Inductive reasoning is much more difficult to do well than is deductive reasoning, since it is a more creative activity. In inductive reasoning, the mind notices that several different things (ideas, events, facts) are similar in some way, brings them together in a group, and comments on the significance of their similarity.

归纳推理比演绎推理更难做好，因为它是一种更具创造性的活动。在归纳推理中，大脑注意到一些不同的事物（观点、事件、事实）在某些方面相似，将它们归为一组，并对它们的相似性的重要性进行评论。

In the example of the Polish tanks cited in Exhibit 17, the events were all defined as warlike movements against Poland. Hence, the inference that Poland was about to be invaded. If, however, the events had been defined as preparations by Poland’s allies to attack the rest of Europe, a quite different inference would have been in order.

在图表17中引用的波兰坦克的例子中，这些事件都被定义为针对波兰的战争行动。因此得出波兰即将被入侵的推论。然而，如果这些事件被定义为波兰盟友为攻击欧洲其他地区所做的准备，那么得出的推论会完全不同。

This brings us to the two major skills one must develop to think creatively in the inductive form:

• Defining the ideas in the grouping

• Identifying the misfits among them

这引出了需要发展两项主要技能才能以归纳形式进行创造性思考：

• 定义分组中的想法

• 识别其中的不匹配项

How to do both things with precision is explained in considerable detail in Chapter 7. But at this point, you need only understand the rudiments of how it is done to be able to distinguish the process from deduction.

如何精确地做到这两点将在第7章详细解释。但在此阶段，你只需理解其基本原理，便能将这一过程与演绎推理区分开来。

How it works
The key technique is to find one word that describes the kind of ideas in your grouping. This word will always be a plural noun (a) because any ‘kind of’ thing will always be a noun, and (b) because you will always have more than one of the ‘kind of’ idea in your grouping.

如何运作
关键技术是找到一个词语来描述分组中想法的类别。这个词总是一个复数名词，因为（a）任何“种类的”事物总是名词，（b）你的分组中总会有不止一种“种类的”想法。

‘Warlike movements’ is a plural noun in this sense, and so is ‘preparations for attack.’

例如，“战争行动”和“攻击准备”在这个意义上都是复数名词。

If you look at the inductive groupings in Exhibit 21, you will easily be able to see that each one can be described by a plural noun: schemes, ways of working, and ways of hurting.

如果你查看图表21中的归纳分组，你会很容易发现每一组都可以用一个复数名词来描述：计划、工作方式以及伤害方式。

The next step is always to check your reasoning, and this is done by questioning from the bottom up. For example, if you see a man who wants to found a city in which only Latin should be spoken, dig a deep hole in the center of the earth, etc., can you infer that this is an ingenious man but not a man of strong practical sense?

下一步总是检查你的推理，这是通过自下而上的提问来完成的。例如，如果你看到一个人想要建立一个只说拉丁语的城市、挖掘地球中心的深坑等等，你能否推断出这是一个富有创造力但缺乏实际感的人？

Yes, you can, or at least you could when the statement was originally written.

是的，你可以，或者至少当这些陈述最初被写下时你是可以的。

By contrast, consider the two examples in Exhibit 22. If you see managers who don’t face reality, won’t countenance criticism, etc., can you infer that they mismanage because they want to? Certainly not; it’s sloppy reasoning and writing.

相比之下，考虑图表22中的两个例子。如果你看到经理不面对现实、不接受批评等，你能否推断出他们管理不善是因为他们想要这样做？当然不能，这是草率的推理和写作。

What about the next one? If productivity is low, overtime high, and prices uncompetitive, can you infer that you have a profit-improvement opportunity? Perhaps, but I can think of three or four other things that could also be labeled indicators of a profit-improvement opportunity.

再看下一个例子。如果生产率低，加班多，价格缺乏竞争力，你能否推断出你有利润改进的机会？也许可以，但我能想到三到四件其他事情也可以被标记为利润改进机会的指标。

In fact, however, this is really a deductive argument masquerading as an inductive one, as you may have remembered from the example in Chapter 3.

然而，事实上，这实际上是一个伪装成归纳论证的演绎论证，正如你可能记得的第3章中的例子。

The low productivity led to the high overtime, which led to uncompetitive prices. Whenever you have only one piece of evidence for anything, you are forced to deal with it deductively.

低生产率导致高加班，这又导致了价格缺乏竞争力。只要你对任何事情只有一个证据，你就只能通过演绎的方式来处理它。

Thus, the point implied at the top is something like ‘Our prices are high because our productivity is low.’

因此，顶层暗含的观点类似于“我们的价格高是因为我们的生产率低。”

The point here is that inductive reasoning requires more than simply observing similarities among facts or events; it demands a careful process of grouping and inference based on plural nouns and precise reasoning.

