2018 Technology Preview: How Retailers Can Use Predictive Analytics to Grow The Bottom Line
Every day, retail stores collect millions of data points. From how many customers walk into a store to which items are most likely to sell out first to which employees are the most reliable and engaged, retailers have a goldmine of data they can use to make more informed decisions regarding staffing and operations.
But the data collected by store managers often comes from disparate sources, making it difficult for retailers to turn their raw data into actionable insights. However, aggregating data and using it to make managerial decisions speeds up the decision-making process, freeing managers to focus on what is most valuable—developing strategy, coaching their employees, and by being more efficient—resulting in cost savings. Predictive analytics is about using available data points to make the workplace more efficient, more cost-effective, and allows managers to focus on managing and leading.
Predictive data analytics empower retailers to make smarter and more agile business decisions
New technology, including digital workplace platforms, has made it make it possible for retailers to digitally monitor all parts of their business. Once that data is compiled and thoroughly analyzed, it surfaces useful information retailers can use to manage their workforce.
Take, for example, decision making in workforce scheduling. Using a digital workplace platform, retailers can track how many hours an employee works each week, which are the most engaged, and analyze levels of productivity during each shift. Managers can then use this information to determine which employee is best suited for additional shifts and remove individuals whose past behaviors raise a red flag. If an employee is slated to work on a busy holiday but has missed their last few shifts, for example, predictive analytics can suggest to managers a different employee who is more reliable. On a macro level, predictive analytics can help employers identify dysfunctional teams early on and address leadership and functional needs before it becomes a wide scale issue.
Retailers that are able to take advantage of their employee and sales data will better understand their business and identify ways to improve their retail and employee experience compared to their competitors. While some retailers may question a machine’s ability to make decisions currently entrusted to HR, inventory and sales managers, there is growing evidence that predictive analytics can effectively supplement the activities of retailers today. It is happening in 2017 and will explode in 2018.
The new frontier will be in using predictive analytics to grow company culture and create environments where managers are empowered to lead their hourly associates because technology is enhancing their decision-making capacity.
As businesses continue to compete for the lion’s share of the market, retailers will need to not only embrace their store data but also go beyond data analysis to anticipate what the workplace needs next. With the assistance of predictive analytics, retailers can expand their ability to provide their customers the best shopping experience possible while maximizing their sales potential and growing the business’ bottom line.