????但流行的商業(yè)管理分析很少有這樣周全的解釋,。出色的企業(yè)會立即被奉為偉大的公司，原因則眾說紛紜,。商業(yè)書刊出版商也總是有它們的最愛：大概有十多年是西南航空（Southwest Airlines）,，今天則輪到了蘋果公司（Apple）。人們各持己見,，將這些公司的成功歸結(jié)于于戰(zhàn)略,、文化、管理能力和其他因素,。

????所有這些解釋都言之有理,，但正確的解釋必須要弄懂所有的相關(guān)事實，弄懂為什么它們比其他解釋更好,。這就是錢德勒的研究成果曾經(jīng)達(dá)到過得標(biāo)準(zhǔn),。不幸的是，當(dāng)今的商業(yè)案例研究往往要靠讀者自己去決定什么是合理的解釋,，讓讀者權(quán)衡證據(jù)是否可靠,。

預(yù)測：接下來會發(fā)生什么

????談到預(yù)測，情況就更糟糕了,。大多數(shù)商業(yè)管理書籍從夸大其辭的解釋更進(jìn)一步,，跳到了毫無根據(jù)的預(yù)測。他們的觀點是既然它在他們那里適用,，那么在你們這里也同樣適用,。這種觀點的基礎(chǔ)是：“這種做法過去有效，因此有望幫助你按照自己愿望來決定未來”,，但這種假設(shè)顯然存在缺陷,。

????做出合理預(yù)測的唯一方法是給出預(yù)測,，然后看看它是否經(jīng)得起反復(fù)的驗證。我不知道如今的商業(yè)管理書籍有哪本曾經(jīng)對它給出的建議進(jìn)行過哪怕能跟科學(xué)方法沾得上一點邊的預(yù)測準(zhǔn)確性驗證,。（對了,，我知道有這樣的一本數(shù)。但它是我自己寫的,，因此我本人不方便評價它的優(yōu)劣,。）

????現(xiàn)實世界非常復(fù)雜，要進(jìn)行控制性的實驗幾乎不可能,。但無法提供預(yù)測準(zhǔn)確性的證據(jù),，并不是說我們就能改變證據(jù)規(guī)則。而且,，把虛構(gòu)的事情當(dāng)做事實只會具有危險的誤導(dǎo)性,。只有當(dāng)案例研究包含了可靠的因果關(guān)聯(lián)，它們才能有助于我們準(zhǔn)確地預(yù)測結(jié)果,。

????有了描述,、解釋或預(yù)測的支持，案例研究能為我們提供幫助,，但方式可能不盡相同,，可靠性也各異。因此,，下次再有人開口說“比如”時,，你可得好好想想。

????Michael Raynor是《創(chuàng)新者宣言：自我顛覆,，脫胎換骨》（The Innovator's Manifesto: Deliberate Disruption for Transformational Growth）一書的作者,，也是咨詢公司Deloitte Consulting LLP的董事。他住在多倫多近郊,。

????When it comes to the explanations offered by popular business analysis, however, there is rarely such care. Companies with great track records are immediately lionized as great companies for all sorts of reasons, and the business press always has a favorite. For a decade or more, it was Southwest Airlines; today it's Apple's (AAPL) turn: there are any number of competing arguments that can attribute success to varying combinations and types of strategy, culture, leadership, and other elements.

????All of these explanations make sense, but the right explanation needs to make sense of all the pertinent facts, and it needs to make sense of them better than the alternatives. This is a standard that Chandler's work rose to. But when it comes to today's business case studies, unfortunately, it is often left to the reader to determine what the competing explanations might be and to weigh the evidence.

Prediction: What happens next

????When it comes to prediction, it gets worse. Most business books move from overstated claims of explanation to entirely unjustified predictions based on the notion that because something seems to have worked for them over there it will work for you over here. This belief is based on a flawed assumption that using ideas that worked out in the past will somehow allow you to shape the future in a desired way.

????The only way to justify a prediction is to make one and see if it holds up under repeated tests. I don't know of any business book that has subjected its prescriptions to tests of predictive accuracy that bear even a distant relationship to the scientific method. (Well, I know of one. But I wrote it, so I'm not in a position to offer an opinion on its merits.)

????The real world is a messy place, which can make controlled experiments impossible. But the inability to generate evidence of predictive accuracy does not allow us to change the rules of evidence. And it is dangerously misleading to treat fables as fact. Only when case studies are elaborations of a validated connection between cause and effect can they contribute to our ability to predict outcomes accurately.

????Case studies can be useful in support of description, explanation or prediction, but in different ways and with different degrees of confidence. So the next time someone begins a sentence with "for example," think twice.

????Michael Raynor is the author of The Innovator's Manifesto: Deliberate Disruption for Transformational Growth and is a director at Deloitte Consulting LLP. He lives just outside of Toronto.