linkedin gender companies female employees estimates male

Women in Tech: A Study on the Gender Gap in 50 Tech Companies### LinkedIn ad targeting dataIt’s quite simple to pull data on the female and male employee estimates forcompanies.First, we created a draft text ad to use as a placeholder to get to theaudience targeting tool. Targeting data is available without purchasing orpublishing an ad.For each company, we found the estimated number of the: * Total company workforce on LinkedIn. * Female employees of each company with LinkedIn profiles. * Male employees of each company with LinkedIn profiles.Data for this study was collected Feb. 28-March 1, 2017.### A massive data setLinkedIn ad targeting gave us a much larger sample than used in most corporateresearch we’ve come across.For the 50 companies in the study, LinkedIn ad targeting could determinegender for roughly 1.839 million employees. (We arrived at this number byadding together the total male and female estimates for all 50 companies.)### First name inferenceLinkedIn states that gender is “inferred in English from first name ofmember.”This practice is not unique to LinkedIn. While companies use a variety ofmethods to identify gender at scale, first name determination is a common one.Solutions such as Genderize.io , GenderPredictor , SexMachine and Beauvoirrely on first names to identify gender.Initially, we were concerned that there could be a potential bias towardassigning gender to predominantly English names. But when we checked ourresults against recent diversity reports, the targeting data was pretty closeto the reported gender ratios. For this reason, we did not investigate Englishname bias further for this study.### Finding the dataThough LinkedIn gives several options for ad audience targeting, we usedcurrent company and gender.LinkedIn gives audience estimates for total workforce, male employees, andfemale employees rounded to the nearest thousand.For example, the target audience of female Facebook employees on LinkedIn wasestimated at “5,000+”. We used the number 5,000 as the female employeeestimate for Facebook in our study.Here’s an example of gender information provided by LinkedIn ad targeting. Inthis case, we narrowed the ad audience to female Facebook employees.## Companies in our study had to have 1000+ employeesLinkedIn gives the message “your audience is too narrow” when it estimates anaudience to be less than a thousand. That is why we only included companieswith thousands of employees in this study.We did not include companies in our study that had an estimated female or maleworkforce of less than a thousand. In such instances, LinkedIn generates themessage, “Your audience is too narrow.”## Gender unknown profiles and ratiosWe also considered how the total male and female estimates compared to thetotal company estimates on LinkedIn.Of the 50 companies we looked at, male and female estimates represented anaverage of 82 percent of the total company estimates on LinkedIn. Meaning,LinkedIn could not determine the gender of an average of 18 percent of thecompany’s employees with LinkedIn profiles.Since female employee estimates were drastically lower than male estimates formost of the companies we looked at, it was unlikely that the names LinkedIncould not assign a gender to would significantly alter the male/female ratioin all but a few instances. For example, Concur and SAS.Of the 50 tech companies in our study, Concur and SAS had the highestestimated percentage of female employees in their workforce.Concur was the only company to have equal male and female employees estimates,though LinkedIn was unable to identify a gender for 20 percent of the Concuremployees with LinkedIn profiles.Concur and SAS were two of the few companies in our study where the percentageof employees that LinkedIn could not assign a gender to could change themale/female ratio in a significant way.It’s worth noting that all the names that LinkedIn could not determine agender for would have to be women for SAS’s workforce to be 50/50 male/female.## Women are still a minority in major tech companiesHere are some of our findings: * On average, women represented 24 percent of their workforces. Men represented 58 percent of their workforces on average. An average of 18 percent of the workforce was gender unknown. * Women made up only 20-30 percent of the workforce for most of the companies we studied. * Not one of the companies we studied had 50 percent or higher estimates for women in the workforce.According to LinkedIn ad targeting data, women made up 20-30 percent of theworkforce for most of the companies we studied.Gender unknown LinkedIn profiles could shift the male/female ratios. However,in most cases, it is unlikely the change would be drastic unless all theunassigned profiles were women.