There are hundreds of thousands of new job opportunities unfilled because they require a higher level of STEM-related skills than what most job seekers possess. Along with science, technology, engineering and math, there is an under-recognized skill: data literacy.
In our technologically accelerating world of real and alternative facts, where numerous people construct their news to fit their views, to successfully navigate as individuals some form of data literacy is imperative. This is not to say that we should turn everyone into data scientists, but the increasing impact that big data is having on our lives means everyone should at least be informed about data—how it works, how to read it, who owns it and how it is generated and used. This especially true for experiential designers.
Where data literacy falls on the spectrum from data conversant to data scientist depends on need. As experiential designers, there is a need to be at least conversant with data. That means having some understanding of how data can be gathered, stored and applied from various types of sensors and devices like traffic cameras, satellites, motion and touch sensors, digital wayfinding, mobile apps and RIFD tagging systems.
We need to know about these methods not only because our clients are using data in new ways, but because technology trends like the Internet of Things, machine vision, personalization, artificial intelligence, interactive media experiences and self-driving cars are rapidly changing our markets. For example, self-driving cars do not need the same type of wayfinding that humans do.
Another compelling reason for data literacy? As our client base is going digital, they challenge themselves to think several years out about different business models and consider whether they're disruptive enough. Our clients are in a rapidly increasing digital transformation where the creative-destructive process of going digital happens fast. To companies, this means entirely new ways of engaging with customers and doing business. For retail, museums and visitor centers, going digital means offering relevant, personalized experiences rooted in data from multiple channels.
Behind all these new types of experiences, trends, services and products are data—big data. Big data is still a language of power. The ability to parse and communicate data into accessible forms will continue to be invaluable throughout the 21st century—in the workplace, public spaces, education, emerging smart cities, politics and policy and compelling personal journeys.
A vast array of government programs, research labs, private firms and universities are developing applications using big data, while commercial, retail, cultural and educational organizations are starting to incorporate data-driven experiences into their processes, services and programs. Many cultural institutions struggle to develop usable and successful data-driven experiences. Very few institutions are focused on data literacy. Too often institutions believe that data literacy should remain in the realm of the data scientist. Perhaps they fear the content is too dry to be enjoyable for audiences.
So how can we make data literacy exciting, useful and widespread? There are many challenges to growth in data literacy. Data is complex. It exists in diverse forms and is designed for different levels of expertise. And, in many cases it is dry as toast.
Big data software is also exceedingly complicated. Accessing and sustaining live data feeds, storing data, obtaining permission for data use, and having data in a form people can understand are also challenges. Organizations that want to use data and do not typically handle it—like visitors centers, retail locations and museums—simply don’t have the infrastructure to support data literacy.
Just as the Depository Trust & Clearing Corporation sits at the center of stock trading and is where all stocks settle, there is a need for a central custodial organization that help would make data literacy flourish. This organization could facilitate and create a shared learning resource through the technology, tools, information and applications for data literacy.
Having a shared resource would allow other institutions to use their own scarce resources to focus on higher-value programming, developing new types of content and programs with increased social impact and greater relevancy. And, it could be fun to become data literate.
Creative Destruction Series: Introduction
Creative Destruction Series Part 01: Palpitations on the Slopes of Technology
Creative Destruction Series Part 02: Designing for Plurals, the Evolving Audience
Creative Destruction Series Part 03: Relocating Humanity
Creative Destruction Series Part 04: A Curious Stepchild of Inbound Marketing
Creative Destruction Series Part 05: Automated Design
Creative Destruction Series Part 06: Embracing Serendipity in the Digital Age
Creative Destruction Series Part 07: Three Versions of "US"
Creative Destruction Series Part 08: 12 Strategic Predictions for 2017
Creative Destruction Series Part 09: The Mythology of Online Searches