Companies often champion meritocracy, touting promotion and reward based solely on good work. The commitment to meritocracy is often used to justify a lack of policies that support diversity. If people are evaluated for their skills, abilities, and merit alone, then factors such as gender and race should not contribute to executive decision making. However, merit-driven systems often trigger biases instead of preventing them.
Our last few blog posts focused on bias in the workplace in regards to gender, ethnicity, and age– emphasizing the importance of removing biases and leading together so businesses leverage top talent for maximum results. This topic will be further explored during Momentum’s biennial breakfast with keynote speaker Dr. Heather Foust-Cummings.
Emilio J. Castilla, a professor at MIT’s Sloan School of Management, researched how meritocratic ideals play out in organizations…and reached some unexpected conclusions. In Castilla’s analysis, women, ethnic minorities, and non-US-born employees received a smaller increase in compensation compared with white men, despite holding the same jobs, working in the same units, having the same supervisors, the same human capital, and importantly, receiving the same performance score.
Upon further research with Indiana University sociology professor Stephen Bernard, each experiment found that in companies emphasizing meritocratic values, those in managerial positions awarded a larger monetary reward to the male employee than to an equally performing female employee. Castilla and Bernard termed their counter-intuitive result “the paradox of meritocracy.”
The concept of meritocracy can work, but it requires equal attention to training, systems and policies to make sure that implicit biases are not working against the merit-based practices. When executives implement a merit-based performance system, they tend to lose focus on biased decisions that may also come into play. When companies implement a merit-based system alongside training and policies to prevent implicit biases, they see positive outcomes.
After five years, Emilio J. Castilla reanalyzed data after a company created a performance-reward committee to monitor compensation increases and sharing information with top management about pay broken down by gender, race, and foreign nationality. The demographic pay gap disappeared.
The collection and analysis of data on people-related processes and outcomes–termed “people analytics”– is key to enabling companies to identify and correct workplace biases. Building awareness among managers about how implicit bias can affect their “merit-based” evaluations is key to retaining the best top talent. True meritocracy is then possible, allowing the most productive and efficient employees to rise to the top.