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What is the Difference Between Likelihood vs Probability in Risk Management?

What is the Difference Between Likelihood vs Probability in Risk Management? Many Project Managers (PM) and project teams confuse the terms of “likelihood” and “probability” and even consider them synonyms.  But are they?  Both likelihood and probability expresses odds of occurrences but there is a clear difference in their meaning and use in the risk environment.  If you ask a mathematician to explain the difference between the two terms you might get a very long detailed answer that might confuse you even more.  But as PM and Risk Managers we need to be able to teach our teams good risk management processes and understanding this concept is critical.   This article is a part of a series of articles under the Deliverable Centered Project Management series.

The usage of likelihood as we will see from the definition below indicates risks are only managed by a qualitative measurement.  Qualitative measurements are subjective.  We have found that too many PM and project teams never measure risk quantitatively as they feel this method is too difficult to assess.  However, a quantitative measurement is the only method that can result in a risk equivalent value (REV) to our projects.  Quantitative analysis, as opposed to qualitative analysis has a track record for improving decisions.  But many PM still do not analyze risk in a quantifiable measure as they feel their risks are too complex or cannot be measured.

Let us start with the purpose of risk analysis which is to determine the risk probability of occurrence (RPO) and the risk cost of impact (RCI) which will determine the risk equivalent value (REV).  Risk analysis should be in some form of a quantitative predictive method which includes models that use historical information and expert knowledge.

First, let us discuss the meaning of the two terms and then discuss how they impact risk assessments.


Likelihood refers to the possibility of a risk potential occurring measured in qualitative values such as low, medium, or high. By the way, these three assessment labels are also referred to as ordinal assessments since they only order the potential without providing any understanding of the difference between low, medium or high. Likelihood is a qualitative assessment that is subjective with little objective measurement.  An example is:  there is a high likelihood of rain tomorrow.


Probability refers to the percentage of possibilities that foreseen outcomes will occur based on parameters of values.  Probability is a quantitative measurement of outcome.  An example is:  there is a 70% chance of rain tomorrow.

Current bodies of knowledge tend to encourage qualitative scoring methods that offer little to no quantifiable information on project risks to be done first. Risks are scored by an ordinal scoring process which excludes a quantitative risk analysis method altogether. The use of likelihood is used solely and no quantitative assessment is completed.  Qualitative risk assessment encourages scoring risks quickly with no concrete data for why an assessment was decided upon, just a subjective guess fitting into an ordinal scale (low, medium, high), or a cardinal scale (1 to 5).  In addition, by using a scoring system of 1 – 5 or high, medium, low there is no valuable method to determine the risk’s cost of impact to your project.

The concern this author has with assessing risk with likelihood over probability is the loss of the risk’s REV.  Without a REV value, risk potentials cannot be rank-ordered for mitigation attention or funding. Assessment of risks with likelihoods lead to scoring risks with no ability to see the cost impact.  This type of scoring does not take into account low risk likelihood with a high impact.  It will be seen as the same number on the risk matrix as a high risk with a low impact.  The difference between the two risks constructs could be significant, but will never be shown due to using faulty scoring methods.  There is not enough information in this method to discriminate between what matters in risk rankings resulting in little support in making critical decisions on the project’s true risk exposures.

Frankly, qualitative risk analysis is done mainly due the fact that many PM will say they do not have enough knowledge to use quantitative methods, therefore they will not use them.  The key that they are missing is that probabilities need to be used because there is limited information.

Using a probability assessment is showing our level of uncertainty about the risk event occurring. Scoring on a scale of low, medium, high provides little valuable information about the occurrence uncertainties.  If I were to tell you there was a 50% chance of snow tomorrow, this gives you more information than my telling you there is a medium chance of snow tomorrow.  By telling you there is a 50% chance of snow, I am telling you there is 50% probability of this event (snow) occurring.  Having a probability provides information that can put the project team in a position to make solid decisions.  By merely indicating there is a medium chance of something happening tells us little.

Many PM do not understand the concept that probabilities help us understand more about the uncertainties to which they are descriptive. The important concept to grasp is you use probabilistic methods because you do not have perfect information.  If we had perfect information, we would not need to provide probabilities and the value of uncertainty would be zero.  Remember, risk is about the events that could negatively affect our projects that have NOT happened yet – that is future events. If you have perfect information about the risk, you do not need probabilities since perfect information removes all uncertainty.

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