这里的关键是，归纳推理不仅仅是观察事实或事件之间的相似性，它需要一个基于复数名词和精确推理的分组和推断过程。

When inductive reasoning is done well, as shown in Exhibit 21, it leads to clear and compelling arguments. For example:

• Maupertuis was an ingenious man, but not a man of strong practical sense, as evidenced by the schemes he was incessantly devising:

• To found a city in which only Latin should be spoken

• To dig a deep hole in the earth to find new substances

• To institute psychological investigation by means of opium

• To explain the formation of the embryo by gravitation

当归纳推理做得好时，如图表21所示，它会导致清晰且令人信服的论证。例如：

• 莫佩尔蒂是一个富有创造力的人，但缺乏实际感，这可以从他不断提出的计划中看出：

• 建立一个只使用拉丁语的城市

• 在地球中心挖一个深坑以寻找新物质

• 通过鸦片进行心理学研究

• 用引力解释胚胎的形成

In another case, inductive reasoning might focus on eliminating wasted effort in on-site activities:

• Create smaller, more highly skilled workforces

• Deploy the workforce to accommodate work availability

• Ensure delivery of relevant information on work availability to the sites

在另一个案例中，归纳推理可能集中于消除现场活动中的浪费：

• 创建更小、更高技能的工作团队

• 部署人员以适应工作的可用性

• 确保向现场传递相关工作可用性信息

However, when inductive reasoning is poorly executed, as shown in Exhibit 22, the arguments become weak or misleading. For example:

• Managers mismanage because they want to:

• Don’t face reality

• Won’t countenance internal criticism

• Won’t cut off losing activities

• Neglect details

• Don’t question policies

然而，当归纳推理执行不当时，如图表22所示，论证就会变得薄弱或具有误导性。例如：

• 经理管理不善是因为他们想这样做：

• 不面对现实

• 不接受内部批评

• 不停止亏损活动

• 忽视细节

• 不质疑政策

This type of reasoning is sloppy because it doesn’t truly connect the observations to a strong or valid inference. Similarly, a second example from Exhibit 22 fails as well:

• Composing room costs may represent a profit-improvement opportunity:

• Productivity is low

• Overtime is high

• Prices are uncompetitive for simple jobs

这种推理是草率的，因为它并没有真正将观察与有力或有效的推论联系起来。同样，图表22中的第二个例子也失败了：

• 排版室成本可能代表了一个利润改进的机会：

• 生产率低

• 加班多

• 简单工作的价格缺乏竞争力

In reality, this is not inductive reasoning at all but rather a deductive argument. Low productivity leads to high overtime, which leads to uncompetitive prices. This chain of causation is inherently deductive, even if it is presented as inductive reasoning.

实际上，这根本不是归纳推理，而是一个演绎论证。低生产率导致高加班，进而导致价格缺乏竞争力。这种因果链本质上是演绎的，即使它被表现为归纳推理。

Inductive reasoning, when properly executed, requires you to carefully group similar ideas and identify patterns or connections. It is this precision and creativity that distinguish it from deductive reasoning.

当归纳推理被正确执行时，需要你仔细分组相似的想法并识别模式或关联。正是这种精确性和创造性使其区别于演绎推理。

To ensure inductive reasoning is properly executed, you must always check the logical coherence of your groupings and avoid overgeneralizing or forcing connections that do not exist.

为了确保归纳推理被正确执行，你必须始终检查分组的逻辑一致性，避免过度概括或强行建立不存在的联系。

A key aspect of inductive reasoning is ensuring that your conclusions are not based on assumptions but rather on observed patterns that align with the facts. For example, if you infer that low productivity is linked to high costs and uncompetitive pricing, you must ensure that these observations truly stem from related data points and not from a single piece of evidence.

归纳推理的一个关键方面是确保你的结论不是基于假设，而是基于与事实一致的观察模式。例如，如果你推断低生产率与高成本和缺乏竞争力的定价有关，你必须确保这些观察确实来自相关的数据点，而不是基于单一证据。

This brings us to another critical skill in inductive reasoning: identifying and dealing with misfits in the grouping. Misfits are elements within a grouping that do not align with the central idea or pattern. They must either be explained as exceptions or excluded from the grouping to maintain the integrity of your reasoning.

这引出了归纳推理中的另一个关键技能：识别和处理分组中的不匹配项。不匹配项是分组中不符合核心思想或模式的元素。必须将它们解释为例外，或者将其从分组中排除，以维护推理的完整性。

For example, in Exhibit 21, the grouping around "eliminating wasted effort in on-site activities" includes three subpoints:

• Create smaller, more highly skilled workforces

• Deploy workforces to align with work availability

• Ensure delivery of relevant information on work availability

例如，在图表21中，围绕“消除现场活动中的浪费”的分组包含以下三个子项：

• 创建更小且更高技能的工作团队

• 根据工作可用性部署工作团队

• 确保传递与工作可用性相关的信息

Each subpoint contributes directly to the central theme. If one of the points, for instance, proposed hiring more unskilled workers to reduce costs, it would be a misfit because it contradicts the idea of creating "more highly skilled workforces."

每个子项都直接为核心主题做出贡献。如果其中某一点，例如，建议雇佣更多低技能工人以降低成本，它将成为不匹配项，因为它与“创建更高技能的工作团队”的概念相矛盾。

In contrast, poorly executed inductive reasoning, as shown in Exhibit 22, fails to maintain logical coherence. For instance:

• Managers mismanage because they want to.

