Difference Between Quantitative And Qualitative Risk Analysis

  • Project Management
Created on :
December 2, 2019
Saket Bansal
Updated on :
June 23, 2023
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In the context of the PMP exam, it is crucial to identify and address uncertainties or risks that can hinder the achievement of project goals and objectives. By understanding and evaluating these risks, you can effectively mitigate their negative impacts or potentially enhance their positive effects. Two common techniques for evaluating and prioritizing risks are qualitative risk analysis and quantitative risk analysis. In this blog, I will explore the differences between these two approaches and shed light on their respective uses and benefits.

Before delving into the difference between qualitative and quantitative risk analysis, it is important to understand all identified risks are listed and recorded in a Risk Register or on a Risk Board in the case of Agile.  In general, you always have a long list of risks, and it is not practical to plan each risk with the same priority. You need to invest time and resources wisely, so you need to rank these risks. Due to limited time and resources, risks must be prioritized. This step involves assessing risk impacts and likelihood to determine which risks require immediate attention. You perform the subjective qualitative assessment first, and then, if further support is required, you use a quantitative assessment.

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 What is a Qualitative Risk Analysis?

Qualitative Risk Analysis refers to a technique used to prioritize risks in a project by evaluating their likelihood of happening, potential impact, and other relevant factors.

Risk severity is typically determined by multiplying the probability of occurrence by the potential impact. This assessment of both factors allows for the measurement of the overall severity of a risk. The process involves facilitation among the project team and stakeholders, leveraging their expert judgment to assign values to probability and impact guided by the Risk Management Plan. Through collaborative discussions, consensus is reached on the likelihood and impact levels, which are then used to calculate the severity of risks. Here is an example table illustrating the relationship between likelihood and impact levels derived from the qualitative assessment of identified risks by the project team and stakeholders.

likelihood / Impact0 – Very Low0.2 – Low0.4 – Medium0.6 – High0.8 – Very High
0 – Rare00000
0.2 – Unlikely00.040.080.120.16
0.4 – Possible00.080.160.240.32
0.6 – Likely00.120.240.360.48
0.8 – Almost Certain00.160.320.480.64

In this table, the likelihood and impact levels are represented using numeric values from 0 to 1; you can use 1 to 5 instead. All these guidelines are available in the risk management plan, and the team uses value accordingly. Here, severity values are calculated by multiplying the corresponding likelihood and impact values. You can observe the following definitions of Risk Severity from this table –

  • Low Severity: Risks with low severity have minimal impact (0-0.2) and a low likelihood (0-0.2) of occurring.
  • Medium Severity: Risks with medium severity have a moderate impact (0.2-0.5) and likelihood (0.2-0.5) of occurring.
  • High Severity: Risks with high severity have a significant impact (0.5-1) and a high likelihood (0.5-1) of occurring.

It should be noted that this approach does not provide a quantitative evaluation of risks. All these are subjective assessments.

Key Tools and Techniques for Qualitative Risk Analysis:

  • Expert Judgment: It is a valuable tool that leverages the knowledge and expertise of individuals or groups experienced in similar projects or domains. These experts offer subjective assessments and opinions on identified risks, including their potential impacts and the likelihood of their occurrence. Other qualitative assessment tools also benefit from the incorporation of expert judgment. For example, when conducting an urgency assessment, experts often rely on their extensive experience in similar situations to make informed judgments. This experience enables them to assess the level of urgency accurately and provide valuable insights to support decision-making processes.
  • Interpersonal and Team Skills: Interpersonal and team skills play a crucial role in facilitating effective risk analysis discussions and achieving consensus among project team members. These skills include active listening, effective communication, negotiation, and conflict resolution.
  • Risk Probability and Impact Matrix: Assessing the likelihood and impact of risks using qualitative rankings.
  • Risk Categorization: Organizing risks based on criteria such as project phase, source, or impact area.
  • Risk Urgency Assessment: This tool helps determine the urgency of addressing identified risks. Risks with higher urgency require immediate attention and mitigation actions, while risks with lower urgency can be addressed at a later stage.
  • Risk Data Quality Assessment: This tool assesses the quality and reliability of the data used to analyze risks. It ensures that the information used for risk assessment is accurate, complete, and up-to-date, which enhances the overall effectiveness of the risk analysis process.

