What Happened to the New Norm for Retail?

Post-pandemic the retail industry was anticipating the new normal which never came. While retailers were establishing scalable solutions for challenges that surfaced from supply chain to shelf, artificial intelligence was becoming more accessible to consumers. Fast-forward a few years and what started as a new era quickly shifted to a mandate to do business differently — driven by the ever-evolving needs of the consumer. Retailers are now leveraging data and analytics more than ever to enhance experiences, optimize inventory and drive profit. So, what’s next?

Before we explore what's next for the retail industry, it's important to review the five current factors impacting  today’s “retail as usual.” Expectedly, inflation/rising interest rates and the broken supply chain are two of the top factors. These conditions are further fueled by the current state of consumers who are managing 40-year high inflation rates, nearly 30-year high interest rates, and dealing with dwindling personal savings accounts and record debt levels. These financial factors are further complicated by the identification of three new factors, namely more transient consumers via movement across the U.S., global warming implications, and body sizing shifts from weight loss drugs.

Consumer mobility is at heightened levels with more people moving in the last three years than in the previous 50 years combined. This shift in the shopper base is complicating merchandising, inventory and allocation decisions. Retailers can no longer rely on prior year/season trends; they need to consider the market shifts from/to warm, cold states and generational/demographic movements. Similarly, global climate changes are creating significant weather disruptions. Increasing floods, record high temperatures and more significant storm destruction are not only alarming, but are impacting retailer predictions from design to delivery.

The final factor, the increasing use of weight loss drugs, may seem unrelated to retail, but analysts state that a 2 percent shift in the industry’s size curve reduces gross margin rates by 360 basis points. Changing body types impact the food industry's sales, lifestyle choices and wardrobe selections. All of which can amount to significant changes in business trends.

Given the already complex marketplace and speed of customer change and expectations, retailers are turning to technology to help them solve for the emerging lack of predictability to their businesses. AI and machine learning have become more accessible over the last two years and have become a requirement to stay competitive. The progression of leveraging data comes down to:

• Statistical Modeling: creating logical assumptions based on a set of probabilities and a conditional framework.
• ML Application: processing existing and historical data for evolved learnings without the need to change programming structure.
• AI Generation: scalable data absorption and processing at granular levels using complex and predictive variables with the capability to provide forward-looking knowledge and generate new/nonexistent data/content.

The progression from statistical modeling to AI has allowed for retailers to address the current factors impacting their businesses. Specifically, AI creates value for:

1. Digital growth and experiences (conversational commerce)
2. Marketing and customer outreach (content creation)
3. Sustainable and efficient operations (customer services and back-of-office streamlining)
4. Associate and store productivity (training and task management)

AI was once deemed more theoretical by those who couldn't understand its application. However, with the use of quality data and insightful analytics, retailers today are applying technology to provide real-life solutions to market complexity and unforeseeable variables all while creating greater efficiency, accuracy and speed. One immediate win for retailers is the use of AI to identify and solve for lost sales. Brands are applying AI solutions to answer questions like “Why are we losing sales in our top/evergreen products?” and “How can we never be out of stock without simply increasing inventory levels?” AI can review large scale data inputs and tailor solutions down to regional or even store/consumer levels with custom assortments, demand and capacity considerations, and even predicting shared product allocations across channels.

But why is this only available now? Experts agree that while ML relied on historical data to predict and forecast, it had a technical deficit — namely, it couldn't generate new data to access patterns and identify risks. AI is trained to adapt and learn without human intervention (redoing data models). AI acts as a force multiplier to accelerate and amplify. Hence, the future is now and retailers need to get on board.

According to Columbus Consulting’s Managing Partner and Board Chair Elizabeth Elliott, “we are seeing clear AI applications in end-to-end inventory management. AI is helping some of our clients define their best products (sellable plus on-brand plus profitable), while establishing the most efficient inventory levels considering both supply and demand and applying optimized allocation plans across fulfillment centers and sales channels.”

Two cautions that Elliott speaks to about AI implementation is that retailers need to clearly define what they're asking AI to solve for before they start to leverage it. Furthermore, they need to consider how to prepare their organization for change and adoption.

“The true benefits of AI enable agility, responsiveness, predictability, visibility and resiliency,” added Elliott. In addition, she says that there's a greater opportunity for AI to be used earlier in the product lifecycle — at product creation rather than at delivery. This shift will help reduce waste, drive higher full-price sell-throughs, and minimize product transfers, all immediate cost benefits from early AI application.

The industry is at the end of manual, meaning that retailers are at a crossroad to pivot from manual intervention for running their businesses to leveraging AI to deliver greater accuracy, insights and profitability. So, what's next for the industry? Retailers have a choice today to either grow or decline. In order to grow, they need to be additive without layering on complexity and overhead and they need to find better means to de-risk their plans and execute their business. To do so AI/ML is an absolute requirement.

Lucille DeHart is principal of MKT Marketing Services. She is also the founder of Yogassists,