Want to automate your warehouse? Wait until you understand your data
CHICAGO — Jack Kaumo sees a lot of customers quick to jump on the automation bandwagon, especially when they observe their competitors buying a new shiny tool or system. "That may not be the correct way to go about it," the director of iWarehouse sales at Raymond told a session at ProMat 2019 in Chicago. "Before you do that, you need to make sure you're ready."
Being ready starts with gathering and understanding data. Gathering data doesn't require much change for warehouses. By their nature, the facilities already have data-generating systems in place.
Warehouse management systems (WMS), transportation management systems (TMS), ERPs and operator assistance programs continuously collect data. RFID, barcodes and robotics provide data. So do equipment maintenance schedules and employee time clocks.
The data collection systems don't even need to be high-tech — a paper Occupational Safety and Health Administration checklist is a form of data.
Once the data exists, the next step is to synthesize and analyze it. "Without understanding the data first and knowing where you are today, or where you were last year, you can't truly predict what you're going for," John Slavik, iWarehouse sales manager at Raymond, said at the session. "You're just guessing."
Data synthesis is built into many warehouses, due to the overlap and coordination between various systems. WMS and TMS overlap and together shape transportation operations, Kaumo said. Similarly, WMS, warehouse execution systems (WES) and warehouse control systems (WCS) coordinate to influence distribution center operations. "There's a good chance your operation isn't necessarily taking advantage of that overlap," he said.
Kaumo gave the example of an avoidable accident with an equipment operator that caused damage to the rack and the product. (Though, fortunately, not the person.) Each damage and accident report would typically be filed in disparate systems. If warehouse managers instead read the data points as a collective entity, they can view the situation holistically and understand the overall impact on people, product and maintenance.
"Now they can understand, 'if I have the ability to reduce the impact to a certain level, it's going to conversely also reduce my avoidable costs,'" he said.
Reading the data points together creates what Slavik referred to as a "data story," which provides insight into warehouse operations as a whole. Data stories can unearth pain points in a facility's operations and guide decisions around what solutions to implement to best solve existing problems. If fast-moving products are far from the door, the solution could be route optimization software. If worker training is an issue, virtual reality systems could offer relief.
"Whether you're looking at automation, you're looking at robotics, you're looking at better lighting ... you're trying, in some way, to optimize your story," Slavik said.
The data story is critical as facilities change and add products or customers. The initial thought may be to add capacity, whether in the form of more square footage, taller racks or more trucks. "But is that really what you have to do? Maybe look at the data and understand where you're inefficient" before making a significant change to a facility, Kaumo said. Almost always, the solution is not to add more trucks — rather, most companies find they have too large a fleet, he added.
Data stories can also help with forecasting, particularly for hiring during peak seasons. Data reports deliver detailed information to managers on the number of workers employed during peak season, their productivity, the business growth during that time and more. "That way, I know exactly how many people I need to hire in my temporary workforce," Kaumo said.
Each company's data story will be different and result in different systems being automated. Kaumo and Slavik foresee all warehouses will adopt some form of automation — if they haven't already.
"We're not going to suddenly see automation stop, like 'oh that was cool but now we're bored with this and now we're just going to go back to using regular people," Slavik said. "This is the future of where we're going. There's no turning back."
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