Closing The Gender Gap in Big Data and Analytics
It’s well known that the burgeoning field of advanced analytics will impact business. The Big Data Analytics (BDA) market, which is expected to exceed $225B in the next several years, is a primary driver of job opportunities according to the US Bureau of Labor Statistics and LinkedIn.
But advanced analytics, Machine Learning (ML), and AI will materially shape every aspect of our lives – from business innovation and government policies, to the environment and our health and wellbeing, according to Mary Purk, the Executive Director of Wharton Customer Analytics and AI for Business, who is co-chairing the third annual Women in Data Science (WiDS) Philadelphia @ Penn Conference on February 9-10.
“It’s easy to characterize big data and AI as a technical field, when in fact it is highly interdisciplinary in nature and impacts almost every aspect of our lives,” says Purk. “Our WiDS 2022 programming highlights real-world examples of how big data and analytics are creating change in areas as wide ranging as designing the customer experience, managing risks, developing a more equitable future, improving healthcare, and accelerating R&D.”
There is a lot of investment and energy going into building AI and analytics technologies. Global venture capital investment in AI-focused startups has grown twenty five fold in the last decade to $75B, according to an analysis by the Organization for Economic Co-operation and Development (OECD).
Today much of this investment is focused on a relatively concentrated set of technologies, use cases, and industries. Right now these VC dollars are going into driverless cars and mobility (25%), healthcare, drugs, and biotech (16%), and business process transformation (11%) according to the analysis. And in business, the top use cases are in product development, customer service optimization and experience design, and risk modeling according to research by McKinsey.
That investment is going to quickly expand to other industries ranging from transportation, logistics and construction to retail, telecommunications, and financial services. “Data analytics is going to be like digital: everyone’s going to need to have a base level of it,” according to Bhushan Sethi, who leads PwC’s People & Organization practice at a forum hosted by Wharton Customer Analytics.
The problem is for all the energy being put into the technology, there is a less clear picture around the investments in talent.
To meet this rapid growth, the world will need more workers with STEM skills overall, particularly in the fields of data science and advanced analytics, where demand for talent is high, salaries are growing, and future job growth is skyrocketing.
Sparked by the internet, and accelerated by an explosion of data from devices, products and systems – demand for data scientists in the job market has grown 15-20 fold in the past several years, according to Allen Blue, the co-founder of LinkedIn. Data science and machine learning-related jobs, taken together, represent five of the top 15 growing jobs in America across a widening range of industries that include software and high-tech but also education, marketing and manufacturing.
There are not enough young people overall moving into these fields, despite the potential for high paying jobs, rewarding careers, and the ability to make a big impact. This is particularly true when it comes to young women. When viewed as a resource, industry is severely underutilizing women in data science, according to Cornelia Lévy-Bencheton, author of the book Women in Data.
Women make up 57% of undergraduate students and 60% of post graduate students, but only 35% pursue studies in STEM fields. Women represent 56% of the US workforce but only 25% are in technology jobs. That number falls to under 20% when it comes to data science fields, according to a study by BCG. These young professionals have relatively few mentors and role models. Only 17% of C-suite technology leaders and 15% of Chief Information Officers are women according to Levy-Bencheton. While women are making some inroads into aspects of the profession (for example, 45% of market research analysts are female), there is a big gap to fill.
Just as the ability to access computers and the internet has become increasingly important to participating in the economic, political, and social aspects of life – analytic skills increasingly define our careers, opportunities, policies, and even our health and our communities. A ”data-divide” in big data is emerging on social, economic, and gender lines according to Mary Purk at Wharton Customer Analytics. “Any conversation about the future of business analytics and data science, in any field, must include gender representation,” says Purk. “First, because we need more data scientists, but more importantly, we need a diversity of viewpoints to effectively solve problems with data.”
Business leaders echo this sentiment. “When it comes to analytics, diversity is less about good HR policy and much more about business impact,” says Julie Roehm, the Chief Marketing and Experience Officer who is leading the digital transformation of the retailer Party City. “In a world where AI and advanced analytics will be the primary drivers of value creation, the customer experience, operational efficiencies and innovation – the team with the most data scientists has an edge. The businesses with the most diversity of skills and perspectives will win.”
To Purk, and the professors and professionals hosting the WiDS event, it’s not just a matter of opening up new jobs and opportunities to women – it’s also about the impact analytics can have on our economy, society, and environment.
