I’ve been reading The Halo Effect: … and the Eight Other Business Delusions That Deceive Managers by Phil Rosenzweig. It’s all about how businesses create stories to explain success and failure instead of looking at hard data and analyzing what really happened. For example, when Cisco was riding high, its employees were happy, its CEO had a brilliant sense of making acquisitions, etc. When Cisco’s fortunes flopped, suddenly those same employees had been miserable and the CEO had been making acquisitions foolishly.
And did you ever wonder how the newscasters on Bloomberg know precisely why some index is up today, before they’ve had time to study it, or poll people buying stocks, or something? The answer, of course, is they have no idea: they’re just picking a plausible explanation and hoping you’ll buy it.
This is what film has been doing for the past thirty years. In a recent article, If audiences don’t want women as leads, why did Aliens succeed?, I pointed out some of the serious questions that somebody ought to be asking before proclaiming that mainstream movies with female leads don’t do so well, except when they do, which doesn’t count – and doesn’t raise any questions. That’s a story, not an analysis of actual data with sound conclusions.
You can certainly look at numbers and see that most of the best-performing movies feature male leads, and lots of movies featuring female leads perform poorly. Then again, lots of movies featuring male leads also flop. And, as William Goldman explained, lots of movies featuring women exceed industry expectations, but instead of investigating them to see why they did well and how their success can be replicated, they get dismissed as non-recurring phenomenon. Wow. With jargon like that, it almost sounds scientific.
It’s not. When a movie featuring a white man flops, the industry at least concocts a story to explain it, and sometimes there may even be genuine analysis involved: perhaps it was marketed badly, or it was released at the wrong time or the film itself was bad. Rarely do you ever hear, “I guess no one likes [insert male lead’s name] anymore.” Never, ever do you hear, “The audience just doesn’t want to see movies about white guys.”
But when it’s a movie about a woman (or a man of color), that’s all the story we get: it had a woman, or a man of color, so it flopped. This, by the way, is what belies the industry’s claims that it’s the audience’s bigotry, not the industry’s, forcing women (and others) out of lead positions in films. If the industry was so bigotry-free, they’d be asking the same questions about female-led flops as they ask about male-led ones. They’d be investigating to see if there’s a way to turn it around to their advantage.
So before you keep accepting this alleged bit of “numbers don’t lie” logic, consider this. Here’s a list of questions the industry would be able to answer (or at least show us their work so far) if they had ever scientifically examined the claim that merely casting a woman in a non-“chick flick” film causes it to flop:
- Who precisely isn’t watching these movies?
- Why don’t they want to see them?
- What, if anything, would persuade them to see them?
- Are they influencing others not to see them?
- Could there be other factors influencing the film’s success, such as bad marketing or the film sucking or, you know, any of those things they examine when a male star’s latest film flops?
- ETA: what did the movie earn per theater, or per seat (ticket sold)? These are granular metrics the industry considers when trying to figure out why a film did unexpectedly well or poorly. Sometimes these numbers indicate stuff like whether the movie would have profited more with a wider or narrower release (how many theaters played it).
You can probably come up with others; stick them in the comments, and I’ll edit the post. These are precisely the kinds of questions the industry bothers to ask when films starring white males flop. And whenever I asked these questions of film pros claiming films featuring women just can’t perform, they had clearly never considered them before. Must be sexism, they’d admit with appropriate sadness in their tone. I’d point out that I grew up in a very sexist place and time, yet all the hardcore misogynist guys saw Aliens. “Must’ve been for the special effects,” they’d suggest. I’d point out that there was no shortage of SFX bonanzas in the 80s for misogynists to watch instead. They’d suddenly have someplace else to be.
An extremely important part of data analysis and science in general is: asking the right questions. Without that foundation, the best data in the world won’t inform you of anything meaningful. Sometimes the questions a researcher poses (or lack thereof) reveals a bias on his or her part. Biases make numbers “lie” through the humans that interpret them. The desire to make the numbers tell a particular story is the worst kind of bias an analyst can have.