Researchers Examine Bias, Salary Benchmarking
Two recent MIT IDE seminars focused on gender inequality at startups and labor market salary tools
By Paula Klein
Is there data to show that female entrepreneurs face discrimination? Will salaries be more competitive if they are aggregated among employers? The answer is ‘yes’ in both cases, according to speakers at the IDE’s fall seminar series. At two recent sessions, researchers addressed inequalities resulting from AI and platform models, and also how data analytics can advance business goals and help employees.
In a one seminar, Rem Koning, Assistant Professor in the Strategy Unit at Harvard Business School, presented data from a prominent online platform for launching new digital products documenting that sampling bias discriminates against female entrepreneurs.
Koning defined the bias as “the difference between a startup’s target customer base and the actual sample on which early `beta tests’ are conducted.” The bias “has a systematic and persistent impact on the venture’s success.”
Gender Matters
Specifically, “products with a female-focused target market launching on a typical day, when nine in ten users on this platform are men, experience 45% less growth a year after launch than those for whom the target market is more male-focused.”
On days when there are more women beta testers on the platform — reducing the amount of sampling bias for female-focused products — the gender-performance gap shrinks towards zero, according to his research.
While not surprising, the experiment was able to measure the gender bias of online tech platforms to drive home the huge need for improvement. Koning hopes to alert algorithm designers to the problem so they can do a better job going forward.
Corrections will not only boost female entrepreneurs and their funding, but will lead to better product offerings for consumers, he said.
Watch Koning’s seminar presentation here.
The Case for Salary Transparency
On December 6, another speaker from Harvard Business School, Zoe Cullen, Assistant Professor of Business Administration, talked about the effects of salary benchmarking on the labor market. “While U.S. legislation prohibits employers from sharing information about their employees’ compensation with each other, companies are still allowed to acquire and utilize aggregated data provided by third parties,” she said. Most medium and large firms report using this type of data to set salaries — known as salary benchmarking — but little is known about the effects of this practice on employees and employers.
Cullen’s research examined the actual effects of these tools by using administrative data from ADP, one of the leading providers of payroll services and salary benchmarks. The evidence suggests that salary benchmarking has a significant “compression” effect on salaries and is used by employers to set market wages that allow them not to overpay, or underpay, employees. Firms with access to the benchmarks, therefore, adjust their salary offerings in line with competitors. Rather than creating unfair practices,
Cullen concludes that using the benchmarks boosts competition in a positive way and may yield increased salary and better retention for lower-skilled workers.
Watch the seminar video here.
