Category: Analysis

Suspiciously Recurring Numbers and More Implications of The Netflix versus Crazy Rich Asians Debate

(This is the third part of a multi-part series exploring one specific Netflix number. To read the other pieces:

Introducting “Datecdotes”, when Streaming Companies use Data to Win the PR Wars

Did More People Watch Crazy Rich Asians or a Netflix Rom Com Last Summer?

Netflix versus Crazy Rich Asians: What Else Does Netflix “80 Million Customer Accounts Tell Us?)

Okay, enough skepticism. If we take the latest datecdote from Netflix, at face value, what can we learn from it?

Well, to start, let’s take a look at the history of “80 million” in Netflix releases…

What other evidence of “suspicious” numbers do you have?

In a future article, I’ll write about another “theme” of this website called, “Theme X: Be Skeptical”. Especially with competitors. Don’t give them the benefit of the doubt! 

One of the corollaries to that theme relates to data. The corollary is, “Be wary of large, rounded numbers.” Data isn’t often rounded so evenly. This applies to scientific studies, political causes and other social phenomena. Oh, and entertainment success stories.

I’d add, if the same company keeps repeating the same big number that would be weird, right?

Netflix has this problem with their original movies, and I don’t think anyone has pointed this out yet. Researching the “80 million customer accounts” I naturally googled to try to find every news source uncritically repeating this datecdote. Imagine my surprise when the first occurrence of 80 million accounts wasn’t October in the Q3 shareholder report, but actually in June!

See, their “Summer of Love” romantic comedies weren’t the first time they had “80 million customers” watch something. For example…

– In June, Reuters was given data from Netflix that 80 million customers had watched a Netflix Original movie in 2018.

– In June, Dana Feldman on Forbes also reported that 80 million customers had watched a “romance film” on the service. Rereading it, this looks like it includes both originals and licensed films. This came from a Netflix tweet.

Then in their Q3 letter to shareholders, Netflix repeated the 80 million customer accounts number.

Clearly there was some rounding going on. And for press releases or on information provided on background, Netflix is under no obligation to be precise. But let’s assume the numbers are close enough. If the baseline assumption is all Netflix movies combined get 80 million customers accounts involved, the “Summer of Love” films didn’t really boost viewership that much did they? Either for romance films or original films. Eighty million customers is just what big groups of movies promoted by Netflix tend to get.

But if I wanted to be skeptical, I mean, what are the odds that exactly 80 million customers watched an original in from January to June, which is the same number that over the previous year watched a “romance movie” and then, after two more months of Netflix rom-coms being released in the “Summer of Love”, they had all in 80 million customers watch an original romantic comedy? Is that crazy overlap, or three part coincidence?

What if we take all the recurring 80 million customers at face value? What can we learn from this number?

We can triangulate the floor for Netflix “Monthly Active Users”.

This is the biggest way that streaming video distributors, social platforms and subscriptions services in general try to game the narrative. A customer or user includes anyone who “samples” a subscription. So you order from Blue Apron, or start a Hulu free trial, or sign up for SnapChat. Those are all users or customers.

But Monthly Active Users (MAUs) is a much better approximation of who is actually using your service regularly. (Or weekly or daily active users, which are even smaller time periods.) That means actual people you can monetize through ads or monthly billing. With Netflix, we have no clue what their monthly or weekly active users are. Most social platforms include this in their SEC filings. Netflix does not—it isn’t a social platform—and instead focuses on “subscribers”.

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Netflix versus Crazy Rich Asians: What Else Does Netflix “80 Million Customer Accounts” Tell Us?

(For Part I of this series on Netflix versus Crazy Rich Asians, click here.)

If you can’t tell by my article last week, I had a lot of fun with my comparison between Netflix romantic comedies and Crazy Rich Asians. Unfortunately, I had a lot of ideas for that article that hit the cutting room floor. 

Some because they were too speculative, some to save room, and some to make a tighter narrative. (I had tried a long shot publication at a bigger outlet.) And some because I couldn’t prove them. So for a respected publication, it didn’t make sense.

But this is my website. I’m free to make all the speculation and ask all the tough questions I want to here. Since Netflix only provided me one number—80 million customer accounts watched an original romantic comedy the last summer—well, I want to ask that number a lot of questions. I want to interrogate that number to within an inch of its life. So that’s what I’m doing today. Asking—and answering—all the other questions inspired by this comparison.

What other “circumstantial” evidence did you leave out?

A few pieces, but one major one. Essentially, the major studios stopped making romantic comedies for two reasons. First, they don’t have a high enough “ceiling” in that they don’t ever tend to have billion dollar movies. Second, and crucial for our math, is that they also don’t tend to perform well overseas. This applies generally to all comedies. Comedy is a local phenomena so it’s rare for comedy films to do well overseas unless they are very, very broad. (Some of the broad sitcoms like The Big Bang Theory or Simpsons do travel. Others, I’ve heard, don’t.)

We’re seeing this right now. Aquaman is the number one movie in the world…and it didn’t open in America. Crazy Rich Asians, meanwhile, flopped in China. To show this effect, here’s some data. For my series on Disney’s Lucasfilm acquisition, I made a data set of 50 “franchise” movies. These provide a good set of comps for comic book movies and their ilk. As you can see, franchises now see 63% of the total box office come from overseas (and even this still includes a lot of old Star Wars and Indiana Jones data.)

