AI Inventory Management

American retailers hold about $1.43 in inventory for every $1 they make in sales. This, coupled with accounts payable and accounts receivable assets, account for nearly $1.1 trillion in inventory, which is about 7% of the United States GDP. These worrying statistics come as no surprise considering the fact that 46% of small to medium-sized businesses don’t have an inventory management system in place [2]. However, the digital transformation currently underway in the warehouse and logistics sector is poised to revolutionize inventory management through AI capabilities.

This article will take a closer look into the role of artificial intelligence in inventory management, how to implement it, and the future of AI in inventory management.

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What is inventory management?

Inventory refers to the goods and materials a business intends to sell for profit. Therefore, inventory management encompasses all the processes and techniques employed in the manufacturing, storage, and distribution of goods. Its aim is to ensure the availability of the right goods at the right place and at the right time.

It achieves that by tracking all inventory from the manufacturers to the point of sale, allowing you to monitor inventory levels, sales, orders, and deliveries. AI in inventory management take these processes up a notch by identifying and responding to consumer trends. This ensures that there is always enough stock to meet customer demands.

Inventory management is vital to the success of any B2B or B2C business because it limits the possibility of having too much or limited stock at hand. It is also necessary for regulatory compliance with the Sarbanes-Oxley (SOX) Act[1] and Securities and Exchange Commission (SEC) rules, which require all public companies to document their inventory management processes.

How to use AI for inventory management?

Artificial intelligence in inventory management can help optimize business processes at all stages. Implementing AI, for example, in inventory management practices like item-level tagging can increase inventory accuracy to 95% [3]. Here are other ways in which you can use artificial intelligence for inventory management.

Streamlining the entire inventory management process

Inventory management isn’t just about keeping track of stored and delivered items. It’s also about forecasting, planning, and control. By leveraging AI in inventory management, a business can minimize the possibility of overstocking and understocking. That’s because AI technology can consider location-specific demand, analyze and correlate demand insights, and detect and respond to consumer demand for a specific product.

AI solutions can also analyze all internal and external factors impacting the successful planning, stocking, and delivery of inventory. This ultimately reduces errors associated with inventory management, thus helping a business save costs and increase customer satisfaction.

Using AI-based robotics in the warehouse

Large retail companies like Amazon already use AI-based robots in their day-to-day logistical tasks. These machines present numerous benefits over human staff, especially when it comes to increasing productivity in routine operations.

Unlike humans, robots can work tirelessly round the clock moving items around the warehouse. They also come equipped with scanners that enable them to scan inventory for wear before loading it into delivery vans.

Robots are also more efficient from an operational standpoint since they can analyze data and predict demand patterns. They also eliminate the possibility of human error and offer more efficiency in terms of time spent per action.

From a budgetary standpoint, AI-powered robots require less operational costs than human employees. These machines only require a one-time acquisition payment and regular maintenance costs, as opposed to human employees who need monthly salaries and benefits.

Stocking management and delivery

Warehouses need to run smoothly for optimum business performance. Inventory management issues like planning errors and inadequate stock monitoring can lead to inventory shortages and delivery delays, which could have a negative impact on revenue and customer satisfaction.

Artificial intelligence in inventory management systems can analyze customer behavior patterns and help businesses stock the right inventory, arrange stock, automate inventory fulfillment procedures, and optimize inventory delivery by suggesting the best routes.

Additionally, using AI for inventory management can help optimize factory-to-warehouse and warehouse-to-client transportation, leading to on-time deliveries, which positively impacts customer satisfaction. The AI can also analyze a company’s delivery process and suggest ways of improving it.

Data mining and processing

AI can analyze customer data and transform it into valuable insights that can help a business respond to specific trends. By analyzing different aspects, such as trendy goods, sporting events, or any other factors that could drive up demand for a certain product, AI systems can ‘advise’ a business to overstock or understock specific products, thus driving up sales and minimizing the risk of dead stock.

