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Closing the Gap: More women drawn to data analytics

Wednesday, March 2, 2022

Women in data analytics

Data analytics has impacted nearly every area of study at Krannert, and some of its best students are increasingly women, says Cara Putman, a clinical assistant professor of management and director of the school’s Brock-Wilson Center for Women in Management.

Despite closing the gap, women are still underrepresented in the field. Putman cites a 2020 study done by the National Center for Women in Information Technology showing that while women are 57% of the overall workforce, they still hold only 26% of computing and math occupations. Krannert is countering that trend with hands-on coursework, experiential learning opportunities, and an emphasis on career preparation.

“I think Krannert is well-positioned to help young women who are interested in STEM and the applications of it in a business context to be prepared to excel in the workforce,” Putman says. “Over the last couple years, we have been very proactive and intentional about not just thinking about what the current workforce needs, but how we can position students today for jobs that are coming in five and 10 years.”

Jiacen (Jessie) Liu, a senior majoring in applied statistics and industrial management, and fellow senior Hui (Vivian) Zeng, who is majoring in supply chain, information and analytics and industrial management, are among Krannert’s rising stars in the field of data analytics.

Liu and Zeng first displayed their analytics skills in the Fall 2020 Purdue Undergraduate Research Expo, then joined forces for the 2021 Crossroads Classics Analytics Challenge, taking home first place and a $3,500 prize. They also partnered for first place and $1,000 in the 2021 INFORMS Data Mining and Decision Analytics Workshop Poster Competition and placed second in the Spring 2021 Purdue Undergraduate Research Conference. Both are applying to graduate programs.

“Studying industrial management and applied statistics helped me build the essential qualifications for the data-driven supply chain management field,” Liu says. “Specifically, I appreciate the curriculum’s focus on building the hands-on skills for creating, validating and testing data analytics models to address complex, uncertain and dynamic business challenges. I also appreciate the program’s dedication to the development of soft skills, entrepreneurial mindset, and personal integrity.”

Zeng has been engaged in practical projects and research related to data analytics since her sophomore year. “Through my academic studies and project experiences, I have improved my problem identification skills, analytical skills, and modeling skills,” she says. “I am now comfortable with building statistical and machine learning models to deal with different kinds of analytical problems.”

Another standout business analytics student is Congyu Pu, who will graduate in 2022 with a bachelor’s degree in finance. A Summer Stay scholarship recipient, Pu took part in the Fall 2021 Undergraduate Research Expo and is currently applying to grad schools with data analytics programs. She credits not only the hard skills she’s developed, but also the team environment at Krannert.

“By working with people from different backgrounds, I get to learn from them and share thoughts from different perspectives,” Pu says. “That makes me a more valuable contributor.”

Vinni Guan, a senior studying marketing, has also made her way into the data analytics field. “I found my projects related to data to be very interesting, as I was doing more than just analyzing the skills and strategy of a company,” she says. “I applied the methods, models, and codes I have learned to an actual dataset, then came up with my own insights after I found the relationship between those factors. Those are skills that can help us solve problems.”

The four students agree that although data analytics has typically been thought of as a field for men, women are beginning to make their mark. “In almost all the data analytics classes I have taken, I have been the only female in my project group,” says Pu. “However, the people I know who put in hard work, fight for opportunities, and have been successful in these classes are female.”

Guan says some of the best students in her data analytics courses are also female: “They are hardworking, pay great attention to detail, and spend a lot of time thinking of different ways to solve a problem.”

“We need more women in data analytics,” adds Liu. “I think the current landscape is rich with opportunity, regardless of gender. Many young women I meet just lack a bit of confidence and need a little nudge to believe in their abilities.”

Zeng believes women in data analytics actually have a skill advantage. “As a female, I am confident that I can capture both the overview of the problem and the small details that may affect the overall outcome,” she says. “I act as a leader on many of my group and research projects, and have also met a lot of excellent female leaders in this field.”

Another thing that Liu, Zeng, Pu and Guan have in common is their mentor — Matthew Lanham, a clinical assistant professor of management who teaches Krannert's suite of data analytics courses and serves as associate director of student engagements for Purdue's Krenicki Center for Business Analytics & Machine Learning.

“I recall my final project in MGMT 474, Predictive Analytics, in which my team completed a hands-on research project and presented our research findings at the Purdue Fall Research Conference,” Liu says. “Professor Lanham mentored us to perform data mining, build predictive models and provide insights for this real-world business problem. He inspired me to not only think critically about the course subject matter, but also began leading me towards a career path in business analytics.”

“I am so grateful to have Professor Lanham as my mentor,” adds Zeng. “He is supportive and always willing to help with coursework and projects. He also refers us to a lot of great opportunities such as the graduate-level industry practicum and other Krannert competitions. Moreover, the material he taught is so useful and practical. We are exposed to real-world examples that allow us to not only digest the course material, but also apply predictive analytics and different models in the business world.”

For Lanham, it’s about establishing a culture and expectation of students to showcase their work.

“What a pity when a student has invested so much time and effort to do something impactful, and they lack a coach to help them articulate that work externally,” he says. “Students should learn from these exemplars by being proactive and reaching out to faculty for analytics opportunities. Do not be shy. Many of us are here to serve and help develop you, with the promise that you will help others in the future when the opportunity arises.”