These tools and techniques assist in evaluating and prioritizing risks, enabling project teams to make informed decisions and develop appropriate risk responses.

In simpler terms, qualitative risk analysis is a way to figure out which risks are more important and need more attention by considering how likely they are to occur and how much they could affect the project. It is a kind of subjective evaluation normally involves the expert judgment of the project manager, project team, and stakeholders. After evaluation, risks are generally described using terms such as very high, high, moderate, low, or very low. The main goal of qualitative risk analysis is to:

  • Identify or highlight risks that need further examination using Quantitative Risk Analysis.
  • For the risks that are not marked for further analysis, it helps determine appropriate risk responses based on their likelihood of happening and the impact they may have on project objectives. Project Team discovers risk responses based on subjective evaluation like very high, high, moderate, low, or very low.

After qualitative analysis, you can do quantitative analysis. There is no need to do a quantitative analysis of each risk.  You do this analysis only for those risks you mark for further analysis by the Perform Qualitative Risk Analysis process.

What is a Quantitative Risk Analysis?

Performing Quantitative Risk Analysis is a method of using numbers to study the combined effect of individual risks in a project, as well as other sources of uncertainty, on the overall project goals.

 

In simpler terms, Quantitative Risk Analysis involves using numerical analysis to understand how various risks and uncertainties can impact the project as a whole. It helps us assess the overall effect of individual risks and other uncertain factors on the project’s objectives. The objectives of quantitative risk analysis are as follows:

  • Determine Risk Exposure: This process quantifies the level of risk exposure and estimates the size of cost and schedule contingencies.
  • Predict Likely Project Outcomes: By considering the combined effects of risks, quantitative risk analysis predicts project outcomes in terms of time or money. It also estimates the likelihood of meeting project targets and communicates the necessary contingency measures to achieve the desired level of comfort.

Quantitative Risk Analysis is typically employed for risks with a high level of qualitative ranking. In such cases, the primary objective is to determine the most probable monetary value of the impact. This analysis relies on calculations rather than subjective assessments. It serves as a means of discovering the potential financial loss associated with the occurrence of a particular risk.

Commonly used tools for doing Quantitative Risk Analysis:

  • Simulation: Simulation involves using computer models to analyze risk factors. For instance, when dealing with high risks related to fluctuating exchange rates, a project team can simulate project budgets under different exchange rate scenarios. By inputting various exchange rates into the simulation model, they can observe how the project’s budget, costs, revenues, and profitability may be impacted. This process provides valuable insights into the financial risks associated with uncertain exchange rates, allowing the team to make informed decisions and protect the project’s financial success. Monte Carlo simulation is a technique that utilizes schedule and/or cost inputs, either from real data or past projects, to project future expenses or costs. It generates a quantitative analysis of overall risk, specifically in the context of cost and schedule. This analysis model aids in assessing and evaluating the integrated quantitative cost-schedule risk analysis.
  • Sensitive Analysis: It utilizes the Tornado diagram, which helps determine the greatest risks in a project. The Tornado diagram is a visual tool presenting a horizontal bar chart that compares the relative importance of various risks, with the highest-ranked risks positioned at the top. This diagram provides a clear view of the factors that can significantly affect the project’s objectives. For example, in a construction project, factors like unfavourable weather conditions, delays in material delivery, and labour shortages may emerge as the top risks. By analyzing the Tornado diagram, project managers can identify the risks with the most significant impact on project duration, allowing them to prioritize risk management efforts and allocate resources accordingly. The diagram showcases the relative importance of risks and displays both positive and negative impacts on the project’s schedule.
  • Decision Tree Analysis: Decision Tree analysis is a valuable tool for evaluating a series of events with their corresponding probabilities and impacts. Branches in the decision tree represent decisions or events, each associated with costs and risks. For instance, when considering the probability of obtaining the PMP certification within one month, the decision tree branches out into two possibilities: getting the certification or not getting it. Within the “getting it” branch, another branch explores the probability of securing a job. By following this path, decision-makers can assess the likelihood of obtaining both the certification and subsequent job opportunities. The end points of these branches represent the positive or negative outcomes, providing a clear view of the potential results based on the associated costs and risks at each stage of the decision tree. Decision Tree analysis is particularly useful for complex decisions involving multiple layers of events and decision points, allowing for a structured and systematic approach to decision-making.
  • Influence diagrams: Influence diagrams are used as an alternative to decision trees when the complexity of the decision problem makes it difficult to represent all the relationships and variables in a concise manner. They are especially useful in situations where multiple variables interact with each other and the impact of one component on others needs to be analyzed. For example, in the context of exchange rates, an influence diagram can help determine how changes in exchange rates will impact various parameters and their interconnected relationships.
  • EMV, or Expected Monetary Value: It helps evaluate the potential value of an outcome. It is calculated by multiplying the monetary value of a possible outcome by its probability of occurrence. For example, when considering whether to buy a lottery ticket, you can calculate the EMV by multiplying the potential winnings by the probability of winning and subtracting the cost of the ticket. If the resulting EMV is positive, it indicates a favourable outcome. For instance, if the potential winnings are $1 million and the probability of winning is 1 in 1 million, the EMV would be ($1 million * 1/1 million) – cost of the ticket. This calculation allows you to assess the average expected value from participating in the lottery.

