SherpaShare: helping drivers make sense of their drives

With the buzz around Uber’s latest phenomenal, unprecedented, [add your superlative here] round of funding, it’s clear that the poster child of the sharing economy is here to stay. Yet, and there is always a yet, while Uber is flying high, the workers in this sharing economy aren’t doing as well. Earlier this year, the Washington Post talked about the investment that drivers had to make to be Uber drivers and Forbes wrote about what happens when the non-employees in sharing economy works are injured on the job. All of a sudden, it turns out that even if drivers are earning Uber’s average rate of $19 an hour, it may not be enough to cover their investment and risk.

Analyzing income on the SherpaShare dashboard.
Source: SherpaShare

Enter SherpaShare, a free service that helps drivers analyze their drives and help them make changes that could lead to more income. SherpaShare offers a dashboard that automatically analyzes income from the different services and allows couriers/drivers to factor in expenses by automatically tracking mileage and gas costs as well as manual expenses such as insurance. Right now only Uber, Lyft, Sidecar, Postmates, and DoorDash are supported.

First, I really like that there is an app that can help out the drivers/couriers. After all, Uber et al have a bevy of engineers working to optimize their algorithm and the drivers/couriers are somewhat passive participants. Second, the app might help the sharing apps compete for the driver/courier’s service. Just as SherpaShare helped Steve Smith, an Uber driver, understand that driving in San Francisco earned him $10 more per hour than driving in Berkeley, which in turn was $10-$15 more than driving in his hometown of Walnut Creek, it could also help drivers realize that driving for Uber might be more beneficial than driving for Lyft and that driving in general was better than making food deliveries. Maybe Postmates and the other food delivery apps would need to raise their fees to attract drivers.

I also wonder about how these companies can perhaps use their sophisticated driver-rider pairing algorithm to be a bit more beneficial to drivers. Once drivers flex their freedom-of-choice muscles and, as long as demand stays high, they will flock to the services that pay them the most. For example, a lot of time is wasted waiting for rides and waiting means that there is no income. That’s what Mr Smith attributed his increase in income when working in Berkeley and the San Francisco. By changing cities, he spent more time driving passengers and less time waiting for rides, thereby optimizing his time and earning more. Could Uber and Lyft take into account this idling time when connecting a driver to a ride request? If driver A has been waiting longer than driver B and both are within a close distance to the rider, can driver A be awarded the ride? Sure, the rider waiting time from call to driver arrival needs to be minimized but do an additional few seconds waiting time really inconvenience them? I doubt it. What other driver-side parameters could be optimized aside from waiting?

In the long term it seems that SherpaShare might help to balance the uneven playing field between drivers and the companies. The number of drivers is not limitless and drivers will shift to services that pay them more. When companies start competing for these drivers,they will pay more and offer loyalty perks, ensuring that their users get drivers when they need them. Right now, Uber’s pitch to drivers is to “enjoy total freedom, total flexibility.” It would be interesting to see what happens when drivers are free to chose the services that treat them best.