Blockbuster TableNow compare that to romantic comedies. I don’t have as large a list, so I pulled some sample romantic comedies. The trend is clear…

RomCom US Inter Splits

Four recent romantic comedies that did “well”, had over 70% of their box office come from the US market. Crazy Rich Asians, notably, only had 22% of its total box office come from overseas. Compare that to massive blockbusters like Avengers or Pacific Rim, where over 66% or 75% of their box office came from overseas.

This has implications for Netflix. Mainly, three facts collide that can’t all be true simultaneously: 

– Netflix had 80 million customer accounts watch an original romantic comedy last summer.

There are 60 million US customer accounts. (Rounded up slightly.)

– US romantic comedies tend to have 60-40 splits in US to international viewing, sometimes as high as 70-30.

This puts us in an awkward place when it comes to the Netflix number. Based off Crazy Rich Asians and other romantic comedies, I could easily assume 60% of the viewership was US based. That leads to some really tricky “consultant math”. Go with me on these assumptions:

– Assume 60% to 40% domestic to foreign split on Netflix romantic comedies

– Assume 1.4 “viewers” for every Netflix customer account.

Black Panther sold 76 million tickets in the United States.

– Assume 15% rewatch rate for Black Panther. 

Here’s those assumptions, now it table form:

Screen Shot 2018-12-11 at 3.41.39 PM

Now, even worse than Netflix claiming it beat Crazy Rich Asians, if we take some conservative assumptions, more people watched a Netflix romantic comedy than the biggest movie in the US last year (Black Panther). Do you honestly believe that?

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Did More People Watch Crazy Rich Asians or a Netflix Rom-Com Last Summer?

The romantic comedy is dead. The highest grossing romantic comedy this year is Crazy Rich Asians, which at $174 million in domestic box office pales in comparison to behemoths like Black Panther ($700 million domestic box office), Avengers: Infinity Wars ($678 million), Incredibles 2 ($608 million) and Jurassica World: Fallen Kingdom ($416 million). Who shall return the romantic comedy to glory?

Netflix. Because of course Netflix.

This summer, Netflix released a series of romantic comedies it dubbed, “the summer of love”. In a letter to shareholders, Netflix celebrated their success. Here’s Vox writing about a particular fact Netflix provided:

This summer, Netflix invested in resurrecting the mid-budget romantic comedy, acquiring movies like Set It Up and To All the Boys I’ve Loved Before for what the streaming service branded as its “Summer of Love.” And now, it’s looking like the gamble paid off: Variety reports that more than 80 million subscribers watched one of the 11 rom-coms on the Summer of Love slate, according to Netflix’s quarterly earnings report.

Vox wasn’t alone in singing Netflix’s praises. They were joined by Variety, Screen Rant, The Ringer and others to write an article on Netflix’ new found success in romantic comedy. All using one “datecdote”, a term I coined yesterday.

In our hurry to constantly keep up with the news, we let little tidbits like Netflix’s above fact wash over us and move on to the next story. So let’s pause and reflect on the fact Netflix revealed. Does this fact seem true? Since Netflix didn’t provide a comparison, I will:

Did more people around the globe watch Crazy Rich Asians or a Netflix Romantic Comedy last summer?

It’s a tough question, isn’t it? If you answer that more people saw a Netflix romantic comedy, then why did the media spend so much time on the phenomena of Crazy Rich Asians? But if you think more people saw Crazy Rich Asians, then how can Netflix numbers possibly be true?

Streaming video companies, like Netflix, have a lot of data, a lot of ways they can manipulate that data, and, most crucially, a lot of data they just don’t give the press. But we can learn a lot about how movies are distributed and judged in today’s media landscape by trying to answer that tough question with the data and facts we do have.

So let’s do our best to get some answers.

How Many People Watched a Netflix Romantic Comedy?

On the surface, this is fairly straight forward. Netflix in their letter to shareholders—a document submitted to the SEC, so a legally-binding, carefully vetted document—used this phrase:

More than 80 million accounts have watched one or more of the Summer of Love films globally.

Netflix chose two words very carefully in the above sentence. First is “accounts”. Not “profiles” or “viewers” but accounts, since this is the only unit of measurement Netflix knows for sure. They know that because they have one account per credit card. I’ve seen this called “users” or “customers” at other companies. 

By definition, this is the floor for the actual number of people who watched a romantic comedy on Netflix. If two people watched a film together, well they still only count as one “account”. If two different profiles under the same account watched, they would still probably count as one. (It’s unclear.) If someone shares their password with someone else, but they use the same profile, that still counts as one view.

If account is a precise definition, “watched” is a term so loose that it could mean anything. For instance, Netflix could count as “watched”, a person who only watches ten minutes of a film and turns it off. They could only count as “watched” people who watch greater than 80% of a film, either by run time or who watched past the 80% point in the film. We just don’t know.