Summary of Differences between Quantitative and Qualitative Risk Analysis:

 Qualitative Risk AnalysisQuantitative Risk Analysis
Scope of AnalysisConsiders all identified risksFocuses on risks marked for further analysis after qualitative assessment, typically those with high impact on project objectives
MethodologyRelies on stakeholders’ inputs and expert judgmentUtilizes probability distributions, project models, and simulation techniques
EvaluationAssigns qualitative rankings (e.g., very high, high, moderate, low, very low) to assess impacts and likelihood. In some cases, we assess individual risks by assigning a numeric ranking of probability and impact; like; a rank of 0 to 1. where 1 demonstrates high.It predicts likely project outcomes in terms of money or time based on the combined effects of risks. It also estimates the likelihood of meeting targets. And communicates the contingency needed to achieve the desired level of comfort.
ApplicationIdentifies risks for further analysis and determines actions based on combined effects of probability and impactDetermines risk exposure, quantifies cost and schedule contingencies, predicts project outcomes, and communicates necessary contingency measures
UsageApplied to almost all projectsNot used in simple and moderately complex projects; may not be applicable in software projects. It is used industries like construction, energy, financial services, and pharmaceuticals etc

Leveraging Qualitative and Quantitative Techniques in Agile: Enhancing Risk Analysis during Ceremonies and Events:

During various Agile ceremonies and events, such as iteration planning, daily stand-ups, and retrospectives, the project team actively engages in discussions and evaluations to identify and manage risks efficiently.

For qualitative risk analysis through collaborative discussions, the team identifies and prioritizes risks based on their potential impact and likelihood of occurrence. These risks are then recorded and visualized on a risk board, providing a centralized platform to track and manage them effectively. The risk board becomes a valuable reference point for the team to stay informed and take appropriate actions to address identified risks.

While qualitative risk analysis is the primary technique used in Agile, quantitative risk analysis can be applied selectively for high-impact risks. By conducting numerical analysis and simulations, the team gains deeper insights into the financial implications of these specific risks. However, the quantitative analysis is performed to a lesser extent and focuses on risks marked for further examination. This approach ensures that resources are allocated wisely, and attention is given to risks that require a more detailed assessment.

In conclusion, Qualitative and quantitative risk analysis techniques serve distinct purposes in project risk management. While qualitative analysis helps identify and rank risks for further analysis, the quantitative analysis focuses on numerically evaluating and predicting the combined impacts of identified risks on project objectives. Both techniques are valuable tools for project managers, and their selection depends on project complexity and the desired level of risk assessment. By understanding the differences between these approaches, project teams can effectively manage risks and increase the likelihood of project success.

I hope this blog helped you to clarify all the doubts related to differences in Qualitative and Quantitative risk analysis.

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