It’s no secret that data is pervading every aspect of our work and home lives. Data is at the center of many global conversations, touching everything from elections to the nature of privacy and the shape of work.
As with most topics, there are multiple sides. On one hand, fears of automation about AI and machines have prompted many thought-provoking articles and books such as Only Humans Need Apply, while documentaries such as The Great Hack focus on how data pervades our lives via social media.
From the other perspective, data for good is a real movement, bringing the public and private sectors together through efforts like the Private Sector Roundtable and NGOs like C40 Cities, which is using data to help the mayors of the world’s largest cities address climate change issues.
The one constant is a sense of inevitability. IDC is forecasting a tenfold increase in worldwide data by 2025, and data is now regularly discussed as the driver of the fourth industrial revolution and referred to by some as the second language of business.
The underlying thread I see in all these areas is the need to increase data literacy.
As defined by MIT, data literacy is "the ability to read, work with, analyze and argue with data." As the nature of work changes, our skills need to continually evolve to keep pace. Communities like the Data Literacy Project, which my company is a founding member of, have emerged to offer free courses and resources to help anyone start or make progress on their data literacy journey. Gartner and others are heavily discussing the role of data literacy’s measurable impact on corporate performance. And the need to close the data literacy gap is now on the radar of C-level executives like never before, with market leaders like Amazon announcing upskilling pledges. This is all encouraging to see.
I recently spent some time with MBA students and faculty at Montclair State University, where I serve on the foundation board. As we spoke about the need for data literacy, something became clear: Although they had training in basic economics and accounting and grew up as digital natives, even these advanced students were just learning what it meant to be data literate.
It made me wonder if we’re preparing our youth with the necessary core data-related skills — both technically and in the softer skills such as communication and analysis — from an early enough age to succeed. Do we need to rethink some of our beliefs about the design and role of education? Do we need to explore how to invoke data-related thinking at an earlier age for students? Two recent news items show I’m not alone in asking these questions:
• On a recent Freakonomics podcast, Steven Levitt suggested that the math being taught in American high schools is outdated and should be replaced with real skills such as data literacy and data fluency. Steven discussed how the SATs have recently been updated to include questions related to basic statistical concepts and data literacy. According to the podcast, "Twenty percent of the SAT math questions test data fluency; and, amazingly, 10% of the questions on what used to be the verbal section are data questions also. A decade ago, those numbers would have been close to zero."
• E-learning leader Pearson just released its first Global Learner Survey. The survey outlines eight key trends Pearson is seeing. For example, the days of having a 40-year career are gone; digital and virtual learning will become commonplace over the next 10 years; the next generation of workers no longer believe that a college degree is a requirement before entering the workforce (supported by a recent survey by our company that highlights how employers are looking for skills over degrees); and, most alarming, the general public no longer has confidence in our education systems.
I think there are a few contributing factors to these findings and trends around core topics like the SATs and the nature of education. While we’ve seen a significant investment in STEM education and initiatives like coding for kids that are making education more digitally focused, base data skills and knowledge seem to still be missing from the core curriculum.
There is also a need to change the perception of data from a heavy algorithmic/data science discipline to one that’s applicable for everyone. Demystifying data in early education and making it relatable to learners' everyday lives can be an entry point into creating a data-literate foundation, with math courses tailored to this more real-world application.
Being more data literate from an early age will equip youth with skills that are applicable to work, but also to life in general in a data-driven world. Understanding data, when blended with core communication and analysis skills, can spur curiosity. Curiosity can lead to further questions, which then helps develop an understanding of data-related outcomes, which naturally leads learners to being able to draw more complete conclusions.
This is a global issue. If data literacy becomes more integrated into overall school curricula, countries will start to develop a generation of higher-performing, innovative and skilled workforces across the public, private and nongovernment sectors. This will ultimately enable economies and society to thrive and develop. It’s vital that we take the need for data literacy seriously, not only for corporate performance, but for the health and success of our continually integrated and data-driven world.