People in the business of reviewing business advice get it by the truckload. After a while, every book delivered to your door looks just like the last one. All strategy prescriptions are backed by comprehensive research and every author is impressively credentialed. It is hard to determine who is adding value to the conversation for two reasons: One, no one has time to read all these books; two, there's tremendous incentive for an author to spin hard conclusions out of mucky data.
"It's very tempting, consciously or subconsciously, to impose a pattern on data that isn't really there in order to support a hypothesis," says Michael Raynor, co-author with Mumtaz Ahmed of The Three Rules: How Exceptional Companies Think. "After all, if you stare at the poundcake long enough, Elvis's profile will surely appear."
“为了支持一个假设，作者总是自觉或下意识地给数据强加一个其实并不存在的理论模型，”迈克尔•雷诺说。“毕竟，如果你盯着一块磅饼足够长时间，猫王的轮廓就一定会出现（流行音乐巨星猫王以喜欢磅饼著称——译注）。”雷诺曾与蒙塔•艾哈迈德合作撰写了《三个规则：卓越的公司如何思考》(The Three Rules: How Exceptional Companies Think)一书。
The Three Rules conforms to type by citing impressive study numbers -- 25,000 companies over 45 years -- then allocates several pages to unpacking their study methodology. So I asked Raynor how he reads business books. Is there a way to assess research claims quickly, respectfully, but skeptically?
Raynor's first prescription is to remember that persuasive storytelling requires that the storyteller leave out the weeds. This is especially relevant to corporate biographies, since the form requires the narrator to omit people and events that turn out to be irrelevant only in hindsight.
His second note of precaution is about what to do when presented with causal claims. Most smart people know not to mistake correlation for causality, but we do it all the time. Or we dismiss someone else's claims by saying that they haven't proved causality (just because one event happened after another doesn't mean the first happening caused the second). True enough, says Raynor, but "nobody has evidence of causality." Causation exists -- there would be less incentive to leave the house in the morning if it didn't -- but it's difficult to prove in complex systems (and any system that includes humans is a complex system).
Raynor also advises watching out for what Phil Rosenzweig dubbed "the halo effect." In other words, make sure you aren't letting the reflected glory of a company's signature achievement in one arena color your view of their performance in other areas.
此外，雷诺还建议我们小心提防菲尔•罗森茨维格所称的“晕轮效应”(the halo effect)。换句话说，一定不要让一家公司在某个领域的标志性成就所反射的荣耀影响你评价它在其他领域的表现。
Next, be aware of the data's limitations and your own. Why dwell on your own limitations? Our intuition as to what's statistically significant can be terrible. When we pick up a book that profiles certain companies, we tend to assume that the companies being profiled have, in fact, delivered noteworthy performance.
But "that's an assumption that's worth questioning," says Raynor. "If two companies differ in profitability by 0.1% in return on assets over a five-year period, would you study those two companies to understand behavioral differences that drive performance differences? Of course not. Because it's too small a difference over too short a period of time."
So watch for sample selection and time frame. "In a short season, luck can overcome skill."
Raynor's last note concerns an all too common criticism of business success studies. Say a company 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 author botched the analysis. ("Hey wait a minute, you said that company was great and then three years 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 perpetually excellent before you can learn something [from them] is nonsense," Raynor says.
雷诺的最后一个建议涉及商业成功案例研究频频遭到指摘的一面。一家受到某本流行商业书籍称赞的公司——比如吉姆•柯林斯在其2001年的著作《从优秀到卓越》(Good to Great)一书中表扬过的电器城公司( Circuit City)——最终令人大失所望。批评家们随后一拥而上，纷纷指责作者搞砸了研究（“嘿嘿，等一下，你不是说这家公司非常了不起吗，怎么才过了三年，它就破产了呢？你其实并不知道你自己在说什么。”）这种评价不仅有失公允，而且相当短视。雷诺说：“在他们看来，首先必须好好研究一家永远都表现优异的公司，然后才可以从中提炼出某种结论。这种观点完全是无稽之谈。”
The best rebuttal, he says, is to point out that Usain Bolt will probably not be an Olympic gold medal winner at age 60, but that doesn't mean the techniques he uses now will not be worthy of study in years to come.
Our best defense against seeing Elvis in poundcake, however, is one both authors and readers can use daily: Realize that the smartest people in any room appreciate it when you acknowledge data that doesn't support your conclusions. So, in cases where the rules you've devised don't appear to hold up, say so. Mention how you might be wrong, and then present a case for why you believe what you believe anyway, says Raynor. That kind of candor is flattering to your audience's intelligence and -- most importantly -- memorable.