In the last fifty years, we’ve seen retail move from main street to the mall and from niche shops to superstores. There have been massive shifts and waves in the industry but until the early part of the last decade, the basic logistics have been the same: A customer in 1908, 1980, or 2008 wanted to buy something, traveled to the store, browsed the available inventory, paid for their purchase, and took it home. Even considering factors like special orders or layaway, the customer journey was not that different ten years ago than it was 100 years ago.
Ten years later, that is no longer the case.
Surviving in the modern retail landscape means being agile, adaptable, and able to embrace AI and automation to streamline and optimize processes, manage inventory, and mitigate customer expectations.
In fact, many experts now say that AI powered automation is no longer an option, it’s a requirement. A recent McKinsey study predicts that automation will “reshape retail business models and the broader value chain, creating organizations with fewer layers and a better trained and trusted workforce empowered by real-time data and analytics.”
Retail has been a roller coaster ride over the last ten years. Amazon’s super streamlined, instant gratification machine has driven seismic shifts into the industry. The last decade has seen the world of retailed completely upended. On-demand culture hasn’t just disrupted retail. It’s forced retailers to reconsider their entire process from warehouse to cash register to keep up with rapidly evolving customer expectations and survive in a digital world.
“Margins are stressed from all sides: higher costs to manage e-commerce supply chains, growing demands from suppliers to pass on raw-material cost inflation, higher investments to match new competition, and steadily rising labor costs. At the same time, the customer’s expectations continue to surge as digital natives and disruptors alike raise the bar for personalized service—on the back of what, at times, is an advantaged cost structure.” – From McKinsey, Automation in retail: An executive overview for getting ready
These shifts have left behind a lot of casualties. Thousands of brick-and-mortar retailers have been forced to shutter their doors. Some, like big music stores, were doomed by advancements in other industries. Others simply failed to evolve. A lack of adaptability and inefficient operations has been the downfall of many retailers that were once behemoths. Former employees of Sears, for example, cited “selling products consumers don’t want, not maintaining stores and inventory” as key factors that contributed to the closing of their doors last year.
A lot of people hear words like “automation” and immediately recoil with fear that whatever you’re about to say next will decimate a workforce and ruin lives. Those fears are not entirely unfounded, but they are largely misplaced. The McKinsey study mentioned above also indicates that roughly half of all retail activities can be automated using current technology. While they acknowledge this is an alarming number, they are also quick to point out that, “the change will be less about job loss and more about the evolution of jobs, the creation of new ones, and reskilling. Only about 5 percent of all jobs can be fully automated with current technology, and automation will lead to the creation of jobs as companies invest in growth.”
Embracing AI and Automation
The customer-facing side of retail is evolving in a variety of ways to direct customers away from their screens and into stores. Many stores that are thriving are doing so because they have completely revamped their interiors; moving away from utilitarian spaces with massive inventories in favor of engaging, customer experience focused spaces.
Creating these spaces requires a lot more than a good interior designer and a fresh coat of paint. It requires precise, streamlined inventory management. When customers venture into a store rather than making a purchase from their phone, they expect to find what they are looking for, and quickly.
Reducing inventory to make sure customers find what they’re looking for in-store might seem counterintuitive but AI-assisted automation makes it extremely doable. Modern problems require modern solutions and the answer to digital disruption in retail lies in digital assistance.
“AI-assisted technology running on big data can help optimize inventory at all levels in the demand chain. It even can predict future buying behavior and detect and act on supply chain anomalies in a timely fashion. With the implementation of “smart” warehouses, retailers are beginning to reach new levels of efficiency.” – From E-Commerce Times, AI-Powered Inventory Management: A Make-or-Break Tool for Retailers
The benefits of AI and Automation are as varied as they are abundant. Companies stand to improve their consistency and agility while reducing costs and freeing up their people to focus on more specialized, complex tasks.
Proper data analytics and AI-driven programs allow retailers predict demand in ways that were never possible until now. Automated inventory management can help select the best products to stock in each store and even speed up shipping times by moving certain products to their optimal geographic locations ahead of ordering. AI and machine learning are especially helpful for predicting and pin-pointing flash-bang demand for products and future trends, allowing supply chains to be more flexible and reactive.
Smart warehouses, fully integrated with machine learning, AI, and other automated analytics are the future of the supply chain. Automating the inventory process has allowed retailers to drastically reduce the amount of time it takes to get a product from warehouse to store.
This isn’t a pipedream for a distant future, it’s happening now. In fact, you’d be hard-pressed to find a successful retailer who isn’t using automation in some form.
Ryder, for example, has claimed “20 percent better efficiency, 100 percent product visibility, and a 20 percent decrease in operational costs” since implementing smart warehouses. Standardized machine automation removes unstable, potentially costly variables such as human error, and allows supply chains to react more fluidly to consumer demand.
Lowe’s has been testing a fleet of multilingual robots that can direct customers to the right aisle. North Face (and many other companies) has implemented a particularly useful chatbot that helps customers select the right jacket for their needs and personal style.
Kroger’s new Kroger Edge digital shelves display prices, nutrition facts, coupons, and video ads, all controlled and updatable from a central hub. As they rollout their smart-shelves to more and more stores, the grocer plans to link the shelves to their smartphone app for even more personalization.
Re-Skill, Don’t Replace
All of this automation means a lot of shuffling of existing processes and people. It also means that certain jobs will inevitably be eliminated. It does not, however, have to mean that the people holding those jobs need to be eliminated. Research shows that while reskilling employees does take some effort, it offers a far better ROI; 1.5 to three times better, in fact. The average cost of replacing an employee is 20 to 30 percent of an annual salary while reskilling comes in at less than 10 percent. Reskilling also allows retailers to “retain institutional knowledge” and eliminate onboarding time required with new hires.