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Using big data and AI to optimize warehouse inventory management

Written by: Erhan Musaoglu
Originally published on August 8, 2024, Updated on August 8, 2024
Using big data and AI to optimize warehouse inventory management

Warehouses by definition store massive amounts of inventory — but have you ever considered how much data moves through them? Modern technology has revolutionized inventory management processes, and many of the tools that keep warehouses running are powered by data. Lots of data

In this article, we’ll look at the role of big data in inventory management and how it’s enabled AI to transform the industry. We’ll show you how big data enables mission-critical inventory management processes such as real-time inventory tracking and predictive analytics, and even how it’s contributing to a more sustainable world. Then, we’ll show you how Logiwa can turn the data that your warehouse generates into better performance.

When you are ready, schedule a call with one of our fulfillment experts. We can help you understand how the leading fulfillment management system, Logiwa IO, can ensure all of your data is put to work improving your operations.

The role of big data in inventory management

Big data in inventory management refers to the massive amount of datasets that your warehouse generates. Data that you rely on for your operations. But that data is defined not only by its volume, but also by its velocity (how fast it changes and must be imported) and its variety (highly diverse and often unstructured nature).

Some sources of data in inventory management include:

  • Product information (weight, size, fragility)
  • Picker and product movement
  • Sales transactions (repeat purchases, value drivers)
  • Market trends (seasonality, purchases by demographic)
  • Customer behavior (purchasing habits, product reviews, cart abandonment)
  • IoT data (warehouse temperature, inventory levels, backlogs)

Once companies tap into these data points, they can gain valuable insights into how they can improve warehouse processes, like:

  • Avoiding overstocks and stockouts
  • Improving demand forecasting
  • Making data-driven decisions

Armed with these insights, warehouse managers can then leverage the capabilities of their AI-powered tool to optimize their operations.

Check out this short video to see how Logiwa IO uses data and AI to automate and streamline multiple warehouse operations.

Real-time inventory tracking and management

The fast-paced nature of big data in ecommerce inventory management requires warehouses to stay on top of both product variety and incoming information. Companies that effectively manage their data can use it to power real-time inventory tracking with AI. This provides significant advantages, especially in handling omni-channel orders from multiple ecommerce stores, giving them an edge over the competition.

The gains in operational efficiency are perhaps the biggest benefit, as real-time inventory tracking and management allows ordering new inventory only when needed, greatly reducing the number of stockouts and overstocks experienced. The technology also enables dynamic order processing and faster shipping speeds, which in turn leads to greater customer satisfaction — and higher profitability.

Real-time inventory tracking with AI offers multiple business advantages. IoT devices and barcode systems allow AI-driven fulfillment management systems (FSM) like Logiwa IO to track inventory levels and alert you when to order new products. High-volume fulfillment operations need a system that serves as the central hub, connecting all their warehouse-related data.

Predictive analytics and demand forecasting

With these tools in place, you can use predictive analytics in supply chain management to anticipate trends and reduce inventory waste. Demand forecasting is the process of using historical data to anticipate when certain items will need to be reordered, and what quantities should be kept on hand. Such AI-driven inventory optimization ensures that warehouse managers have exactly enough product in the warehouse to be able to fill the expected number of customer orders without having their resources drained by excessive inventory.

AI and sustainability in warehousing

Another area where big data in inventory management is making an impact is on the environment. Sustainability is becoming a top priority. At a time when customers are committed to purchase only from suppliers that share their values, it’s essential that shippers take every possible step to contribute to a more eco-friendly world.

It turns out that there are several ways that AI drives sustainability in warehouse management. For example, route optimization can help shippers find the shortest path from warehouse to customer, reducing fuel and transportation costs and cutting back on emissions. AI-driven inventory optimization also helps warehouses cut back on excess inventory and unnecessary packaging materials, which results in less material sent to a landfill, creating a cleaner world for us all.

Benefits of AI and Big Data integration

As we’ve seen, leveraging big data for warehousing operations can bring benefits to nearly every phase of your inventory management processes. The list is not exhaustive, but here’s a review of the main benefits you’ll see:

  • Cost reduction: Lower labor costs, less overhead, and reduced shipping expenditures
  • Increased operational efficiency: Faster picking and packing processes, fewer stockouts and overstocks, faster shipping times, optimized warehouse layout, and process automation
  • Enhanced customer experience: Improved quality control, faster shipping time-to-consumer, and higher perfect order rates

From better business resiliency to smoother supply chain dynamics to higher customer satisfaction, integrating big data into your inventory management processes can improve your business across the board.

Harnessing big data for warehouses Logiwa

Today’s warehouses generate massive amounts of data. Companies that convert that data into actionable insights can streamline their operations, reduce labor and overhead costs, and even contribute to a more eco-friendly environment — but companies that don’t will soon find themselves lagging behind.

Logiwa uses the power of AI to solve modern inventory management problems. Our flagship product, Logiwa IO, is cloud-based and empowers you to manage your data. And it’s AI-driven to optimize your operations.

If you’d like to see how Logiwa IO can help you harness all of your data and convert it to profit, contact one of our fulfillment experts today to request a free demo.

FAQs about big data in warehousing

What is big data?

Big data is defined as massive datasets with a large degree of variety that are imported to your system at a greater rate than typical data inputs.

How do you implement big data analytics in inventory management?

The first step to get the most out of your warehouse data is to choose an AI-driven system designed to help optimize your operations. Companies like Logiwa can then help you ensure you onboard smoothly by helping you assess your needs and objectives.

How do cloud-based inventory management systems help you manage big data?

Cloud-based inventory management systems store a warehouse’s big data in the cloud, where more storage space is available. This allows for faster data usage and enables greater data capacity, preventing your system and operations from getting bogged down.

What are the benefits of using predictive analytics in supply chain management?

Fewer bottlenecks, fewer stockouts and overstocks, improved resiliency, and faster shipping times are a few of the benefits that predictive analytics can bring.

How does big data work together with AI in inventory management?

Big data supplies the information that AI algorithms need to make their decisions and execute your inventory management processes.
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