Importance of Q-Linker data analysis.

Importance of Q-Linker data analysis

The bank's operating manager received hard blame when he justified the congestion in the bank as a rare case.
The file has been referred to the development and performance monitoring department, using Q-Linker data analysis Software.
It turned out that the congestion is repeated periodically when the receipt of weekly dues to a big company of customers of the bank!
During checking the employee’s activities the behavior of the staff of the department related to the problem.
 It turned out that Most followed the series shows a Saturday night on late chatting, which has negatively affect their activities on the next day.
This default is evident when it coincides with the date of receipt of weekly dues, where congestion exceeds the normal rate,  as the active employee noted that on March 3,  2019, recorded the highest rate of congestion, which coincided with the date of receipt of salaries of retirees as it coincides with the beginning of the month on Friday, which is an official holiday Most of them come to the bank on  Sunday  !!!
It wasn't easy to change the bank's staff habits so it was to handle them intelligently and solve the problem and he presented to his management with an action plan under the following items:
 1- Delay starting reception on Sunday to the 9:30 instead of 8:30 and increase an hour on reception.
2- Preventing leaves on Sunday only necessary because there is no alternative “Temporary procedure pending the training of reserve staff".
3- Preventing hourly leave on Sunday between 10:30 and 13:00 because there is no alternative "temporary procedure pending the training of reserve staff".
4- Preventing holidays and hourly leave on the days of when the retired employee's salaries are due on Sunday because there is no alternative "temporary procedure pending the training of reserve staff".
5- Training of "six employees from less crowded sections" on the work of the concerned department that they perform the functions of any employee in his absence.
6- Leaves are studied in the department concerned and reserve staff so that the number of employees in the department concerned and reserve staff not less than (101%).
The plan succeeded, the problem was overcome and the active employee received praise.
The scientific and intelligent use of data analysis provides limitless services and it can know the flow rates of customers and analyze the behavior of customers and their operations to draw up better plans to avoid problems and get more profit.


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