Grading system is one way to make the Compensation & benefit have any relationship with the job description (job evaluation). Therefore, this system is more developed ranging from simple to very sophisticated.
Method is quite simple to do the job evaluation of the work of the system and then convert them into points. In the simple method, from this point and made the range and level of the edges is the grading system. While in the advanced methods developed by the consultant is not much different, there are only modifications are to be here.
Cases that often occur in the making is when seen from a zero or a company in the early stages stand, the debate may be different in such a way can be eliminated, especially during the judgment, but if the company is already well established and stable, then the debate will appear in there-here.
Besides, many systems developed in the process of force caused a grade level or into a certain level. It is a fun, if a grade level or we ride with the grading system because it made automatically will increase the status and our salaries, but what if the status and salaries that we are forced down by the grading system made by management, would make the problem itself.
During this often neglected in making the grading system is no historical data, employees, whether office, salary, salary increase each year for employees. As a result, the process is forced into the range so that a disruption occurs in the system Compentation & Benefit demotivasi and for those who are forced down gradingnya.
Because of that needs to be done to validate the existing conditions so that the process of forced and demotivasi disruption and can be avoided in such a way. This is often neglected by practitioners Compensation & Benefit, so something that was ignored during this bring great effect.
Grading method that was developed in this training is to use simple statistical methods. In this method than using the old methods also include historical data, all employees are treated with the method of evaluation that resulted in a cluster group (cluster) of the grading system that is made. Clustering-clustering of this range and then made grading or leveling of a position. In this way, the process forced the group to enter into a position-specific groups will not occur. This method is at once menvalidasi existing grading, and grading the correct time.
The advantages of this method is another, because the clustering method (statistics) this is dynamic, then we can review the grading system altogether menvalidasi quickly at any time, in line with changes in job description (job evaluation). This also means we can quickly review the system Compensation & benefit the company. Because these are dynamic, then this statistical method, will follow the conditions in the accordance with the data available in the company so flexible.
Besides, the level of the lowest to the highest will be automatically by the system analysis methods that have, so that the process of intervention and bias of the estimator to be minimal (statistical system that will process all). Estimator with the bias itself akan eliminate data that is output statistics.
Method is quite simple to do the job evaluation of the work of the system and then convert them into points. In the simple method, from this point and made the range and level of the edges is the grading system. While in the advanced methods developed by the consultant is not much different, there are only modifications are to be here.
Cases that often occur in the making is when seen from a zero or a company in the early stages stand, the debate may be different in such a way can be eliminated, especially during the judgment, but if the company is already well established and stable, then the debate will appear in there-here.
Besides, many systems developed in the process of force caused a grade level or into a certain level. It is a fun, if a grade level or we ride with the grading system because it made automatically will increase the status and our salaries, but what if the status and salaries that we are forced down by the grading system made by management, would make the problem itself.
During this often neglected in making the grading system is no historical data, employees, whether office, salary, salary increase each year for employees. As a result, the process is forced into the range so that a disruption occurs in the system Compentation & Benefit demotivasi and for those who are forced down gradingnya.
Because of that needs to be done to validate the existing conditions so that the process of forced and demotivasi disruption and can be avoided in such a way. This is often neglected by practitioners Compensation & Benefit, so something that was ignored during this bring great effect.
Grading method that was developed in this training is to use simple statistical methods. In this method than using the old methods also include historical data, all employees are treated with the method of evaluation that resulted in a cluster group (cluster) of the grading system that is made. Clustering-clustering of this range and then made grading or leveling of a position. In this way, the process forced the group to enter into a position-specific groups will not occur. This method is at once menvalidasi existing grading, and grading the correct time.
The advantages of this method is another, because the clustering method (statistics) this is dynamic, then we can review the grading system altogether menvalidasi quickly at any time, in line with changes in job description (job evaluation). This also means we can quickly review the system Compensation & benefit the company. Because these are dynamic, then this statistical method, will follow the conditions in the accordance with the data available in the company so flexible.
Besides, the level of the lowest to the highest will be automatically by the system analysis methods that have, so that the process of intervention and bias of the estimator to be minimal (statistical system that will process all). Estimator with the bias itself akan eliminate data that is output statistics.
NIce Post Friend.....
ReplyDeleteVery Educate.....
Please Coment BAck In My New Post...
great sobbb...
ReplyDelete