One way to overcome the disadvantage of a simple average of relative method is to use a weighted average method. This method takes into account the importance or significance of each item being compared.



The weighted average method assigns a weight or importance factor to each item being compared. The importance factor is usually expressed as a percentage or decimal. The weights are then multiplied by the relative comparison values of each item and the results are summed. The sum is then divided by the total weight to get the weighted average value.

For example, if we are comparing the performance of two employees in a company, we might assign a weight of 60% to sales performance and 40% to customer service performance. Employee A might have a sales performance rating of 90% and a customer service rating of 80%, while employee B might have a sales performance rating of 80% and a customer service rating of 90%.

To calculate the weighted average for employee A, we would multiply the sales performance rating of 90% by the weight of 60% (0.6) and the customer service rating of 80% by the weight of 40% (0.4). We would then add the results together (54 + 32) to get a total weighted score of 86. To calculate the weighted average for employee B, we would follow the same process and get a total weighted score of 84.



The weighted average method provides a more accurate comparison because it takes into account the importance of each item being compared. This method is useful when comparing items that have different levels of significance, such as when comparing the performance of employees in different job roles.



In conclusion, the weighted average method is a useful tool for overcoming the disadvantages of a simple average of relative method. By assigning weights to each item being compared, we can get a more accurate comparison that takes into account the importance of each item.