No matter which vertical a warehouse-owning company serves, or the size of the company, inventory in warehouses needs to be counted. Despite numerous changes in modus operandi or the technologies involved, inventory counting remains an important part of warehousing operations. While this task has been done manually for quite some time, AI/ML and robotics are about to transform it, by fully automating such repetitive tasks.
The advantage of automating manual tasks is that stakeholders can realign their human resources towards more productive tasks, thus saving costs and improving productivity. Moreover, AI technology can be a boon when it comes to complex activities like image processing, object recognition, and virtual assistance. The application of AI in the warehouse context can help identify gaps in the existing inventory processes as well as reduce the margin of error.
Coming to supply chain or warehousing operations, AI can offer an array of capabilities to revolutionize the way day-to-day tasks are carried out. From monitoring the temperature levels in a food and beverage warehouse to detecting thefts of high-value inventory items, the possibilities unlocked via AI are endless.
Warehouse managers can reap the benefits of AI for inventory counts, as follows:
1) Smarter Data Management:
The biggest advantage of AI when it comes to inventory data is the speed and accuracy at which it can help generate and manage data. Getting real-time insights from AI will soon be essential for warehouses looking to ride the trends of e-commerce and same-day delivery, and manage their procurement and inventory accordingly.
Based on the data points generated by AI, warehouse managers can make smarter decisions by identifying and improving the inventory processes. With real-time insights into inventory trends, warehouse managers can even predict the future demand as well as work down the inventory which doesn’t see enough demand, thus realigning the resources towards more productive and profitable goods. Furthermore, inventory managers can compare the data with various sources for different purposes. The data collected by AI can be compared to that in the ERP or WMS systems to verify and validate the correct data. This ensures maximum accuracy and minimization of human errors.
2) Speed and Scalability:
Warehouses are dynamic in nature and the midpoint between the factor and the end customer. Thus, they need to operate at a speed at which it can fulfill consumer demand. Modern warehouses are equipped with technologies that can carry out the tasks quickly without compromising accuracy or agility.
Unfortunately, the high dependence of traditional warehouses on manual operations is the reason why repetitive tasks like counting the inventory consume valuable resources.
With automation as a driver, AI-enabled drones can scan inventory rapidly. These drones are compact in nature, and hence are able to access difficult locations with ease. Multiple warehouses or distribution centers can each have dedicated drone fleets for cycle counts.
There remain concerns about the seemingly high costs of AI-enabled automation. While the one-time setup or deployment fees can seem high initially, deploying AI for inventory scans can result in a quick payback period and high RoI.
As labor markets tighten, and labor rates and turnover soar, manual operations further reduce operational margins. Instead, AI-centric inventory automation can do the job with high efficiency, at scale, and at lower costs. As an example, warehouses who deploy the FlytWare fleet of autonomous drones can expect payback periods of less than 12 months.
Warehouses and AI: Present and Future
The days when Artificial Intelligence was a buzzword or clickbait are gone. Across large warehouses and DCs, AI is delivering enormous improvements in the way critical tasks are carried out, including inventory counts.
Amazon is an excellent example of a conglomerate adopting AI successfully and demonstrating enviable results. Amazon has optimized its warehousing operations in such a way that almost all the processes like inventory audits, learning user demand, supplier management, delivering goods, etc. are powered by AI/ML.
Early adopters of technology always have a strategic and competitive edge because, by the time the technology becomes mainstream, they have already experienced the benefits and payback generated by the same, thus staying ahead of the curve. Therefore, it is imperative for warehousing or supply chain managers to change the way their existing tasks are carried out, by exploring the capabilities of AI.
Companies usually begin with pilot projects involving AI applications, which are often customized for every warehouse, since there is no one-shoe-fits-all approach. The accuracy of these algorithms is validated via training data sets. Taking this data-driven approach ensures the accuracy and generalizability of automated inventory counts.