What we don’t know dwarfs what we little we do know. We don’t know how many total hours of romantic comedies were viewed. (Netflix, interestingly, loves to cite this number to describe how popular their platform is, but choose not to provide that fact here. For example, they released earlier this year that they had 350 million hours viewed in one day in January.) We don’t know where people watched—this is a “global” number—or even when. While presumably over the summer, it likely wasn’t a hard three month window.

How Many People Watched Crazy Rich Asians?

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Disney-Lucasfilm Deal Part VIII: The Theme Parks Make The Rest of the Money

(This is Part VII of a multi-part series answering the question: “How Much Money Did Disney Make on the Lucasfilm deal?” Previous sections are here:

Part I: Introduction & “The Time Value of Money Explained”
Appendix: Feature Film Finances Explained!
Part II: Star Wars Movie Revenue So Far
Part III: The Economics of Blockbusters
Part IV: Movie Revenue – Modeling the Scenarios
Part V: The Analysis! Implications, Takeaways and Cautions about Projected Revenue
Part VI: Disney-Lucasfilm Deal – Television
Part VII: Licensing (Merchandise, Like Books and Comics and Video Games and Stuff))

If you’ve been reading along after 47 pages and six months of writing, you know that Disney more than made its money back on its purchase of Lucasfilm through releasing wildly successful Star Wars sequels, and then making another $1.7 billion in licensing revenue. So they made their money back.

But to truly get a great return on investment—as I wrote in the introduction in my “gut” section and again when referring the licensing & merchandise—theme parks are the whipped cream and cherry on top. In 2019, if it stays on track, in Disneyland and in Disney’s Hollywood Studios, Disney will open Star Wars: Galaxy’s Edge, which have been under construction since 2016.

And they could be huge money makers.

Theme parks allow The Walt Disney Company to make more off its IP than any other studio. (That’s its competitive advantage.) So let’s figure out how to quantify that benefit. Then, we’ll figure out the costs.

The Challenge: Disentangling the Marginal Benefit of new Theme Parks

With movies, calculating the revenue is messy, but we have lots of data. With toys, forecasting the revenue is easy, but we have way less data. What about for theme parks? In this case, the toughest part of the process is assigning the value.

Think of it like this. We know that putting in a Star Wars: Galaxy’s Edge at Disneyland will drive attendance and revenue. The problem with theme parks is untangling how much revenue they will drive.

In other words, the “marginal benefits”.

Some day I’m going to write “Marginal Benefits Explained!” because it’s a core economic principle—the core principle?—and I’ve seen 7-figure-earning business execs screw it up. Marginal benefits are the additional revenue a business generates by changing an input. So if you’re making a million dollars a year and raise prices, and it goes up to $1.2 million, your “marginal benefit” for the price raise is $200K, the additional revenue you generated.

(You want to know my biggest frustration/pleasure with this website? Every time I write a new article, I think of two more posts to write inspired by it. The “hydra problem” of the Entertainment Strategy Guy.)

This idea is what stymies the analysis with theme parks. Let’s visualize it with an example.

Next year, I’ll walk into Disneyland in the off-season (probably September-ish). I’ll be wearing a Star Wars shirt. My brother will probably rock a Marvel shirt. That said, I’ll also have a three year old wearing, if current trends hold, either an Elsa (Frozen) or Belle (Beauty and the Beast) dress.

So how much of that trip do you allocate to the opening of ? (Punctuation side note: do you italicize theme park lands? I did, but should I?) My family already averages one trip to Disneyland every year, and my daughter knows that Mickey lives at Disneyland. So she’d go anyways. But what about me? I’ll definitely go to see the new park at some point. We could make an analogy of a theme park to a content library on a streaming platform. People pay for the whole thing, not the parts. With content libraries—which is essentially what a theme park is—untangling and clarifying the value offered by each piece can be tough.

The Economics for Theme Parks

When in doubt, I like to boil things down to a simple formula. So let’s do the rough “business model” for a theme park. I came up with this:

Slide63

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Disney-Lucasfilm Deal Part VII – Merchandise

(This is Part VII of a multi-part series answering the question: “How Much Money Did Disney Make on the Lucasfilm deal?” Previous sections are here:

Part I: Introduction & “The Time Value of Money Explained”
Appendix: Feature Film Finances Explained!
Part II: Star Wars Movie Revenue So Far
Part III: The Economics of Blockbusters
Part IV: Movie Revenue – Modeling the Scenarios
Part V: The Analysis! Implications, Takeaways and Cautions about Projected Revenue
Part VI: Disney-Lucasfilm Deal – The Television!)

In business school, as I said in my first article in this series, I was super bullish The Walt Disney Company. The Lucasfilm acquisition followed on the heels of the Pixar and Marvel acquisitions—which were already doing well—and at the time ESPN was a cash juggernaut. Strategically, they’d made a series of great decisions.

Still, those moves, while good, weren’t the core reason why Disney has succeeded so much over the last forty or so years. I believed then, and still do now, that Disney is one of the few movie studios that has a business model derived from a distinct competitive advantage. As others have written about, this competitive advantage goes back to drawings by Walt Disney in the 1950s.

