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Creating Optimal Schedules for the Holiday Season
Accurate demand forecasting is crucial for retailers year-round, but especially so during the holidays, when they experience significant surges in demand. These surges can potentially disrupt processes across the business, from inventory to labor operations. Without proper preparation, those disruptions can impact the customer experience, jeopardizing business results during one of the most critical periods of the year.
Fortunately, recent advancements in technology have allowed retailers to better predict demand fluctuations. Artificial intelligence-powered demand forecasting solutions help retailers ensure they have the right staff in the right place at the right time. As part of a modern workforce management system, they enable managers to instantly create optimized schedules that match business needs with employee skills and preferences.
As we enter the thick of the busy season, now is the time for retailers to harness the power of AI to improve their demand forecasting — and thereby improve the quality of their in-store experience.
With retailers hiring fewer seasonal employees this year, optimizing labor efficiency is a top priority. It’s critical that retailers have the proper staffing during peak periods.
Precise demand forecasting is a prerequisite for optimized holiday staffing. However, traditional methods of demand forecasting can be extremely labor intensive, less accommodating to variability, and deliver subpar results. Manual processes for forecasting often apply a one-size-fits-all approach to forecasts, rendering them incapable of precisely forecasting the demand for specific items by location across all customer touchpoints. These methods often fail to incorporate external factors that could have a significant impact on demand such as local events and weather.
AI-powered demand forecasting solutions streamline the information-gathering process, automatically ingesting and analyzing thousands of data points, including historical operational data and syndicated data such as local events and weather. This reduces the reliance on manual intervention to aggregate and analyze data. AI-powered demand forecasting not only leads to the automated generation of optimized schedules, but also helps retailers improve their business agility, accuracy and labor efficiency. A 1 percent improvement in demand forecast accuracy typically leads to a .5 percent decrease in labor costs, which can add up to millions of dollars in savings for a national retailer.
The most advanced AI-powered demand forecasting solutions are able to continuously adapt to changing business conditions. AI-powered solutions enable higher accuracy by regularly retraining their algorithms, often as frequently as once a week. By having a system that can autonomously learn and improve, retailers will receive more accurate forecasts to optimize their labor.
The adoption of AI-powered demand forecasting empowers retailers to navigate the unpredictable terrain of customer demand with unprecedented precision. Yet, the ultimate success of this transformation hinges on the creation of optimized schedules that improve operational efficiency and empower employees with schedules that automatically match their skills and preferences to open shifts. In the intricate dance between technology, data and human insight, retailers find the means to not just meet but exceed customer expectations during the bustling holiday season.
Michael Spataro is the chief customer officer at Legion Technologies, a workforce management platform that maximizes labor efficiency and employee engagement simultaneously.
