所以零售和人们如何tality companies improve the employee experience with AI and ML? Employee-first scheduling (such as the capabilities built intoWorkday Scheduling) is a massive opportunity for both industries, as employee flexibility is a powerful retention booster (for example, some workers may be balancing more than one job and need tools that make their lives easier). With AI at the core, Workday Scheduling matches worker availability, preferences, and skills to open shifts, creating schedules that meet the needs of everyone involved. Adapting to change and scenario planning for the business becomes easier, and guesswork is a thing of the past. More flexibility = happier employees = better retention.
The proof of this approach is already showing, according to the studycited above—applications offering employee-first scheduling are much more likely to be used by companies who are reporting lower-than-average turnover rates.
Career and Skills Development
Another key opportunity in the power of AI and ML to improve the employee experience is with greater support for career development. The lack of a clear career path can practically open the door for any employee to leave, but the opposite can also be true. When employers can unearth skills that they might not have known about, a clearer understanding of each employee’s abilities comes to light.
Workday Skills Clouduses AI to provide employers with a holistic view of each worker’s skills, and with that knowledge, gaps can be proactively identified and filled. As the director of human resources for a major retailer said, “The ability to use that (skill) information and figure out creative ways to create career advancement for employees is fantastic.” And the opportunities extend to making managers’ lives easier as well.
Shake Shack CIO Dave Harris spoke to this point in aWorkday case study. He said that wherever possible, the company focuses on automating processes to reduce the time that managers spend on administrative tasks, so they can spend more time on value-adding activities with their teams and guests.
Finance Accuracy and Planning
Shifting gears a bit, the potential of AI and ML for retail and hospitality can play a huge role in improving operations, particularly for finance leaders. Anomaly detection, spend category recommendations, and demand forecasting are a few examples.
How does this play out in real life?Team Car Careis a great example of the proverbial rubber meeting the road. Before Workday, spreadsheets were the company’s main artifacts for financial planning. But as Team Car Care implemented the full Workday Enterprise Management Cloud platform, it found ways to utilize ML to predict demand across locations by connecting to weather data andbuilding out the demand forecastwith that in mind. (Not surprisingly, people don’t like to get their oil changed during a downpour or blizzard.)
ML is also helping Team Car Care forecast how many of each of 500 products it will need to have in stock at each store, to automate replenishment. To power this effort, Team Car Care is an early adopter ofWorkday Intelligent Demand Forecasting. As its Manager of Financial Planning and Analysis and Corporate Data Science Pranay Arya said, “Workday has been a game-changer for us. It’s so much easier for us to partner across the business now that we’re on the same page using real-time data.”
Whether the goal is to reduce turnover by improving the employee experience or getting smarter about business planning, retail and hospitality leaders would do well to think creatively about the potential of AI and ML for their business operations—as they move toward a brighter future.