Slide57

Basically, while having a great content is at the center of the plan, they develop and reinforce their relationship with customers through everything else. Or, to be cynical they make their money off everything else. Walt Disney created an iconic character in Mickey, then another in Snow White, then another in Cinderella, and so on to start. Then Walt Disney (the person and the company) would monetize the characters through music and books and comics and eventually television. Then they pioneered the concept of theme parks. Michael Eisner took this approach and applied it to home entertainment and acquiring TV networks.

When I was in b-school, I took the famous chart and summarized it in economic terms thusly:

Slide58

This is the simplest description of supply and demand in the marketplace, the core model at the heart of economics. Basically, along any curve, you maximize your price and quantity sold to yield the highest profit. I’ll cover this more when I write an article on “Transaction Business Models Explained!” (the sequel to my two articles on subscriptions) but for movies you basically can only charge the same price per movie ticket, regardless of movie. As a result, to maximize revenue you need to maximize customers, and hence Hollywood makes blockbusters.

Most studios stop there. But not Disney. They aren’t just selling movie tickets, they’re selling merchandise on top of that. And then, for the piece de resistance, they sell theme park admissions (and in park up-sales) in an experience they own outright. Other studios do this, but nobody does it as well as consistently as Disney.

In my adventures after business school, I’ve only become more convinced that Disney knows its business model, knows its competitive advantage and makes moves to sustain that model. They may be the only movie studio, er, “giant media conglomerate” that has a competitive advantage. To continue our series on Lucasfilm, I’m going to add in the rest of those boxes going up, starting with merchandise.

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Putting Numbers to the Oscar Best Picture and “Popular” Film

If you want to know why I started this website, just take a look at the furor unleashed on the Academy of Motion Pictures Arts and Sciences when it announced (via Twitter!) that it would add a new category called “Achievement in Popular Film”.

First came the questions: “How would this even work? By box office? By user reviews? By top 25 films at the box office?”

Then came the pondering: “Hey, what film would have won in the last ten years? What will happen to Black Panther?!?”

Then came the criticism: “Hey, this won’t work. This won’t solve the problem.” Or summarizing Rob Lowe on Twitter, this will just plain suck.

Throughout all those takes, the data was largely missing from equation. In data’s place lived assumptions. Assumptions from which the rest of the arguments derived. Consider what a flawed world that is: how can we fix something if we don’t know what the problem is? Or worse, when we don’t know what caused the problem?

Well, no more. Let me step into the void with as much data as I can muster to challenge the assumptions permeating the Oscars debate. Let’s separate fact from fiction. Call out our assumptions. Review what we know from what we can only guess. Let’s do this.

But first, my usual warning on data when it comes to media & entertainment.

Warning: We’re in small sample size.

I’m not going to go into as much detail as I did for my series on Mergers & Acquisitions in media and entertainment on my data, but the same admonition that drove that series drives this one: we’re firmly in the realm of small sample size.

Box Office Mojo tracked “Oscar bumps” going back to 1982, so that’s the sample of Best Picture nominees I used. So that’s our starting sample size: 216 films. However, drawing conclusions from 1982 data just seems wrong. Too much has changed since then. From DVDs to going from 200 or so films per year to over 500. As a result, we’ll leverage the last 20 years of data, which is only 136 films, 81 since 2009 and 55 from 1998-2008.

Assumption 1: The Oscars feature fewer and fewer “popular” movies.

Rating: True.

The ostensible reason the Academy needs to make a “popular film” category is because popular films aren’t being included in the nominees for Best Picture. This statement seems obvious which is why so many people said it on podcasts or in articles summarizing the issue. Narratively, this is an easy case to make: In 2017, only two films grossed over $100 million dollars, Dunkirk and Get Out. Worse, the winners in 2016 and 2017 grossed under a $100 million dollars combined, and had a combined box office of $45 million when they were nominated. No films have been nominated since 2014 that we could call a “blockbuster” meaning it did over $250 million at the box office.

(I defined movies as either “popular” with greater than $100 million in domestic box office or “blockbuster” with greater than $250 million. “Popular” and “blockbuster” are my definitions, but they work pretty well.)

The problem with easy narratives is they can often be countered with an equally compelling counter-narrative. If I squint at 2015, it’s hard not to call The Martian a near blockbuster since it did $228 million in domestic box office and more at the international market. I could also point out that La La Land, which was so close to winning it was even announced as the winner, did $400 million in total box office. Or I could just play with the timing: The Oscars don’t have a problem with nominating blockbusters since Star Wars was nominated in 1997, ET in 1982, Beauty and the Beast in 1992, Titanic in 1997 or even Avatar as recently as 2009.

So let’s go to the data. I plotted this a few ways, and they all tell roughly the same story. First, the raw counts:

Slide01Chart 1: Count of “Popular Films” and “Blockbuster Films” in Best Picture Nominees. Data: Box Office Mojo

Even that doesn’t really tell the story right, since the number of films eligible doubled in 2009, as the Academy expanded from 5 films per year to “up to 10”. So here is the percentage of films defined as popular or blockbuster for all films nominated.

Slide02

Chart 2: Percentage of “Popular Films” and “Blockbuster Films” in Best Picture Nominees. Data: Box Office Mojo

But even that doesn’t tell the whole story. That’s about one or two movies passing a certain threshold. Arguably, the more important fact is the average box office performance of the nominees. How has that trended?

