英語(yǔ)課外閱讀知識(shí)
英語(yǔ)課外閱讀知識(shí)
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英語(yǔ)課外閱讀1
People in the business of reviewing business advice get it by the truckload. After a while, everybook delivered to your door looks just like the last one. All strategy prescriptions are backed bycomprehensive research and every author is impressively credentialed. It is hard todetermine who is adding value to the conversation for two reasons: One, no one has time toread all these books; two, there's tremendous incentive for an author to spin hard conclusionsout of mucky data.
商業(yè)建議類書籍的書評(píng)人總有汗牛充棟的資料供其研究。每每一本書遞送至家門口時(shí)，它看上去總像是最后一本。所有的戰(zhàn)略處方皆有全面的研究支持，每位作者似乎都具備令人敬畏的資質(zhì)。出于兩個(gè)原因，我們很難確定誰(shuí)正在為相關(guān)討論增添價(jià)值。其一，沒有人有那么多時(shí)間讀完所有這些著作;其二，作者往往有很強(qiáng)的動(dòng)機(jī)從令人生厭的數(shù)據(jù)中歸納出確鑿的結(jié)論。
"It's very tempting, consciously or subconsciously, to impose a pattern on data that isn'treally there in order to support a hypothesis," says Michael Raynor, co-author with MumtazAhmed of The Three Rules: How Exceptional Companies Think. "After all, if you stare at thepoundcake long enough, Elvis's profile will surely appear."
“為了支持一個(gè)假設(shè)，作者總是自覺或下意識(shí)地給數(shù)據(jù)強(qiáng)加一個(gè)其實(shí)并不存在的理論模型，”邁克爾•雷諾說。“畢竟，如果你盯著一塊磅餅足夠長(zhǎng)時(shí)間，貓王的輪廓就一定會(huì)出現(xiàn)(流行音樂巨星貓王以喜歡磅餅著稱——譯注)。”雷諾曾與蒙塔•艾哈邁德合作撰寫了《三個(gè)規(guī)則：卓越的公司如何思考》(The Three Rules: How Exceptional Companies Think)一書。
The Three Rules conforms to type by citing impressive study numbers -- 25,000 companiesover 45 years -- then allocates several pages to unpacking their study methodology. So Iasked Raynor how he reads business books. Is there a way to assess research claims quickly, respectfully, but skeptically?
《三個(gè)規(guī)則》同樣遵循了這類書籍的常規(guī)范式：援引令人印象深刻的研究數(shù)字(2.5萬(wàn)家公司45年的發(fā)展歷程)，然后使用幾頁(yè)的篇幅闡述其研究方法。于是，我詢問了雷諾一個(gè)問題：他自己是如何閱讀商業(yè)書籍的?有沒有一種方式讓我們謙卑且迅速地評(píng)價(jià)研究結(jié)論，但同時(shí)又不放棄質(zhì)疑精神呢?
Raynor's first prescription is to remember that persuasive storytelling requires that thestoryteller leave out the weeds. This is especially relevant to corporate biographies, since theform requires the narrator to omit people and events that turn out to be irrelevant only inhindsight.
雷諾的第一個(gè)處方是：務(wù)必記住，有說服力的故事需要講故事的人忽略雜音。對(duì)于公司傳記類書籍來說，這一點(diǎn)尤為中肯，因?yàn)檫@種體裁需要講述者省略在事后看來無(wú)關(guān)宏旨的人物和事件。
His second note of precaution is about what to do when presented with causal claims. Mostsmart people know not to mistake correlation for causality, but we do it all the time. Or wedismiss someone else's claims by saying that they haven't proved causality (just because oneevent happened after another doesn't mean the first happening caused the second). Trueenough, says Raynor, but "nobody has evidence of causality." Causation exists -- there wouldbe less incentive to leave the house in the morning if it didn't -- but it's difficult to prove incomplex systems (and any system that includes humans is a complex system).
他的第二個(gè)告誡與如何評(píng)價(jià)作者的因果關(guān)系論斷有關(guān)。大多數(shù)聰明人都知道，不要把相互關(guān)系錯(cuò)誤地理解為因果關(guān)系，但我們一直都在犯這個(gè)錯(cuò)誤?；蛘?，我們常常以其他人沒有證明因果關(guān)系為由，不予理會(huì)他們的論斷(僅僅因?yàn)槟骋粋€(gè)事件發(fā)生在另一個(gè)事件之后并不意味著前者導(dǎo)致了后者的發(fā)生)。的確如此，雷諾說，但“沒有人能夠拿出因果關(guān)系的證據(jù)。”因果關(guān)系確實(shí)存在——要是不存在的話，人們恐怕就沒有那么大的激勵(lì)一大早離開家去工作了——但在一個(gè)復(fù)雜的系統(tǒng)中，我們很難證明這一點(diǎn)。需要說明的是，任何有人類存在的系統(tǒng)皆是復(fù)雜的系統(tǒng)。
Raynor also advises watching out for what Phil Rosenzweig dubbed "the halo effect." In otherwords, make sure you aren't letting the reflected glory of a company's signature achievementin one arena color your view of their performance in other areas.
