According to one of GlobalData’s latest Disruptor Database reports, retailers and fast-moving consumer goods (FMCG) companies will need to follow trends in A.I. across several categories if they want to maintain competitiveness. That’s not only because A.I. is generally less cost-intensive than traditional big data analytics, either. A.I. can be and has been additionally utilized in a vast array of predictive analytics use cases which helps optimize decision making from supply chain to retail locations. Meanwhile, the benefits returned by that range from cost savings to additional sales and better customer service. Those companies that take advantage of A.I., GlobalData suggests, will excel in their respective markets while those that fail to will quickly fall behind. What’s more, citing examples from Procter & Gamble’s Olay to Amazon, there aren’t necessarily any markets that will be left out of that trend.
All told, GlobalData highlights six portions of the “value chain” where A.I. can bring value to those companies or businesses that invest in it. Of course, that all starts with product design and development, where machine learning can be used to forecast future design and optimize current designs. Those optimizations range from cost-cutting measures in the production itself to the creation of prototypes. The concept makes sense given that an A.I. could feasibly be programmed to learn how and where a product could be scaled back in terms of material used without harming quality in a noticeable way. That's also something that it could create various prototypes for as proof of concept, although that's really just one example. Moving on from that, supply chains and source, manufacturing, or operations management is another area where A.I. can massively improve things. GlobalData points to better workflow and warehouse management as well as enabling real-time on-demand production and product targeting. Tied in with that aspect of business operations is A.I.’s ability to actively target on the retail side of the equation while also actively adjusting pricing for optimal performance. Furthermore, it can be used with new retail locations to determine the best location for the business to operate from.
Beyond the storefront itself, A.I. can be utilized for better marketing and to forecast sales and production needs. Part of that would include keeping track of trends among competitors and planning the timing of sales around big data analytics as performed by A.I. Following on recent trends with the technology in its use for chat-bots and virtualization, A.I. will also have a place in customer relations. Not only can it be used to assist customers via communication. It can also stand apart as a way to better reach customers who might be interested in products or services, to begin with. Meanwhile, dressing rooms and other aspects of the consumer’s decision-making process can be digitized using A.I. for a more seamless experience using augmented or virtual reality. That same type of system could go further to offer intelligent advice and product suggestions based on consumer response and preference. Last but certainly not least, A.I. could be used as a way to ensure products meet safety regulations and ensure compliance with other consumer regulations such as those pertaining to credit assessments. That's in addition to its use in addressing cybersecurity issues such as fraud.