When the holiday season begins to fire up typically in early September, retailers look to gain extra help to accommodate the increase in customer traffic from the extremely hectic holiday shopping season. Retailers not only prepare inventory, new marketing plans and planned promotions, but they also prepare to hire extra staff which is usually offered as a part-time/seasonal basis. Organizations hire employees to help with stocking shelves, managing distribution and fulfillment, serve as customer service agents or help overall with store operations. This holiday season, the NRF predicts between 700,000 and 750,000 seasonal employees are to be hired to help with store responsibilities.
When looking for extra help, hiring managers and store managers sometimes try to use this time as an opportunity to hire friends and family who are looking to make a few extra bucks during the holidays. However, this may lead to improper favoritism or bias treatment in favor of these loved ones when it comes to creating a preferable schedule, allowing them to clock in sooner to get more pay than they actually worked or giving them the oppurtunity to work overtime when it may be underserving. By identifying realtionship based exceptions in the field, it can greatly impact your organization in a postive way by putting a stop to such behavior as it can increase moral for those full-time employees who work day in and day out or those seasonal employees who are not "in the family" of the manager. How does one identify nepotism you may ask? The answer is by using the data you have from different sources to piece together a pattern of nepotism.
Using an exception reporting solution like Retail 20/20 you can identify anomalies that lead to identifying nepotism. This is done by systematically running reports on different data sets. One report one could run is payroll/ time & attendance data to see if the "special" seasonal employees are given more hours on average than the normal seasonal employee or if the manager is approving hours that were never worked. A trend that can be easily spotted through excpetion reporting software is the fixing of schedules for special employees. You can see when favored employees are scheduled to work the "good" shifts during the day or during off-peak hours more consistently compareed to other unfavorable hours.
By looking at these reports and creating thresholds in the queries ran in the software, you can see when associates are clocking in a little sooner to get paid an hour more than scheduled, seeing that certain employees have more overtime than the average employee and noticing patterns of associates maybe taking longer breaks than they should. You could also find the opposite with associates not taking a break at all when they are mandated to by law which creates possible legal headaches as well. By putting a stop to these fraudulent behaviors, it can save the organization countless dollars, increase efficiency and even prevent a lawsuit from these seasonal employees looking to catch the retailer at their busiest time. We all know sometimes politcs can interfer at the store level during this time of year but excpetion reporting can put some fairness back into your orgainzation.