Measurements of consequences

For discussion purposes, this broad classification will be subdivided into two groups that we will refer to as actual loss measurements and potential loss measurements.

These are, as the words imply, measurements of the results of actual loss producing events.  They could include personal injury or property damage and are usually expressed in terms of frequency and severity.   

While the general classifications of loss for personal injury and property damage are quite similar, measurement techniques vary considerably.  The table below shows examples of injury and property damage measurement calculations.

The number of serious (or reportable) injuries occurring in the average occupational establishment is 5 to 20 times larger than the number of disabling injuries.  

While the number of serious injuries (in comparison to the total number of incidents) is still very small from a statistical standpoint, the broader base for analysis certainly gives a more valid point of reference than the extremely small population segment involved with disabling injuries alone. 

These are techniques that can be utilised to measure the rate of undesired events that do not result in loss but, under slightly different circumstances, could.  

The whole premise in using these techniques is that many more incidents do not result in loss than do, and that many of these undesired events not only could have resulted in loss but could have resulted in major loss.  

By utilising measurement of techniques to report and analyse these no-loss incidents, the measurement system utilised not only has a much larger statistical base but assures a predictive posture rather than the widely used reactive ones dependent on loss-related data.

Several advantages for using measurements of consequences are given below:

• Motivate management.
• An accepted standard.
• Long history of use.
• Taught by recognised risk control organisations.
• Used by governmental agencies.
• Used by industrial associations.
• Easy to calculate.
• Indicate trends in performance.
• Good for self-comparison.

There are also disadvantages. 
These include:

• Lack statistical validity
• Reactive
• Easily manipulated
• May not reflect actual work experience because of biasing.  

Factors biasing injury rates are :

• Restricted or light-duty availability.
• Management’s attitude toward restricted/light duty work.
• Doctor’s influence.
• Worker’s attitude toward light-duty work.
• Wage structure regarding light-duty work.
• Compensation system.
• Size of business.
• Union policies.
• Safety awards and competitions.
• Culture of blame.
• Administrative difficulties and paperwork. 

When using measurements of consequences:

• Base conclusions on several rates.
• Use rates for self-comparisons.
• Use statistical control techniques to assist in rate’s interpretations.
• Use rates to establish loss results, not loss control.    

Figure 1 below shows that there are relatively few opportunities to measure actual consequences.  Measuring potential consequences renders more data; however, the measurements are still reactive – the incidents have already occurred!

Figure 2 below shows the area of the causation model addressed by measurements of consequence, cause and control.