increasingly using diversity data to drive their agenda.
Firms are rethinking their approach to data to deliver improvements to their workforce, according to research from New Financial.
The think tank found that boards are raising their data requirements in response to external pressures.
Legislation requires employers with 250 or more employees to publish the pay gap between female and male employees each year.
Shareholders and clients are also requesting information on diversity within firms.
The more progressive firms are unpicking their gender data to understand why employees join, are promoted or leave.
Jayne-Anne Gadhia’s 2016 Empowering Productivity review of women in financial services recommend companies track a number of data points. These included the gender split for the firm, the board and each business unit.
The think tank said that the most commonly collected data set is gender. It can then act as a gateway to collecting other strands over time.
Yasmine Chinwala, partner at New Financial and author of the report, said: “The diversity data discussion is not about choosing women over men, or a person from a diverse background over a more qualified candidate. It is about injecting rigour and accountability into the processes”.
New Financial’s case studies prove that firms that have stepped up their approach to diversity data are seeing quick results.
The Financial Conduct Authority said that the act of measuring data has had a “transformational impact.”
Similarly, the study found that improved data at Schroders is changing managers’ behaviour. The asset manager said: “Decisions are more thoughtful and considered because everyone sees that data.”
Tara Kengla, chair of the London Women’s Forum, which sponsored the research, said: “Unlocking the power of data analysis is critical to driving harder and really turn the dial on diversity.”
Chinwala said: “The industry recognises that it needs to improve”.