Is The Connected World Killing Predictive Modeling?
from the the-speed-of-information-is-faster-than-your-algorithm dept
Here's an opinion piece that caught my eye, suggesting that the interconnected world and things like Twitter mean that predictive modeling tools for things like retail sales may be in trouble. Effectively, the argument can be summed up as: information flows faster than your algorithm. I'm not sure it's really necessarily true, but it's certainly worth thinking about. Specifically, he's suggesting that as much as you can try to model "expected behavior" you simply cannot predict or measure sudden flash-fads, which are more common and more impactful with the speed of information these days.The example he uses is where Michelle Obama recently wore a J. Crew outfit, driving sales of that outfit through the roof. No predictive model could expect that. In some ways, this actually reminds me of another recent story as well. Comedian David Chappelle was apparently in Portland and told a couple people he was planning to show up at a certain city square to do an impromptu midnight outdoor show with a tiny amp and microphone he had just purchased. But in the course of about seven hours, the news spread rapidly via Twitter and Facebook. Chappelle had expected perhaps 200 people, and estimates in the end put the number at many thousands of people (the small amp apparently couldn't amplify his voice enough, and the large crowd became such a concern that he basically sent everyone home after a few attempts to get a bigger amp). While it didn't involve an algorithmic predictive model, this case involved Chappelle's human predictive model that over the course of a few hours you could maybe expect 200 people who would (a) find out about it (b) be nearby and (c) be willing and able to come out at midnight. But the ease of communication changed that equation and made it a lot more difficult to predict the outcome.
Now, of course, the issue with both of these are that they may be outliers. Most other clothing at J. Crew probably followed a typical predictive sales path. And a less famous comedian would probably struggle to get anywhere near 200 people to show up. So, I'd say I'm not at all convinced (as the article posits) that Twitter "confounds" predictive modeling. I think it still requires other random events to occur -- and those have always happened in the past. Perhaps the interconnected nature of the world today can massively amplify a sudden flash fad, but that doesn't necessarily mean you toss predictive modeling out the window. Considering it was such an odd claim to use a few random outliers to damn an entire useful tool, it seemed worth digging a bit deeper... and (surprise!) it turns out that the guy who wrote the article runs a company selling a tool that competes with predictive modeling software focusing on "behavioral analytics." So, his argument is basically a strawman against predictive modeling that uses some outlier data without any evidence of a real trend. I'm certainly interested in the ability of social media to amplify a fad, but I don't think it has a really serious impact on most predictive modeling.
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Filed Under: flashmob. randomness, predictive modeling
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Kudos
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Modeling
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We communicate more quickly, and that will always have an effect. But at what point does a human speed transaction change for that communication? Hmmm.
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Yawn
Actually, it would be kind of cute to incorporate Social Web content into the data warehouse for social trend analysis (and I'm fiddling with this right now: ECMI) but that would almost certainly get stomped on by everyone (EFF, ACLU, ...). I've done autonomous models of this type before. In any case, the standard predictive model is so well entrenched that it will take quite a while, or a few extremely successful players, to change the playing field. The compute cloud may also change this, especially for smaller players.
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The models are wrong.
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Does behavior analysis fall under the realm of predictive models? I mean, what's the purpose of it if it can't make predictions? What good would his behavioral analysis be if it can't make predictions? Seems rather ironic that he's saying predictive modeling doesn't work yet he's trying to sell something to help people make predictions.
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Fundamental Theorem
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Re: The models are wrong.
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Re: Fundamental Theorem
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Re:Fundamental Theorem
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Re: Fundamental Theorem
Jack Pine wrote:
As is well known, it doesn’t.
Think of the economy as a dynamical system. Or, for a simple (but mathematically useful) analogy, consider the suspension system of a car. The springs are the error-correcting mechanism: they represent how the market adjusts to new information. But there is also the inertia of the car body: this represents expectations that things will continue the way they have in the past. So when you hit a bump, the springs try to move the car body to a new position, but the inertia makes it overshoot. Then the springs pull the other way, and it overshoots again. So it ends up oscillating. If the pattern of bumps matches the resonant frequency of the system, the result can actually damage the car. Not to mention the effect on the occupants...
Which is where the shock absorbers come in. They are designed to dissipate energy from the system, and slow down the rate at which it responds to stimuli. In short, they waste energy, and by doing so, they dampen down the tendency towards instability. The equivalent in the economy is Government regulation. That, too, reduces the efficiency with which the system responds to new stimuli. And by doing so, it makes it less likely to self-destruct.
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Re: Re: Fundamental Theorem
I would argue that a system that quickly responds to new stimuli is an economically more efficient system. If someone is going to punch you and you respond 1 minute late you're already hurt by then. Allow people to respond to stimuli, lets not have the government force us not to be informed about important news that we should know. This sounds like an attempt to limit our freedom of speech in ways that the government has no business doing. After all one of the assumptions about free markets and why they cause more efficiency is that information is freely available.
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Predictive Modeling For Me When I Worked
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Predictive modeling just now has to take into account how fast information flows. This is just an evolution.
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