Human Behavior2 July 20262 min
What problem is Waymo actually solving?
This was a discussion I had this weekend in Austin, Texas with participants who were looking to find a unique and prevalent problem to build their business around. I repeatedly mentioned that we need to spend most our time identifying, validating, and iterating the problem statement ahead of moving to solutions.
Now, when you talk problems, you can’t assume that each archetype has the same problem. That’s where stakeholders and client profiles come in
Riders: Car shortages leaving you stranded when it matters most
Those who can't drive: No license leaving you without independence
Walkers & cyclists: Getting hit by drivers who don't see them
Communities: Drunk and reckless driving putting everyone at risk
Drivers: Impaired drivers causing accidents on the road
One insight from the workshop is that we all carry our own biases and therefore may miss critical design elements that make a truly brilliant solution: One female participant stated that Waymos provide a safer ride because being 1:1 in a car with a stranger at night was not the most comfortable feeling in the world. The constant need for mobility solutions brought daily fears to her life, which Waymo directly solved. Wow – I didn’t consider that!
This brought me back to a TedTalk I saw about the design of bathrooms – if a female is involved in the design process of a building, the structure of female bathrooms is adapted to the needs of a female, and not identical to those of males.
Group diversity and deeper root cause thinking matter more than ever in today's accelerated AI world.
Now, innovative solutions don’t come without their own challenges. My Waymo ride to the workshop encountered some problems. The Waymo got confused about where it was taking me and it went the wrong way down a drive thru of El Tacorrido and insisted to drop me off there. I was nearly late to my meeting because I had to walk the rest of the way, but I laughed hysterically in the moment. In fairness, I love tacos, so maybe the algorithm is getting so good that it knew what I wanted before I did…