When Orange is the New Black, House of Cards, and Crown became mega-hits for Netflix, many people credited the analytics capabilities of the company. Mining the customer data had enabled the firm to project the type of original programming that would be highly successful. By this logic, Netflix would achieve a lower failure rate on new shows than the major television networks. After all, broadcasters such as CBS and NBC cancel a substantial share of their new shows each year, some after only a few episodes.
On the recent Netflix earnings call, many investors were pleased to hear about strong subscriber growth at the firm. However, some investors came away concerned about the amount of spending taking place as the firm acquires or develops new content. Moreover, some observers and analysts have expressed concern about the recent cancellations of some new Netflix original shows. Tom Huddleston Jr. reported on the company's reaction to this criticism in a recent Fortune article:
Meanwhile, also on the Monday earnings call, Netflix's chief content officer Ted Sarandos defended the company's recent cancellations of a handful of expensive, but underperforming, original series. "The more shows we have, the more likely in absolute numbers that you’ll see cancellations, of course," Sarandos said. The executive compared Netflix's recent spate of cancellations—including big-budget series like The Get Down and Sense8—to traditional TV networks that cancel nearly one-third of their new shows after their first seasons. Netflix, he said, has renewed 93% of its original series. With respect to the shows that Netflix opted not to renew, Sarandos argued: "If you’re not failing, maybe you’re not trying hard enough."
This quote from Sarandos raises a fascinating question. What is the "optimal" failure rate at Netflix? Surely, we would like the failure rate to be lower than the broadcast networks. We would like to see the company reaping the benefits of its analytics capabilities. At the same time, no one should want Netflix's failure rate on original programming to be zero. We want the firm to take some chances in hopes of landing some surprising breakthrough hits. Hopefully, the firm isn't simply guessing or drawing on the intuition of the "creatives" in the business. We would like to see them engaging in "enlightened" experimentation, using big data to guide them while still taking some risks. If they balance data mining and risk-taking in an effective way, the failure rate won't be zero, but it will be much lower than their broadcast and cable competitors.