Netflix DVD JTBD

If I listened to my customers, Henry Ford lamented, they’d have asked for a faster horse. Let’s peel back this meme.

Superficially, Ford noted, customers do not know what they want. It takes visionary God-given insight to make things for people. Maybe.

What’s happening is that customers share a suggested solution. Ask the right questions to find the problem.

Prior to streaming in 2007, Netflix mailed DVDs. The business worked better than Blockbuster because movies came right to the customer, who returned them whenever they pleased. Life was good.

Mostly. People told Netflix they wanted new releases faster. That was the suggested solution. Instead, Netflix asked questions. If some customers got their newly released movies right away and others did not, would customer churn differ between the two groups?

And it did!

But not by much. At least not by enough to justify the extra cost of 2004’s The Machinist.*

But people wanted more new movies. Right?

Here Netflix got into the problem part of Ford’s words. Customers ask for one thing but what do they really want?

What the Netflix customers really wanted was any movie faster. To address this JTBD Netflix did two things.

First, they built more shipping centers so more movies were geographically closer to more people. During this expansion, Netflix went from ~20 centers to ~100.

Second, they changed the website so ‘local’ movies were presented on the homepage. A customer might log in to see Shrek 2 rather than The Incredibles.

Customers said they wanted newer movies, but what they wanted was faster movies.

*That’s another Netflix find. We tend to like Adam Sandler movies more than Drama/Thriller

Three problem-solving prompts

1/ What is the asymptotic limit? To be a multi-planet species, says Elon Musk, people will need to design, build, and use reusable rockets. Okay. Is that possible? One way is to think to the limit. “Look at the raw materials of a rocket: aluminum, steel, titanium, Inconel, speciality alloys, copper. Now ask the weight and raw material value. That sets the asymptotic limit for how low the cost and weight can be unless you change the materials.” Musk calls this the magic wand number. What’s the cost if you had a magic wand to rearrange the atoms?

Another way Musk uses limits is to think about scale. Making many versions of a thing is much much harder than one version. This too is a problem for Disney imagineers, writes Kevin Rafferty. Coming up with attractions is fun but the hard work is what Rafferty calls ‘day two problems’. What happens when this thing has to be open for ten hours a day 365 days a year?

2/ Is this a money problem? Starting the cable channel Discovery, John Hendricks had a lot of challenges. One was content, but that was easy. The BBC was willing to sell their documentaries to Hendricks and enjoy the found money. Later Netflix would take this to detrimental consequences to the content providers, but in 1985 Ted Sarandos was managing eight video rental stores in Arizona.

But there was cable regulation working against Hendricks. The deregulation of cable (like with airlines) wasn’t a money problem. Host Guy Raz analogizes it to having a new iced tea and having to call every convenience store operator in America to get on the shelves. Hendricks then had one problem that was a money problem but another that was a political one.

3/ Is this a branding problem? One of the covid lessons ‘we clearly haven’t learned‘ according to Zeynep Tufekci is to follow best practice. “We have everything we need,” she told Ezra Klein, “not a day goes by that I don’t get a pitch for some gimmick, some new mask that is blah blah blah. Thank you, but I just need an N95. I don’t need your new potentially miraculous science.”

This, says Rory Sutherland, is a marketing mistake. Good marketing changes the perceived value without changing the thing. Good marketing is ‘being better than Superman‘. To Tufekci, we’ve not figured this out – yet.

2a March 24 update, winter wheat is the largest wheat crop in the world and that has to be planted in certain places at certain times. Russia’s invasion of Ukraine is going to influence how much the planted wheat can be harvested. This is not a money problem.

Meaning and marginal effects

‘Is diet a form of counter signaling among wealth people?’ wonders Rory Sutherland. “If so it won’t really scale. It will be profitable. It will be large enough, there are enough wealthy people. But if it doesn’t scale beyond the highly educated and well paid then obviously the environmental benefits won’t be so great.”

Though I agree with Rory (a lot) here he’s surprisingly wrong.

Blockbuster Video and Southwest Airlines had the same business model, though they aren’t the only ones to operate this way. For Blockbuster the problem wasn’t everyone having Netflix but some people having it. If they lost 5% of their customers, sometimes their most profitable ones, in any given area that changed the unit economics. The same fixed costs spread over fewer customers meant the non-fixed costs had to change too. The same with Southwest. In the early days of the airline, founder Herb Kelleher told employees they only made money on the last two passengers.

These marginal customers are the reason Rory is wrong here. Much like the first pounds lost on a diet being the most impactful, the first ‘meat consumers’ lost will also have an outsized gain (or is it loss?). But that’s not all! Because the environment is a complex adaptive system, the effects are almost certainly non-linear.

Most of the podcast between Sutherland and Live Kindly’s Jodi Monelle is about delivering value through meaning. Value through meaning is kosher, it’s vegan, it’s carbon free too! Value, Rory says, is ‘Beyond Meat’. It’s like meat, but better. It’s beyond meat. That’s good value.

What is cheating in chess is winning in life.

Roland Walker (BBC) talking with David Edmonds. The context is how monitors cheating.

“We can’t overstress this enough, humans and computers play utterly differently. Humans play by planning and recognizing patterns. Computers play in unusual ways, it forgets everything that it knew in between every move. A computer doesn’t really have a plan.
“An engine will take back a previous move if it realizes that in the context of the following moves it wasn’t good. A human has a kind of sticky feeling about their plan.”

Chess engines make people better at chess and good players use them to practice, if not to play. It’s the Cowen idea of meta-rationality (more here). The idea of using the right resources.

Computers are good because they compute without bias (kinda) and avoid human mistakes like sunk cost. As Mohnish Pabrai pointed out, “when we spend a lot of time on something, we feel we should get something in return for that time, it’s a danger if you say, I’m going to research a company and decide if I want to invest or not. I think you’re better off researching a company with no such preconceived notion.”

This week my daughters (12, 10) and I watched both Sherlock (also BBC) and Enola Holmes (Netflix, we loved it). In both the episode and the movie, the characters had to be more objective to solve the crime.

However, it’s going full-Sherlock as much as moving in that direction. Like someone training to gain/lose weight, the goal isn’t to become extremely skinny/strong but to be more than the current state.

Meta-rationality then is under indexed, unless of course, it’s outlawed like chess.

h/t Cowen-kinda-queue, a podcast feed of Marginal Revolution mentions.