Slide03

Chart 3: Average Domestic Box Office per Best Picture Nominee. Data: Box Office Mojo

Does even that metric tell a misleading story? See, a dollar in box office in 1998 isn’t equal to a dollar in box office in 2017. According to Box Office Mojo, a 1998 ticket only cost $4.69 whereas on average in 2018 that price has jumped to $9.27. So we need to make the three tables above, but adjust for the price of a ticket in a given year. Fortunately, Box Office Mojo does this for us.

Slide04

Chart 4: Count of “Popular Films” and “Blockbuster Films” in Best Picture Nominees, in 2018 adjusted dollars. Data: Box Office Mojo

Slide05

Chart 5: Percentage of “Popular Films” and “Blockbuster Films” in Best Picture Nominees, in 2018 adjusted dollars. Data: Box Office Mojo

Slide06

Chart 6: Average Domestic Box Office per Best Picture Nominee in 2018 adjusted dollars. Data: Box Office Mojo

Accounting for ticket price inflation, everything looks even worse for the Academy. The worst measure is the average box office per film. It was on a downward slide that was only arrested for a two year period, then it has gone back downward. The number of blockbusters per year looks equally bad, as the period from 1998 to 2004 regularly featured blockbusters, then again besides the period from 2009-2014, they haven’t featured any.

Taking those six charts together, we see a narrative forming that in our time period, we’ve seen two slides away from popular films and towards smaller films. Starting in the 2000s, the popularity of the films started dropping, bottoming out in 2005, and staying in that low period through 2008. So in 2009, the Academy expanded the field to 10 films to hopefully get more “popular” films. It worked, and the number of popular films, blockbusters and average box office jumped right back up.

But after this initial surge of popular films and blockbusters, the voters returned to form and the number of popular films, blockbusters and average box office per film plummeted again. To show this, I combined the data of films through these three time periods:

Slide07Of course, the key question for the Academy is how a lack of popular films reflects in TV ratings. (I’d personally argue that ignoring blockbuster films means the Best Picture category isn’t truly representative of the quality of films in a given year, but I can’t quantify that.) So let’s test that next.

Assumption 2: Featuring more “popular” movies will drive TV ratings for the Oscar telecast.

Rating: Maybe, leaning towards true

Again, narratively this is a really seductive argument. Basically, if you feature really popular films, people will tune in to see those films rewarded with nominations and wins at the telecast. Of course, the counter-narrative is also persuasive and I heard it on two different, influential podcasts (The Ringer’s Press Box? and KCRW’s The Business with Kim Masters): the types of people who watch the Academy Awards don’t watch/like popular movies anyways.

So here’s the one the chart that implicitly everyone referenced but I never saw: TV ratings plotted against average box office per film. (I also did the percentage of popular films, but it was even noisier than this line chart.)

Slide08

Chart 8: Average Domestic Box Office per Best Picture Nominee in 2018 adjusted dollars versus TV Ratings, in Millions. Data: Box Office Mojo, Nielsen data from Wikipedia.

So what can we draw from this? Honestly, not much. Technically, I should plot this as a regression model using a time series analysis, but I can tell you ahead of time it won’t be statistically significant so I’m not going to introduce that bad data to the world. Instead, the strongest conclusion we can draw is the Oscar telecast peaked in 1998 at 55 million people and have been sliding down ever since.

As for whether popular movies have slowed this decline, you can cherry pick data either way. First, let’s make the “popular movies matter” case. In 2008, ratings hit their nadir at 32 million, just above 2017’s 32.9 million. Each of those years represented near low points in average box office per film. Then in 2009 and 2010 saw increases in the TV ratings, and those two years were the highest average box office since 1998.

I can also make the case that “popular movies don’t matter” pretty easily. 2014 had the highest ratings since 2004—remember this for a minute, I’ll get back to it—and it only featured 1 movie with a box office over $100 million dollars. 2015 saw an increase in the number of popular films and average box office, but ratings still fell from 2014. 2003 had a huge average box office per film, but TV ratings ticked down that year. Moreover, even blockbusters like Titanic weren’t enough to bump up TV ratings, if you look back that far.

How do we draw a conclusion from this? Well, first we admit that one variable like “popularity of films nominated for Best Picture” is just one variable among hundreds. Other variables like the host(s), the date of the telecast, the length of the telecast, the quality of the broadcast, major a-list celebrities nominated and more could all impact TV ratings. Focusing on one variable to explain all our conclusions is a fraught enterprise.

Assumption 3: The Oscars haven’t featured diverse films in the recent past.

Rating: False.

Okay, so I didn’t actually read anyone who wrote this specifically. Or relating it to the move to make “Achievement in Popular Film” a category. But you can’t talk about the Oscars since 2015 without addressing the #OscarsSoWhite controversy.

Arguably, no groups has benefited more from the move from 5 films per year than diverse films and filmmakers. (Except maybe science fiction films, which I’ll get to.) Take a look at the number of films featuring African-American characters or themes measured before and after the expansion in number of films:Slide 9The difference is stark.

