![]() Less severe: An employee or student is injured from a fall on ice at campus during the winter There is some uncertainty about the consequences because they depend on the person who has fallen and their level of physical fitness, where they fall (e.g., if there are any edges they might hit), what they are wearing e.g., if they are wearing a thick quilted jacket or hat that may soften the impact when they hit the ground.Įstimate consequence: As the outcomes may be relatively different here, we choose to divide the undesired event into two events: (NB! If you assess consequences for more than one value, you only have to include the category of consequence for the value that has the highest level of consequence in the risk matrix.) Consequences may range from bruises, sprains, broken bones and be both severe and less severe. Very probable”. We need this figure when plotting probability in the risk matrix.Ĭonsequences: To simplify the process, we only assess consequences relating to the value life and health. Based on the criteria – categories for probability from 1 to 5 – this would be defined as a “3.On the basis of this knowledge, we can apply the criteria to estimate the probability as “Between once a month and once a year” given that there are only a few months each year when the weather conditions could cause a person to fall on icy ground.This assessment must also include the fact that gravel is spread around campus, but that the winter conditions in Bergen are unpredictable and there is a large area to cover, so we assume that there may be occasions when some areas on campus are slippery, despite the hard work to spread gravel.Probability can be assessed by, for example, checking HSE non-conformities to identify how often falls caused by icy conditions in the winter on campus are reported.Undesired event: An employee or student is injured from a fall on ice at campus during the winterĬauses: Weather conditions, failure to spread gravel Object of analysis: A hypothetical campus in Bergen, populated by employees and students. When using CIM for Risk and Vulnerability Analyses (RVA/ROS-analysis) or the Excel template for HSE risk assessments, the event will be plotted automatically in the risk matrix after you have chosen the probability and consequence degrees for the event. This does not apply to probability in our analyses, as there is one only category of probability selected per event. To avoid having to make a risk matrix for each value, we choose the value with the highest degree of consequence to represent the risk involved in the event in the matrix (in this example, “D. A certain risk”) and another degree of consequence for the value environment (e.g., “D. An event may, for example, have one degree of consequence for the value life and health (e.g., “B. These are predefined criteria utilised to plot the risk involved in an undesired event in a risk matrix. The event then ends up in the green, yellow or red area in the matrix.Ī single event may have consequences for several of our values, but with different degrees of consequence. The criteria for probability and consequence provide an overview of the probability and the degree of consequence. Nonetheless, the risk matrix is a good tool provided that you are aware of its weak points and you ensure that your decisions are not based on the matrix alone, but on an overall evaluation based on the entire risk assessment. In addition, the matrix does not provide any information on uncertainties or the level of knowledge behind the assessments. The risk matrix provides a very simplified visual presentation of risk. Read the section on risk acceptance criteria below for a definition of these colours. The risk matrix is divided into coloured fields – red, yellow and green – to illustrate the level of risk. The higher up and farther to the right the event is plotted in the matrix, the greater the risk. The size of the matrix may differ, but the University of Bergen uses a matrix with 5 x 5 cells (5 x 5 matrix) for risk assessments related to HSE and emergency preparedness. This provides a picture of the risk in two dimensions - probability and consequence. Risk is often presented in a risk matrix, where the consequences are illustrated along one axis and the probability (likelihood) along the other.
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