A project is incredibly susceptible to risks caused by internal and external factors. When you operate as a project manager, you need to meticulously oversee the project’s compliance with the initial planning and budget to ensure its success.

And for that, you will need various tools to operate the tasks avoiding inconveniences. While you would be able to resolve most issues without many adjustments, some might require additional evaluation.

And a Quantitative Risk Analysis does just that to assist PMP professionals. So, read on to acquire in-depth knowledge on this concept and how you should utilize it to your advantage.

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**What is a Quantitative Risk Analysis?**

Just as the name suggests, Quantitative Risk Analysis is a Risk Assessment tool used in project management. But first, what is risk assessment? It is a project risk analysis technique incorporated with the planning to estimate the likely risks and their severity. Its utilization helps you understand what to expect throughout the project run-time and be prepared for it beforehand.

That said, Quantitative Risk Analysis is the breakdown of the highest probable risks identified using verifiable data to evaluate the effects of project threats. It analyzes in terms of cost overruns, resource consumption, scope creep, and schedule delays. It uses a numerical evaluation technique to provide a report on the project risk likeliness and its impact.

Unlike other project risk analysis tools, quantitative risk analysis is only performed based on project type and data available. Since a project managers’ task includes shuffling through multiple projects, they do not have the privilege to distribute time and energy equally to trivial matters.

So after the project runs through the Qualitative method, the Quantitative method allows a broader spectrum of evaluation. Its data driven-results help identify the appropriate strategies needed to deal with both the positive and negative aspects of the project discrepancies.

**The Difference Between a Qualitative and Quantitative Risk Analysis**

One of the prominent differences between these two risk assessment tools is that while Quantitative Risk Analysis has an objective approach, Qualitative has a subjective approach towards risks.

Qualitative Risk Analysis is a pre-defined relative to rate or scale the probability occurrence and its impact. In this process, the probability and effect of the project get evaluated verbally based on a low, medium, or high rating scale. Thus, it helps recognize the tasks that need immediate attention and prioritize them for further risk analysis.

While both Qualitative and Quantitative analysis is a risk assessment process, Quantitative is the latter procedure. Since it doesn’t depend on the numerical data, you can execute Qualitative analysis on any project regardless of its type. Once the project threats are rated, the ones with the most priority get evaluated through Quantitative analysis to present an alternative risk response to the stakeholders.

With that said, Quantitative analysis is better for managing modern-day projects since it provides evidence-based data on how the consequences will affect the project outcome.

However, even though you don’t need to master special tools and techniques to implement Qualitative analysis, Quantitative offers the benefit of managing triple constraint.

So, while Qualitative might be a more hassle-free approach, Quantitative is the one offering the most robust analysis.

**When Should You Use a Quantitative Risk Analysis?**

A Quantitative Risk Analysis tool has to be incorporated within the primary stage of the project, most likely its planning period. However, the process comes after Qualitative analysis. The reason being, it supports the decision-making process and re-evaluating the planning of the project.

Once you have identified and rated the projects, the most priority-rated projects need to get further broken down using the Quantitative Analysis method. Safe to say, you need to use this project in terms of critical threats or opportunities.

You need to use this process for processes that require the contingency reserve to manage the budget and risk of the project. Some projects require meticulous evaluation to determine the necessary steps to avoid future discrepancies. Thus, these projects get simulated through data-driven techniques for detailed probability occurrences.

**How to Perform Quantitative Risk Analysis? **

**Quantitative Risk Analysis Tools and Techniques**

Since the process requires a data-driven evaluation, you need to use various tools to get an accurate result based on logistics, budget, and project run-time. However, note that the analysis process is not limited to the tools and techniques mentioned below.

**Three-Point Estimate **

The three-point estimate applies to both the cost and duration estimates. It allows you to figure out associated risks and generate three distinct assessments. These estimates being Optimistic estimates, Pessimistic estimates, and Realistic estimates.

While using this formula, project managers ought to jot down all the values for the three estimates and the time required for each of them and then calculate a weighted average based on the following formula.

**(O+4R+P)/[6]**

**Monte Carlo Analysis **

The Monte Carlo technique allows you to consider multiple scenarios for probable occurrences by showing you more than one outcome. It works based on historical data, so it runs through random simulations to offer a range of possibilities. So the most pragmatic way to assess the results of this process is in the form of a histogram.

Moreover, this technique most likely uses Optimistic estimates and Pessimistic estimates to determine the total cost and duration of the project. The process should get utilized when the problems are too complex and daunting to execute through direct calculations.

