Leverage Artificial Intelligence to Optimize Labor Scheduling
Ineffective labor schedules create a variety of problems at the store level that impact management, store associates, and customers. Understaffed stores that can’t accommodate the actual in-store workload have consequences including poor task completion rates, sub-standard customer interaction, and increased stress on store associates and management.
Creating labor schedules can also be time consuming for store managers. Accounting for employee requests, schedule restrictions, and adhering to complex local labor rules are overwhelming for a manager and max out the capabilities for most automated systems. But even more critical to the success of a store is scheduling the right employees, with the right skills in the right numbers. This is where labor scheduling systems have fallen down.
Retailers looking to create smarter schedules are embracing AI-enabled workforce management (WFM) as one way to address these issues. With so many variables affecting the accuracy of labor scheduling—customer traffic, store workload, employee skill set, and more—it takes an intelligent solution analyzing all of this information in real time to truly optimize employee schedules.
Here are three ways that AI-enabled WFM can optimize labor scheduling:
1. Optimize Schedules for Maximum Productivity
Store associates have varying skillsets and levels of expertise. While trying to juggle these parameters during labor scheduling, it can be easy for managers to overlook a required skill or expertise needed in a department, or to schedule an inexperienced group of associates to the same shift. It’s also difficult to schedule specific employees who work well as a team to the same shift, which would help store associates complete their daily tasks.
With AI-enabled WFM, historical data on associate skillset, experience, performance, and other key metrics is automatically analyzed in real time and used to generate labor schedules optimized for all of these variables. This also frees up the time that store managers would have otherwise spent trying to sift through all of this data manually, giving them more time to interact with customers and train associates.
2. Improve Scheduling Precision During Peak Sales Periods
Scheduling needs fluctuate during holiday seasons and new product releases. More store associates might be needed in certain departments to adjust to increased customer traffic. There might also be a need for more store associates who have expertise across departments, so they can assist as customer traffic to certain departments spikes. Without having insight into historical sales data, it’s incredibly difficult to create schedules that adequately staff stores for holiday seasons and other peak sales periods.
AI-enabled WFM allows retailers to analyze historical labor scheduling and sales data, comparing it to real-time data in order to provide more insight into staffing requirements during peak sales periods. AI-enabled WFM can then suggest how many seasonal employees to hire, in what departments they need to be staffed, and what their availability needs to be in order to maximize sales and manage the projected store workload.
3. Calculate Labor Needs More Accurately
Creating accurate schedules requires an in-depth understanding of key metrics like customer traffic and in-store workload. However, translating those metrics into actionable insights requires analyzing a massive amount of data—far more than the average store manager can handle week-to-week. Even with comprehensive analytics solutions and corporate reporting, store managers are still bound to rely on their best guess and to overschedule or underschedule for certain shifts, if they don’t have visibility into real-time trends and how they impact labor needs.
By assessing historical and real-time operational data, AI-driven WFM can finely tune labor schedules to account for all of these drivers. This ensures that store associates have time to complete all critical tasks, assist and interact with customers, and sell more during peak sales periods.
For more insight into how to create more effective labor schedules with AI-enabled solutions, read our latest guide: “Where Does AI Fit into Your Retail Store Operations Strategy?”