Data and analytics are everywhere today. Paired with Artificial Intelligence (AI) and Machine Learning (ML), big disruptions are either coming or already underway in many industries. However, it’s not all sunshine and rainbows. Lots of companies are pushing the envelope too far, too fast and getting burned. Let’s talk about what happened to Zillow.
Zillow started an on-demand home-buying unit called Zillow Offers in April of 2018. The strategy was to use their algorithm that determines the Zestimate you see on a given listing on Zillow to make an all cash offer on a home. The plan was to purchase certain homes, upgrade them and sell them at a profit better known as ‘flipping’ homes. Long story short, it didn’t go as planned. In the third quarter of 2021, Zillow Offers caused the company to take loses of $420 million dollars. Ouch.
In November of 2021, Zillow CEO Rich Barton would close the Zillow Offers part of their business, sell the rest of their inventory and lay off 25% of their workforce or 2,000 employees. Yikes.
What went wrong with the Zillow Offers project?
The primary technical reason was that their algorithm was inaccurate. The margin of error was larger than it needed to be to succeed. This meant Zillow overpaid for homes and overestimated what homes would be worth when they went to sell them causing them to take losses instead of profits.
They also made some rather foolish assumptions. For many reasons, Zillow was unable to renovate homes as quickly as they assumed they could. There just wasn’t enough help to go around to renovate thousands of homes all over the country at once. This led to massive delays and skyrocketing costs.
Was this an inappropriate use of the technology?
Yes and no. The technology could certainly help predict what a home may be worth, but the problem they were trying to tackle was too ambitious. They made some ridiculous assumptions which screams a lack of subject matter expertise. There’s a huge difference between knowing what a tool does and actually using it to deliver successful outcomes. Knowing how something works in theory doesn’t guarantee results in practice.
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Interesting story, but how does this apply to me and my firm?
The main lesson here is that you don’t have to tackle everything all at once. Zillow wanted the technology to drive all the decisions, but if they were more closely managing the results they would have easily seen that it wasn’t working and they should make some changes.
Your technology strategy shouldn’t be to go from 0 to 100 in one step. You should accelerate gradually along with the pace your firm can keep up with while staying focused on the objective. If achieving that objective starts to slip then you need to take a pause and reevaluate.
The amount of progress, time and money that have been lost on failed technology project is too high to count. Technology is a tool like any other and any tool can be used wrong.
Make sure your firm always has the right technology strategy in place. If you’d like my help evaluating your firm’s technology strategy, book a session so we can review together.
PS. Go here to learn more about Zillow Offers debacle.