此外，雷諾還建議我們小心提防菲爾•羅森茨維格所稱的“暈輪效應(yīng)”(the halo effect)。換句話說，一定不要讓一家公司在某個(gè)領(lǐng)域的標(biāo)志性成就所反射的榮耀影響你評(píng)價(jià)它在其他領(lǐng)域的表現(xiàn)。
Next, be aware of the data's limitations and your own. Why dwell on your own limitations? Ourintuition as to what's statistically significant can be terrible. When we pick up a book thatprofiles certain companies, we tend to assume that the companies being profiled have, in fact, delivered noteworthy performance.
接下來要注意數(shù)據(jù)和你自身的局限性。為什么要充分考慮自身的局限性呢?看到具有統(tǒng)計(jì)意義的數(shù)據(jù)時(shí)，我們的直覺或許是非常可怕的。當(dāng)我們捧起一本闡述某些公司的書籍時(shí)，我們傾向于假定這些正在被作者詳細(xì)分析的公司其實(shí)已經(jīng)取得了值得關(guān)注的成就。
But "that's an assumption that's worth questioning," says Raynor. "If two companies differ inprofitability by 0.1% in return on assets over a five-year period, would you study those twocompanies to understand behavioral differences that drive performance differences? Ofcourse not. Because it's too small a difference over too short a period of time."
但“這是一個(gè)值得質(zhì)疑的假設(shè)，”雷諾說。“如果兩家公司的盈利能力差異微乎其微，比如說，某個(gè)五年期間內(nèi)的資產(chǎn)收益率相差0.1%，那么你是否會(huì)悉心研究這兩家公司，以理解導(dǎo)致業(yè)績(jī)差異的行為差異呢?當(dāng)然不會(huì)。因?yàn)檫@個(gè)時(shí)間段太短，而這個(gè)差異又幾乎可以忽略不計(jì)。”
So watch for sample selection and time frame. "In a short season, luck can overcome skill."
所以，我們一定要留意樣本的選擇，以及分析的時(shí)間框架。“在一個(gè)很短的時(shí)期內(nèi)，運(yùn)氣成分很可能大于技能因素。”
Raynor's last note concerns an all too common criticism of business success studies. Say acompany praised in a popular business book -- for example, Circuit City in Jim Collins's 2001Good to Great -- ultimately disappoints. Critics then pile on to say that the authorbotched the analysis. ("Hey wait a minute, you said that company was great and then threeyears later they're in bankruptcy. You don't know what you're talking about.") That's unfair – and shortsighted. "This whole notion that you have to study a company that is perpetuallyexcellent before you can learn something [from them] is nonsense," Raynor says.
雷諾的最后一個(gè)建議涉及商業(yè)成功案例研究頻頻遭到指摘的一面。一家受到某本流行商業(yè)書籍稱贊的公司——比如吉姆•柯林斯在其2001年的著作《從優(yōu)秀到卓越》(Good to Great)一書中表?yè)P(yáng)過的電器城公司( CircuitCity)——最終令人大失所望。批評(píng)家們隨后一擁而上，紛紛指責(zé)作者搞砸了研究(“嘿嘿，等一下，你不是說這家公司非常了不起嗎，怎么才過了三年，它就破產(chǎn)了呢?你其實(shí)并不知道你自己在說什么。”)這種評(píng)價(jià)不僅有失公允，而且相當(dāng)短視。雷諾說：“在他們看來，首先必須好好研究一家永遠(yuǎn)都表現(xiàn)優(yōu)異的公司，然后才可以從中提煉出某種結(jié)論。這種觀點(diǎn)完全是無(wú)稽之談。”
The best rebuttal, he says, is to point out that Usain Bolt will probably not be an Olympic goldmedal winner at age 60, but that doesn't mean the techniques he uses now will not be worthyof study in years to come.
他說，最好的反駁方式是以博爾特為例。你可以指出，到了60歲時(shí)，這位牙買加飛人或許就拿不了奧運(yùn)會(huì)金牌了。但這并不意味著他現(xiàn)在使用的技術(shù)，值得我們?cè)诮窈髱啄昀镒屑?xì)研究。
Our best defense against seeing Elvis in poundcake, however, is one both authors and readerscan use daily: Realize that the smartest people in any room appreciate it when youacknowledge data that doesn't support your conclusions. So, in cases where the rules you'vedevised don't appear to hold up, say so. Mention how you might be wrong, and then present acase for why you believe what you believe anyway, says Raynor. That kind of candor isflattering to your audience's intelligence and -- most importantly -- memorable.
然而，防止在磅餅中看到貓王身影的最佳策略是作者和讀者每天都在運(yùn)用的一個(gè)辦法：你知道，當(dāng)你承認(rèn)有些數(shù)據(jù)不支持你的結(jié)論時(shí)，任何一位絕頂聰明的人都會(huì)贊賞這種態(tài)度。所以說，碰到一些你制定的規(guī)則似乎無(wú)法解釋的案例時(shí)，你最好坦誠(chéng)地指出來。雷諾建議，提醒讀者你可能是錯(cuò)的，然后陳述一個(gè)理由，以說明你為什么依然相信你所相信的觀點(diǎn)。這種坦誠(chéng)不僅僅是為了討好讀者的智力，更重要的是，它令人難以忘懷。
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