Delivering personalized customer experience

Most businesses today have large volumes of customer data. By leveraging AI-based software, businesses can use this data to create personalized customer experiences by tailoring relevant products and services to specific customers. The result is personalized user experiences built around the specific customer’s demands.

The benefits of using AI for inventory management improvement

Effortless demand forecasting

In the past, businesses relied on demand forecasting methods such as exponential smoothing and autoregressive integrated moving averages. But these methods are rapidly becoming antiquated as businesses generate more data, thus necessitating the need for a robust system that can spot demand patterns and use the data to forecast and optimize inventory replenishment plans.

That being said, AI uses real-time data to provide instant forecasts on inventory management. This reduces reliance on traditional forecast methods, which are not only time-consuming but are also affected by human error.

Additionally, AI-powered demand forecasting can reduce supply chain errors by a big margin, which increases accuracy and reduces monetary losses due to unplanned consumer demand and incorrect stock numbers.

It might be interesting for you: Reduce Operating Costs and Improve Efficiency Using AI

Automated material procurement

All manufacturing businesses need an elaborate and efficient procurement process. However, the large number of documents and suppliers involved is enough to confuse any human worker, leading to mistakes and inefficiencies.

Artificial intelligence can help automate such processes, right from getting the best quotes to taking the materials through the supply chain.

According to a recent McKinsey report, businesses that use AI in their procurement process report a 35% to 65% improvement in inventory and service levels and a 15% reduction in logistics costs [5].

Safety stock management

Traditionally, businesses set a static quantity for their inventory levels, which basically meant reserving a bare minimum for walk-in sales that were not factored into other fulfillment channels such as eCommerce.

However, today’s ever-changing consumer expectations and omnichannel engagements have made it nearly impossible to conveniently rely on generalized information. In today’s market, businesses need to dynamically shift their stock levels to leverage and react to incoming demand.

In order to achieve profitable results across all fulfillment channels, businesses need intelligent solutions that can balance fulfillment costs against service demands to improve customer experience, enhance return on investment, and encourage repeat purchase behavior.

Using AI in safety stock management can also help avoid inventory issues such as overselling and then over-purchasing inventory, promising customers goods that cannot be delivered, and overstocking on ‘unpopular’ goods.

Improved productivity through AI algorithms

Artificial intelligence is becoming an integral part of normal day-to-day business operations. AI algorithms can, for example, be used to manage and oversee tasks, thus limiting the need for human workers to undertake mundane, repetitive tasks.
The result is improved productivity, efficient utilization of resources, and better monitoring of aspects such as lead times, quantities, and operational inefficiencies.

Reduced storage and shipping costs

Businesses lose more than $300 billion in revenue due to poor inventory management [6]. However, by leveraging AI capabilities to improve inventory management, they can cut operational costs and improve cash flow by a huge margin.

By harnessing AI for inventory management enhancements, businesses can, for example, prioritize critical processes to resolve bottlenecks, meet ever-changing customer demands, and mitigate costly risks. The resulting effect is a significant reduction in high rental storage costs, unsatisfied customers due to inventory shortages, and unsold products. AI can also enable you to make additions to your product line-up and inventory with little or no added costs.

Reduced demand-supply gap

When combined with data analytics, artificial intelligence can accurately predict customer demands and maintain healthy stock levels at all times. These systems generally work by analyzing customer demand for seasonal products for the past few years, then using the data to forecast demands for the upcoming season. Some systems can also pre-order the products, thus streamlining business operations even further.

Data accessibility support

Lack of visibility is one of the most common data-related inventory challenges that often lead to gaps and inaccuracies in important inventory and sales information. This issue often stems from the use of legacy systems and manual inventory management methods, which are susceptible to human error.

AI in inventory management enables you to automate the storage, collection, and dissemination of all inventory-related data. These include product tracking, supplier delivery times, product information, and item location within the storage facility.

Improved employee performance

A well-managed inventory can significantly reduce performance pain points for all employees across all areas of business. Recent surveys reveal that AI can boost employee performance by up to 40%, especially for customer-facing employees, who can make accurate and timely product recommendations based on available data and insights.

