AI and ML for Retail and Hospitality: 3 Key Opportunities

Retail and hospitality industry leaders are no strangers to disruption. In recent years, some had to upend their traditional business models to survive. Now a new kind of disruption has arrived, one laden with promise to transform these industries in a positive way: artificial intelligence (AI) and machine learning (ML). 

And as they pursue that promise, leaders understand that how they use AI and ML is both responsible and ethical. To quote Spider-Man’s Uncle Ben Parker, “with great power comes great responsibility.” 

Given the amount of news about AI and ML these days, it’s easy to be skeptical. Although the hype is at full volume, exploring the game-changing possibilities of AI and ML is far from new. The focus has just been turned up in recent months (looking at you, Chat-Bot-That-Shall-Not-Be-Named). 

As retail and hospitality leaders look forward, what are some key opportunities to utilize the vast potential of AI and ML? Let’s take a look.

Employee Engagement

Turnover, turnover, turnover. It’s long been a huge issue for retail and hospitality leaders, as they traditionally have some of the highest attrition rates of any industry. And the disruption of the last several years hasn’t helped matters—a recent Workday study found that retailers are facing even higher rates of turnover than normal. Retail workers are looking for better visibility, pay, training, and flexibility. In short, better engagement. 

Hospitality leaders are dealing with similar struggles. Another Workday study found that 56% of hospitality leaders say there’s a growing gap between where their business is today and where it needs to be to compete, and one of the biggest challenges is employee tools don’t access quality data that can deliver true insights. Both retail and hospitality organizations are looking for ways to bridge the gap between how things are and how they could be, and AI and ML can be the building materials for that bridge.

So how can retail and hospitality companies improve the employee experience with AI and ML? Employee-first scheduling (such as the capabilities built into Workday 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 study cited 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 Cloud uses 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 a Workday 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 Care is 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 and building out the demand forecast with 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 of Workday 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.