The pandemic taught us a lot about ourselves, each other, and the societies in which we live. It forced us to adjust how we socialize, work, and even shop. And it sparked shifts in behaviors that, in many cases, are here to stay—including the increased use of shopping apps, mobile checkout, and in-store pickups.
Within days and weeks of the pandemic’s onset, customers stormed both brick-and-mortar and online stores, stocking up on everyday produce and products. This rush in demand presented retailers with both significant opportunities and serious challenges; the fact that in-store shoppers were stocking up on everyday products while, simultaneously, online shopping soared resulted in popular items flying off shelves and becoming unavailable more quickly than they could be replaced.
Encountering out-of-stock items is frustrating for consumers—and it can be especially disconcerting for personal shoppers attempting to fulfill those online orders. Deciding how to substitute an out-of-stock product is complex and highly personal to each customer. There are nearly 100 different factors that can go into that decision, and even just weighing a few of those factors is time consuming. Which is why retailer Walmart turned to artificial intelligence (AI) to help.
Troubleshooting with compound innovation
Walmart’s solution was to look to AI for answers to help both customers and personal shoppers select the best substitute for an out-of-stock item. The Walmart team combined digital and human elements to meet this challenge, in an example of what MIT’s Paul McDonagh-Smith refers to as “compound innovation.”
A compound model of innovation identifies multiple dimensions along which innovation can be created to ultimately forge a successfully innovative product and/or service. However, in his online course Accelerating Digital Transformation with Algorithmic Business Thinking, McDonagh-Smith stresses the importance of human elements in this equation, explaining that “elements like creativity, curiosity, and compassion are the glue that binds these technologies together.”
"If we bond technologies together with human elements, we will create a foundation upon which we can build the sustainable and productive companies of today and tomorrow."
Walmart created a technology solution that uses deep learning AI to consider hundreds of variables—size, type, brand, price, aggregate shopper data, individual customer preference, current inventory, and more—in real time to determine the next best available item for a customer when their first choice was out of stock. Then, once the personal shopper has selected another option based on the AI system’s recommendation, they contact the customer to let them know about the substitute item. This allows the customer to pre-emptively approve the substituted item before they collect their order or before it’s delivered. As more shoppers purchase online, the AI technology keeps learning and thus continuously improving its recommendations to existing and new customers.
This example of compound innovation, which combines AI, social media, and cloud computing technologies, is bound together by the human elements of communication, choice, and continuous learning.
“Compound innovation enables us to create robust and sustainable solutions that are more than combinatorial collections of technologies,” says McDonagh-Smith. “If we build solutions that are simply combinations of digital technologies, we will literally be building our futures on silicon—upon pillars of sand. However, if we bond technologies together with human elements, we will create a foundation upon which we can build the sustainable and productive companies of today and tomorrow.”
Learn more about Accelerating Digital Transformation with Algorithmic Business Thinking on our website and in this recently recorded info session with Paul McDonagh-Smith.