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Forbes: Why Big Data Is Failing Women In STEM And How To Fix It

Lessons For Women In Tech, From 25 Years As A Female In R&d At Progress

This article was written by Joan Michelson and published by Forbes. The article features insight from SWE’s Senior Manager of Research, Roberta Rincon, Ph.D. You can view the Forbes article here.

Walmart can tell you how many of anything are in a given store or warehouse at any moment. Apps track your heartrate and your phone tracks your location at any moment. C-suite executives monitor everything in their organizations daily. Big Data dominates our economy. Yet, we don’t have consistent, standardized and real-time data on the jobs driving that 21st century-Big Data economy: science, technology, engineering and math (STEM). Especially for women.  In the labyrinth of sources, the government’s Bureau of Labor Statistics (BLS) data seems to be the most detailed, but it’s relative; it’s not even clear exactly which jobs they include.

“Where data comes in is to put greater pressure on educational institutions and on employers to monitor what they’re doing and be held accountable if they lose women, if they keep losing women, or keep not getting women in the first place,” Ariane Hegewisch, Ph.D., Program Director Employment & Earnings at the Institute for Women’s Policy Research, told me. She added that it’s important to see the racial data as well, because, “it does impact women of different racial and ethnic backgrounds very differently.”

The devil’s in the definitions: “There is no standard definition of a STEM occupation.”

A big part of the problem is defining these jobs. The BLS lists all occupations and you need to mine their breakdown to find what you want. The BLS defines STEM jobs as: “Science, technology, engineering, and math (STEM) occupations include computer and mathematical, architecture and engineering, and life and physical science occupations, as well as managerial and postsecondary teaching occupations related to these functional areas and sales occupations requiring scientific or technical knowledge at the postsecondary level.”

Using this definition, women made slight gains in computer science jobs in 2020, from 24.9% overall in Q1-2020 to 25.1% by Q4-2020, based on unpublished data the BLS sent me. A BLS spokesperson wrote me that unpublished data, “may contain estimates that do not meet CPS publication standards,” for quantity of people in a given job. Roberta Rincon, Ph.D, Senior Manager of Research at the Society of Women Engineers (SWE), told me it could also be because the BLS uses sampling surveys, so it’s not counting every job.

Rincon explained that different sources use different definitions. For example, she said, “are you going to count engineers as people who graduated with engineering degrees, or are you counting them because their job title is ‘engineer’?” Then there are people who work as engineers but don’t have either a degree or such a title.

The largest organization for women in technology, Anita, did their own study on “women technologists” in late March/early April 2020, before the pandemic really hit, and got different data than the BLS for comparable jobs in Q1-2020. Anita defines “women technologists” as: “technical jobs in computing and information technology, including technical management and technical leadership. We do not include scientific positions in this that are unrelated to computing and information technology (ex: civil engineer, biologists, etc.).”

Catalyst, the 59-year-old nonprofit focused on advancing women in the workforce that compiles a wide range of data from around the globe, defines STEM this way: “’STEM’ refers to the fields of science, technology, engineering, and mathematics. There is no standard definition of a STEM occupation… [for them] STEM incorporates professional and technical support occupations in the areas of life and physical sciences, computer science and mathematics, and engineering. Less agreement has been made on the inclusion of educators, healthcare professionals, and social scientists in STEM; therefore, these occupations are not covered here.53

STEM drives the 21st century economy, so here’s what we need to measure these jobs:

Any business leader will tell you that investment and accountability follow measurement.

Jobs data is reported every month, including demographic data, which is how we know that all the jobs lost in December 2020 were held by women and all the job gains then were made by men.  Many companies collect diversity and jobs data and review it internally, but don’t want to release it publicly, “because it doesn’t always make them look very good,” as Rincon put it. But, she added, different sources collect and report data on gender differently, and others lack the resources or incentives to either collect or report it.

“So, unless you have an organization like the government who is telling them, ‘this is what we want you to report and this is how we want you to report it and this is how we’re defining it,’ then you have apples and oranges in some cases,” SWE’s Rincon explained.

Therefore, since STEM jobs drive the 21st century economy, and leaders need to be accountable for diversity, we need:

(a) A standard definition of STEM jobs, to include educators, healthcare professionals, and people who work in related roles, such as Chief Sustainability Officers, or in communications and finance roles in STEM fields, such as in electric vehicles, energy companies, or vaccine development;

(b) Tracking systems befitting the 21st economy that provide accurate, consistent data for these roles on a timely basis; and

(c) An organization like the government demanding this data, and providing standards for it and for reporting it.

These systems also need to be adaptable as the economy evolves. For example, new roles are being created across the economy as climate change, diversity and related initiatives, such as environment-social-governance (ESG) investing, take center stage in the 21st century economy.

If we want to hold business leaders and policymakers accountable for advancing women in STEM jobs – and to train our workforce according to market needs – we need consistent, timely data. Big data needs to step up.

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  • Joan Michelson

    Joan Michelson is a career coach, dynamic public speaker and host of the acclaimed podcast Green Connections Radio with women innovators making an impact.