**Sensitivity Analysis **

Also known as “what-if analysis,” this process is used by financial analysts and economists. The procedure determines how the target variables are affected due to discrepancies in other variables. In general, this process is used in various fields to evaluate how independent variables affect dependent variables.

The process can easily get implemented using Excel. Here the process lies under the Data section of the ribbon and the What-if analysis button, which comprises the Goal Seek and Data button.

**Expected Monetary Value Analysis **

The Expected Monetary Value of EMV establishes the contingency reserves for a project’s schedule and budget. Simply put, it shows you how much money you can expect from an individual decision.

Since the procedure consists of probabilities, a single formula cannot determine the entire contingency reserve. After calculating the prospect and impact, you need to multiply the two of them to achieve your desired outcome. However, in terms of multiple risks, EMV needs to be calculated for each of them individually.

**Fault Tree Analysis **

Also known as the FTA analysis technique, this process evaluates the cause of system failure through a structured diagram. The FTA process is more convenient to perform than the Failure Mode and Effects Analysis (FMEA) technique.

It uses boolean logic to combine a range of lower-level events. The process works as a top-down procedure to determine the component level failure. Here, the entire operation works to identify the system failure and showcases the reasons behind its occurrence.

Moreover, the process uses logical gates, and the goal is to mitigate the component level failure for a smoother project run.

**Decision Tree Analysis **

Lastly, the Decision Tree is the graphical representation that supports the decision-making process. With this process, you are allowed to investigate a range of options laid out by the provided structure.

Imagine a tree diagram where various outcomes show possible results that you can draw from it. A decision tree is where you assign cash value and score to each probable consequence of the diagram and evaluate the worth of the estimated outcome.

**Examples of Quantitative Risk Analysis **

**Example 1 **

Let’s start by analyzing an Expected Monetary Value or EMV where risks include both opportunities and threats.

We know, EMV = Probability*Impact

Risk | Probability | Cost Impact | EMV |

Threat | 88% | $100,000 | $88,000 |

Opportunity | 50% | $100,000 | $50,000 |

Threat | 30% | $10,000 | $3,000 |

Total EMV | $33,000 |

To get the exact value of EMV, we have subtracted the opportunities from the threats. Here, the total Estimated Monetary Value represents the contingency reserve and project risk exposure.

**Example 2**

Let’s assume that a cosmetic company faces the likely risk of laying off workers. In such instances, they have a 60% chance of keeping the staff, which brings their cost to $100,000. Moreover, they have a 50% chance of losing their workers, which results in their total cost being $200,000.

Now,

EMV = Probability*Cost

= (60% * $100,000) + (50% * $200,000)

= $60,000 + $40,000

EMV = $100,000.

**Pros and Cons of Quantitative Risk Analysis**

**Benefits **

The benefits of Quantitative Risk Analysis are plenty. One of the notable benefits is that it offers better estimates. Quantitative analysis provides more data for critical business decisions than Qualitative analysis. Since it is a software-centric tool, it can import data from qualitative charts and offer simulations that mitigate risks.

Moreover, these software data help identify the external factors playing into the system failure of the project using a method called “Event Chain Method.”

In detailed management terminology, the outcomes get expressed. The safety level of those project risks is determined based on three basics, namely – accessibility, reality, and privacy. Furthermore, since this project is data-driven, there is no room for personal bias affecting the overall analysis result. Safe to say, the outcomes received from this analysis method are accurate.

**Disadvantages**

Since this procedure is data-centric, the usage of this analysis tool is limited, unlike Qualitative analysis. Moreover, since the process requires analysis through different software tools, a PMP professional must master the techniques. Thus, complex calculations can get tricky without an automated software tool.

Without mastering this technique, a project manager cannot interpret the results since the results get expressed in monetary value. Moreover, the researcher’s knowledge based on the questions and objectives is crucial to collect quantifiable data.

**Quantitative Risk Analysis in Project Management **

Learning the process of Quantitative Risk Analysis is a prerequisite to earning a PMP certificate. The reason being, this process offers the benefit of mitigating the risks and completing the project in compliance with the budget and schedule.

And obtaining a PMP certificate allows you to not only be able to distinguish between Quantitative and Qualitative but also interpreting and executing them.

To learn how you can pass your PMP certification exam in the next six weeks, sign up for a free class to get a study plan + valuable tips & tricks!