We have reached the tipping point in big data. We can now access, manage and manipulate massive amounts of data with such ease that the real work has shifted to analysis and practical applications across industries. This new discipline, called data science, will not be exclusive to the male-dominated computer science profession, and a tidal wave of opportunity will arise for women.
The world of finance, of course, has benefited greatly from data and data science, but most of the action in big data has been reserved for computer scientists. Right now, there are fewer women graduating with computer science degrees than in the 1980s. Nevertheless, as we move from big data to data science, doors will open for more and more women.
Women now make up 40 percent of graduates with degrees in statistics - that's a good indicator for women in an environment increasingly obsessed with data. As we've seen with most technologies, the code is eventually abstracted away from the user and the dirty work of putting the tech to use in real business situations begins. Women no longer need to be expert coders to get in on the data science game.
If you have any doubt that women are moving quickly to capitalize on this trend, I encourage you to look at today's Women in Data Science conference at Stanford University (livestreaming here), which is an unequivocal show of strength for women in the field. It's hard enough to find a woman at most technology conferences, and I've been to quite a few; yet, this data science conference managed to fill out the audience and speaker list exclusively with women.
So where does this trend go next?
Data Will Meet Women Where They Are
There has been exhaustive discussion of the underrepresentation of women in technology over the past 10 years, but the solution can't simply be to enroll more women in university programs. The more direct path to empowerment has just as much to do with applying data science across industries.
Consider the impact that data could have in female-dominated professions. Women are well represented in health care and education, but they also have higher rates of senior management positions in hospitality, professional services and the food and beverage industry.
Each of these industries is well suited to reap the benefits of data science. My own experience in the health and education worlds confirms as much. We are using data to get better drugs to market faster and to personalize treatment plans. In education, we're using data to better assess and tailor learning across the world while simultaneously getting a clear view of teacher performance across entire school districts.
The benefits in data-driven decision making in business and administration, which is the most popular degree among today's female graduates, are well-documented. Data science is already making its mark from sourcing and supply-chain management to HR and customer-experience management. But it's also about second, third and fourth most popular degrees among women, whose respective fields could all see transformative change if women brought data science into the fold.
While women have a strong presence in these roles and industries, competency in data science will help to fast-track their path to senior-level positions and equal pay. They already own the expertise and experience in these positions; data science merely shatters the glass ceiling between them and the C-suite.
Data will amplify the social impact of female leaders
While data science will create career opportunities for women across the globe, it's perhaps more important to talk about the opportunity it creates for women to have a larger impact on the world.
Today, women make up 75 percent of the nonprofit workforce. The number is even higher among social workers, where women make up 82 percent of the total. These careers rarely offer the financial benefits available in the for-profit sector, but women choose them anyway.
For some, this may seem like a poor use of the earning potential of more than 50 percent of our college graduates, but most women would beg to differ. Female entrepreneurs are more likely to use business as a vehicle for social or environmental change, and they are 1.17 times more likely to create social ventures than men. A Georgetown University study revealed one potential driver of this trend: Women are the biggest believers in supporting causes.
As data science goes mainstream, these women will be armed with tools that help them make a bigger impact on our world.
Consider the collaboration between DC Greens and ClickMedix, where data science made it possible to get more low-income residents of Washington, D.C., access to fresh produce through a new voucher program. Their success in D.C. is now a blueprint for efforts in cities across the country. Both organizations were founded by women that put causes first, and data was the force multiplier for efficacy.
This is what I expect to see across the globe in the years to come. Female entrepreneurs are already leading the charge for social change. When you're solving complex, multifaceted problems, progress can be slow, but big data accelerates the process - insights come faster and decisions are more precise.
Most importantly, women capable of fostering sweeping change will wield disproportionate leverage in our politics, business communities and economy.
Bias, Meet Truth
Assuming women are able to capitalize on the opportunities that data science creates, there's still the challenge of retaining their position at the highest levels of a business. A recent study from the Rockefeller Foundation found that when a company is failing, female CEOs are blamed for poor leadership far more often than male CEOs. The contrast was stark: 80 percent of news stories blamed the female CEOs, compared to 31 percent for men.
I'm encouraged by big data because it will not only empower women, it will level the playing field in the C-suite.
Studies have proven that companies with more women in the C-suite are more profitable than those with fewer women. Other research has shown female CEOs in the Fortune 1000 outperform the S&P 500 over their tenures; yet, only 5 percent of the Fortune 1000 companies have female CEOs, and the "double bind" problem for female leaders persists even today, according to research from Catalyst.
In the near future, the double standard women face in the workplace will wane as adoption of data-driven decision making grows. Gone are the days of trashing a female executive for her "leadership skills" without taking a closer look at her personal and financial-performance metrics.
For that very reason data science doesn't just help women advance their careers, it secures their footing at the top. The result is better-performing businesses, accelerated social change and a global economy that works better for all of us.