What Happens When Businesses Make Big Bets?

Big bets versus smaller bets. It’s a decision business leaders often face. And, how big a bet a business makes can have a major impact upon success. That’s why making the right kind of bets is crucial. And, it turns out that big bets generally do not bring business success.

A recent high profile situation offers an excellent example. Zillow, a key player in the real estate sector, had a good business in real estate data. More recently, however, the company branched out into using its algorithms to predict the prices of pieces of real estate, then buying that real estate for cash and selling it at a profit. In the real estate world, this business is known as iBuying.

More recently, Zillow shut down its iBuying business after experiencing large losses with that endeavor. This occurred at a time when the housing market experienced some major price shifts. As this happened, however, Zillow competitor Opendoor, apparently continues to see iBuying as an attractive business.

What might explain why Zillow’s losses with the market shift were severe enough to shutter that line of business, while competitor Opendoor continues onward with iBuying?

A major contributor to Zillow’s trouble was that Zillow made a big bet. And, after researching business success and failure patterns for 25 years, smaller bets, not big bets, are what generally drive business success. Even in industries whose very nature is characterized by big bets, as I wrote about years ago, success can depend on keeping the bets somewhat smaller.

The way the November 18, 2021 issue of the Wall Street Journal titled its article on Zillow’s troubles illustrates where the company went wrong. The front page article, which was written by Will Parker and Konrad Putzier, was titled “How a Real Estate Algorithm Derailed Zillow’s Big Bet“.  The article’s continuation on another page had the title “Zillow’s Big Bet Unravels”.  As I see it, the article is very right that Zillow made a big bet with its iBuying business.  However, I do not agree that the algorithm is what derailed the big bet. Based on my research into business success and failure patterns, taking extremely big bets generally fares quite poorly. Running the business as a big bet is apparently what derailed Zillow’s iBuying venture.

Just because the algorithm did not correctly predict price shifts in the housing market, it does not mean the algorithm derailed the Zillow business.  Algorithms can be used for predictive modeling.  And, forecasts produced by predictive models are not always right. For example, weather forecasts are usually good enough for deciding whether to wear a sweater or bring an umbrella. Yet, weather forecasts are not always right.  The same is true of the algorithms used for producing business forecasts.  Sometimes, businesses forecasts are not right. But, getting forecasts wrong usually is not enough to completely derail a business.

What does generally derail businesses, however, is making bets so big that the company is unable to successfully manage those bets.  And, it is the big bet that the Wall Street Journal mentions in its headlines that has been driving Zillow’s iBuying derailment.

Zillow moved into iBuying later than competitor Opendoor. According to the Wall Street Journal article, Zillow focused heavily upon catching up with Opendoor. According to the article, “Zillow put together a plan to speed up the pace…to catch up to Opendoor. Zillow planned to buy more homes by spending more money, offering prices well above what its algorithm and analysis picked as market value, people familiar with the matter said.” “The company was buying so many homes that its overstretched staff started running behind on closings and renovations.” “Zillow was in danger of sitting on homes for longer, adding to insurance and debt bills.” “Analysts whose job it was to confirm the prices of homes found that they were routinely overruled, those people said, because the company had retooled the system to raise the analysts suggested prices.” Eventually, as homes had to be sold at a loss, Zillow eventually shut down this iBuying business.

As I see it, the algorithm itself played a minor role in the demise of this business.  It was Zillow’s extreme focus on a bet too big to win. The derailment was due to striving to catch up with Opendoor no matter what the cost, even if that meant overpaying. When the company decides to retool the system to overpay, it’s not the algorithm that derailed the business. It’s a decision to run the business a certain way, despite analysts on staff identifying the dangers of doing so. These kinds of missteps are common when a company makes a big bet and tries to move into new areas too fast.

Eventually Zillow management recognized that the iBuying business was too risky. So, they shut it down. I’ll point out that Zillow’s original business in real estate data is very different from its newer venture as an iBuyer. In iBuying, there’s big investments in purchasing all those properties, and there’s managing the renovations and marketing the properties. These functions require competencies that differ from what it takes to be a real estate data company. Zillow apparently never took the time to truly hone these competencies.

Making a big bet and expecting to thrive quickly in the new iBuying venture just was not realistic for Zillow. And, unrealistic expectations about the odds of winning a big bet can easily lead to a derailment, just as it did for Zillow.

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