In the 9 years since expanding the field, a film featuring African-American characters or themes has been nominated every year except 2015 and 2010, and 2009 featured two, if you count The Blind Side. I debated it since arguably Sandra Bullock is the main character and it is her story, but if we exclude The Blind Side, I’d rule out three of the films from the 2000s for the same reason, which would only make my case stronger. Of the four films in the 11 years before the change that I counted, three are ensembles that don’t really focus on African-American themes. I could easily say that only Ray really qualifies. Before the Academy expanded the field it really ignored African-American characters.

(And obviously I’m only dealing with Best Picture here, not the acting categories, which in a lot of ways was the key driver of the #OscarsSoWhite movement.)

Of course, I could define “diversity” in a variety of ways. Take “global diversity”. Has the expansion of eligible Best Picture nominees helped foreign language films? Not really. From 1998 to 2008, four foreign language films were nominated for Best Picture (Life is Beautiful, Crouching Tiger, Hidden Dragon, Letters from Iwo Jima and Babel) and since then only one film has been nominated (Amour), which is even worse when you consider how many more films are nominated since the expansion.

(I’d also say you could look into Latino-American-themed films, but you’d basically find zero examples of any films in any time period. The Oscars may be so white, but they’re even less Latino-representative than African-American representative. Asian-Americans fair similarly poorly.)

Assumption 4: The Academy wasn’t nominating enough different types of films.

Rating: False, but trending towards true.

One of the biggest topics around this year’s nominees was the bugaboo about Get Out. Specifically, I heard people claiming it was unique because it was a horror movie, and those types of films never get nominated.

Well…

To test this, I wanted to see how many “genre” films were nominated before and after this change. I defined “genre” films as any film in the following genres: science fiction, fantasy, war, musical, comedy or animation. And if a film in Box Office Mojo was more a drama than a fantasy (say, The Curious Case of Benjamin Button) or more a drama then a comedy (Juno was a tough edge case here), then I excluded it. Again, we’re looking for films known as genre films, not films that happen to have genre elements.

Slide10

In this case, nothing much has changed. From 1998-2008, roughly 69% of the films were “drama” films. From 2009 to present, 62% were “drama” films. So it’s gone up by 7%, but that’s within the margin of error. Even the last two years which “felt” like not a lot of genre films were featured still had one-third genre movies.

Of course, for certain categories, the change has really helped. As I mentioned above, since the change 9 clear “science fiction” movies have been nominated: Avatar, District 9, Her, Inception, Gravity, Her, Mad Max, The Martian, Arrival and, last year’s winner, The Shape of Water. Some of those films were also blockbusters or popular. Though the three biggest science fiction films since Avatar (Star Wars) haven’t been nominated. War films have also done very well, but have been generally less popular than the science fiction films, including American Sniper, Hacksaw Ridge and Dunkirk. The other categories all had smaller changes which are more likely noise than genuine signal.

The last category I’d call out is animation. During the first two years when the Academy expanded it’s number of films, two Pixar films achieved Best Picture nominations, Up and Toy Story 3. Arguably, Pixar’s quality the last few years has been at its highest with Inside Out and Coco being frankly, masterpieces (Both were “universal acclaim” on Metacritic.) but it hasn’t seen the respect from the Academy. I would argue that if the Academy really wanted to train a new generation to love movies, putting films like Coco and Inside Out (and even Frozen) would help a lot.

Assumption 6: Politics hurts the Oscars.

Rating: True, but not for the reason you think.

Well, maybe for the reason you think.

The one narrative that was hinted at throughout the #OscarsSoWhite campaign was that featuring non-diverse filmmakers would keep a diversifying America from watching the campaign. As we saw above, though, diverse films have regularly been featured as Best Picture nominees. Instead, the arguably bigger lack of diversity comes from the lack of political diversity in the films.

To explain this, I go back to the biggest discrepancy in the data comparing TV ratings to average box office: why were 2014’s ratings SO high? Again, this year only featured one movie grossing over $100 million dollars, which happened to be its lone blockbuster. So it was an unpopular set of movies that also lacked any major A-list talent. What happened?

American Sniper was the one film.

American Sniper was a major topic on Fox News and other right wing new sites. That’s right, if the Academy is looking honestly at its whole slate of Best Picture nominees, this is pretty much the only film that could be labeled “right leaning” that has been nominated since 2010. (Maybe Zero Dark Thirty too.) The conclusion here is that far from “popular” films, the Academy needs popular films that also appeal to the political-cultural right. (I’m not necessarily recommending that, just acknowledging that this data says.)

Conclusion: A Summary

So here’s my short line summary of the history of the Academy Awards as it relates to popular films and TV ratings.

– By the end of the 1990s, the Oscars featured generally popular films such as Forrest Gump, Titanic, Gladiator and The Sixth Sense, while also featuring critically acclaimed but unpopular films such as Chocolat or The Cider House Rules. 
- Then, from 2000 to 2008, the Oscars featured increasingly fewer popular films, as shown by multiple metrics. The nadir was 2005 to 2008.
– In 2009, the Academy expanded the number of films from 5 to 10 and changed the voting system. As a result, from 2009-2012-ish, the were more popular than the previous five year period.
– Since 2014, the Oscar films have trended downward in popularity, especially among “blockbusters”—films grossing over $250 million—which the Academy hasn’t nominated since 2014.
– The TV ratings have been on a general downward trajectory, though limited evidence (2009, 2010, 2012 and 2014) indicate that popular films can help increase TV ratings.
– The expansion in number of Best Picture nominees helped African-American films/film-makers more than any other category.
– While the films have decreased in popularity, “genre” films have been represented at roughly the same rate. In other words, “dramas”, which tend not to be “popular” have earned about 62-67% of nominations.
– Finally, the biggest discrepancy in the “TV ratings to film popularity” came in 2014, when American Sniper arguably drove the biggest TV ratings in the decade, a film that was the personal favorite of Fox News and its viewers.