AI in inventory management can also improve the overall performance of a retail business through business education tools such as administration programs that offer trading courses and management information.

The future of AI in inventory management

AI is poised to take inventory management to a new level through faster, smarter, and more efficient inventory management systems. AI can enable businesses to track multiple orders simultaneously and identify any inventory issues and delays in production and shipping times.

AI-based inventory forecasting is also expected to gain widespread popularity across the retail industry as businesses seek to gain a competitive advantage. By pulling historical sales data and matching it to consumer trends, AI-based forecasting will enable businesses to identify trends beforehand and increase stock accordingly.

AI will also change how businesses perform inventory checks through automated surveillance systems. This will allow businesses to limit reliance on human labor and utilize their assets and resources in other areas of business.

AI-based robots are also expected to gain widespread usage across major warehouses due to the level of convenience and cost-effectiveness they provide. In fact, major retailers have already started using these robots, and in the near future, we’re likely to see them being employed in other areas, such as delivery.

Final Thoughts on AI for Inventory Management

Businesses that leverage AI for inventory management across the supply chain can gain a competitive advantage and secure long-term growth. AI helps retail, warehouse, and logistics companies eliminate the pain points of inventory management by automating repetitive tasks and providing valuable insights.

Mundane tasks like manual inventory checks and relocating and tracking items, for example, are slowly being replaced by AI-based algorithms and robots that can do the job faster, more efficiently, and at a fraction of the cost. See our AI consulting services to find out more.

AI in Inventory Management: FAQ

What is inventory management?

Inventory management encompasses all the processes involved in the manufacturing, storage, and distribution of a business’s goods and materials. It aims to ensure the right goods are available at the right place and time by tracking inventory from the manufacturer to the point of sale.

How does AI improve inventory management?

AI in inventory management supports organizations by identifying and responding to consumer trends, analyzing and correlating demand insights, and detecting consumer demand for specific products. It minimizes overstocking and understocking through intelligent forecasting and control, thereby increasing accuracy and customer satisfaction.

What are some applications of AI in inventory management?

AI can be applied in various aspects of inventory management, including streamlining the entire process, using AI-based robotics in warehouses for increased productivity, optimizing stocking management and delivery, automating material procurement, and providing personalized customer experiences.

How does AI contribute to demand forecasting in inventory management?

AI uses real-time data to instantly forecast inventory requirements, reducing reliance on traditional methods that are time-consuming and prone to human error. AI-powered demand forecasting improves accuracy and reduces supply chain errors, leading to optimized inventory replenishment plans.

Can AI manage safety stock levels?

Yes, AI in safety stock management helps businesses dynamically adjust their stock levels to meet incoming demand across all fulfillment channels. It balances fulfillment costs against service demands to enhance customer experience, improve ROI, and encourage repeat purchases.

This article is an updated version of the publication from Oct 20, 2022.

References

[1] Scdigest.com. Newsviews. URL: https://www.scdigest.com/assets/newsviews/15-04-23-1.php?cid=9231. Accessed October 17, 2022
[2] Waspbarcode.com. Small Business Report. URL: http://www.waspbarcode.com/small-business-report. Accessed October 17, 2022
[3] Researchgate.net. Improving Inventory Accuracy Using RFID Technology. URL: https://bit.ly/3VvsEKx. Accessed October 17, 2022
[4] Researchandmarkets.com. Chatbot Market Growth Trends-Covid 19 Impact. URL:  https://www.researchandmarkets.com/reports/4622740/chatbot-market-growth-trends-covid-19-impact. Accessed October 17, 2022
[5] Mckinsey.com. Succeeding in the AI Supply Chain Revolution. URL: https://www.mckinsey.com/industries/metals-and-mining/our-insights/succeeding-in-the-ai-supply-chain-revolution. Accessed October 17, 2022
[6] Mytotalretail.com. Hidden Costs of Poor Inventory Management. URL: https://www.mytotalretail.com/article/hidden-costs-of-poor-inventory-management/.