Early thoughts My original interest in personal journey mapping stemmed from a desire to curate memorable experiences while traveling abroad. But the disconnect between mapping apps, content sites, and recommendation engines kept me mostly head down while exploring new cities.
My desire as a curious traveler, in addition to getting from A to B, was to experience some degree of serendipity and discovery between my destination pins. After I returned home, nothing was more frustrating than realizing I had missed a highly recommended shop or must-see sight one street over from where I had been simply because didn’t know it was there. The kick-me phrase “if only I had known” began to haunt me.
After several years of building a huge wayfinding library of map pins and travel apps, I stumbled upon the book “Wayshowing” by Per Mollerup, a famed Danish designer. In the book, he redefined the term of designing user-led journeys from wayfinding to wayshowing—essentially redefining the design process. He described the difference between the two as: “Wayshowing and wayfinding relate to each other like writing and reading. Wayshowing precedes and enables wayfinding.”
The book, originally published in 2005 and updated in 2013, only briefly addressed the use of technology, mainly highlighting screen-based mapping. Despite Per Mollerup’s new spin on wayfinding, I found the concept of wayshowing still primarily rooted in orientation-based design.
By 2016, mobile apps were starting to unlock new ways to access and reveal information based on geolocation, time of day, personal preferences, etc. Digitally-enabled journeys, I wondered, should be less about showing and more about knowing. No existing design terminology seemed to accurately account for that, and the term Wayknowing was born.
AdAge Having developed human-centered journeys for clients at my former brand agency, Eleven, I was asked to submit an article to AdAge for their DigitalNext column.
The first public reveal of this notion was published in 2016 in AdAge with the now-cringy title: ‘Wayknowing’ is the Smart future of Wayfinding - Next Step for Spatial Problem Solving Is Integrating Real-Time Data with Directions.
SXSW Based on the AdAge article, I was invited to present my ideas on Wayknowing at SXSW in 2017. I wanted to ensure that the topic covered a complete interrogation on urban mobility so I invited Kinder Baumgardner, a Managing Partner at SWA Group, to join me as a co-presenter. Kinder provided a valuable urban and architectural design lens to the session topic.
The original program description read: Wayknowing: The Future of Getting from A to B ”As cities modernize and begin to publish and share more urban data, there is a growing need to interpret all that digital exhaust in more relevant ways. Smarter wayfinding, open public data, and conversational Al technologies are now converging and hold the promise to knit together more complex, intelligent ‘wayknowing’ journeys.”
Expanded application Originally coined to describe urban wayfinding, Wayknowing can also be applied to consumer journeys that connect online and offline experiences. For example, consider how the pandemic forced new behaviors, expectations and processes via online store pickup orders. From your first email confirmation to text reminders, directions, and arriving at a numbered parking spot, we’re now better informed at every step.
At its core, Wayknowing is based on human-centered design—it should anticipate needs, wants, and desires. Over the years, I have applied the fundamentals of Wayknowing toward consumer-led brand journeys for clients. Since 2014, I have helped lead experience design initiatives for clients ranging from Chevrolet, Dignity Health, Pella, Google, and San Francisco International Airport.
What it isn’t The term is not intended to describe how much Big Tech companies “know” about us—which is already too much for most people. Nor is it intended to describe the economy of surveillance capitalism as identified by Shoshana Zuboff in her book The Age of Surveillance Capitalism.
Wayknowing disciplines and practices should ideally leverage the data we all generate to our own advantage versus simply feeding more surveillance data.
