Rumor is that they had to put their thumb on the scales (i.e. tweak the model) to get enough sellers to sell to them. In other words, if paying what their model actually thought was the right price, not many people sold to them. Instead of saying "our division's whole business model won't work, you should fire us", they tried to cut the margin too close, resulting in losses which got the CEO's attention to the problem.
This kind of thing is difficult to confirm from the outside, of course. But that they adjusted the model to pay more towards the end is pretty widely known.
"Speaking of middle managers, word on the street is that Zillow Offers put their thumb on the scale of the algorithm to make it engage in more aggressive trades. Manually adjusting an algorithm isn’t necessarily a bad thing, but you need to do it for the right reasons. And clearly that didn’t end up working out..."
That not everyone in the organization knew that, is just me speculating.
Ah, I was trying to find that article earlier today. (I searched "Sean Spicer data science Twitter" to no avail, ha.)
Actually that piece also hints at an uneven understanding of these issues across the organization:
> In one tweet, I semi-joked that what happened was lower and mid level employees convinced upper management that the algorithm was 99% accurate by hiding the caveats of what “99% accuracy” means.
This kind of thing is difficult to confirm from the outside, of course. But that they adjusted the model to pay more towards the end is pretty widely known.