Using data and analytics to crack the glass ceiling for females
More and more women are stepping into the C-suite and other upper management roles.
However, the data shows that women are still less likely to succeed in these higher-level roles than their male peers.
Why is this the case and how can people analytics level the playing field?
- The number of women replacing males in lower-level positions has increased by 25%, indicating potential upcoming cracks in the glass ceiling.
- People analytics improved the female leadership ratio by 11.5%.
- Data has the power to get leaders to step up and take accountability for gender diversity.
Despite the progress around gender diversity, conversations around the topic are still often uncomfortable. It is for this reason the boardroom often witnesses unwillingness from leaders to engage in them or even start them in the first place. This webcast discusses how data and analytics can overcome this challenging roadblock. Lydia Wu, Head of Talent Analytics, at Panasonic USA claims, “data enables us to drive the agenda forward because at the end of the day, while experiences may be a little bit debatable, it’s really hard to dispute data.”
The key learning for Experian in their people analytics journey is ensuring focus is on the right population, which Olly Britnell, its Global Head of People Strategy, Technology, and Analytics, refers to as the ‘pipeline population’. Instead of just focussing on the headline number of the female leadership ratio, Britnell says it’s important to probe the layers below that. Ultimately this is where the pipeline and opportunity exists.
Watch this on-demand webinar as it takes a deep dive into inclusion and how we should focus on action and contribution instead of measuring it on feelings. Are women able to make an impact on organizations?
Our experts discuss how people analytics can measure participation, employee patterns, and recognition data to see whether women are actually empowered to make a difference and succeed as leaders.
Watch On Demand
"*" indicates required fields