By Inna Kuznetsova
C200 member Inna Kuznetsova is the CEO of ToolsGroup, whose AI-powered solutions enable companies to navigate supply chain uncertainty. Inna previously served as CEO of 1010data and as President & COO of INTTRA. She currently serves on the board for Freightos, a SaaS marketplace platform for international freight.
Over the last few years, we have seen a drumroll of supply chain crises—from rising and falling shipping prices to volatile demand and disruption of supply—caused by Covid-related closings in China and the war in Ukraine. Today many retailers are dealing with another type of inventory crisis: overwhelming amounts of overstock and unusable inventory.
This excess inventory puts retailers in a vulnerable position to face the current global economic headwinds. Lora Cecere, the founder of the firm Supply Chain Insights noted that companies entered this year with 2022 inventory levels at the highest they have been in a decade.
In actuality, inventory to sales ratios in 2023 have grown to levels not seen since 2007. Many retailers shipped in excess to ensure that a longer lead time, shipping delays, or changes in demand would not lead to empty shelves. Others failed in forecasting product mix for what today’s consumers—heavily impacted by inflation and post-pandemic changes in lifestyles—wanted.
The Struggle to Keep Pace with Consumers
The significant expansion of ecommerce prompted many retailers to implement new approaches to provide a seamless omnichannel customer experience, including options for customers to purchase products online and return them in a physical store, as well as consistent pricing and promotions across both online and brick-and-mortar stores. However, many retailers have not extended this same holistic approach to their inventory management across channels. They are struggling to adapt to the fast-changing patterns of consumer shopping due to outdated technology that limits their ability to quickly adjust merchandising strategies.
CNN reports that return rates for fashion items bought online are between 15 and 30 percent (compared to less than 10% of those bought in brick-and-mortar stores); retailers lack the ability to triage and direct the returns to stores, discounters, warehouses, or discarding facilities. They often end up absorbing shipping for at least two moves—first to a warehouse and then to the end destination—without tools to view real-time inventory status to select the most profitable way of dealing with each return.
With the US Commerce Department predicting continued consumer spending declines, retailers are looking for a more cost-effective way to manage stock.
The Future of Inventory Management
AI is poised to take inventory management to a new level through smarter and more efficient stock management systems, where retailers can quickly move inventory between locations and channels to meet customer demands. The adoption of AI technology offers a range of benefits, including enhanced decision-making, lowered costs, reduced risks, optimized warehouse operations, and increased productivity.
The adoption of AI technology offers a range of benefits, including enhanced decision-making, … [+]
By utilizing this technology, businesses can gain valuable insights into trends by analyzing vast amounts of data. This allows them to effectively manage their inventory and reduce shipping costs by identifying all potential variables and determining the most efficient and cost-effective methods of order delivery.
The convenience, personalization, and reliability that AI provides can generate a newfound sense of customer brand loyalty. Using AI technology, retailers can algorithmically manage inventory, resulting in less overstocks and out-of-stocks. Prescriptive analytics can be used to put machine learning software to work, allowing retailers to analyze consumer trends and make real-time decisions regarding pricing, promotions, and assortment. It’s been estimated that prescriptive analytics alone can raise same-store sales by 2 to 5 percent.
Overcoming the Complexity of Balancing Supply and Demand
To maintain product availability in an omnichannel retail environment without overstocks, retailers need real-time data and advanced analytics to respond to perpetual inventory signals. AI data provides a centralized view of on-hand inventory and changing demand to set optimal inventory levels across entire networks of stores, distribution centers (DCs), and fulfillment centers (FCs), along with a picture of real-time demand across all sales channels.
AI-powered analytics enable retailers to improve their speed and precision, so they can minimize inventory levels with confidence as they monitor and predict changes in consumer purchase behavior. Improving supply-demand alignment helps to avoid price reductions to clear excess inventory in stores or on warehouse shelves, thereby preserving profit margins.
Retailers can leverage machine learning to better forecast new product introductions and the impact of promotions. A form of self-learning artificial intelligence, machine learning (ML) can analyze past introductions to find correlations with a new product for determining the initial amount of needed inventory. ML can also be used to examine past promotions to determine the impact of a promotional lift so inventory planners can buy just the right amount of product to meet demand.
Many organizations were caught off guard by disrupted supply chains during the Covid-19 pandemic. If they don’t act promptly to adjust their inventory levels, they may face similar difficulties in the future as the economy weakens and inflation persists. AI-powered tools can help retailers manage inventory and demand by providing the information and insight to maintain an optimal balance of inventory. As a result, they can achieve faster inventory turnover, higher sell-through rates, fewer markdowns—and maintain profit margins even in a slowing economy.
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