StoreX provides significant labour cost savings for retail companies with artificial intelligence based processes. As in every sector, in the retail sector, one of the common inefficiency cause is the incorrect number of staffing. Nowadays to become an efficient retailer, it is important to optimize the number of staff in stores.
But How?
Required staff calculation for multiple stores is a difficult optimization problem. The problem worsens with the increasing numbers. Sometimes over sometimes low-staffing occurs. While employing less staff leads to sales losses, on the other hand, over-staffing dramatically decreases profitability. In both cases, companies are exposed to serious money losses.
StoreX helps retailers to calculate the right size for different time frames for multiple stores. This requires instantaneous visit statistics and intelligent analysis of huge datasets for every store and not possible or feasible to accomplish this with professionals. Most of the retailers try to do this intuitively, however, ends up with huge inefficiency. Artificial intelligence based systems like StoreX can calculate this efficiently and create maximum benefit for the company by getting rid of human superego or faults.
What are the reasons for the wrong staffing in retail stores?
If we look at the reasons, we see mainly personal reasons such as low leadership skills, superego (id impulses to manage large teams), and tendency to increase comfort zone (to reduce workload or to work less).
In retail, staff always have diverse requests to make their life better. They want to change shift plans in order not to work on weekends or to take more off days.
For example, weekends are the busiest days for retail stores. Unwillingness to work over the weekend creates indecent requests from staff. While many of the executives often try to stand against these pressures, but some lose their foresight or forget the priorities of the business. This leads to unnecessary staffing and can only be avoided by centrally managed staffing processing based on artificial intelligence based calculations. StoreX can make this possible for every retail organization.
Let us examine the shift plan from a store the following real data.
Even if we only correlate between working times and sales, we see serious problems as clearly seen in the chart below. On weekends, while staff shortages are seen, it is another serious problem on weekdays. Even if only sales rates are considered, there are serious problems.
StoreX approaches for this problem: makes shift plans with the following parameters and relationships between all these parameters:
- Sales data
- Customer Visit Counts
- Number of Customers Passed by in front of Store
- Incoming Customer Gender split
- Incoming Customer Age split
StoreX has determined that women expect more services than men. As seen in the tables below, it was seen that women visited the store more in shift1
As seen in the chart, if the shift plan is done in the way that StoreX suggests, the ratio of 13.3% less staff and sales are much more accurate.
StoreX makes it possible for you to know your customers better and to plan the right number of staff and increase profitablity.