Having a diversity of viewpoints, skills, and perspectives is critical to the discipline of data science. While the creation of huge new datasets and tools are essential ingredients to create advances in AI, ML and advanced analytics, it’s the data scientists and business analysts that matter the most. The ability of humans to frame the problems to be solved and ask the right questions of that data is still the most critical part of turning analyses into innovations, insights, and solutions to solve the world’s biggest problems.
Gender diversity will have an impact, because as women enter the field and join data teams, the diversity of perspectives, frameworks, and knowledge will only further improve solutions, value, and speed of delivery. And the impact and profitability of big data analytics initiatives will only increase. In a world where 80% of big data professionals are men, and 11% of data teams are only men, more diversity of thought can only improve processes and expand our ability to capitalize on the enormous data assets being generated.
Skill diversity is also important, according to the University of Pennsylvania faculty. Skills are functional, but real-world problems are messy, and interdisciplinary. Data skills need to be incorporated into a wider variety of curriculum – from statistics to economics, biology, math, applied science, engineering, and robotics – and at every level (including middle and high school curriculum). 80% of future careers will require STEM-skilled workers and some foundational knowledge of computer science, according to Cornelia Lévy-Bencheton. But most US middle and high school students don’t take STEM classes, nor do they have computer science classes offered in their schools. As a result, new jobs in computer sciences are posted but remain unfilled.
Mary’s co-hosts at WiDS, Susan B Davidson and Linda Zhao, are professors of Computer and Information Science and Statistics and Data Science, respectively, at the University of Pennsylvania and Wharton. Davidson has introduced a Master’s In Data Science at the School of Engineering and Zhao has incorporated big data and ML into the statistics and mathematics curriculum. Other academics on the program include Tal Rabin, a professor in Computer and Information Science who researches cryptography, and Dean Vijay Kumar, who teaches Electrical Engineering and Applied Science, and researches advanced robotics.
Big data executives echo the sentiment that diversity is essential. “I believe that data and analytics are still in their formative years thus creating opportunities for the tech industry to capitalize on this to develop and grow towards a diverse workforce,” says Jeanine Charlton, the Chief Technology Officer of Merchants Fleet, who is at the vanguard of using big data to enable EV fleets and ultimately networks of driverless cars.
WiDS Philadelphia @ Penn reinforces the need for diversity in skills and the breadth of opportunities by profiling business and academic leaders in the fields that are likely to be most impacted by the revolution in big data – healthcare, customer experience management, and electronic vehicles and mobility.
So how can we bridge the gender gap in big data and analytics?
At WiDS, Purk, Davidson, and Zhao are advocating for a practical combination of mentorship, education, community, and awareness. These get at many of the root causes underlying socioeconomic and gender gaps in big data identified by an analysis by the UN Equals Research Group. While resources, skills, and access are some of the most pressing limiting factors contributing to the gender gap in big data and analytics, many of the causal factors involve more personal issues like confidence, aspiration, motivation, and participation. For example, most (74%) young women are interested in STEM careers when they are in middle school, but very few of them wind up majoring in computer science by the time they are high school seniors.
“We need more women to serve as role models to encourage young female professionals to feel confident that they can build a successful career in the data and analytics space”, says Jeanine Charlton, who has been feted as one of the leading Chief Information Officers in industry and one of the fifty most powerful women in technology. “I am passionate about this and have served as a mentor for over 25 years both inside and outside the companies I have worked for.”
To that end, the WiDS Philadelphia @ Penn conference features role models by highlighting leaders in business and academia from organizations like Amazon, CVS Health, Petco, PepsiCo and UnitedHealthcare. The conference’s keynote speaker, Michelle Peluso, Executive Vice President, Chief Customer Officer, and Co-President of Retail at CVS Health, is responsible for transforming CVS Health’s consumer experience, accelerating the company’s digital transformation, and leading the company’s marketing and branding teams. She will share her experiences on the front lines during the pandemic, using data to allocate resources to the people and institutions with the greatest needs.
The WiDS conference also features academics and business leaders who are sharing examples of how women are leading innovation in a wide variety of fields, ranging from customer experience and pricing optimization to risk management and fraud detection, to improving operational efficiency and resource allocation, and policy development.
To help build the community of data professionals and mentors, UPenn is hosting networking sessions on Mentorship in Analytics & Data Science Careers to provide attendees the opportunity to meet professionals and mentors in the field.