Uber Pool and other startups like Bridj and Leap talk about using technology to match carpoolers who want to avoid the hassle of congestion, but the Atlantic’s Eric Jaffe reports on smart mobility consultant Steve Raney of Cities21‘s recent thought experiment: “Suburban Ridematch Needle in the Haystack Problem.”
Raney’s assumptions and conclusions:
- You have 10,000 people working in downtown Palo Alto.
- A zipcode in nearby Redwood City with a population of 31,500 residents is home to the largest share of commuters who work in downtown Palo Alto:500.
- If 10 percent of these commuters were willing to carpool to work, as per national averages, then the demand for a ride-share service is at most 50 people a day. (And that’s a generous assumption, since the vast majority of carpoolers are family members or coworkers, as opposed to complete strangers.)
- If all 50 of these workers keep normal hours with standard morning commutes—again, a generous assumption—then they would all head to the office in a two-hour window. But since not everyone leaves for work at the same time, that window should be broken up into segments. Raney uses six 20-minute segments for the two-hour peak commute period.
- The six segments turn Redwood City’s 50 potential ride-share users into groups of about eight. In other words, eight out of 31,500 people in Redwood City might be matched for a carpool into downtown Palo Alto on any given morning.
- If there are even just two competing ride-share services, that number halves to four out of 31,500.
Can a startup work with essentially zero percent of its market?