Fix Inventory Accuracy with Autonomous Inventory Management

Summary

In the ever-changing landscape of e-commerce and global trade and the growing requirement to do more with less, the demand for efficient, error-free and streamlined operations has made warehouse automation a crucial element for operators. Warehouse automation involves utilizing new types of machines and equipment, such as robots/AGVs for sorting, picking and moving inventory, as well as software for improving the management of data and orchestration of operations. These solutions generally manage or enhance warehousing and fulfillment tasks typically handled by human workers, such as inventory tracking, packing and shipping.

The adoption of warehouse automation solutions provides businesses with enhanced control and visibility over their operations, with research indicating that 26% of warehouses are expected to be automated by 2027, compared to 14% a decade earlier.
 
Within the context of this evolving landscape, inventory accuracy is one of the most important key performance indicators (KPIs) for any 3PL or warehouse. Achieving higher accuracy rates is directly linked to faster order processing, leading to efficiencies that reduce overhead costs, improve customer service and enhance the capacity to support more business. Traditionally, warehouses relied on extensive manual labor for cycle counting, often involving safety hazards when dealing with inventory stored at dangerous heights. However, the increasing adoption of automation capabilities, specifically Autonomous Inventory Monitoring, is revolutionizing inventory management.
 

Defining autonomous inventory monitoring

Autonomous Inventory Monitoring is an approach that utilizes autonomous drones and cloud-based analytics to transform the conventional inventory cycle counting process. These drones seamlessly navigate through warehouses, scanning inventory, visually inspecting what is on each shelf location and providing an accurate inventory snapshot to managers. By offering true awareness of actual inventory, including insights into empty bins and inventory analytics, productivity and efficiency are significantly improved. Notably, it can also provide an indicative 40%+ return on investment, eliminating the need for the trade-off between heavy investments in manpower or accepting the costs of shrinkage.
 
Representing the culmination of years of Nokia Bell Labs research, Autonomous Inventory Monitoring stands as a testament to the integration of AI-enabled drone-based hardware, camera-based indoor localization, data analytics and computer vision. It brings together cutting-edge technologies, offering a unified warehouse management service.
 

Addressing challenges with innovative solutions  

To further underscore the significance of Autonomous Inventory Monitoring, Nokia commissioned Roland Berger, an international management consulting firm, to study what makes this technology attractive to the warehousing and logistics industry.
 
The study focused on addressing pain points related to warehouse inventory counting, particularly major labor challenges like attracting and retaining staff and striking the right balance between accuracy and counting costs. In addition, another pain point identified is the lack of understanding of the location and quantity of existing inventory creates stockouts and high labor costs, disrupting shipment deliveries that lead to unsuccessful sales, impacting customer satisfaction.
 
Drones emerged as a solution by automating routine tasks such as inventory counting and scanning, significantly expediting warehouse operations. When equipped with advanced computer-vision-based scanning technology, drones can efficiently scan inventory at any time within the warehouse, including areas not accessible by humans and not in direct line of sight.
 
This automation eliminates the need for employees to engage in long hours of simple and repetitive tasks and also enhances the attractiveness of the job profile, leading to improved worker retention, health and safety.

According to a Former Head of Innovation in Global Transport and Logistics, during drone testing, there was no significant resistance because the technology automates tedious tasks and is seen as a solution for understaffed warehouses. The outcome is improved accuracy and efficiency at lower costs.
 
Beyond labor considerations, this service addresses operational pain points by streamlining count preparation, eliminating inefficiencies and facilitating more frequent counts at little incremental cost. According to a Distribution Centre General Manager in the Retail sector, increasing counting frequency for accuracy improvement is often considered too costly, but Autonomous Inventory Monitoring drones cover more ground in a shorter time with no excessive costs. Using advanced computer-vision-based scanning technology, drones accurately identify and record the location of each inventory item and can also detect empty bins and junk/debris on pallets.
 
In conclusion, the study uncovers that Autonomous Inventory Monitoring is a transformative solution, able to bridge the gap between efficiency, cost-effectiveness and technological innovation in the ever-evolving landscape of warehouse management. Beyond confinements, this approach showcases its versatility, not limited to a specific industry. The evidence lies in its potential to elevate service levels for warehouse operators, distributors, third-party logistics, equipment manufacturers and retailers.