There is more information in one Sunday edition of the New York Times than contained in all the printed material in the 15th century.
The average person hears or reads over 90,000 words a day. For reference, the word count of To Kill a Mockingbird is 99,121.
We are swimming in data. Near-drowning in the information rich environments of our daily lives.
So how can it be, when it comes to data on women — how they go about the business of their lives, their spending power, the routes they travel, their health and safety — we know next to nothing?
Simply put, for millennia, we have seen “male” as the standard. The ramifications for data collection meant women were either collapsed into the same category as men (think drug trials up until 1990 and crash test dummies up until roughly 2004, both involving the male body as the universal norm) or not seen as especially relevant, as in the case of women’s transportation needs and uses, something less than a handful of cities across the globe measure and study.
In a day and age when one can determine in less than thirty seconds the global migration patterns of the Great White Shark — a relatively nascent scientific discovery in and of itself — we cannot find a definitive answer for the percent of consumer spending decisions made by women. Why? Because consumer expenditure surveys don’t disaggregate their data by gender. By race? Yes. Occupation? Yes. Age, geographic region, and pre-tax income? Yes, yes, and yes. But not gender. (Incidentally, this number is considered to be between 70–83%, quite a wide statistical berth.)
Good data is the foundation for good policy, good programs, good design. No one argues with this axiom. What does it mean when we have little to no data on 51% of the population? Can we look at the design of our physical places, our programs and policies with the same confidence?
You Cannot See (or Value) What You Do Not Measure
Obviously, we need more data. It seems almost strange to say as much in an economy wherein attention is increasingly the most coveted resource — a response to the glut of information and data in our markets. But when it comes to women — their perspectives, challenges, contributions, and lives — data is indeed in short supply.
Data is accounting. And accounting, in this instance, means to take women into account. To see them. To value them. To measure them so as to learn how best to move forward in designing worlds, both physical and systemic, more suitable to everyone.
Taking women into account in collecting and disaggregating data by gender is a very new enterprise, one we don’t currently tackle often or widely. The call for data specific to women feels simultaneously obvious and innovative and will surely spark conversations around design in a range of applications.
New Appreciation for the Data-Design Relationship
For now, understanding the need for data on women, their lives, and experiences also reinforces the relationship between data and design. Data collection is preceded by thoughtful design — the design of methods and instruments most suitable for collection — and is followed by the design of tools for data analyses. One can imagine the process as a water fountain with a series of cascading buckets. As one bucket fills and tips over with the water’s weight, the water flows into the next bucket, and so on until the water reaches the basin and is recycled to the top of the fountain where the process repeats.
This energy, momentum, and cyclical flow is one way to characterize the data-design relationship. Looking at the practice of design through the lens of valuing and seeing women allows us to find new appreciation for this synergy and apply it to creating better workplaces, neighborhoods, cities, programs, policies, and more — for women and in service to everyone.