Ladies Who Tech: Fiona Fang on the Importance of Data Literacy

This article comes from Ladies Who Tech (WeChat ID: LadiesWhoTech), which aims to tell the stories of Beijing's burgeoning tech industry and the women behind it.

As China throttles forward in its economic development, a staggering amount of data has been produced by the latest generations. But while we have become expert creators of data, many of us don’t know enough about how to use the data that gets produced. We are, in effect, data illiterate.

But how important is it, really, to be data literate? Generations in the past have functioned perfectly well without the volume of data that we have now, nor the computing power to process all of it.

We spoke with veteran data scientist, Fiona Fang, about her rich experience at DangDang, Xiaomi, 360, VIPKID, and JingDong to find out more. According to Fang, data illiteracy can result in incomplete analysis, misrepresented and misleading insights, the weaponization of data to validate existing beliefs, and other gross misuses of data. The resulting misrepresentations in the media, in conversation, and in workplace decision-making processes, has ushered in efforts to become more data literate. But how? 

One thing is clear: data literacy is not only important for those who are crunching the numbers.

Well, as Nate Silver, founder and editor in chief of FiveThirtyEight says, “On average, people should be more skeptical when they see numbers. They should be more willing to play around with the data themselves.” And that is exactly what Fang did.

Few people know that Fang's career began in a marketing role in a traditional industry. She entered the workforce in 2004, when appreciation for leveraging data for business decisions in China was only beginning to emerge. At the internet companies where she worked, she observed that data was increasingly relied upon for decision making. Companies were also investing in the infrastructure to collect data and hiring people with data analytical skills. She further realized that she had a knack for analysis and that by beginning in the marketing department, she had the advantage of understanding how to leverage data to produce insights that would be impactful to the business.

These observations became the springboard for Fang's pivot into data science and statistics. Across e-commerce, hardware, and education industries, Fang has identified key success factors in the relationship between data scientists and analysts and their business partners. One thing is clear: data literacy is not only important for those who are crunching the numbers.

For those studying and working in data, Fang recommends voracious curiosity about the business you are serving, and a deep understanding of the methods and theories used to derive insights.

Data analysis is a means of seeking the truth and learning to welcome its ability to help you make the most effective decisions.

On the other hand, for running business units, building products, and making critical business decisions, upskilling your data skills is the key to making sound decisions that are validated to create greater value for your company. Abstracted from Fang's relationships with many business partners are two key skills that are a prerequisite to using a data team effectively for data-driven decision making. In laymen’s terms, you need to know how to break down requirements and processes and what to benchmark the data insights to. The former allows you to articulate what you are trying to measure, effectively guiding the way that insights will be derived from raw data; the latter ensures that you can recognize a significant result when the data shows one. Data analysis is a means of seeking the truth and learning to welcome its ability to help you make the most effective decisions.

And indeed, Fang's experiences showcase the immense amount of value that can be created when business analysts and operators come together to make data-driven decisions. At one company, Fang's analysis and insights were used to support business leaders to make an enormous decision about the smart hardware that was being developed. When the analysis began, the leaders saw the losses of the business unit and hoped that it would turn around eventually. By robustly analyzing the return on investment of their research and development, the team was able to adjust its strategy. In an industry and space where margins are usually razor thin, or even operating at a loss, this business unit now turns a profit of RMB 10-50 million annually.

READ: Cutting Edge Capital: Beijing Ranked World’s Fourth Most Innovative City

Image: Luke Chesser (via Unsplash)