34% of U.S. workers believe their pay is based on what their manager feels they deserve to make, rather than on their performance. This means that one in three workers is unlikely to ask for a raise based on achievement of goals, since they don’t feel their salary is performance based. For women in particular, not feeling like their salary is performance-based is a major disadvantage; this perception could keep women from even asking for the raise.
Even when they do ask – and research from Australia suggests that women ask for pay raises just as often as men — they are only successful 15% of the time. Men are successful 20% of the time.
In the U.S., the House of Representatives in March passed the Paycheck Fairness Act, which is designed to help close the gaps that disadvantage so many women, particularly women of color. The vote was 242-187 largely along party lines, with seven Republicans joining the majority. Now the bill is headed toward a Republican-majority Senate, where it’s not expected to pass.
While the U.S. waits for the government to provide federal pay equality in the form of law, technology, specifically AI, can help individual companies administer pay more fairly by providing hiring managers and CHROs with pay equity data. These systems can measure trends and predict performance through a variety of metrics such as education and experience, without taking into account age, gender, race, or other characteristics, thus providing a more realistic picture of the employee’s capabilities and filtering out any potential emotions and unconscious bias.
This can do much to combat the perception 31% of U.S. workers hold that employees at their companies are not fairly compensated due to age or race.
Creating transparency
Fifteen states have passed laws to implement some form of pay transparency into the compensation process. For example, in Connecticut, employers cannot prohibit employees from discussing their wages with another employee or require an employee to sign a document that denies their right to disclose or discuss their wages.
These laws have likely spurred pay conversations among employees, which create a form of transparency. While this transparency is a step in the right direction, it’s in the best interest of employers to take the lead in salary conversations to avoid speculation and reduce the opportunities for misinformation and rumors among workers.
HR departments can turn to AI-powered tech to create industry salary and cost of living benchmarks that show employees what their salaries should look like based on external factors. Additionally, providing more overall transparency into the company’s financials can give employees a greater sense of trust that they are being paid fairly, as well as provide a greater overview of the company’s goals and how the compensation strategy plays into them.
Technology can help
Pay is certainly not the only driver of employee happiness or employee turnover in your organization, but when you look at total compensation and benefits, if employees don’t feel they’re getting fair rewards packages, or packages that meet their personal needs, they’ll be much more likely to leave. This may be manageable at smaller organizations through employee surveys and one-on-one conversation, but for companies with hundreds or thousands of employees, it’s much more difficult and costly to measure employee satisfaction at scale.
Implementing AI allows businesses to personalize total rewards by taking into account multiple factors — even identifying employees who may be a flight risk — and recommending pay rates, bonuses or other types of rewards using data rather than emotion.
By employing AI compensation and benefits technology, organizations can improve worker perceptions of fairness and equity and make progress to closing the gender pay gap. Technology is a viable solution to start the movement. With AI, companies big and small can increase pay transparency, decrease turnover and eliminate unconscious bias — all of which not only contribute to a better workplace, but a more equal society.