No hace mucho, Uber inició una revolución en el trabajo: gestionar trabajadores, ¿o son autónomos? - a través de una aplicación basada en un algoritmo. Nació la economía de los conciertos. Su promesa era ahorrar dinero a los consumidores y hacer dinero rápido y fácil para cualquiera que tenga un automóvil. Y, por supuesto, para enriquecer a los fundadores e inversores de Uber.
Was when. We know better now.
Oh, the model is more popular than ever. Thanks to the COVID-19 pandemic, for example, food delivery services have exploded: 60% of US consumers now order delivery or takeout once a week from DoorDash, Uber Eats, Grubhub-Seamless or its smaller competitors. Just a little problem. All these promises of the gig economy turned out to be lies, an important lesson for small businesses that might be tempted to try to emulate all this "success."
Sure, sometimes consumers have saved money, but at other times skyrocketing prices have left holes in their wallets. The workers feel screwed for good reason. And, with the exception of founders who raised venture capital like an elephant made of peanuts, gig companies were largely unprofitable.
For example, Airbnb, the leading algorithm-based vacation rental service, reported a net loss of around €1.1 billion in the first quarter of 2021. ¿Uber? He had a "good" first quarter of 2021. His net loss was just €108 million. And DoorDash, the top IPO food delivery service, lost just €110 million in the first quarter of 2021.
We've been in the gig economy for over a decade. You'd think someone other than a founder who cashed in would have already made a real profit.
Yes, yes, I know everything about growth rather than profitability. But still, at the end of the day, or the end of the decade, you have to show profit.
As New York Times tech columnist Kevin Roose recently pointed out, these companies know it, too. For years, investors "flooded these businesses with cash, which was often passed on to users in the form of artificially low prices and generous incentives."
Now the silver rain has slowed to a trickle. The result? “The average ride for Uber and Lyft costs 40% more than a year ago, according to Rakuten Intelligence, and food delivery apps like DoorDash and Grubhub have steadily increased their fares over the past year. The average daily rate for an Airbnb rental has increased by 35%. The cheap race is over.
In fact, it has never been so cheap to start. We don't cheaply pay for our Lyft rides. Andreessen Horowitz LLC was, with its investment of €60 million.
Even when another conventional company is involved, you don't pay all the freight. For example, as a recent investigative article from New York Magazine and The Verge by Josh Dzieza noted, "The main reason restaurants wouldn't let you order a single bacon, egg, and cheese for 50 blocks for almost free is that it's a awful business model. Expensive, unnecessary, laborious, you would waste money on each order. The apps promised to solve this problem through algorithmic and scaling optimization. This has not happened yet, neither company is consistently profitable.
They also don't work well with other companies. For example, DoorDash is suing instead of giving restaurants access to basic consumer data, such as their customers' names and addresses. (If my business relied on delivery services, I would really want to know who my customers are.)
The painful truth is that although all algorithms seem technical and efficient, they are not. The main problem is that the employees behind the algorithms, the faces and hands behind fast and easy service, are underpaid and abused by ruthless programs. Instead of a bad boss, they have bad algorithms.
Is it any wonder that soloists join the great resignation? Oh sure, they'll take a job to get ahead. But loyalty? Good job? Please! The algorithm only cares about X number of trips in Y time. Workers know this and will stop working as soon as they can leave because they know the program will fail them as soon as it is no longer effective.
Worse still, despite the poor business record of algorithmic management, it is now on its way to other types of businesses. Some companies are turning to facial recognition and real-time scheduling; smart credentials and QR codes; and GPS employee tracking and wristbands to track office workers. Personally, I wouldn't mind if my employees were in their home offices from 9 a.m. at 5 p.m. as long as they were doing their job.
If you are considering giving an algorithm some level of management, think twice. Instead of digital efficiency, you'll end up alienating your employees. And, with workers quitting their jobs at an all-time high, do you really want to take advantage of this opportunity?
Instead of turning to algorithms, turn to good old-fashioned people management that shows you value your people and their work. People respond much better to being treated as people than as numbers. I believe that respect between bosses, workers, managers and employees has always been the best way for a company to manage its affairs.
So read this:
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