I still have a ton of questions to answer on this (some fun, some business) but I think that’s enough for this post.

Debunking the M&A Tidal Wave: Part V – Other Thoughts That Didn’t Make It In

Was I too strong in calling this series, “Debunking the M&A Tidal Wave in Media and Entertainment?

I don’t think so.

I want emphasize the “think” in that previous sentences. I’ve thought about this a lot. I mean, asked myself many, many, many times, “Wait, are you sure there won’t be a tidal wave surge in M&A now that the Justice Department lost in its AT&T battle? Even if M&A has been high the last few years, couldn’t it get higher? Are you implying you think M&A could go down in the future?”

Upon reflection—all that thinking, hat tip to iFanboy—and yes, I think I am appropriate in calling this a debunking. Certain narratives catch hold—coincidentally, like a tidal wave—and most everyone tends to repeat that narrative. The internet started this phenomena, but social media like Facebook and Twitter and Reddit amplify it.

To sum up all I’ve learned, here’s the brief history of M&A in media and entertainment:

– Media and entertainment (and communications/internet) has been consolidating since the 1980s, like all industry.
– After the recovery from the Great Recession, media and entertainment companies began consolidating again.
– By my numbers, the growth in M&A was somewhere between 8%-25% per year in total deal value (depending on the years you pick) and mega-deals (deals over $1 billion in value) increased from 8 in 2011 to 18 in 2017.
– These deals included both horizontal mergers (within the same industry), conglomerations expanding (conglomerates continuing to acquire new businesses) and vertical mergers (within different industries, including distributors such as cable or internet firms acquiring media and entertainment companies).
– Consolidation likely would have continued even if the Justice Department had won their lawsuit preventing the giant and horizontal AT&T-Time Warner Merger.

Phew. Sorry, I had to get that out.

Knowing what we know above, we can use that as our baseline. For any new information on M&A, we can update our priors, to use Nate Silver speak. Basically, if a new deal is announced or a current deal opposed by the government, we have a solid context to understand its impact on the larger M&A in media and entertainment (and communication/distributors/tech/social media) landscape.

For today, any time I dive super deep into a topic, I end up with a bunch of stray thoughts that don’t quite fit in any of my other articles. Today is the catch all round up of those pieces.

Other Thought 1: The Chaos of the Trump Administration

Ignoring the politics of the current administration—and how can you?—what does President Trump and Gary Cohn/Ajit Pai/Wilbur Ross mean for how entertainment companies conduct business? Really, the daily tweets and outrages for liberals or the perceived economic boom times for conservatives matter much less for how he had changed the regulatory environment for business.

But some of those Trump tweets matter. Like how he tweeted opposing the AT&T merger, praising the Disney-21st Century Fox merger and supporting Sinclair/Tribune. In each case, either base political calculations or personal relationships determined his support, not larger idealistic concerns (either free market or pro-consumer). In AT&T’s case, he hates CNN. In Disney’s case, he loves Rupert Murdoch, whose Fox News also supports him. In Sinclair, I think he knows he has a friendly voice supporting his policies.

Uncertainty is the key, along with the certainty that the key is winning Trump by pledging allegiance to him. That’s how companies can win in the short term, while America’s economy moves towards a rent-seeking/crony capitalist future that curtails economic growth. In the mean time, M&A will proceed apace as the key to execution means wooing Trumps favor. Before you decide to do a deal, think, how do we spin this to make Trump look good, while crossing our fingers Democrats don’t punish us for that?

Speaking of decisions…

Other Thought 2: What decisions can we make off this information?

Imagine you’re a major executive at a major studio, communications provider (cable, satellite or telco) or production company. Maybe you’re the boss or the head of his/her corporate strategy or business development team. The key question following a judge’s approval of the AT&T-Time Warner merger is: how should this influence our decision-making going forward?

Now, if you build it, they will come. In business, this means if you build a team with a mission, that team will recommend decisions in its interest. If you have a team devoted to assessing and executing mergers & acquisitions, they’ll probably recommend that you make a lot of mergers & acquisitions. That team—and its likely influential leader—would therefore recommend most CEOs be aggressive in their deal making. Hence, they probably read a lot into the AT&T merger decision as the green light for future mergers.

Ignore that team/leader.

If a merger with a competitor or supplier or other company makes sense economically, it probably made sense no matter which way this decision went. Now, it likely would change the probability on one line of the economic model—the line one the costs if the merger fails—but I would argue that would only apply to deals that almost exactly mimic Comcast-NBCU/AT&T-Time Warner style deals, meaning it would mainly apply to Comcast. And I don’t think Comcast CEO Brian Roberts has any desire to slow down his deal-making.

