By Grainger Editorial Staff 1/28/20
Today's consumers are shopping online more than ever before. The PwC Global Consumer Insights Survey found that 31 percent of consumers purchase an item online at least once a week—and their expectations for when those items should arrive are shifting. According to a 2018 AlixPartners Survey, four and a half days is the longest delivery window a customer will accept, down from five and a half days in 2012.
This shift in consumer expectation puts increased pressure on warehouse managers to make the necessary changes needed to ensure their facilities can meet these new demands. Warehouse efficiency impacts customer satisfaction, revenue, employee satisfaction and safety. To improve performance, managers don’t necessarily need to overhaul their entire operation. A few adjustments to the following warehouse processes can lead to quick wins in efficiency that add up over time.
Order picking is one of the processes in a warehouse that still relies heavily on humans to do the work. Therefore, a smooth order picking process is crucial, as it directly impacts both your employees' morale and the customer experience. There are many order picking strategies you can choose from, depending on your specific facility. Newcastle Systems, a company providing mobile workstations, outlines eight different order picking methods, for example, including discrete order picking, zone picking and batch picking. Improving your order picking process is one way to boost efficiency in your facility. Supply Management, the official media outlet of the Chartered Institute of Procurement & Supply, recommends using a warehouse management system that automatically suggests the best routes employees should take when picking items to ship.
Mike Calabro, DVD Netflix Warehouse Operations Manager, oversees a facility that holds more than 3 million discs at any given time and ships over 1 million DVDs per week. Calabro explains how the facility uses three machines and algorithms to help employees process orders. "The programmers in the background have built algorithms to figure out what our customers want to see," Calabro says. "What's in their queue, and then anticipate the second disc in their queue. Or also, it's based on the time of year." Calabro sets his team up for order picking success by using data to store discs based on how likely they are to be ordered in the near future.
As companies introduce more personalized products for customers, the more SKUs there will be to account for these products—which means more products on warehouse shelves. Introducing data analytics to help employees decide how and where to store products can help facility managers more efficiently manage these increasing inventory levels. By 2023, International Data Corporation predicts that 65 percent of warehousing activities will use robots and data analytics to store products, which is projected to increase facility capacity by over 20 percent.
Calabro explains that when DVDs come into the Netflix warehouse, for example, the sorter scans the bar code to find out whether there is an existing order for the DVD. If there’s no order for that day, but the computer predicts an order placement the next day, the DVD goes into an easy-to-access container. Unlikely order titles go into “deep storage,” which saves processing time and space in the main facility.
Using barcode scanners can help employees know which products are available, so they aren't wasting time trying to figure out if and where they can find specific products.
While downtime for maintenance is unavoidable, warehouses save time and money when downtime is predicted and planned. Aberdeen research found that unplanned downtime can cost an average of $260,000 per hour across all businesses. Even more concerning, MachineMetrics cited research finding that 80 percent of companies cannot accurately calculate their downtime costs. Additionally, only 24 percent of operators report using a predictive approach to downtime.
By using IoT sensors, warehouse managers can collect real-time data about machine operations. When combined with artificial intelligence, warehouse management systems can detect changes in productivity and performance that can quickly indicate whether a machine might need maintenance.
At the Netflix warehouse, the employees perform weekly preventive maintenance checks and deep cleans. The team removes the backs from machines to blow out the dust and visually inspects the electrical components for burned-out parts. In addition to replacing any worn parts, technicians lubricate all moving parts. By combining physical and predictive preventive maintenance, warehouse managers can reduce and hopefully eliminate unplanned downtime.
These are just a few ways warehouse managers can boost efficiency within their facilities. By taking stock of where labor costs and inefficiencies are adding up, warehouse managers can leverage automation and data analytics to help ensure their facility runs as smoothly and efficiently as possible.
The information contained in this article is intended for general information purposes only and is based on information available as of the initial date of publication. No representation is made that the information or references are complete or remain current. This article is not a substitute for review of current applicable government regulations, industry standards, or other standards specific to your business and/or activities and should not be construed as legal advice or opinion. Readers with specific questions should refer to the applicable standards or consult with an attorney.