How Big is Big Data in Warehouses?
Updated: Apr 14, 2022
With the development of digital technologies, companies have collected huge amounts of data. They then needed powerful techniques to make sense of this data. A recent survey found that 49% of supply chain leaders are able to capture real-time insights from big data and act immediately, while 51% use artificial intelligence and predictive big data analytics to capture insights.
According to another study, 92% of Fortune 1000 companies are increasing their investments in big data and artificial intelligence. These developments clearly show that many companies are starting to embrace big data, realizing the benefits that big data can provide. So why are so many supply chain and logistics firms willing to use big data analytics?
Today, companies want to provide faster service with less cost and more transparency in the conditions of increasing competition. On the other hand, customers continue to digitize with the devastating impact of e-commerce and demand more speed and response. At the same time, online sales and high-tech sensors also provide significant data. Therefore, using big data in supply chain and logistics is transforming from a "nice to have" feature to a "must-have" feature.
Benefits of Big Data Analytics in Supply Chain and Logistics Management
Analyzing customer and order data can generate useful information for us on many issue such as demand forecasting, product placement, pricing, cost and labor optimization, operational risk management and better service delivery.
According to McKinsey, some of the key opportunities of big data analytics for supply chain and logistics management are:
For all activities in the big data analytics supply chain, it offers a wide range of unique opportunities from manufacturing to the end-user. So, as the most critical part of the chain, how is the situation in warehouses?
Using Big Data to Improve Warehouse Performance
Warehousing has traditionally been cost-driven, and companies have been more willing to invest in technologies that provide a competitive advantage. Today, warehouse technologies such as warehouse management systems (WMS) and connected hand terminals, conveyors, forklifts, automated racks, and automated guided vehicles (AGV) have become important data sources and they can create new opportunities in warehousing when blended with analytical techniques.
So how can big data be leveraged to optimize warehouse management and improve performance?
Predictive Demand Forecast
Big data can help retailers and warehouse managers forecast demand for products. It gives them an idea of which products are bestsellers and which are not performing well.
Inventory Planning and Replenishment
Every warehouse manager wants to know the exact amount of stock needed to meet customer demand without overstocking. Big data allows retailers and suppliers to track inventory levels, how much is needed, and where. Big data speeds up the process and encourages timely decision-making, as collating advanced information to forecast demand and monitor stock levels is time-consuming.
Real-Time Visibility of the Supply Chain
Big data provides greater real-time visibility into the entire supply chain. You can monitor end-to-end your supply chain and every stock movement. There is no need to guess where your inventory is or if it will arrive on time. Big data tracks every item, its whereabouts, current state, etc.
Big data can be used with WareOp's visualization service, especially for businesses with large warehouses and those using 3PL storage services. In this way, you can follow all the activities related to your warehouse and supply chain in real-time.
Picking Zone/Storage Area Optimization
Big data provides a real-time classification of your warehouse inventory through demand forecasting and historical order analysis, allowing you to organize a much more efficient warehouse/shelf layout and manage warehouse space. This improves capacity utilization, and the fastest products are always available nearby. Big data enables you to adapt to the ever-changing needs of the market. For example, WareOp's slotting service understands the increasing demand and inventory requirements during Black Friday and the upcoming holiday season and adapts your warehouse in no time, thanks to machine intelligence that learns from order and demand forecast data.
Picking Route Optimization
Optimization of the picking operation, which is a labor-intensive process in warehousing, independent of the sector and operation, is undoubtedly the dream of every warehouse manager. The big data generated by order and barcode data allows you to understand and optimize the walks of the pickers. Likewise, forklift behavior and route preferences can be analyzed and dynamically optimized to increase picking efficiency. WareOp's Machine Learning-based route optimization calculates the shortest route for each order/location and saves 30% of the time spent on the road.
The benefits and advantages your business can derive from harnessing the power of big data can be endless resulting in more effective warehouse performance. Check out WareOp, our Artificial Intelligence-driven optimization platform to help you take your business into a brave new world of big data and explore opportunities.