搞管理的与搞数据的如何和谐共处

    这本书最实用的特色之一，就是详细列出了一系列清单，明确了管理人员和量化分析师彼此应该预期从对方那里获得什么。 一个范例提示：“作为一个企业决策人员，如果你不明白某件事情的话，你应该礼貌地把这件事情退回原处，要求相关人员做出不同的或者更好的解释。”这或许似乎是显而易见的，但许多不擅长数学的人员怯于敦促相关人员做出澄清。

    达文波特指出：“我们看到，在一些机构里，量化分析人员似乎喜欢让‘普通’企业管理人员觉得自己很愚蠢。他们会说类似如下这样的话 ‘你想必知道什么是回归分析吧？’或‘对不起，对我来说，卡方检验简直是太基本的常识了，实在是没有必要加以解释。”

    达文波特主张，如果你听到这样的废话，那么很可能是你自己的过错。他写道，大多数数据分析人员都是“非常容易共事的人，然而在那些聘请了量化分析师、但在面临重要决策时又忽略他们的机构里，数据分析人员有时会出现态度问题，量化分析师和大多数人一样，当自己得到尊重时，就会尊重他人。” （财富中文网）

    译者：iDo98

    One of the book's most practical features is a series of checklists spelling out exactly what managers should expect from quant jocks and vice versa. A sample tip: "As a business decision maker, you should politely push back if you don't understand something and ask for a different or better explanation." That might seem obvious, but many non-math types are too intimidated to press for clarity.

    "We've seen a number of organizations in which quantitative people seemed to delight in making 'normal' businesspeople feel stupid," Davenport notes. "They would say things like, 'Surely you know what regression analysis is?' or 'I'm sorry, a chi-square test is just too elementary for me to have to explain.'"

    If you're getting that kind of guff, Davenport contends, it's probably your own fault. Most data analysts are "wonderful people to work with," he writes, but attitude problems sometimes pop up "in organizations that somehow hired quantitative analysts but ignore them when important decisions come along. Quants, like most people, respect others when they are respected." Enough said.