AI offers retailers the chance to cut waste and costs
What it means: Retail is notoriously a complex industry with networks of stores, supply chains and employees. Layer on the additional obstacles posed by e-commerce fulfillment, and the end-to-end process of retail operations becomes costly and inefficient. AI and machine learning are working to define their value proposition within retail, starting with optimizing the supply chain and improving the customer experience on the front lines. Through seamless inventory management and sales predictors, AI can streamline retail operations and predict consumer behavior with the agility to transform how retailers function.
Read on for more insights, details and what's next!
Smarter inventory management is a critical component for retailers to reduce waste and excess inventory. By predicting customer demand for depth and breadth of inventory — using AI artificial intelligence (AI), predictive analytics and real-time data — retailers can better optimize inventory allocation and adjust, replenish and rebalance in real time. AI can help retailers increase sell-through, reduce out of stocks at individual stores and minimize heavy markdowns and significant end-of-season excess inventory, empowering merchandising and planning teams to make smarter and greener decisions.
In addition to margins, global government regulations are pushing the transition to a sustainable economy, including the latest from the Council of the European Union with its Corporate Sustainability Reporting Directive.
Whether fueled by the need to be eco-conscious, reduce costs or improve consumer experience, retailers are responding by tackling how to get the right amount of product with smarter inventory optimization.
“It's the next-level AI that will help retailers of all types — apparel, grocery, drug, convenience — fuel smarter, more profitable operations,” James Theuerkauf, Syrup Tech’s co-founder and CEO, told Retail Leader Pro. “AI and machine learning technologies continue to improve the customer experience as well as help retailers understand customer behaviors and trends to better meet demand. For example, inventory optimization technologies that enable more accurate inventory allocation and planning decisions are crucial to profitability, especially in an uncertain economy. …New retail applications that leverage AI and machine learning are helping retailers better predict product sell-through, enabling them to sell more items at full price.”
AI and customer experience
Out-of-stocks and empty shelves remain a frustration of consumers. AI helps retailers stay ahead of consumers by continuously tracking point-of-sale data and inventory levels to identify sales opportunities.
“By helping to identify what products are selling at which locations in real time, retailers can transfer or re-buy inventory to avoid stockouts,” Theuerkauf said. “Not only does this prevent empty shelves or an advertised product that is unavailable, but it also allows retailers to become more nimble. Moving inventory from low to high volume stores prevents excess inventory from building up, often resulting in markdowns and lower margins.”
AI and inventory management
AI also can help retailers sell smarter by improving decision making with more accurate and dynamic demand forecasting, as well as using stochastic optimization to optimize distribution and ordering workflows. Together, AI and predictive analytics work to collect, process and analyze years’ worth of data — including real-time data — to help retailers make smarter data-driven business decisions such as anticipating and forecasting inventory needs, eliminating unnecessary markdowns and excess inventory, and, in the end, maximizing margin.
“Managing 10,000 SKUs is a very tedious process,” Theuerkauf said. “AI can cut through the laborious and time-consuming process of manually sifting through mountains of data required to make forecasting decisions in a fraction of the time. AI automates the processes by mining and analyzing data and offering smart insights and recommendations to help retailers make smarter inventory decisions.”
AI and sustainability
Overproduction and excess inventory in retail is a problem that the industry continues trying to solve. AI and data science can help fix this, Theuerkauf explained, by taking the guesswork out of inventory planning and allocation and enabling smarter and greener decisions about ordering and planning.
“Ultimately, AI can help make fashion, one of the world’s most polluting industries, more sustainable by reducing overproduction and only producing what’s needed,” he said.
As consumers continue to tighten their wallets this year, and with margins increasingly thin, retailers must find new ways to drive profitability.
“With increased competition at a global scale, selling more is not an effective tactic,” Theuerkauf said. “Retailers must find innovative ways to not only cut costs, but maximize each and every sales opportunity — and AI is the most effective way to do so. AI and machine learning technologies analyze more data points faster, empowering teams to make smarter, more accurate decisions. It’s not about replacing humans with algorithms, but rather combining AI-powered recommendations with the domain expertise and insights of humans to ultimately drive profitability.”
What's next
As AI becomes more cost effective overtime, retailers and brands need to lay the groundwork for optimizing inventory and supply chain as machine learning infiltrates retail front lines. AI has the potential to change how retailers can adapt and anticipate changing consumer demands in real time and quickly create strategies to meet those needs.