大數(shù)據(jù)的預(yù)測(cè)盲區(qū)
????有什么問(wèn)題是數(shù)據(jù)和分析不能回答的嗎? ????這都存在于一定的范圍內(nèi)。要知道,相對(duì)于我們的潛力,我們做得有多好,與某件事物在本質(zhì)上有多大的可預(yù)測(cè)性,二者是有區(qū)別的。以棒球?yàn)槔?,雖然分析師已經(jīng)研究棒球很久了,但是即便是最優(yōu)秀的棒球隊(duì),勝率也只有三分之二。就算是最優(yōu)秀的擊球手,也只有40%的機(jī)會(huì)上壘。所以在某種意義上,它在本質(zhì)上仍然是不可預(yù)測(cè)的,但是我們有了比較好的方法來(lái)衡量和了解我們所知道和不知道的事情。 ????在很多領(lǐng)域,數(shù)據(jù)分析還沒(méi)有廣泛應(yīng)用。比如我在我的《信號(hào)與聲音:為什么很多地震預(yù)測(cè)失敗了,但有些預(yù)測(cè)說(shuō)中了》一書(shū)中談到了地震的預(yù)報(bào)。千百年來(lái)人們一直在嘗試預(yù)報(bào)地震,我們了解了一些現(xiàn)象——比如加州的地震要比新澤西州多,但是在某一時(shí)刻及時(shí)、精確地預(yù)報(bào)一場(chǎng)地震的能力可以說(shuō)毫無(wú)進(jìn)展。甚至就連經(jīng)濟(jì)也是如此,一旦我們?cè)噲D做出長(zhǎng)期的經(jīng)濟(jì)預(yù)測(cè),我們大多數(shù)都會(huì)做得比較差。 ????是否有行業(yè)已經(jīng)在關(guān)注大數(shù)據(jù)分析可能帶來(lái)的影響? ????有時(shí)并一不定是非常熱門(mén)的行業(yè)。比如零售企業(yè)有大量的每個(gè)消費(fèi)者的交易記錄,也有大量的供應(yīng)鏈管理方面的數(shù)據(jù),所以在制定庫(kù)存優(yōu)化戰(zhàn)略、定價(jià)優(yōu)化戰(zhàn)略以及供應(yīng)鏈應(yīng)急管理戰(zhàn)略時(shí)都會(huì)用到大數(shù)據(jù)分析。并不是非常搶眼的東西,但這些人有非常好的數(shù)據(jù)儲(chǔ)備,通常是高質(zhì)量的數(shù)據(jù),因此可以做出更好的決策。我相信有些企業(yè)已經(jīng)這樣做了,因此它會(huì)帶來(lái)一些前所未有的效率。 ??? 另外還有其它案例,比如你可以看看電視行業(yè)是如何讓人們花錢(qián)的。我認(rèn)為廣告行業(yè)定位顧客的手段變得更先進(jìn)了。諷刺的是,這種效率從某種程度上也給媒體公司帶來(lái)了壞處。廣告業(yè)有一句老話:“你只有一半的廣告預(yù)算花對(duì)了,但你不知道是哪一半?!爆F(xiàn)在人們可能知道那是哪一半了,所以他們只會(huì)花這一半。 ????人們能否通過(guò)數(shù)據(jù)或者分析法精確預(yù)測(cè)股市? ????股市是一場(chǎng)競(jìng)賽,你在和其他股民進(jìn)行競(jìng)爭(zhēng)。所以問(wèn)題來(lái)了:是否股市的某些交易者要比其他人更厲害?我認(rèn)為答案可能是“是的”。我不是一個(gè)純粹的股民,不過(guò)我玩撲克很久了。我認(rèn)為玩撲克跟炒股在很多方面是相通的,你知道有些人越到長(zhǎng)期越得心應(yīng)手,而且更擅長(zhǎng)應(yīng)對(duì)不確定因素等等。不過(guò)股市里還有很多不穩(wěn)定因素和很多運(yùn)氣成分,一個(gè)市場(chǎng)周期可以長(zhǎng)達(dá)幾個(gè)月或幾年。很多不正當(dāng)?shù)拇碳ひ蛩乜赡軙?huì)影響股市。所以盡管我認(rèn)為有些很好的交易者在短期甚至五到十年內(nèi)都可以順風(fēng)順?biāo)?,但最終很大程度還是由運(yùn)氣決定的,所以很復(fù)雜。 |
????Are there any questions out there that can't be answered using data and analytics? ????So I think it all exists along a spectrum. It's important to know, too, that there's a difference between how good we are relative to our potential and how intrinsically predictable something might be. So for example if you look at baseball where analytics have come an awful long way, well it's still the case that the best baseball teams only win two-thirds of their games. The best hitters only get on base about 40% of the time. So it's still intrinsically unpredictable in a sense, but we have a good way of measuring and knowing what we know and what we don't know. ????But there are a lot of fields where analytics have not come very far. I discuss earthquake forecasting in my book [The Signal and the Noise: Why So Many Predictions Fail -- but Some Don't] for instance, where people have been trying for centuries. We know something -- there are more earthquakes here in California than in New Jersey -- but the ability to anticipate a particular earthquake with any precision at a particular moment in time has not gone very well at all. Even economics -- when we try to do long-term economic forecasting, it has been pretty poor for the most part. ????Are there any industries out there that are overlooking the possible impact of big data analytics? ????It's sometimes industries that aren't very sexy necessarily, so big retail businesses for example have tons of records on every consumer transaction they have [completed]. They have a ton of data on supply chain management, so things like that in terms of optimal inventory strategies or optimal pricing strategies or robust strategies for disruption in the supply chain. Not super-sexy stuff, but those people have really good data sets, often high quality data, and can make better decisions as a result. I'm sure that some are doing it already, and there are some efficiencies there that you weren't seeing before. ????There are also cases like if you look at how people consume television, for example. I think the advertising industry is something that's gotten more sophisticated in terms of targeting customers. The irony is that efficiency has become harmful in some ways for media companies, because what was the old adage? "Half your advertising budget is well spent, but you don't know which half." Now people might know which half, so they're only spending half as much. ????Can people use data or analytics to accurately predict the stock market in any way? ????The problem is the stock market is this whole contest where you're competing against other creators. So the question is: Are there some traders that are better than others? I think the answer is probably, Yes. I'm not a pure markets guy, I played poker long enough which I think has parallel skills to trading in many respects where you know that some people are better over the long-term and better at accounting for uncertainty and so forth. But there's a lot of volatility and a lot of luck where a market cycle can last for months or years. There are a lot of perverse incentives that get in the way. So while I think there are some good traders, in the near term, even over a period of five or 10 years, it will mostly be dictated by luck, so it's tricky. |