What about the information I’ve provided showing the huge surge in deal-making going on? Should this influence executives? Maybe.

The case would be strategic. If everyone around you is getting larger, then to continue to be able to negotiate with suppliers or be able to gain a presence in the marketplace, you may need size to compete. If you’re Discovery and Scripps, facing a world with shrinking cable subscribers, doubling the number of channels under negotiations may help keep your affiliate fees higher. Same with movie studios: Disney will be able to negotiate great revenue shares with theaters if they own 50% of the box office, so maybe you need size to compete with that.

But for that strategic case, I could trot out an early version of my “Theme 3: Strategy is Numbers!” At the end of the day, you don’t win in entertainment by simply being the largest player in the world. This isn’t a board game like Risk or Settlers of Cataan where simply being the biggest or lasting the longest means you win. You win by generating cash for your shareholders.

If the deals to get bigger end up costing you more in interest payments than they return in cash, then shareholders will lose money, even with the size. This is usually exacerbated by vertical deals, but all deals risk costing shareholders money. If anything, the frothier the M&A environment, the higher the prices paid, which increase the likelihood that deals don’t make economic sense.
In all, M&A in the larger sphere is interesting, but not determinative on the decisions you need to make as a decision-maker.

Other Thought 3: I’m even more skeptical of conclusions from the M&A data than I was before.

I can’t get over how noisy M&A data is. So noisy.

When you read sweeping conclusions in breathless reports about M&A, remember this. The biggest deals have a huge impact, but are really small in number, while the timing can fluctuate a lot over a given year, which can drastically change the conclusions. a lot, impacting any quarterly or yearly analysis.

The first impact of this uncertainty is to really hinder drawing trends underneath the data. Like say, “Oh look, the majority of deals are about developing innovation” or “achieving economics of scale” or that deals tend to be horizontal or vertical in nature. I’m also hesitant to point to explanations for why M&A is happening, besides that M&A is the natural state of industry in America.

Take the explanation that executives are fearful of the rise of Netflix, Youtube, and Amazon and disruptive business models. That’s a great narrative. But consider that Comcast tried to buy Disney in 2004, did buy NBC-Universal in 2010 and Disney has been buying big new businesses such as Pixar, Marvel, Lucasfilm and Maker Studios. If we tried to quantify this trend, we just couldn’t do it.

The second impact is I tend to look skeptically at any explanation that M&A is increasing year over year based on the most recent data. Again, it just won’t hold up to analytic scrutiny if you can move one or two deals and change the whole picture.

Other Thought 4: Explaining the M&A total number of deals in 2007/2008

In Part IV of this series, I pointed out that in 2007, the number of M&A deals exceeded 1,000. That’s huge, compared to the 800 or so deals we’ve averaged in most of the 2010s. Even though I dismissed this number when making my prediction, it doesn’t mean it doesn’t beg for an explanation.

I have two theories.

Theory 1: 2007 to 2008 was the peak of consolidation of bigger players of smaller mom and pop shops. Basically, this theory says in the 2000s small groups of cable providers, radio stations and independent broadcasters were swallowed up by larger groups. While we focus on the giants of cable, we forget that in the 2000s there were hundreds of cable companies, maybe even thousands. Yet a lot have been swallowed up by the larger players. Now, these deals were sometimes for cable providers as small as a few hundred thousand people, so they just didn’t rate a huge value. Now that they are gone, the number of deals has gone down, but the total value has gone up.

Theory 2: In the 2007 financial crisis, some businesses were divesting not merging. This makes more sense, and I believe one article mentioned this was happening, but honestly I don’t have the data to prove it. If I had Thomson-Reuters data, this is what I would definitely explore.
So I can’t prove either theory above, but they would make for interesting future study.

Other Thought 5: Horizontal versus vertical merger discussions were overblown.

One of the legal hot takes was that the Justice Department had typically ignored vertical mergers and this is what made the move against AT&T so bold. I have two counters.

First, the Justice Department didn’t do a great job of stopping horizontal mergers either.

In my data set, I see a ton of horizontal mergers that went through without scrutiny. In just 2016 and 2017, we saw announced horizontal mergers in broadcast (Sinclair and Tribune), theaters (Cineworld and Regal; Dalian Wanda with two theater chains), radio (Entercom and CBS Radio), conglomerate (Disney and 21st Century Fox), networks (Discovery and Scripps), and other cable/cellular companies, most of which passed scrutiny. So the Justice Department hasn’t done a great job stopping horizontal mergers, which makes the focus on vertical mergers…strange.

Second, the Justice Department has looked skeptical at vertical mergers. Namely, the Comcast-NBCUniversal deal, that it ultimately blessed with many conditions.

Overall, this is one of those data problems where we shouldn’t rely on the sparse data too much. There just aren’t a ton of examples and other factors may explain the conclusions better. Like say size. Many vertical deals just involve really small companies being acquired.

Honestly, just because this vertical deal was successful at trial doesn’t mean future deals will be as well. If cable and satellite companies keep increasing prices after deals clear approval—as both Comcast and AT&T have done—well a future government many decide that these deals aren’t great for consumers.

And wouldn’t that be something.