How AI can help solve retail’s billion dollar shrink problem
Retailers are constantly grappling with a multitude of challenges, but among these, retail shrinkage – the loss of inventory due to factors such as theft, administrative errors and fraud – stands out due to its significant impact on profitability. This costly global problem has long been a thorn in the side of retailers, resulting in billions of dollars of losses in the industry overall.
However, AI is emerging as a powerful ally, with several ways that retailers can implement this technology to help combat the shrink.
Leveraging Predictive Analytics to Outsmart Shrinkage
In the fight against retail shrink, knowledge is power. Predictive analytics offers this knowledge by using historical data, machine learning, and statistical algorithms to predict future outcomes. In the context of retail shrink, predictive analytics can identify patterns and trends in theft and fraud, enabling retailers to take proactive measures. For example, if a particular product is frequently stolen, predictive analytics can be leveraged to alert the retailer so that they can increase security measures around that product.
Additionally, predictive analytics can help identify internal issues such as employee theft or supplier fraud. By analyzing patterns in employee behavior or supplier deliveries, predictive analytics can flag potential issues before they become major problems. This ability to identify and address internal shrink sources can be game-changing for retailers.
Implementing Computer Vision Systems to Prevent Theft
Computer vision systems can reduce shrinkage significantly. These systems use a network of AI-enabled cameras and machine learning models, as well as insights from predictive analytics, to detect instances of theft and immediately notify managers to investigate. They can operate throughout the day, stay focused, and monitor all store areas simultaneously.
In addition, these solutions can help detect and prevent fraud scenarios such as customers leaving the store without paying for an item, track the status and locations of boxes and products in supply rooms for theft prevention, detect known shoplifters and criminals as soon as they walk into a retail store, and more.
Using AI-Powered Forecasting to Balance Supply and Demand
One of the key challenges in retail is maintaining the delicate balance between demand and supply. Overstocking can lead to increased shrinkage as items become obsolete or expire, while understocking can result in lost sales. AI-powered demand forecasting provides retailers with a more nuanced and accurate understanding of demand patterns, enabling them to make more informed decisions about inventory management and ultimately reduce shrinkage.
AI algorithms can analyze current market trends, past sales data, and even nutritional trends to predict future demand more accurately, helping retailers maintain optimal inventory levels. AI can also help retailers understand the impact of external factors such as weather patterns on demand. For example, for a grocer, an unexpected heatwave might increase the demand for cold beverages. With AI, retailers can anticipate these changes in demand and adjust their inventory accordingly.
Reinventing Inventory Management & Security with AI-Powered Robots
AI-enabled robots are helping to minimize shrinkage by scanning shelves for inventory accuracy and identifying potential hazards that could lead to product damage, such as spills or unstable stacks. BJ's Wholesale Club, for example, is deploying Simbe Robotics’ autonomous robot, Tally, in all its retail locations to roam the aisles, ensuring price accuracy and that products are in stock and in the right place. This real-time data enables BJ's to address inventory issues promptly, reducing shrinkage and improving the shopping experience for customers.
Retailers can also use AI-powered robots for security services. Robots can patrol stores during
and after hours, monitoring for suspicious activity and even deterring theft through their mere
presence. For example, Amazon announced Astro for Business late last year, which aims for its
Astro robot to act as a security guard for for small-to-mid-sized business.
customers.
Reducing Human Error & Increasing Efficiency with Automated Inventory Management
Automated inventory management systems powered by AI can significantly reduce shrinkage caused by human error. These systems can track inventory in real-time, automatically reorder products when stock levels are low, and identify discrepancies that may indicate theft or fraud. By reducing reliance on manual processes, these systems can increase accuracy and efficiency, leading to reduced shrinkage and allowing employees to focus on other high value tasks.
Additionally, automated inventory management systems can also help retailers manage their supply chains more effectively. By tracking inventory levels in real-time, these systems can identify potential supply chain issues, such as delayed deliveries or supplier shortages, before they impact the retailer's inventory levels. This can prevent understocking and overstocking,
further reducing shrinkage.
The challenges posed by retail shrink are significant, but the potential solutions offered by AI are equally substantial. As we move forward, the role of AI in retail will only become more important. It's not just about reducing shrinkage - it's about transforming the way we approach retail management. The future of retail is here, and in this future AI is not just a tool — it's a game —changer.
Sudip Mazumder is senior VP, retail industry lead, North America at Publicis Sapient, a global digital transformation consulting company. He can be contacted at [email protected].