• Don’t face reality

• Won’t countenance internal criticism

• Neglect details

相比之下，图表22中展示的不良归纳推理未能保持逻辑一致性。例如：

• 经理管理不善是因为他们想这样做。

• 不面对现实

• 不接受内部批评

• 忽视细节

This reasoning fails because it imposes a causative relationship ("mismanage because they want to") that does not logically follow from the observations. The grouping lacks a clear connection to the central claim and instead creates a biased narrative.

这种推理失败的原因在于，它强加了一种因果关系（“因为他们想，所以管理不善”），但这种关系并未从观察中逻辑地得出。分组缺乏与核心主张的明确联系，而是创造了一个带有偏见的叙述。

To summarize, good inductive reasoning requires:

1. Clear grouping: Ideas must align with a central plural noun and share observable similarities.

2. Logical coherence: Each subpoint must support the central claim without contradicting it.

3. Avoiding misfits: Exclude or explain elements that do not fit the grouping.

总结来说，良好的归纳推理需要：

1. 清晰的分组： 思想必须与一个核心复数名词一致，并具有可观察的相似性。

2. 逻辑一致性： 每个子项必须支持核心主张而不与其矛盾。

3. 避免不匹配项： 排除或解释那些不符合分组的元素。

By adhering to these principles, you can ensure that your inductive reasoning is robust, creative, and compelling, avoiding the pitfalls of sloppy logic or unfounded assumptions.

通过遵守这些原则，你可以确保你的归纳推理具有坚实基础，同时富有创造力和说服力，避免逻辑草率或没有依据的假设的陷阱。

When inductive reasoning is executed correctly, it becomes a powerful tool for creative thinking and problem-solving. It allows for the synthesis of seemingly disparate ideas into coherent, meaningful groupings that reveal patterns or relationships that may not have been immediately obvious.

当归纳推理正确执行时，它成为创造性思维和解决问题的强大工具。它允许将看似不相关的想法合成为连贯且有意义的分组，从而揭示可能并不明显的模式或关系。

A hallmark of effective inductive reasoning is its ability to generate new insights or perspectives. By organizing observations into groupings based on shared characteristics, inductive reasoning facilitates the discovery of underlying themes or causal relationships.

有效归纳推理的一个标志是它能够产生新的见解或视角。通过根据共同特征将观察分组，归纳推理有助于发现潜在的主题或因果关系。

For example, in a business context, you might observe the following:

• Productivity is low

• Employee morale is low

• Overtime is high

例如，在商业环境中，你可能会观察到以下现象：

• 生产率低

• 员工士气低

• 加班时间长

Instead of jumping to a deductive conclusion that "low productivity is due to poor management," you could group these observations under a broader theme such as "workplace inefficiencies" and begin to investigate the root causes. This approach opens the door to more comprehensive solutions, such as revisiting workflows, improving employee engagement, or adjusting resource allocation.

而不是直接得出“生产率低是因为管理不善”的演绎结论，你可以将这些观察归入“工作场所效率低下”这一更广泛的主题，并开始调查根本原因。这种方法为更全面的解决方案打开了大门，例如重新审视工作流程、提高员工参与度或调整资源分配。

Conversely, poorly executed inductive reasoning can lead to overly generalized or inaccurate conclusions. This often occurs when the grouping is inconsistent or when the inferred connections are not logically sound.

相反，执行不当的归纳推理可能导致过度概括或不准确的结论。这通常发生在分组不一致或推导的联系不符合逻辑时。

For instance, consider the example of managers "mismanaging because they want to," as shown in Exhibit 22. This statement lacks credible evidence and forces a causative link that may not exist. Such reasoning can result in biased decisions or ineffective solutions.

例如，考虑图表22中“经理管理不善是因为他们想这样做”的例子。这一陈述缺乏可信的证据，并强行建立了可能不存在的因果联系。这种推理可能导致偏颇的决策或无效的解决方案。

To avoid these pitfalls, it is essential to ensure the following:

1. Consistency in grouping: All elements within a grouping must share a clear and logical relationship with the central theme.

2. Evidence-based inferences: Conclusions must be supported by observable patterns or data, not assumptions.

3. Iterative validation: Regularly review and refine your reasoning to ensure coherence and accuracy.

为了避免这些陷阱，必须确保以下几点：

1. 分组一致性： 分组中的所有元素必须与核心主题有清晰且逻辑的关系。

2. 基于证据的推论： 结论必须由可观察的模式或数据支持，而不是假设。

3. 迭代验证： 定期审查并完善推理，以确保一致性和准确性。

Ultimately, the strength of inductive reasoning lies in its ability to identify connections and patterns that may not be immediately apparent. By carefully constructing groupings and validating inferences, you can unlock deeper insights and develop more innovative and effective solutions.

归纳推理的力量最终在于其能够识别可能并不明显的联系和模式。通过仔细构建分组并验证推论，你可以发现更深刻的洞察，并开发出更具创新性和有效性的解决方案。