Business leaders in the retail industry are leveraging a groundbreaking new way to make their operations more efficient: Machine learning and AI-powered task-management software. These sophisticated platforms are not only revolutionizing retail but also enabling savvy companies to vault to the forefront of their sectors.
“AI and machine learning have come a long way in just a few short years,” says Brianna Van Zanten, Customer Success Manager of InCheq, an AI and machine learning global task management platform. “These systems are real game-changers that can make the difference between a business that asserts its dominance over the competition and one that falls by the wayside.”
Machine learning and AI task-management systems improve business performance in multiple ways.
Automating retail operations
First and foremost, today’s automated-based task-management platforms can complete a surprising number of necessary activities, so human staff members no longer have to.
“Automations can take over those routine things that would otherwise consume a lot of people’s time,” Van Zanten explains. “For instance, in retail, these systems can be coupled with radio frequency or other sensors to track inventory automatically. They can also send restocking alerts and reorder products when supplies start to dwindle.”
In this way, automated systems enhance inventory management, preventing stockouts and overstocking. They can also generate sales reports on demand or a regular basis. “With systems like ours, management always knows exactly what they have on hand, as well as where it is,” Van Zanten says. “It’s the ultimate birds-eye view.”
Indeed, according to the financial services company Morgan Stanley, automation could increase retailers’ efficiency in routine tasks by up to 70 percent.
Moreover, when machines handle these sorts of assignments, the potential for error decreases. “It’s natural for humans to get bored and slip up, sometimes without even realizing it,” Van Zanten says. “In contrast, machine learning is tireless and never becomes complacent. As a result, the system doesn’t hit the wrong key on the keyboard and report the wrong number.”
Another important way machine learning and automated systems can improve retail operations is by optimizing the workforce.
Optimizing the retail workforce
Automated systems are particularly adept at creating schedules for staff members that ensure resources are used as efficiently as possible. “Algorithms can account for everything from seasonal demand, sales trends, and even foot traffic to determine how many employees are needed and where they should be,” Van Zanten says. “Due to automated systems’ ability to track sales volume, it can also tell you when your peak times are and calculate how many cashiers you should have to reduce customer wait times.”
Automated systems can also handle staff scheduling. “These automated platforms heed individual staff members’ availability, so no one ever gets upset because they were scheduled to work when they already requested time off,” Van Zanten says.
Today’s automated-powered systems are dynamic, which means they can respond to changes in the real-world situation without hesitation. “Let’s say someone calls in sick,” Van Zanten says. “This happens all the time. However, with a machine learning and AI-powered task-management system, the manager can get the system’s recommendations for a replacement worker at the same time that they get the original employee’s notification of sick leave. They can pivot immediately to the solution.”
As a result, the store floor is always adequately staffed, assuring high-quality customer service. These systems also elevate the customer experience by personalizing recommendations and placing products in the optimal positions.
But that’s not all. Today’s automated task-management systems are revolutionizing the retail industry through powerful data analytics.
The power of data analytics
“Perhaps the most important thing systems like ours do is empower leadership with up-to-the-second insights about how their wares are performing and what customers are doing,” Van Zanten says. “At any given moment, you can see where things need to be shored up or there’s an opportunity to exploit. In other words, you have the information you need to take action.”
Machine learning and AI-powered task-management software can also enable management to game out potential strategies for the future. “They can predict what would happen if certain changes were made,” Van Zanten says. “This means buyers at retail stores can make the most advantageous decisions about the range of products to offer and how to price them. Another example would be marketing — the machine learning can tell you which messages resonate best and with whom.”
The data analytics that automation enables also gives business leaders a solid foundation upon which to make other major decisions. “Let’s say you are trying to decide whether to open another location,” Van Zanten says. “The automated system can simulate what would happen if you did. It can also show you the likely results if you put the new store in one location versus another. That way, you can create an expansion plan with the best chance of success.”
Greater efficiency translates into greater profitability
With the advent of machine learning and AI, the world of retail will never be the same.
“The more efficient your operations are, the more money you make,” Van Zanten says. “Today’s machine learning and AI-powered task-management platforms ensure your business is as efficient as possible. In this way, it directly supports your enterprise’s profitability.”
