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Monte Carlo simulation is the most common way to analyse risk using numbers. But many people view quantitative risk analysis as too difficult, perhaps because it involves mathematics, statistics and computers. As a result, they miss out on the insights available from this powerful technique.
蒙特·卡罗模拟法，是使用数字分析风险的最常见的方法。然而，很多人认为定量风险分析实在是太难了，也许是因为会涵盖数学、统计学和计算机。因此，他们没有能够从蒙特·卡罗模拟法这个强有力的方法中获得经验。
The following seven steps make it easy to do Monte Carlo analysis properly:
以下七个步骤，可以让使用蒙特·卡罗模拟法分析变得简单：
1. Define your purpose
确定目的
Why do you need to do this analysis? What is the scope? You might only be interested in one type of risk exposure, such as risk to cost, schedule, resource levels, profitability or cashflow. Or maybe you need an integrated view of overall exposure to several types of risk. The questions to be answered should be clearly defined at the start. For example, are we making a 'go/no-go’ decision, or working out how much contingency we need, or assessing what outcomes are possible, or trying to find the biggest risks?
为什么需要做蒙特·卡罗模拟法分析？范围是什么？你可能只对某种风险暴露类型感兴趣，如成本风险、进度、资源状况、盈利能力，或现金流。或者，你可能需要全面了解几种风险的综合风险暴露。需要回答的问题，在一开始就应该要明确定义。例如，我们是否在做一个“go/no go”的决定，或者计算出我们需要多少应急方案，或者评估可能的结果是什么，或者，尝试去找出最大的风险？
2. Develop your model
创建风险模型
The risk model might be built starting from an existing baseline like a project plan or budget, with added risks. Or it might look only at the risks themselves. Einstein’s advice to “Make things as simple as possible, but not simpler” is the key to a good risk model. It needs to reflect reality at a level that allows the effect of risk to be visible. A wide range of proprietary risk tools is available, or a risk model can be created in common office software, and we should use a tool that matches the level of analysis we are doing.
风险模型，可以从某个现有基线开始创建，比如：某个项目计划，或者增加了风险的项目预算。或者，仅仅看风险本身。爱因斯坦的建议是：“要让事情尽可能简单，但不是更简单”，这是创建良好风险模型的关键。风险模型，需要反映真实水准，让风险的影响变得可见。一个广泛的专有风险工具是恰当的，或者，某个风险模型在通用办公软件中创建，我们应该使用与分析水准相匹配的工具。
3. Produce input data
产生输入数据
Now we need data to go into the risk model. These must reflect all relevant risks, including both threats and opportunities. We must include variability on known tasks (using ranges of values), as well as ambiguity (using stochastic branches). We also need to identify dependencies between risks (using correlation). Data are usually based on the current risk register, which provides an important audit trail.
现在，我们需要在风险模型中输入数据，这些数据必须能够反映所有相关的风险，包括：威胁与机会。我们必须将已知任务的可变性涵盖在内（使数值范围），也要把多义性（使用随机分支）包含进来。另外，我们还需要确定风险之间的依赖关系（使用关联性）。数据，通常是基于当前登记的风险，其提供了一个重要的审计踪迹索。
4. Validate model
验证风险模型
The completed model is then tested by running a large number of iterations. This allows us to check that the model is robust with no data input errors or false logic. Any errors should be corrected before we go any further.
随后，完整的风险模型，会被大量的迭代次数进行验证，这也让我们能够检查该风险模型的健全性，且没有错误的数据输入和错误的逻辑，在进一步行动之前，所有的错误都应该被纠正。
5. Run model with and without risk responses
有风险/没有风险响应去运行风险模型
Next we produce a second version of the risk model that includes the effect of agreed risk responses. Comparing this with the first version shows how our planned actions will affect the overall risk exposure, and whether they are adequate or not.
接下来，我们要生成风险模型的第二版，该版本的风险模型包括约定风险响应的影响。将该版本的风险模型与第一版本的风险模型进行对比，可以显示出我们是如何筹划行动的，而这会影响到整体风险暴露，并且会显出示筹划的行动是否恰当。
6. Produce and analyse outputs
产生并分析输出
Monte Carlo analysis can tell us many useful things about risk exposure, including the range of possible outcomes, the likelihood of achieving our objectives and targets, the most influential risks, the main risk drivers, and the most effective actions.
蒙特·卡罗模拟法，可以让我们知道许多有关风险暴露方面的有价值的东西，包括：可能结果的范围，达成目的和目标的可能性，最有影响的风险，主要的风险驱动因素，以及最有效的行动。
7. Decide on appropriate action and report results
决定相关行动与报告结果
Now we need to think, and decide what to do next! Actions could include anything from adopting a completely new strategy to minor tactical adjustments. And we need to tell others what we’ve discovered about our risk exposure and what we’ve decided to do about it.
现在，我们需要思考并决定下一步做什么！行动，可以包括：从一个全新的战略到较小的战术调整。我们需要告诉其他人，我们已经发现了风险暴露，以及决定所要采取的措施。
Monte Carlo simulation does not need to be complex and it should not be feared or avoided. Following these seven simple steps will ensure robust and realistic modelling, and allow you to gain the benefits of this powerful technique. Try it and see for yourself!
蒙特·卡罗模拟法，不需要那么复杂，我们不应该为此感到害怕或想去回避。遵循这七个简单步骤，将能够让确保我们可以健全、明智的建模，并可以获得蒙特·卡罗模拟法这一强有力的方法的好处。试着把蒙特·卡罗模拟法用起来吧！自己去了解！
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